## 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

We are actively recruiting: a postdoctoral researcher for CMS and FAIR AI in high energy physics (apply here), 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 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 National Science Foundation (NSF) under award number #2005369 (Voyager).

## Schedule a meeting

##### News

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 Astronomly 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