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2016-2018 LSSTC DSFP Student Cohort

Below, you will find information about the talented students taking part in the LSSTC Data Science Fellowship Program.


Abolfathi
Bela Abolfathi
University of California - Irvine
2016 LSST Data Science Fellow
Bela is a graduate student at the University of California in Irvine. Her research uses cosmological probes of dark energy such as baryon acoustic oscillations and weak gravitational lensing to study the evolution of the universe.
Alcorn
Leo Alcorn
Texas A&M University
2017 LSST Data Science Fellow
Leo is a PhD student in Astronomy at Texas A&M University. She studies the evolution of galaxies at high redshift in cluster and proto-cluster environments. Her recent work focuses the morphology and kinematics of star-forming galaxies at z~2, the peak of cosmic star-formation history.
Amon
Alexandra Amon
University of Edinburgh
2017 LSST Data Science Fellow
Alexandra is a PhD student at the University of Edinburgh, working as part of the Kilo-Degree Survey (KiDS). Her research uses weak gravitational lensing in conjunction with other cosmological probes to test gravity and study the dark universe.
Babatunde
Akinsanmi Babatunde
Universidade do Porto
2017 LSST Data Science Fellow
Tunde is a graduate student at the University of Porto, Portugal. He is interested in the study and detection of exoplanets using radial velocity and transit techniques. Currently his research uses computational tools to explore the possibility of detecting rings around transiting exoplanets.
Blancato
Kirsten Blancato
Columbia University
2016 LSST Data Science Fellow
Kirsten is a PhD student in Astronomy at Columbia University. She is interested in galaxy formation and evolution and most recently has been working on studying the stellar populations of galaxies in the Illustris Simulation.
Chase
Eve Chase
Northwestern University
2016 LSST Data Science Fellow
Eve is an astronomy graduate student at Northwestern University and recent graduate of the College of William & Mary. She studies computational and data analysis techniques related to gravitational wave astronomy.
Ciuca
Ioana Ciuca
University College London
2017 LSST Data Science Fellow
Ioana is a PhD student at the Mullard Space Science Laboratory, University College London, studying how the Milky Way formed and evolved by analysing the chemo-dynamical structure of the mono-age stellar population of the Galactic disc using ESA's Gaia data together with her advisor, Dr Daisuke Kawata. She is passionate about finding patterns in big data using machine learning. Her other passions are chess tactics, films and travelling around the world.
Fields
Carl Fields
Michigan State University
2017 LSST Data Science Fellow
Carl is an Astronomy & Astrophysics Ph.D. student at Michigan State University. His researches focusses on astrophysical sources of gravitational waves, stellar nucleosynthesis, and multi-dimensional simulations of core collapse supernova explosions and their massive star progenitors.
George
Daniel George
NCSA and University of Illinois at Urbana-Champaign
2017 LSST Data Science Fellow
Daniel is an Astronomy PhD student at the University of Illinois, Urbana-Champaign. He is currently a Research Assistant in the Gravity Group at NCSA and a member of the LIGO, NANOGrav, and DES collaborations working at the interface of deep learning, high-performance computing, and gravitational wave and multimessenger astrophysics.
Giles
Daniel Giles
Illinois Institute of Technology
2017 LSST Data Science Fellow
Daniel is a Physics Ph.D. student at Illinois Tech working on automating the discovery of anomalous data for large astrophysical surveys. He is using machine clustering techniques to identify lightcurves that don't fit into the norm and might provide new insights into astrophysical phenomena, or simply identify bad data.
Gonzales
Eileen Gonzales
CUNY Graduate Center
2017 LSST Data Science Fellow
Eileen is a graduate student at the CUNY Graduate Center in New York City and is part of the Brown Dwarfs in New York City Research Group (BDNYC). She is looking at spectral energy distributions of brown dwarfs and low-mass stars to better understand their atmospheric properties.
Hendler
Nathanial Hendler
Lunar and Planetary Lab, University of Arizona
2017 LSST Data Science Fellow
Nathan is a graduate student at the Lunar and Planetary Laboratory working with Ilaria Pascucci. His research focuses on studying planet formation by way of protoplanetary disk observations with ALMA.
Hosseinzadeh
Griffin Hosseinzadeh
Las Cumbres Observatory & UC Santa Barbara
2017 LSST Data Science Fellow
Griffin is a Ph.D. candidate at the University of California, Santa Barbara. He studies supernovae using Las Cumbres Observatory's network of robotic telescopes, and is heavily involved in scheduling and data reduction for the Global Supernova Project.
Jiang
Tianxing Jiang
Arizona State University
2016 LSST Data Science Fellow
Tianxing is a graduate student at Arizona State University in Tempe, AZ. She is interested in many topics in observational extragalactic astronomy, e.g. galaxy evolution, extreme emission-line galaxies, high-redshift galaxies, epoch of reionization. She is excited to get involved in LSSTC data science!
Jin
Dongming Jin
University of Texas - Arlington
2016 LSST Data Science Fellow
Dongming is a Physics Ph.D. student at UT Arlington. He is conducting stellar simulations about compact binary systems in globular clusters with N-body and MOCCA codes.
Kawinwanichakij
Lalitawadee (Nancy) Kawinwanichakij
Texas A&M University
2016 LSST Data Science Fellow
Nancy is a PhD student at Texas A&M University. She is interested in studying the formation and evolution of galaxies using primarily observational techniques. Her recent work focuses on using satellite galaxies to test of the nature of dark matter and feedback mechanisms in galaxy evolution.
Khakpash
Somayeh Khakpash
Lehigh University
2017 LSST Data Science Fellow
Somayeh is a graduate student at Lehigh University. She is interested in studying exoplanet transits, stellar astrophysics and microlensing method of discovering exoplanets. Her current project involves working on M-dwarf light curves and looking for M-M binaries. She also plans to get more involved in the the microlensing projects for discovering exoplanets.
Leung
Cecilia Leung
University of Arizona
2016 LSST Data Science Fellow
Cecilia is a planetary scientist at the University of Arizona studying atmospheric dynamics and climates of terrestrial planets, as well as their effects on habitability. She has also worked on the dynamics of small bodies in our solar system.
Lucy
Adrian B. Lucy
Columbia University
2017 LSST Data Science Fellow
Adrian is a PhD candidate at Columbia University, where ey's looking for symbiotic stars—vampiric stellar binaries in which a cool giant detectably transfers mass towards a hotter companion. Sifting through giants in a multi-dimensional parameter space built from several large surveys, Adrian hopes to lay a substrate on which the true extent and impact of astrophysical symbiosis may be revealed.
Moeyens
Joachim Moeyens
University of Washington
2016 LSST Data Science Fellow
Joachim worked as a research scientist assistant for LSST and is an incoming graduate student at the University of Washington. He is interested in big data and software driven solutions in observational astronomy.
Mondrik
Nicholas Mondrik
Harvard University
2016 LSST Data Science Fellow
Nicholas is a graduate student in the Department of Physics at Harvard. His interests include photometric calibration of large surveys, the magnetic properties of M-dwarfs, and the role of M-dwarfs as exoplanet hosts.
Moreno
Jackeline Moreno
Drexel University
2016 LSST Data Science Fellow
Jackie is a graduate student at Drexel University. She works with AGN/Quasar lightcurves to learn more about their diverse morphology and accretion disc physics. She is also interested in star formation and properties of all types of galaxies and how they relate to galaxy evolution.
Müller
Tomás Müller
Pontificia Universidad Católica de Chile, Chile
2016 LSST Data Science Fellow
Tomás is a chilean astronomer at Pontificia Universidad Católica de Chile. His current work focuses on Type II Supernovae, although his main research interests include: Cosmology, CMB, Large-scale structures and gravitational lenses.
Peters
Charee Peters
University of Wisconsin - Madison
2016 LSST Data Science Fellow
Charee is a graduate student pursuing an astronomy PhD at the University of Wisconsin - Madison. She is interested in transient and variable events in a new radio survey called CHILES. In her free time, she plays roller derby under the name SiouxperNova.
Prajs
Szymon Prajs
University of Southampton, United Kingdom
2016 LSST Data Science Fellow
Szymon is a student at the University of Southampton, UK working as part of the Dark Energy Survey. His current projects involve studying physical properties of Superluminous Supernovae and photometric classification of new and unusual classes of transients in large data sets.
Robinson
James Robinson
Queen's University Belfast
2017 LSST Data Science Fellow
James is a PhD student at the Astrophysics Research Centre of Queen's University Belfast. He is interested in the formation and evolution of trans-Neptunian binaries and is currently looking at the production of wide, equal mass components with n-body gravitational collapse models..
Rojas
Karina Rojas
Universidad de Valparaíso
2017 LSST Data Science Fellow
Karina is a PhD student, and she studies gravitational lensing effect at different scales in the universe: 1. galactic microlensing events in our galaxy, 2. Strong and microlensing effect in lensed quasars to study the lens galaxy and the inner structure of the quasar, 3. Dynamical analysis of lens group and cluster of galaxies. In her free time, she enjoys doing outreach in spanish under the name of "Star Tres" – a group of three chilean astronomers using different social networking tools (videos, infographics, notes, tweets).
Shipp
Nora Shipp
University of Chicago
2016 LSST Data Science Fellow
Nora is a graduate student at the University of Chicago. She is interested in using simulations and astrophysical observations to constrain dark matter physics.
Thomas
David Thomas
Standford University
2017 LSST Data Science Fellow
David is a graduate student at Stanford University. He is interested in using statistical inference, machine learning, and high performance computing to advance gravitational lensing and to better constrain cosmological parameters. David is looking forward to working with and learning from everyone in the LSST Data Science program.
Vejar
George Vejar
Vanderbilt University
2016 LSST Data Science Fellow
George is a Masters student in the Fisk/Vanderbilt Bridge to Doctorate Program. He is currently studying planetary nebulae and stellar atmospheres through simulated and observed spectra.


Student Auditors

Our auditors are a select group of local students who attend the full LSSTC DSF session hosted by their university.


Aganze
Christian Aganze
University of California - San Diego
Intro to Data Science - Session 1
Christian is a graduate student at UC San Diego. He is interested in studying formation and evolution of very low- mass stars brown dwarfs and exoplanets by characterizing their atmospheres, and studying their population statistics throughout the Milky Way galaxy.
Dempsey
Dino Bekteševic
University of Washington
Session 4
Dino is an astronomy PhD student at University of Washington. He studies computer vision techniques and their application on sky surveys, with special interest in linear features attributed to meteors.
Dempsey
Adam Dempsey
Northwestern University
Intro to Data Science - Session 1
Adam is a graduate student in astronomy at Northwestern University working with Yoram Lithwick. His research focuses on hydrodynamical simulations of planet formation, but he is also interested in the evolution of planetary systems, spiral waves in accretion disks, GPU and high performance computing, and using large survey datasets to map the Galactic potential.
Dirks
Cody Lee Dirks
Northwestern University
Intro to Data Science - Session 1
Cody is a graduate student in astronomy at Northwestern University. His research is in observational studies of the diffuse interstellar medium, focusing on understanding how the diffuse ISM transitions into molecular star-forming regions.
Vines
Dillon Dong
California Institute of Technology
Machine Learning and Visualization - Session 2
Dillon is a Ph.D student in Astronomy at Caltech. He is currently studying star formation in nearby galaxies with the Star Formation in Radio Survey, and exploring the transient radio sky with the VLA Sky Survey.
Vines
Meredith Durbin
University of Washington
Session 4
Meredith is a graduate student at the University of Washington. Their work focuses on resolved stars in nearby galaxies, including characterizing emission-line stars in M31 and predicting WFIRST's ability to measure ages and metallicities of halo populations.
Vines
Matt Hartley
California Institute of Technology
Machine Learning and Visualization - Session 2
Matt is a Caltech graduate student searching for cataclysmic variables, and other rare and unusual sources, using light curves from the Palomar Transient Factory.
Vines
Anna Ho
California Institute of Technology
Machine Learning and Visualization - Session 2
Anna is a graduate student at Caltech, working on the search for orphan afterglows to GRBs in preparation for the ZTF era. She is also interested in millisecond pulsars and data-driven modeling of stellar spectra.
Jin
Miaotianzi Jin
Northwestern University
Intro to Data Science - Session 1
Miaotianzi is an experimental physicist at Northwestern University. He is searching for Dark Matter directly with underground bubble chambers, and he is also interested using machine learning to help analyzing bubble pictures.
Vines
Bryce Kalmbach
University of Washington
Session 4
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 these in ways that can improve photometric redshift estimation.
Vines
Matt Kirby
University of Arizona
Databases and Scalable Programming - Session 3
Matt is a graduate student in physics at the University of Arizona. He is interested in using photometric galaxy surveys to constrain cosmology and cluster scaling relations. While he currently works with galaxy clusters, he is also interested in using both weak lensing and supernovae.
Vines
Lee Rosenthal
California Institute of Technology
Machine Learning and Visualization - Session 2
Lee is a graduate student at the California Institute of Technology. His first research project involves exploring database search methods for supernovae candidates in the Palomar Transient Factory and Zwicky Transient Facility.
Vines
Jan-Torge Schindler
University of Arizona
Databases and Scalable Programming - Session 3
J-T is working with Prof. Xiaohui Fan on an all-sky catalog of bright high redshift quasars to study the early growth of the most massive SMBHs, update the bright end of the quasar luminosity function and provide new quasar sight lines for studies of the Intergalactic Medium.
Vines
José Vines
University of Chile, Chile
Intro to Data Science - Session 1
José is an astronomy and computer science student at the University of Chile in Chile. His main interest is extrasolar planets (aka. exoplanets) and their formation.
Vines
Erika Wagoner
University of Arizona
Databases and Scalable Programming - Session 3
Erika is a graduate student in physics at University of Arizona. She is interested in baryon acoustic oscillations using photometric galaxy surveys including the Dark Energy Survey and LSST.


Cohort Group Photos

Please click the photos below to view a larger image.


Northwestern University, Summer 2016
California Institute of Technology, Winter 2017
 
National Optical Astronomy Observatory, Spring 2017