2023-2025 Cohort

Matt Kwiecien

Matt Kwiecien is a third-year student in the Physics Department at the University of California, Santa Cruz. He is part of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). Matt will be working with university mentor Tesla Jeltema (UCSC) and lab mentor Marc Paterno (Fermilab) in the area of collaborative software infrastructure, specifically on development of the Firecrown Pipeline for LSST DESC. He will train in the development of scientific pipelines and software architecture for experiments. Matt entered graduate school at UCSC after working in industry as a software engineering team lead.

Johannes Wagner

Johannes Wagner is a fourth-year Physics Ph.D. student at the University of California, Berkeley. He is passionate about designing algorithms for high-energy collider physics. Johannes will focus on collaborative software infrastructure in heterogeneous computing and statistical data analysis. He plans to leverage compute-heavy machine learning for jet flavor tagging with the ATLAS detector, in collaboration with his university mentor Heather Gray (UCB) and lab mentor Simone Pagan Griso (LBNL). As an undergraduate, Johannes minored in computer science and data science to build a solid foundation in computing.

Eric Le

Eric Le is a second-year Ph.D. student in Physics at the University of California, Irvine. He works with the ATLAS group at UCI. Eric is focused on the area of hardware-software co-design in the integration of GPUs and FPGAs for triggers and track reconstruction. He will work with university mentor Anyes Taffard (UCI) and lab mentor Viviana Cavaliere (BNL) on optimizing algorithms and improving host-kernel data transfer for event filter tracking. Eric will also develop generic host code to load kernels across FPGAs and GPUs and maintain data transfer queues across different architectures.

Luc Le Pottier

Luc Le Pottier is a third-year student in the Physics Ph.D. program at the University of California, Berkeley. He works in the area of hardware-software co-design on FPGA-based data acquisition systems for high-energy experiments. Luc will work with university mentor Haichen Wang (UCB) and lab mentor Timon Heim (LBNL) on the development of a high-speed readout system for a pixel detector beam telescope. He is interested in improving the throughput of the system with careful attention to the hardware-software interface and limitations. In the past, Luc has lectured on machine learning in physics for undergraduates.

Russell Marroquin Solares

Russell Marroquin Solares is a second-year Physics Ph.D. student at the University of California, San Diego. His interests are in hardware-software co-design, specifically the implementation of advanced computational algorithms for machine learning and triggering technologies. Russell will collaborate with university mentor Javier Duarte (UCSD) and lab mentor Nhan Tran (Fermilab) to enhance the hls4ml tool for new FPGA firmware, making it possible to apply machine learning principles in FPGAs for the CMS experiment. He will also investigate pruning and supporting sparse ML models in hls4ml.

2024-2026 Cohort

Jade Chismar

Jade Chismar is a first-year Physics Ph.D. student at the University of California, San Diego. Her interests are in the area of high-performance computing, specifically particle tracking algorithms for high-energy physics. Jade will work with university mentor Frank Wuerthwein (UCSD) and lab mentor Giuseppe Cerati (FNAL) on a line-segment tracking (LST) algorithm for the CMS experiment. This algorithm is designed to be highly parallelizable and vectorizable on modern processors. Jade will investigate the machine learning possibilities for LST.

Miles Cochran-Branson

Miles Cochran-Branson is a first-year Physics Ph.D. student at the University of Washington. His interests are related to hardware-software co-design, especially in machine learning as-a-service with heterogeneous architectures. Miles will collaborate with university mentor Shih-Chieh Hsu (UW) and lab mentor Xiangyang Ju (LBNL) to investigate GPU algorithms for particle tracking in the ATLAS experiment. This project will build on the ACTS tracking library and the Exa.TrkX software. Miles will develop a working model for the use of ACTS-aaS and Exa.TrkX-aaS at the LHC.

Alex Golub

Alex Golub is a third-year Physics Ph.D. student at the University of Washington. They work with the ATLAS group at UW. Alex’s interests are in machine learning and collaborative software infrastructure. Alex will work with university mentor Gordon Watts (UW) and lab mentor Ben Nachman (SLAC) on developing algorithms to differentiate between charged and neutral particles in the ATLAS calorimeter. This is part of the Global Particle Flow reconstruction software, but it can eventually be applied to other detectors, too. Alex has previously used recurrent neural networks to identify calorimeter signatures of long-lived particles.

Luke Grossman

Luke Grossman is a second-year student in the Physics Ph.D. program at the University of California, Berkeley. His interests are in the area of collaborative software infrastructure, specifically the data processing flow and enhanced tracking algorithms. Luke will collaborate with university mentor Marjorie Shapiro (UCB) and lab mentor Simone Pagan Griso (LBNL) on extended tracking performance using the ATLAS EventIndex catalog. One goal is to make the late processing of selected data more universally applicable in the collaboration.

Charlie Hultquist

Charlie Hultquist is a second-year Physics Ph.D. student at the University of California, Berkeley. His interests lie in high-performance computing, most directly in foundational models for machine learning. Charlie will work with university mentor Haichen Wang (UCB) and lab mentors Steven Farrell and Xiangyang Ju (LBNL) on a prototype system featuring multi-task pretraining and transfer learning. This work leverages the Perlmutter high-performance supercomputer at LBNL, requiring special data handling and resource optimization.

Hadley Santana Queiroz

Hadley Santana Queiroz is in the second year of the Physics Ph.D. program at the University of California, Berkeley. She works in the area of high-performance computing and machine learning, with some connections to collaborative software infrastructure in ATLAS. Hadley will collaborate with university mentor Heather Gray (UCB) and lab mentor Paolo Calafiura (LBNL) on data augmentation for graph neural networks. The data augmentation methods are implemented in the common GNN training framework so that they are available to all collaborators. Hadley is also involved in calibrating the algorithm performance for flavor tagging.

2025-2027 Cohort

Levi Condren

Levi Condren is a third-year student in the Physics Ph.D. program at the University of California, Irvine. He works in high-performance computing and algorithms, specifically in the development of new particle tracking algorithms. Levi works with university mentor Daniel Whiteson (UCI) and lab mentors Xiangyang Ju (LBNL) and Daniel Murnane (LBNL/Copenhagen) on the tracking software pipeline for the High-Luminosity LHC. The most expensive stage of the pipeline is the graph segmentation which produces track candidates. Levi will optimize and rewrite the connected components and walkthrough algorithms, using junction removal to improve performance.

Abdelrahman Elabd

Abdel Elabd is in the third year of the Physics Ph.D. program at the University of Washington. His interest is in high-performance software and scalability on supercomputers. Abdel’s university mentor is Shih-Chieh Hsu (UW), and his lab mentor is Wahid Bhimji (LBNL). His research project will extend the capabilities of the OmniFold unfolding algorithm by implementing multi-GPU capability and test performance on the Perlmutter supercomputer.

Martina Hebert

Martina Hebert is a fourth-year Physics Ph.D. student at the University of California, Berkeley. She works in the area of collaborative software infrastructure with her university mentor Marjorie Shapiro (UCB) and lab mentor Gabriel Orebi-Gann. Martina is developing an end-to-end analysis chain for neutrino detectors, including simulation, calibration, reconstruction, and event-level analysis. This chain will be used for detectors with water-based liquid scintillators and water-based Cherenkov signatures.

Jackson O’Donnell

Jackson O’Donnell is in the fifth year of the Physics Ph.D. program at the University of California, Santa Cruz. His interest is in collaborative software infrastructure in the cosmic frontier. Jackson works with university mentor Tesla Jeltema (UCSC) and lab mentor David Schlegel (LBNL). He is adapting the GIGA-Lens software pipeline for use on strong-lensing galaxy clusters. He will be developing interfaces and testing scalability on large-scale datasets.

Justine Partridge

Justine Partridge is a second-year Physics Ph.D. student at the University of California, Santa Cruz. She works in the area of hardware-software co-design, especially high-throughput parallel data paths. Justine’s university mentor is Mike Hance (UCSC), and her lab mentor is Timon Heim (LBNL). She is studying the bottlenecks introduced by software design for parallel pipelines, and she will be tuning software performance for optimized bandwidth, using the YARR general purpose platform as a testbed.

Jason Weitz

Jason Weitz is in the first year of the Physics Ph.D. program at the University of California, San Diego. He is focused on the area of hardware-software co-design, tailoring algorithms for limited architectures like FPGAs. Jason works with university mentor Javier Duarte (UCSD) and lab mentor Nhan Tran (FNAL). Neural architecture codesign simultaneously considers both the performance of the neural network architecture and its hardware implementation in the CMS L1 trigger system, to ensure that the models are compatible with the hardware and latency constraints.

2026-2027 Cohort

Jose Esparza

Jose Esparza is a second-year Ph.D. student in the Department of Physics at the University of California, Berkeley. He is focused on the area of high-performance computing, specifically on the development of modern workflow-management tools and scalable HPC infrastructure. Jose works with university mentor Haichen Wang (UCB) and lab mentor Xiangyang Ju (LBNL). His research application is photon identification algorithms in the context of precision measurements and searches with the ATLAS experiment.

Liam Foster

Liam Foster is in the fourth year of the Physics Ph.D. program at the University of California, Berkeley. He is working on the development of collaborative software infrastructure with university mentor Heather Gray (UCB) and lab mentor Xiangyang Ju (LBNL). Liam will be developing an optimal transport-based toolkit for classifier calibration that can be distributed and applied widely within high-energy physics. This toolkit will enable classifier calibrations that will improve a broad range of physics results.

Yoshinobu Fujikake

Yoshinobu Fujikake is a third-year Physics Ph.D. at the University of California, Santa Cruz. His focus is in the area of collaborative software infrastructure, specifically in analysis pipelines. Yoshinobu works with university mentor Jason Nielsen (UCSC) and lab mentor Nick Smith (FNAL). He will be developing a columnar analysis infrastructure for the ATLAS Athena framework in a way that minimizes changes to existing user interfaces. This work will also be broadly applicable to the underlying Gaudi framework.

Srikar Gadamsetty

Srikar Gadamsetty is in the second year of the Physics Ph.D. program at the University of California, Berkeley. He also works in the area of collaborative software infrastructure with university mentor Marjorie Shapiro (UCB) and lab mentor Gabriel Orebi-Gann (LBNL). Srikar will develop and implement reconstruction algorithms for hybrid neutrino detectors, leading to a full analysis workflow to calibrate external backgrounds. This work is based on the RATPAC2 software framework.

Joshua Ho

Joshua Ho is a first-year Physics Ph.D. student at the University of California, Berkeley. He is one of the first WATCHEP trainees with special focus on the area of Artificial Intelligence and Machine Learning, specifically on agentic workflows for data analysis tasks and model adaptation of large models in high-energy physics applications. This approach will automate repetitive tasks, thereby freeing researchers to focus on creative analysis strategies. Joshua works with university mentor Haichen Wang (UCB) and lab mentor Paolo Calafiura (LBNL).

Qi Bin Lei

Qi Bin Lei is in the first year of the Physics Ph.D. program at the University of California, Santa Cruz. His interests lie in the area of high-performance computing. Qi Bin will focus his efforts on improving the generalized workflows used for benchmarking high-performance and high-throughput computing in large DOE scientific computing facilities. This work will be conducted with university mentor Mike Hance (UCSC) and lab mentor Ofer Rind (BNL). Qi Bin is passionate about giving back to the open-source scientific software ecosystem and improving user experiences with HPC and HTC systems.

Jake Rudolph

Jake Rudolph is a third-year Physics Ph.D. student at the University of California, Irvine. He is one of the first WATCHEP trainees with special focus on the area of Artificial Intelligence and Machine Learning. Jake works with university mentor Daniel Whiteson (UCI) and lab mentor Ben Nachman (SLAC). He uses neural networks to do anomaly detection in searches for new physics. He is investigating the neural network - field theory (NN-FT) correspondence to train NNs in a physics-informed way.

Ellison Scheuller

Ellison Scheuller is in the second year of the Physics Ph.D. program at the University of California, San Diego. Her research project is in the area of high-performance computing. Ellison is pursuing a multi-tier trigger design by developing a reusable software framework that enables anomaly detection models. This framework is constructed to handle the high data throughput in the CMS L1 scouting data stream. Ellison works with university mentor Javier Duarte (UCSD) and lab mentor Jennifer Ngadiuba (FNAL).