Ph.D. candidate Department of Computer Science University of California, Davis Lab: 2356 Academic Surge E-mail: jiiwang at ucdavis dot edu GitHub | Google Scholar

About me

I am currently a Ph.D. candidate in Computer Science at UC Davis. Before moving to Davis, I earned my Master's degree at Carnegie Mellon University and Bachelor's degree at Nanjing University.

At Davis, I am fortunate to work with Prof. Zhaojun Bai on numerical linear algebra and its applications. At CMU, I collaborated with Prof. Clarie Le Goues on automatic program repair by leveraging SMT in semantic search.

Research

My research interests are parallel and high-performance computing, numerical linear algebra algorithms, and fair and trustworthy AI.

• Mixed-precision computing

• Fast and parallel algorithms for large scale symmetric eigenvalue problems

• Spectral clustering with fairness constraints

• Generalized singular value decomposition and its applications (Documentation)

Publications

• Rethink Baseline of Integrated Gradients from the Perspective of Shapley Value
  Shuyang Liu, Zixuan Chen, Ge Shi, Ji Wang, Changjie Fan, Yu Xiong, Runze Wu Yujing Hu, Ze Ji, Yang Gao
  arXiv:2310.04821.

• Scalable Spectral Clustering with Group Fairness Constraints
  Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai
  Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6613-6629, 2023.

• The identification of endometrial immune cell densities and clustering analysis in the mid-luteal phase as predictor for pregnancy outcomes after IVF-ET treatment
  Yiwei Zhao, Gene Chi Wai Man, Ji Wang, Yingyu Liu, Joseph Kwong, Tao Zhang, Jacqueline Pui Wah Chung, Chi Chiu Wang, Xiaoyan Chen, Tin-Chiu Li
  Journal of Reproductive Immunology 148 (2021) 103431.

Teaching

• Lead Teaching Assistant: ECS-231 Large Scale Scientific Computing, Spring 2022.

• Lead Teaching Assistant: ECS-122A Algorithm Design and Analysis (Discussion Notes), Spring 2021, Fall 2020, Spring 2020, Spring 2019.

• Lead Teaching Assistant: ECS-20 Discrete Mathematics for Computer Science (Discussion Notes), Winter 2021, Winter 2020.

• Lead Teaching Assistant: ECS-160 Software Engineering, Fall 2019.

Useful links

• Books:

  • Matrix Computations, 4th Edition: an encyclopedia/bible of Numerical Linear Algebra by Golub and Van Loan.

• Courses:

  • MAT 221: Applied Numerical Linear Algebra offered by James Demmel at UC Berkeley.

  • 18.S191: Introduction to Computational Thinking in Julia by Alan Edelman, et al. at MIT.

  • 18.06: Linear Algebra by Gilbert Strang at MIT.

  • 17-819: Program Analysis by Jonathan Aldrich and Claire Le Goues at CMU.

• Documentations:

  • Julia Programming Language Documentation: a fresh high-performance, dynamic language appropriate for numerical and scientific computing.

  • LAPACK Users’ Guide 3rd Edition: a standard software library for numerical linear algebra, written in Fortran.

  • MATLAB Documentation.

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