Principal investigator

Javier Duarte is an Associate Professor of Physics at UC San Diego and a member of the CMS experiment at the CERN Large Hadron Collider. He leads a research group developing new artificial intelligence (AI) techniques for high-energy particle collisions to better measure the properties and interactions of elementary particles, like the Higgs boson, and search for new physics. Before joining UC San Diego, he was a Lederman postdoctoral fellow at Fermilab and received his Ph.D. in Physics at Caltech and his B.S. in Physics and Mathematics at MIT. Prof. Duarte has received the APS Henry Primakoff Award for Early-Career Particle Physics, Sloan Research Fellowship, RCSA Cottrell Scholar Award, DOE Early Career Award, and is a co-PI of the NSF HDR Institute for Accelerated AI Algorithms for Data-Driven Discovery.

Research directions

Our lab is interested in:

  • LHC data analysis for Higgs boson and exotic new physics
  • Hardware-accelerated machine learning for trigger and computing
  • Geometric deep learning for particle physics
  • Diversity, inclusion, and social justice in physics

Open positions

Graduate students: apply here, and undergraduate students (email us).

Antiracism

We are committed to creating an antiracist, inclusive, and supportive workspace. For resources to combat anti-Blackness and being an antiracist, see the Resources tab.

Contact information

Office:
Mayer Hall Addition 5513
(858) 246-4980

Lab:
Mayer Hall Addition 5545

Mailing address:
Javier Duarte
University of California San Diego
Department of Physics, 0319
9500 Gilman Drive
La Jolla, CA 92093



Support

Our work is supported by the Alfred P. Sloan Foundation, Research Corporation For Science Advancement (RCSA), Department of Energy (DOE), Office of Science, Office of High Energy Physics Early Career Research Program under award number DE-SC0021187 (ECA), the DOE Office of Advanced Scientific Computing Research under award number DE-SC0021396 (FAIR4HEP) and the Extreme Data Reduction for Science Project (XDR), and the National Science Foundation (NSF) under award numbers 2117997 (A3D3) and 2005369 (Voyager).

Schedule a meeting

News

December 15, 2023:Anni presents the group's latest work on induced generative adversarial particle transformers at the Machine Learning and the Physical Sciences Workshop at NeurIPS 2023. October 24, 2023: Javier is named the 2024 Henry Primakoff Award for Early-Career Particle Physics Recipient

October 6, 2023: Zichun presents Lorentz Group Equivariant Autoencoders at the APS Far West Meeting

September 25-28, 2023: Farouk presents Scalable neural network models and terascale datasets for particle flow reconstruction, Luke presents Optimizing Sparse Neural Architectures for Low-Latency Anomaly Detection, Liv presents FKeras: A Sensitivity Analysis Tool for Edge Neural Networks, and several other collaborators present at the Fast Machine Learning for Science 2023 Workshop

September 13-14, 2023: As the new CMS ML Group convener, Javier co-organizes the 2023 CMS ML Town Hall at CERN

July 10, 2023: Several group members present at the A3D3 High-Throughput AI Methods and Infrastructure Workshop

May 11, 2023: Carlos presents the JetNet Python library and Haoyang (Billy) presents on FAIR AI Models in High Energy Physics in the Artificial Intelligence and Machine Learning Session of the 2023 Conference on Computing in High Energy and Nuclear Physics (CHEP)

May 10, 2023: Dr. Melissa Quinnan was awarded a School of Physical Sciences EDI Excellence Award!

April 26, 2023: Javier was recognized as a university-wide faculty recipient of a UCSD Inclusive Excellence Award for his work on diversity, equity, and inclusion in the Physics Department.

April 15, 2023: The lab volunteered at the 2023 Barrio Logan Arts & Science Expo and shared a particle identity quiz and Particle Zoo buttons with attendees!

February 15, 2023: Javier was named a 2023 Sloan Research Fellow

February 10, 2023: Congratulations to Anni, Thomas, and Rohan for receiving 2022-2023 Physical Sciences Dean's Undergraduate Awards for Excellence

February 9, 2023: Javier was awarded a 2023 RCSA Cottrell Scholar Award

December 3, 2022: Farouk presents "Do graph neural networks learn traditional jet substructure?" at the Machine Learning and the Physical Sciences Workshop at the NeurIPS 2022 Conference

November 1, 2022: Dr. Melissa Quinnan gives the Fundamental Physics Directorate Seminar at SLAC

November 1, 2022: Javier gives the Human Side of Science Lecture at University of San Diego

November 1, 2022: Raghav presents on evaluation metrics for generative adversarial networks in particle physics at ML4Jets 2022

October 27-29, 2022: Russell travels to the SACNAS National Diversity in STEM Conference in San Juan, Puerto Rico

October 24-28, 2022: #BlackInPhysics Week!

October 23, 2022: Farouk presents a poster on the updated machine-learned particle-flow algorithm at ACAT 2022

October 10-14, 2022: The group travels to the CMS ML@L1 Workshop at the Fermilab LPC!

October 10, 2022: Congratulations to Dr. Daniel Diaz for being named a 2023 LPC Distinguished Researcher!

October 7, 2022: IEEE Spectrum writes about machine learning in particle physics

October 3-7, 2022: The group travels to the Fast Machine Learning for Science Workshop and the A3D3 Annual Meeting at SMU! Presentations from Daniel, Rohan, Suki, Andrew, and more!

July 16-26, 2022: The group travels to the Snowmass Summer Meeting at the University of Washington

July 4, 2022: For the 10th anniversary of the Higgs boson discovery, Nature publishes a special collection of articles, including work from our group!

June 29, 2022: Science News highlights Javier's recollection of the Higgs boson discovery

June 3, 2022: Javier presents at the Fermilab Wine & Cheese Seminar on enabling Higgs coupling measurements with highly energetic Higgs pairs in CMS

April 26, 2022: Symmetry magazine article features our group and collaborators on Higgs pair searches

April 6, 2022: MLPerf Tiny Inference Benchmark 0.7 results include our group: FPGAs have the fastest and most efficient (least energy per inference) submissions

March 11, 2022: Our group's work on nonresonant high-momentum Higgs boson pair production in CMS is featured in CERN Courier

March 3, 2022: Congratulations to Tony Aportela for receiving a High Energy Physics Consortium for Advanced Training (HEPCAT) Graduate Student Fellowship!

December 3, 2021: Congratulations to Raghav for receiving a Carol and George Lattimer Award for Graduate Excellence and Zichun for recieving a Dean's Undergraduate Excellence Award from the Physical Sciences Division for 2021-2022!

November 17, 2021: Javier gives a HEP seminar at Columbia University.

November 9, 2021: SDSC Voyager featured by Intel.

October 21, 2021: Farouk and Raghav's work on MLPF and explainable AI is accepted at the Machine Learning and the Physical Sciences Workshop at NeurIPS 2021.

October 21, 2021: Steven, Raghav, Daniel, and Suki's work on Particle Graph Autoencoders and Differentiable Learned Energy Mover’s Distance is accepted at the Machine Learning and the Physical Sciences Workshop at NeurIPS 2021.

September 28, 2021: Raghav's paper on Particle Cloud Generation with Message Passing Generative Adversarial Networks is accepted at the 35th Annual Conference on NeurIPS.

August 12, 2021: Javier gives an AI Distinguished Lecture at Argonne National Lab.

July 26, 2021: Farouk, Raghav, and Javier speak at the 2021 CMS Machine Learning Town Hall.

July 14, 2021: Raghav is selected as a 2021 LPC AI Fellow.

July 6, 2021: Zichun, Raghav deliver talks at the ML4Jets 2021.

June 23, 2021: Raghav delivers an invited talk on message-passing generative adversarial networks for jets at the Machine Learning for Particle Physics Scientific Program at the Mainz Institute for Theoretical Physics.

May 26, 2021: Zichun, Haifeng, and Rushil present posters on their work at the UC San Diego Online Undergraduate Research Symposium (OURS).

May 26, 2021: Daniel presents the CMS search for Higgs boson decays into long-lived particles in associated Z boson production at the 9th LLP Workshop.

May 26, 2021: Javier gives the Department of Physics and Astronomy Colloquium at Cal State LA.

April 22, 2021: Zichun is selected to receive a 2021 Undergraduate Summer Research Award from the Physical Sciences Division.

March 29, 2021: Javier presents a paper on machine learning for scientific low-power systems with \(\texttt{hls4ml}\) at the first tinyML Research Symposium.

January 26, 2021: Efficient AI in Particle Physics and Astrophysics Research Topic in Front. Big Data and Front. AI edited by Javier has been launched.

January 21, 2021: Steven's work on particle graph autoencoders for anomaly detection included in the LHC Olympics 2020 Community Paper. Our paper on machine-learned particle-flow (MLPF) reconstruction is now uploaded to arXiv.

December 11, 2020: Vesal and Raghav will give poster presentations on their work at the 3rd Machine Learning and the Physical Sciences Workshop at NeurIPS 2020.

December 10, 2020: Farouk is selected to receive an IRIS-HEP fellowship to work on MLPF.

October 21, 2020: Javier gives a talk including Vesal's work on GNN Tracking on FPGAs in the IRIS-HEP Topical Meeting.

October 16, 2020: Javier gives an ECE Graduate Seminar on Real-time AI in particle physics at Carnegie Mellon University.

August 12, 2020: Javier gives a virtual seminar on CMS highlights at the Fermilab Users Meeting.

August 10, 2020: Javier is a Co-PI on a DOE grant for FAIR frameworks for AI in high energy physics.

July 8, 2020: Vesal Razavimaleki is awarded an IRIS-HEP fellowship.

July 1, 2020: Javier is awarded a DOE Early Career Award.

July 1, 2020: Javier is a Co-PI on an $5 million NSF grant for an AI supercomputer called Voyager at SDSC.

June 23, 2020: The CMS Run 2 high-momentum Higgs boson search is submitted to JHEP for publication.

May 7, 2020: Steven Tsan is selected to participate in the TRELS Summer Research Program.

April 8, 2020: Javier gives a virtual seminar at Argonne National Laboratory.

Decembter 14, 2019: Javier and collaborators present work at the 2nd Machine Learning and the Physical Sciences Workshop at NeurIPS 2019.