Fred Zhang

I am a PhD student in the Theory Group of the EECS Department at UC Berkeley, advised by Jelani Nelson. My research lies broadly in algorithm design. I am particularly interested in questions arising from high-dimensional statistics, machine learning, and processing massive data.

I was a graduate student in the Theory of Computation group at Harvard, before moving to Berkeley with my advisor. Prior to that, I received my B.S. in Computer Science and in Mathematics from Duke University, where I had the fortune of working with Rong Ge and Debmalya Panigrahi.

I help with Berkeley Algorithms Office Hours, where the goal is to bridge theory and applications of algorithms. If you come up with algorithmic problems from your (applied) research, feel free to reach out.

Publications

Teaching

• CS 294-165: Sketching Algorithms (Fall 20)
• CS 170: Efficient Algorithms and Intractable Problems (Spring 20)

• COMPSCI 330: Design and Analysis of Algorithms (Spring 16, Fall 16, Spring 17, Fall 17, Spring 18)

Notes

• Mirror Descent and Online Learning (lecture note, 2019)
• Tensor Networks, Matrix Product States and Density Matrix Renormalization Group (blog post at Windows on Theory, 2018)
• Goodness-of-fit Testing and Structure Learning of the Ising Model (survey, 2018)
• The Topological Approach Towards Graph Evasiveness (survey, 2017)

Contact