Contact

• Email: dzhao@uw.edu
• Zoom: washington.zoom.us/j/2066010000

Biography

Dr. Dongfang Zhao is a tenure-track assistant professor of computer science at the University of Washington (UW), affiliated with the Tacoma School of Engineering & Technology and the eScience Institute. His research spans across databases, high-performance computing, and artificial intelligence. He is a U.S. citizen naturalized in Sacramento, California; Before moving to the U.S., he completed his thesis under the supervision of Prof. Irène Gijbels in the Department of Mathematics at Katholieke Universiteit Leuven, Belgium.

Academic Services

• Associate Editor: Journal of Big Data (Springer)
• Editorial Board: IEEE Transactions on Parallel and Distributed Systems (TPDS)
• Reviewer: zbMATH (European Mathematical Soceity)
• Technical Program Committee: SIGMOD/PODS, IPDPS, AAAI, WWW, KDD, etc.

Research

• I found the High-Performance Data-Intelligence Computing (HPDIC) research lab
• Publications indexed by third-parties: Google Scholar (overestimated due to my popular Chinese name), DBLP (missing some works)
• If you are interested in working or collaborating with me, here in the following are some potential topics:
  • [SIGMOD'23] Toward Efficient Homomorphic Encryption for Outsourced Databases through Parallel Caching
  • [IPDPS'22a] Topological Modeling and Parallelization of Multidimensional Data on Microelectrode Arrays
  • [IPDPS'22b] DEAN: A Lightweight and Resource-efficient Blockchain Protocol for Reliable Edge Computing
  • [ICDE'21] SciChain: Blockchain-enabled Lightweight and Efficient Data Provenance for Reproducible Scientific Computing
  • [SC'21] BAASH: lightweight, efficient, and reliable blockchain-as-a-service for HPC systems
  • [AAAI'20 oral] HDK: Toward High Performance Deep-Learning-Based Kirchhoff Analysis
  • [SC'19] Swift machine learning model serving scheduling: a region based reinforcement learning approach
  • [VLDB'17] Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads
  • [TPDS'16] Towards Exploring Data-Intensive Scientific Applications at Extreme Scales through Systems and Simulations
  • [IPDPS'13] ZHT: A Light-Weight Reliable Persistent Dynamic Scalable Zero-Hop Distributed Hash Table
  • [TPAMI'09] Incremental Isometric Embedding of High-Dimensional Data Using Connected Neighborhood Graphs

Resources

• UW CSE: bicycle.cs.washington.edu
• UW Web: ovid.u.washington.edu
• UW HPC: klone.hyak.uw.edu
• TACC CPU: 129.114.109.16
• TACC GPU: 129.114.109.59
• UChicago GPU: 192.5.87.159