- Accelerating Distributed Deep Learning using Lossless Homomorphic Compression
- Peer-reviewed Publications:
- ChainedFilter: Combining Membership Filters by Chain Rule, SIGMOD 2024
- StingySketch: a Sketch Framework for Accurate and Fast Frequency Estimation, PVLDB 2022
Research Experience
- Research Assistant: UT Austin, 2023-2024
- Research Intern: Microsoft Corp., 2024 Summer
Education
- Ph.D. Student: Department of Computer Science, The University of Texas at Austin, 2023-Present, Advisors: Prof. Aditya Akella and Prof. Venkat Arun
- B.S. Degree: Turing Class, Peking University, 2023, Advisor: Prof. Tong Yang
Background
- Research Interests: Machine Learning for Systems, Systems for Machine Learning
- About: A third-year Ph.D. student at UTNS (UT Austin Networked Systems group), advised by Prof. Aditya Akella and Prof. Venkat Arun. His research is generously supported by the Amazon AI PhD Fellowship.
- Research Focus: Applying AI techniques to improve performance (e.g., throughput, latency) and usability of modern computer systems, such as data analytics, ML training/serving frameworks, OS, and networks.