DSSI Class of 2022

Undergraduate student in Bioengineering at UC Merced

Ethan Ahlquist is pursing a B.S. at California Polytechnic State University. His internship supported the curation and publication of LLNL metal additive manufacturing data.

Justin is pursuing a BS in Computer Science at UC San Diego. He is interested in applying machine learning to network data in order to predict malicious attacks.

An undergraduate in Computer Science at UC San Diego, Justin works on predicting processes from network data.

A PhD student at UC Merced, Jacqueline Alvarez evaluated various neural network architectures on a datasets involving gamma spectroscopy.

Sven Amaya is pursing a Masters degree at California State University, Sacramento. His internship investigated impacts of multi-simulation data on mesh tangling prediction.

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.

Georgia Institute of Technology

PhD student in Quantitative and Systems Biology at UC Merced

Porter Bagley, an undergraduate at Brigham Young University, enjoys studying deep text modeling.

Ryan is pursuing a BS in Applied Analytics and International Relations. He is interested in natural language processing for transactional data.

A PhD student at Arizona State University, Bryce Barclay worked on acceleration of multi-species transport by dimensionality reduction in combustion engine computational fluid dynamics.

Brian is pursing a PhD in Computational Science at FSU Tallahassee. His interests include multimodal data retrieval with neural networks.

A PhD student at the University of California, Santa Cruz, Sabyasachi Basu worked on understanding temporal subsampling for flow fields.

Master's student in Computer Science at the University of Minnesota

Sila Baykal is a student at Portland State University. During her internship, Sila built a logistic regression classifier for MNIST dataset and image classification.

PhD student in Astrophysics at UC Irvine

PhD student in Computer Science at the University of Texas

Ryan is pursuing a PhD in Computer Science at UNL. His interests include predicting power spikes in site-wide power usage.

Eric is pursuing an MS in Computer Science at Purdue. His interests include topological data analysis of chemical systems.

PhD student in Structural Engineering at Cornell University

Emory University

PhD student in Statistics at Arizona State University

A PhD student at Notre Dame University, Zachariah Carmichael developed new HPC-centric algorithms and methods for neural architectures.

A PhD student at UC Berkeley, Nicolas Castrillon worked on developing fast, accurate physics-informed surrogate models for various physical simulations.

Undergraduate student in Computer Science at UC Santa Cruz

Nicholas is getting a master's in Computer Science at New York University. His summer project was MINOS event predictions with graph neural networks.

University of Iowa

PhD student in Mechanical Engineering at Stanford University

Tim is pursuing a PhD in Statistics at the University of Pittsburgh and is interested in random forests.

Interested in wireless networking, Cazamere Comrie is pursuing his PhD at Cornell University.

PhD student in Mathematical Sciences at Portland State University

During his internship, University of Arizona PhD student Justin Crum worked on the Tardigrade project.

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.

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.

A PhD student at the University of Chicago, Adela DePavia developed new parametric probability distributions over sets and hypergraphs that can reasonably be inferred from data.

Carlos is pursuing a BS in Computer Science at SSU. His interests include applying Fourier analysis to detect wave patterns within discrete data obtained from ReSCAL simulations.

University of California, Los Angeles

PhD student in Engineering and Data Science at UC Riverside

Alec Dunton is a PhD candidate at the University of Colorado at Boulder. During his internship he studied matrix sketching algorithms for large-scale graph clustering.

A PhD student at Purdue University, Duy Duong-Tran studies network properties of brain connectivity.

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.

Master's student in Statistics at UC Santa Cruz

Undergraduate student in Computer Science and Engineering at UC Merced

University of Colorado, Boulder

A PhD student at the University of Arizona, Tucson, Pier Fiedorowicz worked on improving particle reconstruction in high-energy physics experiments using ML.

Master's student in Computer Science and Software Engineering at Texas A&M

University of California, Santa Barbara

A PhD student at Kyushu University in Japan, Yasuhisa worked on SARS-CoV-2 quasi-species sequence analysis.

Jose Garcia-Esparza is pursuing a B.S. at the University of California, Merced. His internship supported machine learning research for the Feedstock Optimization project, which entailed developing and evaluating ML techniques for the prediction of material properties.

A PhD student at Michigan State University, Craig Gross worked on the Arcelor Mittal project. During his internship he learned current processes for running fluid mechanics simulations using OpenFoam software on HPC resources.

Emilia Grzesiak, a graduate student at Duke University, is interested in the CRISPR Genetic Engineering Detection project.

Anthony Guerra is pursuing an M.S. at the University of Southern California. His internship explored a data science pipeline: taking raw imagery, converting it into a usable format, and using that imagery to train a convolutional neural network for classification and detection.

Huan He, a PhD student at Emory University, worked on an uncertainty quantification in DL project using approaches like Bayesian neural networks and post-hoc calibration.

A PhD student at UC San Diego, Xiaolong He worked on developing an efficient surrogate model for instability problems by training various neural networks.

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.

Joseph is pursuing an MS in Statistics and Data Science at Stanford. His interests include natural language processing, specifically using machine learning to identify entities and their relationships within large bodies of text.

A PhD student at the University of Michigan, Ava Hill worked on a project to combine ML and nuclear physics to improve characterization of nuclear model composition.

A PhD student at UC Merced, Alex Ho worked on improving robustness in reinforcement learning agents.

A Masters student at Stanford University, Elyssa Hofgard worked on assessing impact of the incorporation of additional climate variables on DL seasonal predictions of precipitation and temperature over the Western U.S. 

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.

A PhD student at Portland State University, Ruizhi Hua worked on a graph clustering project using DL.

Shoya Iwanami is pursuing a PhD at Kyushu University's (Japan) graduate school of Systems Life Sciences. Shoya's internship project combined machine learning with adaptive sampling molecular dynamics methods to study the reversible binding-unbinding process of a molecular force probe.

Lisa is pursuing her PhD in Computer Science at University of Rochester. Her interests include drug molecule representation learning to improve predictions of tumor response.

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 informa

Eric is pursuing at PhD at UC Davis in Statistics. 

Aidan is pursuing at BS in Computer Science at UC San Diego.

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.

Hyotae is pursuing a PhD in Statistics at UCSC. His interests include nonparametric Bayesian models for the survival function.

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.

Undergraduate student in Computer Science and Engineering at UC Davis

Sean Kulinski, a Purdue University PhD student, is interested in safe and trustworthy machine learning.

Cynthia is pursuing an MS in Computer Science at UCLA. Her interests include improving performance for self-supervised learning.

University of California, Merced

PhD student in Materials Science at Carnegie Mellon University

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.

Samuel Lewis is pursing a B.S. at Oregon State University. His internship explored adversarial behavior in the Decentralized Autonomous Networks for Cooperative Estimation (DANCE) project.

PhD student in Applied Mathematics at UCLA

PhD student in Computer Science at Duke University

University of California, Los Angeles

PhD student in Electrical and Computer Engineering at the University of Utah

Ankur is pursuing a PhD in Electrical and Computer Engineering at Carnegie Mellon.

Daniel Malone is pursing a B.S. at Brigham Young University, majoring in statistics. His internship supported the Joint Test Assembly by developing algorithms to convert and parse raw data into organized, usable data and manipulating large datasets using R or Python.

Sahiyta is pursuing an MS in Computational and Mathematical Engineering at Stanford. She is interested in object-centric video representation learning.

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.

University of California, Los Angeles

University of California, Berkeley

University of California, Merced

A PhD student at UC Irvine, Eric Medwedeff worked on applying microscopic physics to the macroscale through DL.

A PhD student at Tulane University, Akshay Mehra worked on exploring advanced ML techniques to analyze the extract material science data to infer general chemistry of classes of materials.

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.

During his internship, Nagoya University PhD student Kentaro Mori worked on developing data-driven optimization models for transportation planning.

Yamen is pursuing a BS in Physics and Cognitive Science from UC San Diego. His interests include using machine learning to simulate physics problems.

Joy Mueller, a PhD student at the University of Colorado, Boulder, supported the Multilevel Methods project. This effort involved developing deep neural networks for accelerating Markov Chain Monte Carlo simulations.

University of Washington

Garrett Mulcahy is pursing a graduate degree at Purdue University. His internship supported supervised learning of outermost operator in symbolic regression.

Jordan Murphy is pursuing a PhD in Aerospace Engineering at the University of Colorado, Boulder. Jordan's internship focused on simulation, inference, and prediction for stochastic orbit models.

Michelle Ngo is pursuing a PhD at the University of California, Irvine. During her internship she worked on quantifying uncertainties of microscopic nuclear theories.

University of Michigan, Ann Arbor

Kyusha University

Nagoya University

A PhD student at UC Merced, Haoyu Niu worked on discrete optimization tasks.

University of Tokyo

Alan is a computer science student at California State University East Bay. His interests include DL and the complete software development lifecycle.

A PhD student at Florida Agricultural & Mechanical University, Damilola Ologunagba worked on molecular graph neural networks with Gaussian process for property prediction, embedding, and uncertainty-informed sampling of corrosion inhibitor-metal coordination complexes.

University of California, Merced

Adriana Ortiz-Aquino, a PhD student at Kansas State University, worked on the ADAPD Hard Problem 2 project, which involved exploratory analysis of complex structured data.

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.

An M.S. student at Carnegie Mellon, Leonardo Pinero-Perez worked on the PySCES project developing tools and modeling capabilities to rapidly assess the potential scope of impacts that a cyber-attack can have on energy infrastructure.

Randy Posada is pursuing a B.S. at UC Merced. His internship supported the drug safety project.

A PhD student at UC Merced, Maia Powell worked on a cross-platform authorship attribution project extending DL-based models to generalize between social media platforms to find the same author across different social media and have a model generalize to unseen authors.

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.

Undergraduate student in Data Science at UC Berkeley

Alex John is an Applied Mathematics PhD student at UC Merced. He obtained his BS in Mathematics from East Tennessee State University.

Benjamin is pursuing a BS in Computer Science at Northeastern University. His interests include applying machine learning to additive manufacturing.

Albert Reed, a PhD student at Arizona State University, worked on a computed tomography reconstruction project using generative adversarial networks.

Majerle is pursuing a PhD in Applied Mathematics at UC Merced and works on modeling time series data using differential equations and NNs.

Andrei Rekesh is pursuing a B.S. at UCLA. His internship supported drug discovery using feature optimization for safety and pharmacokinetic property prediction.

A PhD student at Pennsylvania State University, Nicholas Rios support the uncertainty quantification for charge-exchange reactions project using Gaussian processes as the target emulator. 

PhD student in Psychology at UC Berkeley

Aaron is pursuing a BS at the Ohio State University. 

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.

Undergraduate student in Nuclear Engineering at UC Berkeley

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. 

Master's student in Applied Statistics at the University of Michigan

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.

University of California, Davis

PhD student in Applied Mathematics at Cornell University

Nicole Stiles is pursuing her B.S. degree at the Massachusetts Institute of Technology. Her internship supported the methods for NLP-enabled exploratory analysis of multi-omics datasets project using statistical and ML techniques.

Furong is pursuing a PhD in Statistics from Virginia Tech. Her interests include Bayesian calibration of computer models.

Undergraduate student in Statistics and Computer Science at California Polytechnic State University

A PhD student at the University of California, Davis, Jack Swett worked on the MADSTARE project during his internship.

Undergraduate student in Physics and Astronomy at the University of Rochester

Clayton is pursuing an MS in Computer Science from UMass Amherst. His interests include using deep reinforcement learning to find personalized treatments for sepsis.

Uttara is pursuing a PhD in Industrial Engineering at Purdue University.

Ayme Tomson is a PhD student at the University of California, Merced, working on the Valkyrie project, which is focused on information extraction from scientific publications.

Tuyen is a Mathematics PhD candidate at Portland State University. Her research interests include convex optimization, convex analysis, DC programming, and ML.

Ken is pursuing a PhD in Computer Science from NCSU. His interests include "satellites!"

University of Illinois, Urbana-Champaign

PhD student in Electrical Engineering and Computer Science at UC Merced

A PhD student at the University of Albany, Tuan Tran worked on a project developing new HPC-centric algorithms and methods for neural architectural search leveraging existing open-source DL and reinforcement learning toolkits. 

Jason Van Tuinen is pursuing a B.S. from UC Merced. His internship supported ML for pattern-of-life analysis in time series data, which entailed implementing a Python algorithm to enable the user to analyze a data stream and examine patterns found in it.

Kaushik Velusamy, a PhD student at the University of Maryland, investigated pattern matching in dynamic graphs during his internship.

Di is pursuing a PhD in Computer Science at the University of Utah. His interests include data visualization.

Yinan Wang is pursing a PhD from Virginia Tech. During his internship, Yinan worked on spatial-temporal dependencies using a data-driven method to predict the “cloud” evolution.

Hannah, a master's student in Statistics at Brigham Young University, is interested in Bayesian modeling with Gaussian processes.

PhD student in Statistics at UC Irvine

PhD student in Pharmaceutical Science at Purdue University

PhD student in Applied Mathematics at the University of Colorado

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.

Takahiro Yamakoshi is pursuing at PhD in Informatics at Nagoya University (Japan). Takahiro's internship included using document relevance as distant supervision for domain-specific information extraction, as well as generating semantic graphs from a set of published articles.

A PhD student at South Dakota State University, James Young supported finding surrogate alternative chemicals and materials for national security applications.

Shehtab Zaman is pursuing his M.S. at Binghamton University. During his internship he investigated scalable deep learning and second order methods using the LBANN toolkit on GPU-accelerated HPC systems.

Ahsan is pursuing a BS in Computer Engineering and Computer Science at USC. His interests include using machine learning methods to predict the cervical cancer disease state.

A PhD student at Northeastern University, Zheng Zhan worked on finding accurate binary neural networks by pruning a randomly weighted network.

University of Texas at Austin

Gaofei Zhang is a PhD student at the University of Notre Dame. During her internship, she worked on the DANCE project.

During her internship, University of Minnesota PhD student Zechen Zhang supported the Numerical Techniques for Multi-scale Machine Learning project.

A PhD student at the University of California, Davis, Zhi Zhang's internship focused on a project with the American Heart Association.

Undergraduate student in Bioengineering at UC Santa Cruz

PhD student in Electrical and Computer Engineering at the University of Michigan, Ann Arbor

A PhD student at the University of Michigan, Jing Zhu developed algorithms that can ensure a more favorable balance of algorithmic fairness and performance in graph ML.

An undergraduate at the University of California, Merced, Teagan Zuniga developed an approach for organizing and retrieving nuclear safeguards data in a safeguards knowledge repository.