My work focuses on using large surveys to study cosmology and the evolution of galaxies. This ranges from studying the clustering of galaxies and their evolution with redshift, weak gravitational lensing of galaxies, and estimating the properties of galaxies based on their colors (aka photometric redshifts). The common theme to this work is addressing the need for massive data sets and how to work with them. One area that interests me a lot at the moment is the Large Synoptic Survey Telescope (LSST) where I lead the development of simulations of what LSST might observe. Beyond cosmology, I am also interested in how to make the technologies that companies use to search the internet useful in research and education.

I’m interested in using time series to understand the physics of black holes and neutron stars, especially using astrostatistics, a field that makes modern statistical methods useful for astronomical data analysis. I have worked on a number of problems, including methods to help us understand variability in fast transients like magnetar bursts, and using machine learning to classify time series from black hole X-ray binaries. At DIRAC, I am hoping to combine X-ray and optical data to make our inferences about black holes better, among other things. I am also interested in how we can use machine learning and statistics to mitigate biases introduced into our data by detectors. I am lead developer for a software project called Stingray, which aims to build a standard implementation of a lot of time series methods used in astronomy. Beyond astronomy, I am interested in finding new ways to teach data science to astronomers as a co-organizer of AstroHackWeek, and I think about participant selection for scientific workshops a lot (via the software project Entrofy).

I’m interested in astronomical ‘Big Data’: developing and applying methods and algorithms that let us use large data sets to answer research questions.

Major astronomical surveys of today are routinely collecting hundreds of terabytes of images, creating databases with billions of objects and several billion measurements. Large surveys astronomers are becoming part data scientists. In my research, I go where the data takes me — I’ve worked on topics ranging from asteroids in the Solar System, Galactic structure, to the scale structure of the universe. My current focus is using survey data to understand the minor bodies of the Solar System and the structure and evolution of the Milky Way.

Željko Ivezić (pronounced something like Gel-co Eva-zich) obtained undergraduate degrees in mechanical engineering and physics from the University of Zagreb, Croatia, in 1990 and 1991. He obtained Ph.D. in physics from the University of Kentucky in 1995, where he worked on dust radiative transfer models and wrote the code Dusty. He moved on to Princeton University in 1997 to work on the Sloan Digital Sky Survey, and took a professorship at the University of Washington, Seattle, in 2004. Željko’s scientific interests are in detection, analysis and interpretation of electromagnetic radiation from astronomical sources. His current obsession is the Large Synoptic Survey Telescope project, for which he serves as the Project Scientist.

James Davenport is currently a NSF Astronomy & Astrophysics Postdoctoral Fellow, working on stellar magnetic activity using time domain surveys such as Kepler and TESS. He received his PhD in astronomy in 2015 from the University of Washington, and will be joining DIRAC full-time as a Research Scientist to study stellar ages and variability in large scale surveys. Check his work here.

My research falls in the category of astrostatistics, an interdisciplinary field of astronomy and statistics. On the astronomy side, I am interested in properties of the Milky Way Galaxy such as its mass, amount of dark matter, stellar populations, globular cluster population, and central nuclear star cluster. On the statistics side, I am interested in Bayesian hierarchical modelling, Markov chain Monte Carlo techniques, and in general, implementing and developing modern statistical methods to and for astronomical problems.

2018 recipient of the J.S.Plaskett Medal

Atousa Salehi, M.D. is a board certified Emergency Physician and a Fellow of The American College of Emergency Physicians. She received her medical degree from Oregon Health & Science University School of Medicine and completed her Emergency Medicine residency at Denver Health Residency program.  Atousa is passionate about the role of big data in shaping our future scientific inquiries, building better predictive models in healthcare and transforming Medicine . She has worked at Overlake Medical Center since 1998 in both clinical and leadership roles and is a part time clinical faculty at the Puget sound VA Health care system. She is an alumni member of Washington Women’s Foundation and has served on the Pooled Fund Grant and Site Visit Committees. She is currently serving as an advisory board member to Vitus Research and Evaluation.  Outside of clinical practice, Atousa enjoys reading about black holes, ripples in space-time, and the many mysteries of the cosmos. She loves traveling, scuba diving and exploring the beautiful San Juan Islands with her family and her dog Lucca.

Bryce is an Asteroid Institute Associate. The main focus of his
academic studies has been the dynamical processes that affect small
body populations in the solar system and how these dynamical processes
affect the population that we see. He uses observational and numerical
modeling approaches on topics such as the evolution of asteroid
families older than two billion years, the collisional history of Main
Belt Asteroids and Near Earth Asteroids, the strength of the Yarkovsky
effect on asteroids’ orbits, asteroids’ thermal and rotational
properties and the photometric characterization of asteroids and
comets.

Mike Halperin, M.D. is a General Co-Chair of the University of Washington’s 5 billion dollar campaign – Be Boundless / For Washington, For The World. Mike is the immediate past president of the Seattle Academy of Arts and Sciences. He has served on numerous nonprofit boards and was a founding member of Seattle JazzEd and the Westerlies. Mike studied at Brown University and the University Of Washington School Of Medicine. He is board certified in Emergency Medicine, and was a long time member and manager of Puget Sound Physicians. Mike is actively involved in the life science start-up and entrepreneurial space. He is married to Jodi Green, Chair of the UW Foundation Board, and has two incredible children – Taylor and Lucy.

Sarah is a B612 Asteroid Institute senior researcher. Her research interests evolve around orbital dynamics problems in the Solar System. This includes studying main-belt asteroid resonances, resonant mechanisms that create asteroids on retrograde orbits, co-orbital Solar System objects, impact and crater formation rates, near-Earth object population modelling, and Earth impact probabilities and hazard mitigation. She has also used observations for near-Earth object follow-up and characterization and confirming that predicted asteroids undergo the Yarkovsky effect. She received her PhD in 2015 from the University of British Columbia. Learn more about her work here www.sarahgreenstreet.com

Mr. Jeff Glickman is a computer scientist trained at the University of Illinois at Urbana-Champaign and is trained in both software and hardware engineering. While there he participated in, and directed, projects in machine intelligence, pattern recognition, image processing, and stochastic computation. Mr. Glickman studied under Dr. Wolfgang Johannes Poppelbaum who performed his post doctorate studies under Dr. John Bardeen, the two-time Nobel Prize winner in Physics. While at the University of Illinois, Mr. Glickman was a Teaching Assistant, Research Assistant, Research Associate, Assistant Director of the Information Engineering Laboratory, and Assistant Director of the Computer Research Laboratory, the first National Science Foundation funded computer center. Since 1982 Mr. Glickman has managed and delivered advanced technology and services, for The Department of Defense, Ford Motor Company, General Motors, NASA, InFocus Corporation, The TC and others.

He holds patents in multiple disciplines including computer architecture, communications, and image processing and pattern recognition. Mr. Glickman has provided expert image and video analysis to corporations, law firms, police departments and local and federal government. Mr. Glickman is a computer scientist, a hardware engineer, a Board Certified Forensic Examiner, a Fellow of the American College of Forensic Examiners, a Senior Member of the IEEE, and a Member of the ACM. He is Chair Emeritus of IEEE Seattle and President of the American Society for Photogrammetry and Remote Sensing, Puget Sound Region, and Member Emeritus of the Washington State Forensic Investigations Council. Mr. Glickman was selected as the Information Technology Contractor of the Year for 2001 by Contract Professional magazine. Mr. Glickman is the past Chairman of the City of Hood River, Oregon, Planning Commission and Past Deputy Mayor of Woodinville, Washington, a suburb of Seattle, where he resides with his wife, daughter and son.

Specialties: Software and Hardware Engineering, Security Engineering, Secure Operating Systems, Image and Video Processing, Parallel Processing, Advanced Technology, Merger & Acquisition, Technology Due Diligence, Strategic Planning, Technology Forensics, Expert Witness.

As president and chief executive officer of Washington Research Foundation, Mr. Howell has guided WRF from being an organization that identified, protected and licensed technologies to one with sufficient assets and expertise to foster the creation of early-stage technology-based companies.

Mr. Howell joined WRF in 1989 and shaped the most successful licensing program in the organization’s history for generating a significant ongoing revenue stream. He continues to provide strategic direction for this effort.

Earlier in his career Mr. Howell was in medical sales and operations. Mr. Howell serves on several boards related to the mission and activities of WRF and WRF Capital, and is a Trustee of the Fred Hutchinson Cancer Research Center. He holds a bachelor of science in biochemistry from Washington State University.

Theodore A. Wagner, M.D. is a clinical professor of orthopedics and sports medicine, specializing in spine surgery. Dr. Wagner is also an adjunct professor in the Department of Neurological Surgery at the University of Washington’s School of Medicine in Seattle.

Dr. Wagner earned a bachelor’s degree from Trinity College in Connecticut and his medical degree from Temple Medical School in Philadelphia. After an internship in surgery in Montreal, he came to the UW for a residency in orthopedic surgery. He is board certified in orthopedic surgery.

Dr. Wagner’s clinical interests include biological spine disk regeneration, scoliosis, spine traumas and spine degeneration.

Dr. Wagner believes spinal surgery is a very definitive type of surgery with somewhat predictive complications of occurrences. He believes in teaching his patients what he knows and what he doesn’t know about their future before he does the index surgery.

I am a Research Assistant Professor in the Department of Astronomy at the University of Washington.

I am leading the development of major portions of two new large optical time-domain surveys. I am the Alert Production Science Lead for the Large Synoptic Survey Telescope as well as Survey Scientist for the Zwicky Transient Facility.

I use optical variability data to classify high-energy sources, particularly compact binaries. My research includes observation, instrumentation, and large-scale data analysis.

I am technical manager for LSST Data Management at Princeton University. Previously, I spent several years at the Anton Pannekoek Institute for Astronomy of the University of Amsterdam. Before that, I was a member of Hertford College, Oxford, where I studied Physics and, latterly, Astrophysics. I was born and raised in Glasgow, Scotland.

I am a research scientist at the University of Washington, working in the Data Management/Alerts Pipeline team of the LSST. I completed my doctorate in June 2010 at Drexel University, in Philadelphia, PA. I use large galaxy surveys to study galaxy evolution and the history and fate of the Universe. The picture above is of me filling the liquid nitrogen dewer of the Goldcam spectrometer on the 2.1m telescope at Kitt Peakduring my first PI observing run.

As with most things I do, there’s a lot of color around here, but not much substance.

I worked with the LSST’s data management group on the alert production pipeline.  In graduate school I studied galaxy evolution and formation through studies of faint gas and stars in galaxy outskirts from deep optical and radio data. My dissertation focused on characterizing star formation in galaxy outer disks and the role of accretion of gas and faint companions in galaxy evolution. As a postdoc, I worked on data intensive analysis pipelines in the cloud before returning to astronomy to work on the LSST transient alert stream.

My background in experimental astrophysics has taught me that the best approach to making a major breakthrough is to develop new instruments and invent new technologies that open up possibilities for research. As a Research Scientist at the University of Washington, I have taken that philosophy to the field of radio astronomy, where I have led the development of a new end-to-end imaging algorithm for radio telescopes called Fast Holographic Deconvolution (FHD). With FHD, we have designed an imaging and deconvolution pipeline to detect the first stars and galaxies to ever form in the universe through the power spectrum of the faint diffuse radio background, but it has also opened up exciting new research opportunities to study the nearby universe, from the diffuse structure of the Milky Way to nebulae and surveys of radio galaxies.

As a PhD student at Caltech, I approached the problem of detecting the earliest stars from a different angle. While the detectable signal at radio wavelengths is emission from neutral Hydrogen outside the pockets where the first stars formed, the ultraviolet-peaked radiation from those first stars will have been redshifted to the near-infrared today and should be detectable in the power spectrum of the infrared background. To this aim, we designed and built the Cosmic Infrared Background Experiment (CIBER), a suite of two wide-field infrared cameras and two spectrometers on board a NASA sounding rocket. As the senior graduate student, I was actively involved in every aspect of the project, from initial design and fabrication, through calibration and preparation for flight, to writing the full pipeline for analysis of flight data from the imagers. During that time, I worked with deep survey data from the Hubble and Spitzer space telescopes to refine the analysis techniques, and published results that challenged the reported detection of a signal from the first stars in the infrared background from those data.

I currently work with the LSST Data Management team as a Project Science Analyst. My main research focus is supernovae, especially those of Type Ia.

I completed a Bachelors of Science with Honours and a Specialization in Astrophysics at Queen’s University in Kingston ON Canada, with a Junior year abroad at the University of Glasgow in Scotland, and a Doctorate of Philosophy in Astrophysics at the University of Victoria in Victoria BC Canada. After a joint postdoctoral fellowship at UC Santa Barbara and the Las Cumbres Observatory Global Telescope Network (www.LCOGT.net) I moved to a senior postdoctoral fellowship at UC Berkeley and then joined the the Large Synoptic Survey Telescope team at the University of Washington as a research staff scientist in 2016.

July 26th – October 26th, 2017.

Jorge is a machine learning expert who works on feature selection, identifying which features provide the most information in a data set.

Jorge was born in Temuco, Chile. He obtained his B.S. and P.E. degrees in Electrical Engineering from the University de La Frontera in 2005 and 2007 respectively.

Jorge obtained his Ph.D. in electrical engineering from the University of Chile in 2015 where he worked on feature extraction and selection method based on information theory. Actually Jorge is a postdoctoral research at the University of Chile and the Millennium Institute of Astrophysics, where he works on selection and extraction of feature group based on mutual information for classification of patterns in astronomical images and time series.

Jorge’s scientific interests are interaction and causality in features selection method using information theoretic, quantization of nonlinear time series and hierarchical learning. The Jorge’s current work focuses in detection of candidate asteroid on stamp images in Moving Object Pipeline System on LSST and dimensionality reduction and feature-learning in astronomical spectroscopic data using Variational Autoencoder.

Working at the UW

In Jorge’s stay at the University of Washington, he works with Andrew Connolly’s team on two main topics:

1)  Study of new strategies to optimize the MOPS process in real time to detect asteroid. In this study they work with unsupervised analysis of images (stamp) and hierarchical classification where they create and select the most relevant individual and group features to discriminate between asteroids and non-asteroid.

2)  Feature Extraction from spectroscopic data using Variational Autoencoder. In this study they work on the dimensionality reduction in spectroscopic data using Variational autoencoder to reconstruct spectroscopic data with with different resolution and to map nonlinear similarities on spectra.

July – August 2017.

Richard McMahon is heavily involved in DES and 4MOST and has been working recently on the detection of lensed QSOs.

The main focus of my current research is in the study of galaxy formation and evolution in the Epoch of Reionization ; focusing on the discovery and characterisation of high redshift primeval active galaxies andquasars powered by the accretion of matter onto supermassive black holes. My research work includes the discovery of quasars and active galaxies that host supermassive black holes, the determination of the space densities, star formation rates and how and when massive galaxies and quasars form.

This research is centered around the building and use of large scale data intensive techniques using optical and infra-red imaging and spectroscopic sensors on telescopes around the world (primarily in Chile) and in space using Gigapixel cameras and Petsacale multiwavelength datasets. 

July 24th -28th 2017.

Tamas Budavari is Assistant Professor in the Department of Applied Mathematics & Statistics in the Whiting School of Engineering at the Johns Hopkins University, where he focuses on computational and statistical challenges of big data.

His contributions to astronomy include Bayesian cross-identification of catalogs, statistical inference of galaxy properties and clustering, as well as advanced data solutions for fast searches against the largest surveys and simulations.

July 2017. 

Francisco Förster is the PI of the HITS program (a time domain survey using the Blanco 4m at CTIO that has been used for supernova, asteroid, and variable star detection).

December 11th – 12th, 2017. 

Danny Goldstein is a fifth-year graduate student in the Astronomy Department at UC Berkeley. His work focuses on strongly lensed supernovae. You can find his CV here.

Talk: Strongly Lensed Supernovae

When: December 11, 2017 @1:30-2:30pm
Where: WRF Data Science Studio, The Seminar Room

December 11th, 2017. 

Concurrently, AURA-LSST is excited to roll out a training video platform called Lynda.com. We were pleased to find out that University of Washington faculty and staff has access to Lynda.com. Chris will partner with the proper channels to ensure all LSST Project Members know how to access this resource so we can share videos within teams and subsystems. 

 February 12-15, 2018.

Naoki Yoshida is a Professor of Astrophysics in the Department of Physics at the University of Tokyo, as well as a  Senior Research Scientist at the Kavli Institute for the Physics and Mathematics of the Universe.

Seminar Talk on February 12, 2018 @12:30pm

February 14-16, 2018.

Eddie is a Hubble Fellow working at Lawrence Berkeley National Laboratory, trying to understand the structure of the Galaxy, and especially its dust, using observations of stars. His most recent work uses the DECam instrument on the Blanco 4-m telescope to image the southern Galactic plane, to understand its stars, gas, and dust. He also uses APOGEE spectroscopy to understand how dust properties vary, and the PS1 survey to infer the three-dimensional structure of the dust in the Milky Way.

February 1-2, 2018.

Seminar on February 2, 2018 @ 1:00pm

I am currently an associate professor in the Astronomy Group in the Physics and Astronomy Department at Vanderbilt University. My research interests lie in the areas of large-scale structure and galaxy formation, as well as ultra-high energy cosmic rays. I completed my Ph.D. degree in Astronomy at the Ohio State University, and my A.B. degree inAstrophysical Sciences at Princeton University. Before that, I lived in Athens, Greece where I attended Athens College.

I am a researcher and developer on the LSST Data Management team.

I write software that will process a deluge of images in real time when LSST begins collecting frames for a decade-long movie of the southern sky. My research includes observing weird binary stars and using them to better understand how all stars work. I hold degree in physics and astronomy from New Mexico State University, San Diego State University, and Harvey Mudd College.

Beyond astronomy I enjoy playing viola, advocating for more equity and less light pollution, and figuring out how to be a parent.

I currently work as a software and algorithm developer on the Large Synoptic Survey Telescope(LSST) as part of the Data Management, Alert Production team at UW. My main interests are in the field of cosmology specifically weak gravitational lensing and large-scale structure and using these measurements to constrain the dark sector of the Universe. I am also involved in the LSST Dark Energy Science Collaboration(DESC) developing methods to estimate galaxy redshifts from galaxy clustering statistics.

February 20, 2018.

Jean-Charles Cuillandre is an astronomer at the Canada-France-Hawaii Telescope (from Observatoire de Paris).

His talk is scheduled for Tuesday, February 20th. Title: The challenge of the distributed Euclid survey

Data obtained using the CFH12K camera on the Canada-France-Hawaii Telescope
Image by Jean-Charles Cuillandre (CFHT) & Giovanni Anselmi (Coelum)
“Canada-France-Hawaii Telescope / Coelum” Copyright © 2018 CFHT

Joachim is interested in big data and software driven solutions to problems in astronomy. During his undergraduate studies at the University of Washington he was presented with the opportunity to work on a research project for the Large Synoptic Survey Telescope (LSST). This project focused on LSST’s photometric calibration in relation to its auxiliary telescope.  He is now working on LSST’s Moving Object Pipeline System (MOPS): the software designed to link millions of moving object detections into realistic and time-forward predictable orbits.

I am interested in phenomena related to Active Galactic Nuclei, including High-Energy Astrophysics, the physics of accretion disks, and black holes. My current research with Dr Ivezić involves studying the variability of  distant galaxies hosting an AGN – Quasars, using the Sloan Digital Sky Survey data, and the Catalina Real-Time Transient Survey data. Understanding the parameters of variability, and the accuracy of the Damped Random Walk model, serves as a useful tool of Physics at the accretion disk scales.

Lynne Jones is the Performance Scientist for the Large Synoptic Survey Telescope (LSST) at the University of Washington and currently co-chair of the LSST Solar System Science Collaboration. She was part of the Survey/Detection panel of the  2010 NRC Commitee to Ceview Near-Earth-Object Survey and Hazard Mitigation Strategies. As part of her work with LSST, Dr Jones evaluates the scientific performance of LSST observing strategies, including the potential for studying small bodies with this next-generation telescope. She received her PhD from University of Michigan, conducting surveys to discover some of the faintest known (at the time) TransNeptunian Objects.

Bryce is a graduate student at the University of Washington and a member of the LSST Dark Energy Science Collaboration. He is interested in applying statistical techniques and machine learning to astronomical datasets and currently focusing on using such methods to improve the very different topics of photometric redshift estimation and asteroid detection.

Bob Abel is a professor of applied physics at Olympic College and collaborator with the University of Washington’s Large Synoptic Survey Telescope Group.

A lifelong daydreamer and former advertising creative, Jim learned from some of the smartest, and most ridiculously creative people in the business before forming a creative agency in Seattle and London. It was this relationship with creativity that inspires change and a chance encounter with Saturn that has sparked his present endeavor.

Jim now has turned his focus skyward co-founding Look Up where he serves as Wondernaut and Executive Director. Look Up explores the power of wonder through art, science and space. The organization is creating collaborative experiences designed to incite curiosity, wonder and further our unrealized potential.

Robert Hart, Ph.D., is currently VP and General Manager of the Institute for Disease Modeling, an operating unit of the Global Good initiative at Intellectual Ventures. 

IDM utilizes advanced mathematical modeling and statistical and large data analysis to help devise policy and programs that will advance the efforts of Bill Gates, the Bill and Melinda Gates Foundation, CDC, WHO and multiple ministries of health around the globe to control and eradicate infectious disease in the developing world.  Dr. Hart received his BS degree in Geophysics from the Massachusetts Institute of Technology and MS and PhD degrees in Geophysics from the California Institute of Technology.  He has founded and managed multiple software companies as an entrepreneur and as a venture capitalist, spanning the fields of nuclear test detection, oil and mineral exploration, image analysis and machine vision, wireless telecom technologies, ultrasound, and early disease detection among others. 

He is an avid amateur astronomer and spends much of his spare time traveling, scuba diving and indulging in underwater photography around the world with his marine biologist wife and, whenever possible, with his three sons and their wives.

June 27-29, 2018.

I work on Galactic Archaeology, which is the study of the structure and evolution of the Milky Way. I did my PhD at New Mexico State University working with Jon Holtzman and Jo Bovy with the APOGEE survey, which is an SDSS3 and SDSS4 spectroscopic survey of several hundred thousand red giants across the Milky Way. I spent two years working in Nice at the Observatoire de la Cote d’Azur with the Gaia-ESO and AMBRE projects, which have spectroscopic observations of tens of thousands of stars throughout the Galaxy. 

Currently, I am an ASTRO 3D fellow working at the University of Sydney with the GALAH Survey. GALAH  is a large-scale spectroscopic survey of 500,000 stars throughout the Milky Way, and aims to measure chemical abundances for 30 different elements to map and chemically tag the stellar populations of the Galaxy. In my talk, “Chemical Cartography of the Milky Way”, I will discuss the chemodynamic properties of different stellar populations throughout the disk and how they vary with location.

I attached a figure of some preliminary results from the GALAH survey, showing how the chemical structure of the disk varies from the inner Galaxy to the edge of the disk.

My research interests lie in Outer Solar System object detection and planetary habitability. For the Outer Solar System, I work on the detection of moving objects below the single-frame noise floor using a gpu-accelerated “shift-and-stack” pipeline called KBMOD. More broadly, I am interested in applying advanced statistical methods to big data in order to utilize these data sets to their fullest extent. For exoplanets, I study the impact of orbital dynamics on the habitability of exoplanetary systems using a multiphysics software suite called VPLANET.

Astronomical observations can probe physical phenomena at length and time scales, possibly in exotic environments largely inaccessible to terrestrial laboratories. While this underlies some of the successes of cosmological surveys over the past decades in discovering new physics, extracting such information is challenging because the data are typically noisy, and includes effects due to different processes (astrophysical, atmospheric and instrumental) tangled together in complex ways. I work in the area of extracting (inference along with classification) of such information from large surveys and am particularly interested in cosmology at late times, mostly through transients like supernovae and large scale structure. I am currently involved in LSST and ZTF. 

October 22-23, 2018.

Katy is a Ph.D. candidate in the Department of Statistics at Harvard University. She does research as a member of both the CHASC: Astrostatistics Group and the Sports Analytics Lab at Harvard. Her Tuesday 12pm talk will be on Defining Regions that Contain Complex Astronomical Structures.

November 8-9, 2018.

I’m a James Arthur Postdoctoral Fellow at the CCPP, NYU. I also have a partial affilation at UMD, where I work with the exciting data from the Zwicky Transient Facility.

November 29-30, 2018.

I’m interested in galaxies: how did they form and end up looking the way they do today? There are lots of different ways to attack this problem: my interest is in observational studies of both nearby galaxies and their star clusters and also distant, high-redshift galaxies. I’ve used quite a few different telescopes and instruments, with a lot of emphasis on infrared observations with the Spitzer Space Telescope. 

April 12, 2019.

David A van Dyk is currently a Chair Professor in the Statistics Section of the Department of Mathematics at Imperial College London. He received his Ph.D. from the Department of Statistics at the University of Chicago and his B.S. in Statistics and Probability from Michigan State University. Professor van Dyk was elected Fellow in the American Statistical Association in 2006. His research focuses on Statistical Computation, Statistical Methods in Astronomy, Causal Inference, and Statistical Analysis with Missing Data.

I am interested in developing data analysis techniques using the latest advances in statistical inference in order to leverage complex astronomical data. I work on probabilistic cataloging, a novel Bayesian technique that is able to handle extremely crowded stellar fields. The method is able to handle deblending ambiguities by treating the number of sources itself as a parameter to be inferred, using trans-dimensional Markov chain Monte Carlo sampling.

Dr. Jones is an Assistant Professor of Statistics at Texas A&M University. His research interests include astrostatistics, hierarchical Bayesian modeling, machine learning methods, Monte Carlo methodology, and more. He has contributed work in exoplanet detection, light curve classification, and disentangling overlapping sources in spatial and spectral analysis.

His seminar talk, “Disentangling Overlapping Astronomical Sources using Spatial, Spectral, and Temporal Information”, will be on Friday Feb. 22, 2019 at 11am in PAB, 3rd floor in conference room  B305.

Hložek studies a variety of problems in theoretical and observational cosmology through observations of the Cosmic Microwave Background, Type Ia supernovae and Baryon Acoustic Oscillations.

Using data from the Atacama Cosmology Telescope, her research focuses on constraining cosmological models, as well as determining the structure and amount of dark energy in the Universe.

She uses Baryon Acoustic Oscillations to constrain and test models of the Universe, and is interested in methods of extracting the signal from both spectroscopic and photometric galaxy surveys.

She also developed BEAMS, Bayesian Estimation Applied to Multiple Species, a statistical method for performing parameter estimation in the presence of contaminated cosmological data, which she applies to datasets such as the SDSS-II SN survey.

Hložek studied at the University of Pretoria and the University of Cape Town. She received her DPhil from the University of Oxford in 2011, where she was a Rhodes Scholar. Before coming to the Dunlap, she was a Lyman Spitzer Jr. Postdoctoral Research Fellow in the Department of Astrophysics at Princeton University and the Spitzer-Cotsen Fellow in the Princeton Society of Fellows. She is also a Senior TED Fellow.

2019-03-26 Lunch Talk: Renée Hložek

My research focuses on developing novel statistical methods for astronomy and cosmology. I am particularly interested in using Type Ia supernovae to probe the accelerated expansion of the universe that we believe is due to some form of “dark energy”.

One aspect of my research focuses on identifying Type Ia supernovae among the millions of astronomical transients that upcoming astronomical surveys such as the Large Synoptic Survey Telescope (LSST) will discover. I am currently developing the “avocado” software package that uses machine learning to classify different kinds of astronomical transients from sparsely sampled light curves with heteroskedastic noise. I am interested in understanding how biases in our observational strategies affect the performance of photometric classifiers and lead to biases in our cosmological measurements.

I am also working on developing better methods to estimate the distances to Type Ia supernovae. This involves using manifold learning techniques to parametrize the diversity of Type Ia supernovae and building non-linear models of their light curves.

Ashley Villar is a Ford Foundation Dissertation Fellow at Harvard University. She studies the eruptions, mergers and explosions of stars using statistical and data-driven methods. Her 10am talk, on Tuesday, November 12th, will be on “Time-domain Astrophysics in the Era of Big Data.” Ashley completed her undergraduate degree in Physics at MIT in 2014. She is super into the statistics of ghost hunting.

2019-11-12 Seminar: Ashley Villar

When: Tuesday, November 12th, 2019 @ 10:00am  Where: PAB, 6th Floor, eScience Studio, Seminar Rm.

Adam is an NSF Graduate Research Fellow and PhD student in the University of Michigan’s Department of Astronomy. He’s interested in how galaxies form and evolve, from the smallest dwarf galaxies to large galaxies like the Milky Way. He uses the gas content, resolved stellar populations, and satellite populations of massive galaxies to understand how they change as a result of their interactions with other galaxies.

More here.

Seminar: The Satellites and Stellar Halos of Nearby MW-mass Galaxies

When: Monday, December 9th, 2019 @ 12:30pm  

Where: PAB, 6th Floor, eScience Studio, Seminar Rm.

Keaton is a NSF Astronomy and Astrophysics Postdoctoral Fellow carrying out an integrated program of research and education titled “Discovering the First Exoplanets Around White Dwarf Stars with the Zwicky Transient Facility.” He aims to open a new field of exoplanet science by searching for and characterizing the first worlds in orbit around white dwarfs, which will ultimately reveal how exoplanets survive and are affected by the violent late stages of stellar evolution.  He is also working to train the next generation of astronomers and data scientists as a research mentor to UW undergraduates.

A big fan of coding and physics, Dino earned a masters in Computational Physics at Faculty of Science Split, Croatia, on the topic of linear feature detection in astronomical images. Having re-analyzed the entire Sloan Digital Sky Survey (SDSS) ~16TB large image dataset he discovered his passion for Big Data and related image analysis problems. As a graduate student at University of Washington, Dino works on Large Synoptic Survey Telescope (LSST) Data Management code, adding support for cloud services and executing Science Pipelines in the cloud. To various different extent he is also involved in other projects such as image differencing, kernel based moving object detection (KBMOD) and deblending.

Angus is a Research Fellow in the German Centre for Cosmological Lensing at the Ruhr Universität Bochum, Germany. His undertook his PhD at the University of Western Australia, where he studied the growth and evolution of baryonic mass as a member of the Galaxy and Mass Assembly (GAMA) collaboration. Following his PhD, Angus worked for the Kilo Degree Survey (KiDS) at the Argelander Institute for Astronomy at the Universität Bonn, where he began his work within weak gravitational lensing. For the last 3 years his research has focused on weak lensing survey science, and particularly on optimisation of photometric image reduction and analysis methods, systematics mitigation, and statistical analyses. Beyond weak lensing, Angus is a keen astrostatistician, a passable astronomy outreach presenter, and an enthusiastic but nonetheless mediocre golfer.

Seminar: Optimising Direct Redshift Calibration for Tomographic Cosmic Shear

When: Monday, March 9th, 2020 @ 12:30pm  

Where: PAB, 6th Floor, eScience Studio, Seminar Rm.

Spencer Nelson is a software engineer working on alerting systems for the Rubin Observatory, ZTF, and SCiMMA. Before joining DIRAC, Spencer worked in industry as a data scientist and software engineer.

Jennifer leads account activities for several clients and manages operations and business development for Communiqué PR. She is the co-author of Strategic Public Relations: 10 Principles to Harness the Power of PR.

Ken Myer is an interim executive for companies going through organizational transitions and is also a leadership lecturer at the UW Foster School of Business. A graduate of the University of Washington with a Masters in Speech Communication and an MBA, Myer began his professional career at IBM where he held a variety of positions including CFO, and then General Manager of the Northwest region. After IBM he went on to hold successful leadership roles at Active Voice, Interval Systems (which he co-founded), and as CEO of the Washington Technology Industry Association. Most recently Myer has served as interim leader for a variety of companies including Yapta, Vivid Robotics, Hydramaster, and Data I/O. Ken has been recognized three times for building a “best company to work for” and in 2009 was recognized as one of Seattle’s most influential business leaders. He is on the on the board of directors of the Washington Trails Association and is an avid hiker and backpacker.

I am a member of the LSST Data Management team and develop software for the LSST Alert Pipeline.

I work on the image differencing features. Following my graduate studies in astronomy, earlier I worked on the data processing pipeline of an ESA exoplanet mission (CHEOPS).
My main research interests are transiting exoplanets and young eclipsing binaries. Beyond astronomy, I am interested in the application of data science in social and economical studies. I have degrees in Physics and Economics.

My work focuses on using large surveys to study cosmology and the evolution of galaxies. This ranges from studying the clustering of galaxies and their evolution with redshift, weak gravitational lensing of galaxies, and estimating the properties of galaxies based on their colors (aka photometric redshifts). The common theme to this work is addressing the need for massive data sets and how to work with them. One area that interests me a lot at the moment is the Large Synoptic Survey Telescope (LSST) where I lead the development of simulations of what LSST might observe. Beyond cosmology, I am also interested in how to make the technologies that companies use to search the internet useful in research and education.

I’m interested in using time series to understand the physics of black holes and neutron stars, especially using astrostatistics, a field that makes modern statistical methods useful for astronomical data analysis. I have worked on a number of problems, including methods to help us understand variability in fast transients like magnetar bursts, and using machine learning to classify time series from black hole X-ray binaries. At DIRAC, I am hoping to combine X-ray and optical data to make our inferences about black holes better, among other things. I am also interested in how we can use machine learning and statistics to mitigate biases introduced into our data by detectors. I am lead developer for a software project called Stingray, which aims to build a standard implementation of a lot of time series methods used in astronomy. Beyond astronomy, I am interested in finding new ways to teach data science to astronomers as a co-organizer of AstroHackWeek, and I think about participant selection for scientific workshops a lot (via the software project Entrofy).

I’m interested in astronomical ‘Big Data’: developing and applying methods and algorithms that let us use large data sets to answer research questions.

Major astronomical surveys of today are routinely collecting hundreds of terabytes of images, creating databases with billions of objects and several billion measurements. Large surveys astronomers are becoming part data scientists. In my research, I go where the data takes me — I’ve worked on topics ranging from asteroids in the Solar System, Galactic structure, to the scale structure of the universe. My current focus is using survey data to understand the minor bodies of the Solar System and the structure and evolution of the Milky Way.

Željko Ivezić (pronounced something like Gel-co Eva-zich) obtained undergraduate degrees in mechanical engineering and physics from the University of Zagreb, Croatia, in 1990 and 1991. He obtained Ph.D. in physics from the University of Kentucky in 1995, where he worked on dust radiative transfer models and wrote the code Dusty. He moved on to Princeton University in 1997 to work on the Sloan Digital Sky Survey, and took a professorship at the University of Washington, Seattle, in 2004. Željko’s scientific interests are in detection, analysis and interpretation of electromagnetic radiation from astronomical sources. His current obsession is the Large Synoptic Survey Telescope project, for which he serves as the Project Scientist.

James Davenport is currently a NSF Astronomy & Astrophysics Postdoctoral Fellow, working on stellar magnetic activity using time domain surveys such as Kepler and TESS. He received his PhD in astronomy in 2015 from the University of Washington, and will be joining DIRAC full-time as a Research Scientist to study stellar ages and variability in large scale surveys. Check his work here.

My research falls in the category of astrostatistics, an interdisciplinary field of astronomy and statistics. On the astronomy side, I am interested in properties of the Milky Way Galaxy such as its mass, amount of dark matter, stellar populations, globular cluster population, and central nuclear star cluster. On the statistics side, I am interested in Bayesian hierarchical modelling, Markov chain Monte Carlo techniques, and in general, implementing and developing modern statistical methods to and for astronomical problems.

2018 recipient of the J.S.Plaskett Medal

Atousa Salehi, M.D. is a board certified Emergency Physician and a Fellow of The American College of Emergency Physicians. She received her medical degree from Oregon Health & Science University School of Medicine and completed her Emergency Medicine residency at Denver Health Residency program.  Atousa is passionate about the role of big data in shaping our future scientific inquiries, building better predictive models in healthcare and transforming Medicine . She has worked at Overlake Medical Center since 1998 in both clinical and leadership roles and is a part time clinical faculty at the Puget sound VA Health care system. She is an alumni member of Washington Women’s Foundation and has served on the Pooled Fund Grant and Site Visit Committees. She is currently serving as an advisory board member to Vitus Research and Evaluation.  Outside of clinical practice, Atousa enjoys reading about black holes, ripples in space-time, and the many mysteries of the cosmos. She loves traveling, scuba diving and exploring the beautiful San Juan Islands with her family and her dog Lucca.

Bryce is an Asteroid Institute Associate. The main focus of his
academic studies has been the dynamical processes that affect small
body populations in the solar system and how these dynamical processes
affect the population that we see. He uses observational and numerical
modeling approaches on topics such as the evolution of asteroid
families older than two billion years, the collisional history of Main
Belt Asteroids and Near Earth Asteroids, the strength of the Yarkovsky
effect on asteroids’ orbits, asteroids’ thermal and rotational
properties and the photometric characterization of asteroids and
comets.

Mike Halperin, M.D. is a General Co-Chair of the University of Washington’s 5 billion dollar campaign – Be Boundless / For Washington, For The World. Mike is the immediate past president of the Seattle Academy of Arts and Sciences. He has served on numerous nonprofit boards and was a founding member of Seattle JazzEd and the Westerlies. Mike studied at Brown University and the University Of Washington School Of Medicine. He is board certified in Emergency Medicine, and was a long time member and manager of Puget Sound Physicians. Mike is actively involved in the life science start-up and entrepreneurial space. He is married to Jodi Green, Chair of the UW Foundation Board, and has two incredible children – Taylor and Lucy.

Sarah is a B612 Asteroid Institute senior researcher. Her research interests evolve around orbital dynamics problems in the Solar System. This includes studying main-belt asteroid resonances, resonant mechanisms that create asteroids on retrograde orbits, co-orbital Solar System objects, impact and crater formation rates, near-Earth object population modelling, and Earth impact probabilities and hazard mitigation. She has also used observations for near-Earth object follow-up and characterization and confirming that predicted asteroids undergo the Yarkovsky effect. She received her PhD in 2015 from the University of British Columbia. Learn more about her work here www.sarahgreenstreet.com

Mr. Jeff Glickman is a computer scientist trained at the University of Illinois at Urbana-Champaign and is trained in both software and hardware engineering. While there he participated in, and directed, projects in machine intelligence, pattern recognition, image processing, and stochastic computation. Mr. Glickman studied under Dr. Wolfgang Johannes Poppelbaum who performed his post doctorate studies under Dr. John Bardeen, the two-time Nobel Prize winner in Physics. While at the University of Illinois, Mr. Glickman was a Teaching Assistant, Research Assistant, Research Associate, Assistant Director of the Information Engineering Laboratory, and Assistant Director of the Computer Research Laboratory, the first National Science Foundation funded computer center. Since 1982 Mr. Glickman has managed and delivered advanced technology and services, for The Department of Defense, Ford Motor Company, General Motors, NASA, InFocus Corporation, The TC and others.

He holds patents in multiple disciplines including computer architecture, communications, and image processing and pattern recognition. Mr. Glickman has provided expert image and video analysis to corporations, law firms, police departments and local and federal government. Mr. Glickman is a computer scientist, a hardware engineer, a Board Certified Forensic Examiner, a Fellow of the American College of Forensic Examiners, a Senior Member of the IEEE, and a Member of the ACM. He is Chair Emeritus of IEEE Seattle and President of the American Society for Photogrammetry and Remote Sensing, Puget Sound Region, and Member Emeritus of the Washington State Forensic Investigations Council. Mr. Glickman was selected as the Information Technology Contractor of the Year for 2001 by Contract Professional magazine. Mr. Glickman is the past Chairman of the City of Hood River, Oregon, Planning Commission and Past Deputy Mayor of Woodinville, Washington, a suburb of Seattle, where he resides with his wife, daughter and son.

Specialties: Software and Hardware Engineering, Security Engineering, Secure Operating Systems, Image and Video Processing, Parallel Processing, Advanced Technology, Merger & Acquisition, Technology Due Diligence, Strategic Planning, Technology Forensics, Expert Witness.

As president and chief executive officer of Washington Research Foundation, Mr. Howell has guided WRF from being an organization that identified, protected and licensed technologies to one with sufficient assets and expertise to foster the creation of early-stage technology-based companies.

Mr. Howell joined WRF in 1989 and shaped the most successful licensing program in the organization’s history for generating a significant ongoing revenue stream. He continues to provide strategic direction for this effort.

Earlier in his career Mr. Howell was in medical sales and operations. Mr. Howell serves on several boards related to the mission and activities of WRF and WRF Capital, and is a Trustee of the Fred Hutchinson Cancer Research Center. He holds a bachelor of science in biochemistry from Washington State University.

Theodore A. Wagner, M.D. is a clinical professor of orthopedics and sports medicine, specializing in spine surgery. Dr. Wagner is also an adjunct professor in the Department of Neurological Surgery at the University of Washington’s School of Medicine in Seattle.

Dr. Wagner earned a bachelor’s degree from Trinity College in Connecticut and his medical degree from Temple Medical School in Philadelphia. After an internship in surgery in Montreal, he came to the UW for a residency in orthopedic surgery. He is board certified in orthopedic surgery.

Dr. Wagner’s clinical interests include biological spine disk regeneration, scoliosis, spine traumas and spine degeneration.

Dr. Wagner believes spinal surgery is a very definitive type of surgery with somewhat predictive complications of occurrences. He believes in teaching his patients what he knows and what he doesn’t know about their future before he does the index surgery.

I am a Research Assistant Professor in the Department of Astronomy at the University of Washington.

I am leading the development of major portions of two new large optical time-domain surveys. I am the Alert Production Science Lead for the Large Synoptic Survey Telescope as well as Survey Scientist for the Zwicky Transient Facility.

I use optical variability data to classify high-energy sources, particularly compact binaries. My research includes observation, instrumentation, and large-scale data analysis.

I am technical manager for LSST Data Management at Princeton University. Previously, I spent several years at the Anton Pannekoek Institute for Astronomy of the University of Amsterdam. Before that, I was a member of Hertford College, Oxford, where I studied Physics and, latterly, Astrophysics. I was born and raised in Glasgow, Scotland.

I am a research scientist at the University of Washington, working in the Data Management/Alerts Pipeline team of the LSST. I completed my doctorate in June 2010 at Drexel University, in Philadelphia, PA. I use large galaxy surveys to study galaxy evolution and the history and fate of the Universe. The picture above is of me filling the liquid nitrogen dewer of the Goldcam spectrometer on the 2.1m telescope at Kitt Peakduring my first PI observing run.

As with most things I do, there’s a lot of color around here, but not much substance.

I worked with the LSST’s data management group on the alert production pipeline.  In graduate school I studied galaxy evolution and formation through studies of faint gas and stars in galaxy outskirts from deep optical and radio data. My dissertation focused on characterizing star formation in galaxy outer disks and the role of accretion of gas and faint companions in galaxy evolution. As a postdoc, I worked on data intensive analysis pipelines in the cloud before returning to astronomy to work on the LSST transient alert stream.

My background in experimental astrophysics has taught me that the best approach to making a major breakthrough is to develop new instruments and invent new technologies that open up possibilities for research. As a Research Scientist at the University of Washington, I have taken that philosophy to the field of radio astronomy, where I have led the development of a new end-to-end imaging algorithm for radio telescopes called Fast Holographic Deconvolution (FHD). With FHD, we have designed an imaging and deconvolution pipeline to detect the first stars and galaxies to ever form in the universe through the power spectrum of the faint diffuse radio background, but it has also opened up exciting new research opportunities to study the nearby universe, from the diffuse structure of the Milky Way to nebulae and surveys of radio galaxies.

As a PhD student at Caltech, I approached the problem of detecting the earliest stars from a different angle. While the detectable signal at radio wavelengths is emission from neutral Hydrogen outside the pockets where the first stars formed, the ultraviolet-peaked radiation from those first stars will have been redshifted to the near-infrared today and should be detectable in the power spectrum of the infrared background. To this aim, we designed and built the Cosmic Infrared Background Experiment (CIBER), a suite of two wide-field infrared cameras and two spectrometers on board a NASA sounding rocket. As the senior graduate student, I was actively involved in every aspect of the project, from initial design and fabrication, through calibration and preparation for flight, to writing the full pipeline for analysis of flight data from the imagers. During that time, I worked with deep survey data from the Hubble and Spitzer space telescopes to refine the analysis techniques, and published results that challenged the reported detection of a signal from the first stars in the infrared background from those data.

I currently work with the LSST Data Management team as a Project Science Analyst. My main research focus is supernovae, especially those of Type Ia.

I completed a Bachelors of Science with Honours and a Specialization in Astrophysics at Queen’s University in Kingston ON Canada, with a Junior year abroad at the University of Glasgow in Scotland, and a Doctorate of Philosophy in Astrophysics at the University of Victoria in Victoria BC Canada. After a joint postdoctoral fellowship at UC Santa Barbara and the Las Cumbres Observatory Global Telescope Network (www.LCOGT.net) I moved to a senior postdoctoral fellowship at UC Berkeley and then joined the the Large Synoptic Survey Telescope team at the University of Washington as a research staff scientist in 2016.

July 26th – October 26th, 2017.

Jorge is a machine learning expert who works on feature selection, identifying which features provide the most information in a data set.

Jorge was born in Temuco, Chile. He obtained his B.S. and P.E. degrees in Electrical Engineering from the University de La Frontera in 2005 and 2007 respectively.

Jorge obtained his Ph.D. in electrical engineering from the University of Chile in 2015 where he worked on feature extraction and selection method based on information theory. Actually Jorge is a postdoctoral research at the University of Chile and the Millennium Institute of Astrophysics, where he works on selection and extraction of feature group based on mutual information for classification of patterns in astronomical images and time series.

Jorge’s scientific interests are interaction and causality in features selection method using information theoretic, quantization of nonlinear time series and hierarchical learning. The Jorge’s current work focuses in detection of candidate asteroid on stamp images in Moving Object Pipeline System on LSST and dimensionality reduction and feature-learning in astronomical spectroscopic data using Variational Autoencoder.

Working at the UW

In Jorge’s stay at the University of Washington, he works with Andrew Connolly’s team on two main topics:

1)  Study of new strategies to optimize the MOPS process in real time to detect asteroid. In this study they work with unsupervised analysis of images (stamp) and hierarchical classification where they create and select the most relevant individual and group features to discriminate between asteroids and non-asteroid.

2)  Feature Extraction from spectroscopic data using Variational Autoencoder. In this study they work on the dimensionality reduction in spectroscopic data using Variational autoencoder to reconstruct spectroscopic data with with different resolution and to map nonlinear similarities on spectra.

July – August 2017.

Richard McMahon is heavily involved in DES and 4MOST and has been working recently on the detection of lensed QSOs.

The main focus of my current research is in the study of galaxy formation and evolution in the Epoch of Reionization ; focusing on the discovery and characterisation of high redshift primeval active galaxies andquasars powered by the accretion of matter onto supermassive black holes. My research work includes the discovery of quasars and active galaxies that host supermassive black holes, the determination of the space densities, star formation rates and how and when massive galaxies and quasars form.

This research is centered around the building and use of large scale data intensive techniques using optical and infra-red imaging and spectroscopic sensors on telescopes around the world (primarily in Chile) and in space using Gigapixel cameras and Petsacale multiwavelength datasets. 

July 24th -28th 2017.

Tamas Budavari is Assistant Professor in the Department of Applied Mathematics & Statistics in the Whiting School of Engineering at the Johns Hopkins University, where he focuses on computational and statistical challenges of big data.

His contributions to astronomy include Bayesian cross-identification of catalogs, statistical inference of galaxy properties and clustering, as well as advanced data solutions for fast searches against the largest surveys and simulations.

July 2017. 

Francisco Förster is the PI of the HITS program (a time domain survey using the Blanco 4m at CTIO that has been used for supernova, asteroid, and variable star detection).

December 11th – 12th, 2017. 

Danny Goldstein is a fifth-year graduate student in the Astronomy Department at UC Berkeley. His work focuses on strongly lensed supernovae. You can find his CV here.

Talk: Strongly Lensed Supernovae

When: December 11, 2017 @1:30-2:30pm
Where: WRF Data Science Studio, The Seminar Room

December 11th, 2017. 

Concurrently, AURA-LSST is excited to roll out a training video platform called Lynda.com. We were pleased to find out that University of Washington faculty and staff has access to Lynda.com. Chris will partner with the proper channels to ensure all LSST Project Members know how to access this resource so we can share videos within teams and subsystems. 

 February 12-15, 2018.

Naoki Yoshida is a Professor of Astrophysics in the Department of Physics at the University of Tokyo, as well as a  Senior Research Scientist at the Kavli Institute for the Physics and Mathematics of the Universe.

Seminar Talk on February 12, 2018 @12:30pm

February 14-16, 2018.

Eddie is a Hubble Fellow working at Lawrence Berkeley National Laboratory, trying to understand the structure of the Galaxy, and especially its dust, using observations of stars. His most recent work uses the DECam instrument on the Blanco 4-m telescope to image the southern Galactic plane, to understand its stars, gas, and dust. He also uses APOGEE spectroscopy to understand how dust properties vary, and the PS1 survey to infer the three-dimensional structure of the dust in the Milky Way.

February 1-2, 2018.

Seminar on February 2, 2018 @ 1:00pm

I am currently an associate professor in the Astronomy Group in the Physics and Astronomy Department at Vanderbilt University. My research interests lie in the areas of large-scale structure and galaxy formation, as well as ultra-high energy cosmic rays. I completed my Ph.D. degree in Astronomy at the Ohio State University, and my A.B. degree inAstrophysical Sciences at Princeton University. Before that, I lived in Athens, Greece where I attended Athens College.

I am a researcher and developer on the LSST Data Management team.

I write software that will process a deluge of images in real time when LSST begins collecting frames for a decade-long movie of the southern sky. My research includes observing weird binary stars and using them to better understand how all stars work. I hold degree in physics and astronomy from New Mexico State University, San Diego State University, and Harvey Mudd College.

Beyond astronomy I enjoy playing viola, advocating for more equity and less light pollution, and figuring out how to be a parent.

I currently work as a software and algorithm developer on the Large Synoptic Survey Telescope(LSST) as part of the Data Management, Alert Production team at UW. My main interests are in the field of cosmology specifically weak gravitational lensing and large-scale structure and using these measurements to constrain the dark sector of the Universe. I am also involved in the LSST Dark Energy Science Collaboration(DESC) developing methods to estimate galaxy redshifts from galaxy clustering statistics.

February 20, 2018.

Jean-Charles Cuillandre is an astronomer at the Canada-France-Hawaii Telescope (from Observatoire de Paris).

His talk is scheduled for Tuesday, February 20th. Title: The challenge of the distributed Euclid survey

Data obtained using the CFH12K camera on the Canada-France-Hawaii Telescope
Image by Jean-Charles Cuillandre (CFHT) & Giovanni Anselmi (Coelum)
“Canada-France-Hawaii Telescope / Coelum” Copyright © 2018 CFHT

Joachim is interested in big data and software driven solutions to problems in astronomy. During his undergraduate studies at the University of Washington he was presented with the opportunity to work on a research project for the Large Synoptic Survey Telescope (LSST). This project focused on LSST’s photometric calibration in relation to its auxiliary telescope.  He is now working on LSST’s Moving Object Pipeline System (MOPS): the software designed to link millions of moving object detections into realistic and time-forward predictable orbits.

I am interested in phenomena related to Active Galactic Nuclei, including High-Energy Astrophysics, the physics of accretion disks, and black holes. My current research with Dr Ivezić involves studying the variability of  distant galaxies hosting an AGN – Quasars, using the Sloan Digital Sky Survey data, and the Catalina Real-Time Transient Survey data. Understanding the parameters of variability, and the accuracy of the Damped Random Walk model, serves as a useful tool of Physics at the accretion disk scales.

Lynne Jones is the Performance Scientist for the Large Synoptic Survey Telescope (LSST) at the University of Washington and currently co-chair of the LSST Solar System Science Collaboration. She was part of the Survey/Detection panel of the  2010 NRC Commitee to Ceview Near-Earth-Object Survey and Hazard Mitigation Strategies. As part of her work with LSST, Dr Jones evaluates the scientific performance of LSST observing strategies, including the potential for studying small bodies with this next-generation telescope. She received her PhD from University of Michigan, conducting surveys to discover some of the faintest known (at the time) TransNeptunian Objects.

Bryce is a graduate student at the University of Washington and a member of the LSST Dark Energy Science Collaboration. He is interested in applying statistical techniques and machine learning to astronomical datasets and currently focusing on using such methods to improve the very different topics of photometric redshift estimation and asteroid detection.

Bob Abel is a professor of applied physics at Olympic College and collaborator with the University of Washington’s Large Synoptic Survey Telescope Group.

A lifelong daydreamer and former advertising creative, Jim learned from some of the smartest, and most ridiculously creative people in the business before forming a creative agency in Seattle and London. It was this relationship with creativity that inspires change and a chance encounter with Saturn that has sparked his present endeavor.

Jim now has turned his focus skyward co-founding Look Up where he serves as Wondernaut and Executive Director. Look Up explores the power of wonder through art, science and space. The organization is creating collaborative experiences designed to incite curiosity, wonder and further our unrealized potential.

Robert Hart, Ph.D., is currently VP and General Manager of the Institute for Disease Modeling, an operating unit of the Global Good initiative at Intellectual Ventures. 

IDM utilizes advanced mathematical modeling and statistical and large data analysis to help devise policy and programs that will advance the efforts of Bill Gates, the Bill and Melinda Gates Foundation, CDC, WHO and multiple ministries of health around the globe to control and eradicate infectious disease in the developing world.  Dr. Hart received his BS degree in Geophysics from the Massachusetts Institute of Technology and MS and PhD degrees in Geophysics from the California Institute of Technology.  He has founded and managed multiple software companies as an entrepreneur and as a venture capitalist, spanning the fields of nuclear test detection, oil and mineral exploration, image analysis and machine vision, wireless telecom technologies, ultrasound, and early disease detection among others. 

He is an avid amateur astronomer and spends much of his spare time traveling, scuba diving and indulging in underwater photography around the world with his marine biologist wife and, whenever possible, with his three sons and their wives.

June 27-29, 2018.

I work on Galactic Archaeology, which is the study of the structure and evolution of the Milky Way. I did my PhD at New Mexico State University working with Jon Holtzman and Jo Bovy with the APOGEE survey, which is an SDSS3 and SDSS4 spectroscopic survey of several hundred thousand red giants across the Milky Way. I spent two years working in Nice at the Observatoire de la Cote d’Azur with the Gaia-ESO and AMBRE projects, which have spectroscopic observations of tens of thousands of stars throughout the Galaxy. 

Currently, I am an ASTRO 3D fellow working at the University of Sydney with the GALAH Survey. GALAH  is a large-scale spectroscopic survey of 500,000 stars throughout the Milky Way, and aims to measure chemical abundances for 30 different elements to map and chemically tag the stellar populations of the Galaxy. In my talk, “Chemical Cartography of the Milky Way”, I will discuss the chemodynamic properties of different stellar populations throughout the disk and how they vary with location.

I attached a figure of some preliminary results from the GALAH survey, showing how the chemical structure of the disk varies from the inner Galaxy to the edge of the disk.

My research interests lie in Outer Solar System object detection and planetary habitability. For the Outer Solar System, I work on the detection of moving objects below the single-frame noise floor using a gpu-accelerated “shift-and-stack” pipeline called KBMOD. More broadly, I am interested in applying advanced statistical methods to big data in order to utilize these data sets to their fullest extent. For exoplanets, I study the impact of orbital dynamics on the habitability of exoplanetary systems using a multiphysics software suite called VPLANET.

Astronomical observations can probe physical phenomena at length and time scales, possibly in exotic environments largely inaccessible to terrestrial laboratories. While this underlies some of the successes of cosmological surveys over the past decades in discovering new physics, extracting such information is challenging because the data are typically noisy, and includes effects due to different processes (astrophysical, atmospheric and instrumental) tangled together in complex ways. I work in the area of extracting (inference along with classification) of such information from large surveys and am particularly interested in cosmology at late times, mostly through transients like supernovae and large scale structure. I am currently involved in LSST and ZTF. 

October 22-23, 2018.

Katy is a Ph.D. candidate in the Department of Statistics at Harvard University. She does research as a member of both the CHASC: Astrostatistics Group and the Sports Analytics Lab at Harvard. Her Tuesday 12pm talk will be on Defining Regions that Contain Complex Astronomical Structures.

November 8-9, 2018.

I’m a James Arthur Postdoctoral Fellow at the CCPP, NYU. I also have a partial affilation at UMD, where I work with the exciting data from the Zwicky Transient Facility.

November 29-30, 2018.

I’m interested in galaxies: how did they form and end up looking the way they do today? There are lots of different ways to attack this problem: my interest is in observational studies of both nearby galaxies and their star clusters and also distant, high-redshift galaxies. I’ve used quite a few different telescopes and instruments, with a lot of emphasis on infrared observations with the Spitzer Space Telescope. 

April 12, 2019.

David A van Dyk is currently a Chair Professor in the Statistics Section of the Department of Mathematics at Imperial College London. He received his Ph.D. from the Department of Statistics at the University of Chicago and his B.S. in Statistics and Probability from Michigan State University. Professor van Dyk was elected Fellow in the American Statistical Association in 2006. His research focuses on Statistical Computation, Statistical Methods in Astronomy, Causal Inference, and Statistical Analysis with Missing Data.

I am interested in developing data analysis techniques using the latest advances in statistical inference in order to leverage complex astronomical data. I work on probabilistic cataloging, a novel Bayesian technique that is able to handle extremely crowded stellar fields. The method is able to handle deblending ambiguities by treating the number of sources itself as a parameter to be inferred, using trans-dimensional Markov chain Monte Carlo sampling.

Dr. Jones is an Assistant Professor of Statistics at Texas A&M University. His research interests include astrostatistics, hierarchical Bayesian modeling, machine learning methods, Monte Carlo methodology, and more. He has contributed work in exoplanet detection, light curve classification, and disentangling overlapping sources in spatial and spectral analysis.

His seminar talk, “Disentangling Overlapping Astronomical Sources using Spatial, Spectral, and Temporal Information”, will be on Friday Feb. 22, 2019 at 11am in PAB, 3rd floor in conference room  B305.

Hložek studies a variety of problems in theoretical and observational cosmology through observations of the Cosmic Microwave Background, Type Ia supernovae and Baryon Acoustic Oscillations.

Using data from the Atacama Cosmology Telescope, her research focuses on constraining cosmological models, as well as determining the structure and amount of dark energy in the Universe.

She uses Baryon Acoustic Oscillations to constrain and test models of the Universe, and is interested in methods of extracting the signal from both spectroscopic and photometric galaxy surveys.

She also developed BEAMS, Bayesian Estimation Applied to Multiple Species, a statistical method for performing parameter estimation in the presence of contaminated cosmological data, which she applies to datasets such as the SDSS-II SN survey.

Hložek studied at the University of Pretoria and the University of Cape Town. She received her DPhil from the University of Oxford in 2011, where she was a Rhodes Scholar. Before coming to the Dunlap, she was a Lyman Spitzer Jr. Postdoctoral Research Fellow in the Department of Astrophysics at Princeton University and the Spitzer-Cotsen Fellow in the Princeton Society of Fellows. She is also a Senior TED Fellow.

2019-03-26 Lunch Talk: Renée Hložek

My research focuses on developing novel statistical methods for astronomy and cosmology. I am particularly interested in using Type Ia supernovae to probe the accelerated expansion of the universe that we believe is due to some form of “dark energy”.

One aspect of my research focuses on identifying Type Ia supernovae among the millions of astronomical transients that upcoming astronomical surveys such as the Large Synoptic Survey Telescope (LSST) will discover. I am currently developing the “avocado” software package that uses machine learning to classify different kinds of astronomical transients from sparsely sampled light curves with heteroskedastic noise. I am interested in understanding how biases in our observational strategies affect the performance of photometric classifiers and lead to biases in our cosmological measurements.

I am also working on developing better methods to estimate the distances to Type Ia supernovae. This involves using manifold learning techniques to parametrize the diversity of Type Ia supernovae and building non-linear models of their light curves.

Ashley Villar is a Ford Foundation Dissertation Fellow at Harvard University. She studies the eruptions, mergers and explosions of stars using statistical and data-driven methods. Her 10am talk, on Tuesday, November 12th, will be on “Time-domain Astrophysics in the Era of Big Data.” Ashley completed her undergraduate degree in Physics at MIT in 2014. She is super into the statistics of ghost hunting.

2019-11-12 Seminar: Ashley Villar

When: Tuesday, November 12th, 2019 @ 10:00am  Where: PAB, 6th Floor, eScience Studio, Seminar Rm.

Adam is an NSF Graduate Research Fellow and PhD student in the University of Michigan’s Department of Astronomy. He’s interested in how galaxies form and evolve, from the smallest dwarf galaxies to large galaxies like the Milky Way. He uses the gas content, resolved stellar populations, and satellite populations of massive galaxies to understand how they change as a result of their interactions with other galaxies.

More here.

Seminar: The Satellites and Stellar Halos of Nearby MW-mass Galaxies

When: Monday, December 9th, 2019 @ 12:30pm  

Where: PAB, 6th Floor, eScience Studio, Seminar Rm.

Keaton is a NSF Astronomy and Astrophysics Postdoctoral Fellow carrying out an integrated program of research and education titled “Discovering the First Exoplanets Around White Dwarf Stars with the Zwicky Transient Facility.” He aims to open a new field of exoplanet science by searching for and characterizing the first worlds in orbit around white dwarfs, which will ultimately reveal how exoplanets survive and are affected by the violent late stages of stellar evolution.  He is also working to train the next generation of astronomers and data scientists as a research mentor to UW undergraduates.

A big fan of coding and physics, Dino earned a masters in Computational Physics at Faculty of Science Split, Croatia, on the topic of linear feature detection in astronomical images. Having re-analyzed the entire Sloan Digital Sky Survey (SDSS) ~16TB large image dataset he discovered his passion for Big Data and related image analysis problems. As a graduate student at University of Washington, Dino works on Large Synoptic Survey Telescope (LSST) Data Management code, adding support for cloud services and executing Science Pipelines in the cloud. To various different extent he is also involved in other projects such as image differencing, kernel based moving object detection (KBMOD) and deblending.

Angus is a Research Fellow in the German Centre for Cosmological Lensing at the Ruhr Universität Bochum, Germany. His undertook his PhD at the University of Western Australia, where he studied the growth and evolution of baryonic mass as a member of the Galaxy and Mass Assembly (GAMA) collaboration. Following his PhD, Angus worked for the Kilo Degree Survey (KiDS) at the Argelander Institute for Astronomy at the Universität Bonn, where he began his work within weak gravitational lensing. For the last 3 years his research has focused on weak lensing survey science, and particularly on optimisation of photometric image reduction and analysis methods, systematics mitigation, and statistical analyses. Beyond weak lensing, Angus is a keen astrostatistician, a passable astronomy outreach presenter, and an enthusiastic but nonetheless mediocre golfer.

Seminar: Optimising Direct Redshift Calibration for Tomographic Cosmic Shear

When: Monday, March 9th, 2020 @ 12:30pm  

Where: PAB, 6th Floor, eScience Studio, Seminar Rm.

Spencer Nelson is a software engineer working on alerting systems for the Rubin Observatory, ZTF, and SCiMMA. Before joining DIRAC, Spencer worked in industry as a data scientist and software engineer.

Jennifer leads account activities for several clients and manages operations and business development for Communiqué PR. She is the co-author of Strategic Public Relations: 10 Principles to Harness the Power of PR.

Ken Myer is an interim executive for companies going through organizational transitions and is also a leadership lecturer at the UW Foster School of Business. A graduate of the University of Washington with a Masters in Speech Communication and an MBA, Myer began his professional career at IBM where he held a variety of positions including CFO, and then General Manager of the Northwest region. After IBM he went on to hold successful leadership roles at Active Voice, Interval Systems (which he co-founded), and as CEO of the Washington Technology Industry Association. Most recently Myer has served as interim leader for a variety of companies including Yapta, Vivid Robotics, Hydramaster, and Data I/O. Ken has been recognized three times for building a “best company to work for” and in 2009 was recognized as one of Seattle’s most influential business leaders. He is on the on the board of directors of the Washington Trails Association and is an avid hiker and backpacker.

I am a member of the LSST Data Management team and develop software for the LSST Alert Pipeline.

I work on the image differencing features. Following my graduate studies in astronomy, earlier I worked on the data processing pipeline of an ESA exoplanet mission (CHEOPS).
My main research interests are transiting exoplanets and young eclipsing binaries. Beyond astronomy, I am interested in the application of data science in social and economical studies. I have degrees in Physics and Economics.