Contact

• Zoom: washington.zoom.us/j/2066010000
• Email: dzhao@cs.washington.edu
• Office Hour (by appointment only)
  • Seattle, Mon/Wed/Fri: CSE 291
  • Tacoma, Tue/Thur: CP 225

Biography

Since 2023, Dr. Dongfang Zhao has been a tenure-track assistant professor of computer science at the University of Washington (UW) Tacoma School of Engineering & Technology affiliated with the eScience Institute and the Allen School of Computer Science & Engineering, where he was previously a postdoc advised by Prof. Ariel Rokem and Prof. Magdalena Balazinska. Prof. Zhao is a U.S. citizen naturalized in Sacramento, California, moving from KU Leuven, Belgium.

Services

• Associate Editor: Journal of Big Data (Springer)
• Technical Review Board: IEEE Transactions on Parallel and Distributed Systems
• Reviewer: zbMATH (European Mathematical Soceity)

Research

• I founded 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 with me on databases/HPC/AI, here in the following are some potential topics:
  • [ICWS'24] Privacy-Preserving Artificial Intelligence on Edge Devices: A Homomorphic Encryption Approach
  • [PAKDD'24] Towards Nonparametric Topological Layers in Neural Networks
  • [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
• If you are interested in working with me on algebraic geometry, I suggest reading the following texts first:
  • Introduction to Algebraic Geometry, by Brendan Hassett. (Mostly computational perspective)
  • Algebraic Geometry, by Robin Hartshorne. (More abstract perspective, e.g., Chapters II & III)

Resources

• UW CSE: bicycle.cs.washington.edu
• UW Web: ovid.u.washington.edu
• UW HPC: klone.hyak.uw.edu
• TACC CPU: 129.114.109.34
• TACC GPU: 129.114.109.59
• UChicago GPU: 192.5.87.159