Michal Derezinski
University of Michigan CSE · Assistant Professor of Computer Science and Engineering
Research focus: randomized algorithms for machine learning · randomized numerical linear algebra · stochastic optimization · machine learning theory
针对 Michal Derezinski 的预审审核：请作为理论导向的 ML 申请人准备：randomized numerical linear algebra、stochastic optimization、random matrix theory 的概率分析以及算法分析应清晰可见于您的档案中。
Who this advisor fits / 什么情况下适合你
- You want theory depth and proof/analysis-oriented problem framing.
- Strong fit for theory-heavy applicants in randomized numerical linear algebra, stochastic optimization, ML theory, and rigorous algorithms-for-data-science work.
- 你要的是理论深度、证明/分析导向的问题设定。
- 适合理论导向申请人的强匹配：randomized numerical linear algebra、stochastic optimization 和 ML 领域的理论，以及数据科学领域的严谨算法工作。
What to watch for / 什么情况下要慎重
- You only want fast benchmarks/API hacking, not domain papers or longer experimental loops.
- 你只想做快速 benchmark / API 拼装，不想读领域论文或做长期实验。
Public evidence as of 2026-06-10
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