Yihui (Ray) Ren

Brookhaven National Laboratory

Computational Science
Bldg. 725, Room 2-205
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-4638
yren@bnl.gov

Pronouns: "he, him, his"

Expertise | Research | Education | Appointments | Publications | Highlights

Expertise

• AI for Science
• AI-hardware Codesign

Research Activities

Current:

• PI, NA22, "Event-based Video Surveillance Camera at the Edge" (NN/AI)
• PI, LDRD, "FM4NPP Foundation Models for Nuclear and Particle Physics" (AI/NP)
• PI, LDRD, "AI-Circuit-Materials Co-Design for Mitigating Memristive Stochasticity" (AI/IO/CFN)
• Co-PI, LDRD, "Real time learning on heterogeneous devices for detector calibration" (HEP/AI)
• KP, SciDAC, RAPIDS-3
• KP, ASCR, "Resilient Federated Workflows in a Heterogeneous Computing Environment"

Past:

• Co-PI, LDRD, "Real-time Information Distillation on Novel AI Hardware" (NP/AI)
• PI, LDRD, "Bridging the Gap between Scientific Simulations and Experiments with Cycle-Consistent Generative Models" (AI/HEP/NP)
• Co-PI, LDRD, "Real-time Image Classification using Machine Learning" (HEP/AI)
• Co-PI, LDRD, "Towards Edge Computing: A Software and Hardware Co-Design Methodology for ASIC-based Scientific Neuromorphic Computing" (IO/AI)
• KP, SciDAC-1 & RAPIDS-2

SULI Student Interns:  Andrew Deutsch, Mario Xerri, Animesh Ghose, Kevin Jimenez Vega

Education

• Ph.D., Physics, University of Notre Dame, 2015
• B.S., Physics, Hunan University, China, 2009

Professional Appointments

• 2025-present, AI Codesign Group Lead, Brookhaven National Laboratory
• 2026-present, Senior Research Scientist, Brookhaven National Laboratory
• 2024-2025, Research Scientist, Brookhaven National Laboratory
• 2024-2025, Deputy ML Group Lead, Brookhaven National Laboratory
• 2021-2024, Associate Research Scientist, Brookhaven National Laboratory
• 2019-2021, Assistant Research Scientist, Brookhaven National Laboratory
• 2018-2019, Postdoctoral Research Associate, Brookhaven National Laboratory
• 2015-2018, Postdoctoral Research Associate, Virginia Tech

Selected Publications

• D. Park, S. Li, Y. Huang, X. Luo, H. Yu, Y. Go, C. Pinkenburg, Y. Lin, S. Yoo, J. Osborn, J. Huang, and Y. Ren, (2025) "FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics" https://arxiv.org/abs/2508.14087 (ICLR 2026)
• D. Torbunov, Y. Ren, A. Ghose, O. Dim, and Y. Cui, (2025) "EvRT-DETR: Latent Space Adaptation of Image Detectors for Event-based Vision," (Accepted ICCV 2025) https://arxiv.org/abs/2412.02890
• Park D, Ren Y, Kilic OO, et al (2024) AI Surrogate Model for Distributed Computing Workloads. SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis 79–86. https://doi.org/10.1109/scw63240.2024.00018
• Y. Huang, D. Torbunov, B. Viren, H. Yu, J. Huang, M. Lin, and Y. Ren (2024) Unpaired image translation to mitigate domain shift in liquid argon time projection chamber detector responses. Machine Learning: Science and Technology 5:045021. https://doi.org/10.1088/2632-2153/ad849c
• D. Torbunov, Y. Huang, M. Lin, Y. Ren, Y. Go, T. Rinn, H. Yu, B. Viren, and J. Huang (2024) Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments. Physical Review C 110:. https://doi.org/10.1103/physrevc.110.034912
• Huang Y, Ren Y, Yoo S, Huang J (2023) Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data. Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. https://doi.org/10.1145/3624062.3625127
• D. Torbunov, Y. Huang, H. Yu, J. Huang, S. Yoo, M. Lin, B. Viren, and Y. Ren, "UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation," 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/wacv56688.2023.00077
• Luo X, Nadiga BT, Park JH, et al (2022) A Bayesian Deep Learning Approach to Near-Term Climate Prediction. Journal of Advances in Modeling Earth Systems 14:. https://doi.org/10.1029/2022ms003058
• Miryala S, Mittal S, Ren Y, et al (2022) Waveform processing using neural network algorithms on the front-end electronics. Journal of Instrumentation 17:C01039. https://doi.org/10.1088/1748-0221/17/01/c01039
• Miryala S, Zaman MA, Mittal S, et al (2022) Peak Prediction Using Multi Layer Perceptron (MLP) for Edge Computing ASICs Targeting Scientific Applications. 2022 23rd International Symposium on Quality Electronic Design (ISQED). https://doi.org/10.1109/isqed54688.2022.9806285
• Huang Y, Ren Y, Yoo S, Huang J (2021) Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). https://doi.org/10.1109/icmla52953.2021.00179
• Ren Y, Yoo S, Hoisie A (2019) Performance Analysis of Deep Learning Workloads on Leading-edge Systems. 2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS). https://doi.org/10.1109/pmbs49563.2019.00017
• Ren Y, Cedeno-Mieles V, Hu Z, et al (2018) Generative Modeling of Human Behavior and Social Interactions Using Abductive Analysis. 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). https://doi.org/10.1109/asonam.2018.8508282
• Ren Y, Eubank S, Nath M (2016) From network reliability to the Ising model: A parallel scheme for estimating the joint density of states. Physical Review E 94:. https://doi.org/10.1103/physreve.94.042125
• Ren Y, Ercsey-Ravasz M, Wang P, et al (2014) Predicting commuter flows in spatial networks using a radiation model based on temporal ranges. Nature Communications 5:. https://doi.org/10.1038/ncomms6347

Research Highlights

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