An undergraduate in Computer Science at UC San Diego, Justin works on predicting processes from network data.
DSSI Class of 2019
Meet the Data Science Summer Institute Class of 2019. Download their posters to get an idea of the type of work our interns undertake during their time at LLNL.
Gabriel is a PhD student in Computer Science at the University of Colorado, Boulder, co-advised by Rafael Frongillo and Joshua Grochow. He received both his MS in Applied Mathematics and BS in pure Math from the University of Massachusetts, Amherst.
Nicholas is getting a master's in Computer Science at New York University. His summer project was MINOS event predictions with graph neural networks.
Ryan is graduating with a BA in Physics, Astrophysics, and Data Science from UC Berkeley in December of 2019. His research interests include using ML techniques to approach astrophysical questions. At LLNL, Ryan worked on applying DL to find black hole microlensing events in MACHO data.
Omar is a PhD student in the Applied Mathematics department at UC Merced. His research focuses on DL techniques as they apply to image processing in a variety of modalities such as synthetic aperture radar and low-photon imaging.
Jose Cadena Pico and Alan Kaplan
Duy is a PhD student at Purdue University, working on the crossroad between industrial engineering/data science and neuroscience. He is interested in theoretical frameworks such as spectral graph theory, random graph, combinatorics, and stochastic processes.
Joanna is an undergraduate at the University of Iowa pursuing degrees in Mathematics and Music. This summer, she worked on developing new training labels in order to improve classification predictions for physics simulation data.
Jenna is an undergraduate student at James Madison University where she is studying Computer Science. Her work this summer includes an ML model used to make video predictions of sand dune data.
Anna is a student in the Computer Science MS program at the University of San Francisco. Interested in information management and with a background in theoretical linguistics, she focuses on the application of NLP for knowledge extraction. Previously she worked in information retrieval at corpora
Joanne is a recent graduate with a BS in Computer Science from Korea University. Her interests include using graph NNs to predict molecular properties and crystal structures. She will continue her research at LLNL as a post-college appointee.
Kelly is a PhD candidate at the University of Colorado, Boulder, in the Institute for Arctic and Alpine Research. Her research focuses on the representation of sub-grid scale snow processes in Earth system models, using computational and data science techniques.
Oscar is a PhD student in Computational and Applied Mathematics at Rice University, advised by Paul Hand of Northeastern University. He received his undergraduate degree in Mathematics from Swarthmore College. His research focuses on methods using DL to solve inverse problems.
Brian Van Essen
Erin is a Computer Science PhD student at the University of Oregon, advised by Allen Malony. Her interests include HPC and ML. At LLNL she worked on implementing distributed I/O for LBANN.
Eric is an undergraduate at UC Berkeley studying Mathematics.
Caleb is an Applied Mathematics PhD student at the University Of Colorado, Boulder.
Divya is pursuing a BS in Electrical Engineering and Computer Science at UC Berkeley. Her research this summer utilizes ML to simulate physical processes.
Sudeepta is a graduate student at Pennsylvania State University, pursuing an MA in Mathematics and PhD in Mechanical Engineering.
Alan is a computer science student at California State University East Bay. His interests include DL and the complete software development lifecycle.
Brian Van Essen
Anmol is a Computer Science PhD student at Marquette University. His research focuses on HPC and data science, usually mixed together and applied to a field like geospatial computing.
J.R. is a Nuclear Engineering PhD candidate at the University of Tennessee, Knoxville, advised by Jason Hayward and Howard Hall. He received his BS in Physics from the University of Virginia. His research focuses on applying data science tools to improve the performance of nuclear detectors.
Alex John Quijano
Alex John is an Applied Mathematics PhD student at UC Merced. He obtained his BS in Mathematics from East Tennessee State University.
Majerle is pursuing a PhD in Applied Mathematics at UC Merced and works on modeling time series data using differential equations and NNs.
Amar is a recent master's graduate from UC Merced and now a data scientist at LLNL working on DL, LEDs, and all areas of computer science.
Kayla will be returning to UC Los Angeles this fall to complete her undergraduate degree in Statistics. This summer, she worked on novelty detection for hazardous material release movement, including weather uncertainty analysis.
Mary Silva is a Statistics and Applied Mathematics masters student at UC Santa Cruz. She obtained her BS in Applied Mathematics from San Francisco State University. Her research focuses on spatiotemporal models in the climate sciences.
Hoseung, a PhD candidate in Statistics at UC Davis, worked on two-sample test and ML while at LLNL this summer.
Uttara is pursuing a PhD in Industrial Engineering at Purdue University.
Tuyen is a Mathematics PhD candidate at Portland State University. Her research interests include convex optimization, convex analysis, DC programming, and ML.
Hannah, a master's student in Statistics at Brigham Young University, is interested in Bayesian modeling with Gaussian processes.
McKell got her BS in Applied Mathematics from Brigham Young University and is starting her PhD in Computer Science at Rice University. This summer she built a temporally recurrent r2u-net for video segmentation.
Kaidi is a PhD student in Electrical and Computer Engineering at Northeastern University. His research focuses on the security of DL, especially adversarial attack and defense, and robustness certification of deep NNs.