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Hi, I am Ray

Yihui (Ray) Ren

Staff Computational Scientist (AI/ML) at Brookhaven National Laboratory

I am a Staff Scientist and Lead of the AI Codesign Group, where I direct multiple research projects aimed at developing innovative AI technologies and advancing the way science is conducted. I began my AI/ML research journey at Brookhaven National Laboratory in 2018. Prior to joining Brookhaven, I was a postdoctoral researcher at the Biocomplexity Institute of Virginia Tech, following the completion of my PhD in Physics at the University of Notre Dame in 2015.

Problem Solving (Advanced)
Leadership
Team Work

News

activity
Oct 27,2025
📅 Convener at 4th AI4EIC at 📍 MIT, Cambridge, MA
activity
Oct 20,2025
📅 Invited speaker at APS DNP AI 4 experiment workshop at 📍 Chicago, IL
activity
Sep 23,2025
📅 AI Edge Symposium GE Vernova 📍 Niskayuna, NY
activity
Sep 16,2025
📅 2025 SciDAC PI Meeting 📍 Rockvile, MD
activity
Sep 11,2025
Track convener, New York Scientific Data Summit 📍 SUNY Global Center, NYC
activity
Sep 05,2025
Invited talk (virtual), European Coalition for AI in Fundamental Physics (EuCAIF) 📍 TUM-IAS, Germany
activity
Aug 21,2025
ARCHIDE: 2nd Workshop on Architecture Design Methodologies and Ecosystems for HPC and Scientific Edge Computing 📍 LBNL, CA
publication
Aug 19,2025
"FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics" has been distributed on arxiv
publication
Aug 19,2025
"Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing" published in Future Generation Computer Systems"
publication
Aug 01,2025
"EvRT-DETR: The surprising effectiveness of DETR-based detection for event cameras" has been accepted by ICCV 2025

Publications

EvRT-DETR: The surprising effectiveness of DETR-based detection for event cameras
ICCV 2025 2025 Artificial Intelligence
Dmitrii Torbunov Yihui Ren Animesh Ghose Odera Dim Yonggang Cui
Generalizable Implicit Neural Representations via Parameterized Latent Dynamics for Baroclinic Ocean Forecasting
arXiv:2503.21588 2025 Artificial Intelligence Physics
Guang Zhao Xihaier Luo Seungjun Lee Yihui Ren Shinjae Yoo others
FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics
arXiv:2508.14087 2025 Artificial Intelligence Physics
David Park Shuhang Li Yi Huang Xihaier Luo others Yihui Ren
Unpaired image translation to mitigate domain shift in liquid argon time projection chamber detector responses
Machine Learning: Science and Technology 2024 Artificial Intelligence Physics
Yi Huang Dmitrii Torbunov Brett Viren Haiwang Yu others Yihui Ren
Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
ICLR 2024 2024 Artificial Intelligence
Xihaier Luo Wei Xu Yihui Ren Shinjae Yoo Balu Nadiga
Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments
Physical Review C 2024 Artificial Intelligence Physics
Dmitrii Torbunov Yi Huang Meifeng Lin Yihui Ren others Jin Huang
Analyzing and Mitigating Circuit Aging Effects in Deep Learning Accelerators
2024 IEEE VTS 2024 Artificial Intelligence Codesign
Sanjay Das Shamik Kundu Anand Menon Yihui Ren Shubha Kharel Kanad Basu
Automated and Holistic Co-design of Neural Networks and ASICs for Enabling In-Pixel Intelligence
arXiv:2407.14560 2024 Artificial Intelligence Codesign
Shubha R Kharel Prashansa Mukim Piotr Maj others Yihui Ren Soumyajit Mandal
Mitigating Parameter Degeneracy using Joint Conditional Diffusion Model for WECC Composite Load Model in Power Systems
arXiv:2411.10431 2024 Artificial Intelligence
Feiqin Zhu Dmitrii Torbunov Yihui Ren Zhongjing Jiang others Meng Yue
Variable Rate Neural Compression for Sparse Detector Data
SSRN 5262322 2024 Artificial Intelligence Codesign
Yi Huang Yeonju Go Jin Huang others Yihui Ren others

Education

Hunan University
2005-2009
B.Sc. in Physics
University of Notre Dame
2010-2015
Ph.D in Physics
Publications:

Experiences

1
Brookhaven National Laboratory

May 2018 - present

Upton, NY

Brookhaven National Laboratory (BNL) is a United States Department of Energy national laboratory located in Upton, New York, established in 1947. I joined the Machine Learning Group (MLG) in 2018. The group has been designated as the AI Department in 2025.

Computational Scientist (AI/ML) RS5

Jan 2024 - present

Responsibilities:
  • AI Codesign Group Lead
  • Lead several research projects such as building a scalable foundation model for nuclear and particle physics
Associate Computational Scientist (AI/ML) RS4

Oct 2021 - Jan 2024

Responsibilities:
  • Deputy Machine Learning Group Lead
  • AI tech lead in multiple projects including unpaired and unsupervised domain mapping techniques to bridge the gap between scientific simulation and experimental data
Assistant Computational Scientist (AI/ML) RS3

Aug 2019 - Nov 2021

Responsibilities:
  • Developed graph neural network-based molecule fingerprinting methods for combating COVID-19.
  • Developed efficient neural compression methods for sparse nuclear physics detector data.
Postdoctorate Research Associate (AI/ML)

May 2018 - July 2019

Responsibilities:
  • Developed deep learning object detection method for nuclear non-proliferation.
  • Benchmared AI workloads on cutting-edge AI hardware including NVIDIA DGX2.
Virginia Tech

Apr 2015 - Apr 2018

Blacksburg, VA

Biocomplexity Institute at Virginia Tech was a multidisiplinary research institute specialized in agent-based modeling, theoretical modeling and high-performance computing.

Postdoctoral Research Associate

Apr 2015 - Apr 2018

Responsibilities:
  • Connected Moore-Shannon Network Reliability with Ising Model in condensed matter physics.
  • Developed probablisitic agent-based modeling for human behaviro and epidemics.
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