About
I am a senior Ph.D. student in Electrical and Computer Engineering at Rice University, advised by Prof. Tong (Tony) Geng. I previously spent two years with the same group at the University of Rochester, and received my B.S. and M.S. from Zhejiang University.
My research sits at the intersection of computer architecture and machine learning systems. I build hardware–software co-designed systems that let physical dynamical systems perform the computation digital accelerators struggle with — spanning graph learning, differential equation solving, and large language model training and inference.
I am always happy to talk about nature-powered computing, accelerator design, and efficient learning systems. Feel free to reach out by email.
- Dynamical-System / Nature-Powered Computing
- Efficient Training and Inference of Large Language Models
- Computer Architecture & Hardware–Software Co-Design
- Scientific Computing Acceleration
Publications
* denotes equal contribution.
2026
- MICRO
BITE: Boosting LLM Training via Sandwich-Bite Dataflow and Dynamic Subspace Auto-Alignment
- ISCA
DS-ISA: Instruction Set Architecture for Dynamical System Units
- ICLR
Zeros can be Informative: Masked Binary U-Net for Image Segmentation on Tensor Cores
- ICML
Solving Time-Dependent Differential Equations with Physical Dynamical Systems
2025
- ISCA
DS-TPU: Dynamical System for on-Device Lifelong Graph Learning with Nonlinear Node Interaction
- ICLR
DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models
- MICRO
DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving
- ICML
An Expressive and Self-Adaptive Dynamical System for Efficient Function Learning
- ICLR
InstaTrain: Adaptive Training via Ultra-Fast Natural Annealing within Dynamical Systems
- DAC
DM-Tune: Quantizing Diffusion Models with Mixture-of-Gaussian Guided Noise Tuning
- ASP-DAC
Nature-GL: A Revolutionary Learning Paradigm Unleashing Nature's Power in Real-World Spatial-Temporal Graph Learning
2024
- ISCA
DS-GL: Advancing Graph Learning via Harnessing Nature's Power within Scalable Dynamical Systems
- ICLR
NP-GL: Extending Power of Nature from Binary to Real-valued Graph Learning in Real World
- LoG
NP-NDS: A Nature-Powered Nonlinear Dynamical System for Power Grid Forecasting
- TCHES
A Highly-efficient Lattice-based Post-Quantum Cryptography Processor for IoT Applications
2022
- TCSVT
A Reconfigurable Convolution-in-Pixel CMOS Image Sensor Architecture
2021
- PIERS
A Near-array Convolution Computing Scheme Based on WSe2 Photodiode
Awards
- 2025 Graduate Teaching AwardUniversity of Rochester
Education
- Jan 2026 – Present Ph.D. in Electrical and Computer Engineering Rice University, Houston, TX
- Sep 2023 – Dec 2025 Ph.D. in Electrical and Computer Engineering University of Rochester, Rochester, NY Transferred to Rice with Prof. Geng's group
- Sep 2020 – Jun 2023 M.S. in Electronic Science and Technology Zhejiang University, Hangzhou, China Overall rank: 1/14
- Sep 2016 – Jul 2020 B.S. in Electronic and Information Engineering Zhejiang University, Hangzhou, China