Overview
I am a Principal Senior Researcher with over 20 years of experience in GPU-accelerated computing, AI platforms, and large-scale distributed systems. My work bridges low-level system architecture with high-impact scientific discovery, including real-time gravitational wave detection and terabyte-scale graph analytics.
I contributed to the GPU acceleration of gravitational wave pipelines that enabled real-time discovery, work recognized by the 2017 Nobel Prize in Physics and the 2016 Breakthrough Prize in Fundamental Physics.
Research & Technical Focus
- HPC & AI Systems Architecture: GPU/CPU co-design, low-latency inference and simulation
- Large-Scale Graph Analytics: Distributed algorithms, Arkouda/Chapel, terabyte-scale data
- Real-Time Scientific Computing: Streaming pipelines, anomaly detection, performance optimization
- Networking & I/O: Kernel-bypass communication, user-level networking
Selected Contributions
Real-Time Gravitational Wave Detection
Led GPU acceleration of detection pipelines, reducing latency from minutes to approximately 10 seconds. This work enabled real-time astrophysical discovery and contributed directly to Nobel- and Breakthrough-recognized results.
GPU-Accelerated Space Weather Forecasting
Transformed high-fidelity space weather models into operational real-time systems on the Titan supercomputer, achieving over 4× speedup and meeting strict forecasting deadlines.
Scalable Graph Analytics Platform (NSF)
Led a 5-year NSF project extending Arkouda to support interactive Python-based analysis of terabyte-scale graphs, combining HPC performance with data-science usability.
Positions
- Principal Senior Researcher, NJIT (2020–Present)
- Associate Professor, Tsinghua University (2001–2019)
Publications & Recognition
- 200+ peer-reviewed publications, 106,000+ citations
- Breakthrough Prize in Fundamental Physics (2016)
- IEEE TCSC Scale Challenge Award (2016)
- Associate Editor: IEEE TPDS, ACM TOPC, JPDC