Wentao Guo

CS PhD student @ Princeton

Princeton University

Biography

Wentao Guo is an incoming CS PhD student at Princeton University. His research advisor is Prof. Tri Dao. His prior research was advised by Prof. Beidi Chen, Prof. Christopher De Sa, and Prof. Thorsten Joachims. He obtained his both master’s and bachelor’s degrees (Magna Cum Laude) in Computer Science from Cornell University.

Interests

LLM efficiency
Efficient and Scalable ML algorithms
Machine Learning Systems

Education

Ph.D. in Computer Science
Princeton University
MEng. in Computer Science, 2023
Cornell University, GPA 3.993
B.S. in Computer Science with Honors, 2022
Cornell University, GPA 3.890

Recent Papers

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Wentao Guo, Andrew Wang, Bradon Thymes, Thorsten Joachims (2024). Ranking with Slot Constraints. KDD'24.

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A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie F. Ruan, Yucheng Lu, Christopher De Sa (2023). Coordinating Distributed Example Orders for Provably Accelerated Training. In NeurIPS'23.

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Yucheng Lu, Wentao Guo, Christopher De Sa (2022). GraB: Finding Provably Better Data Permutations than Random Reshuffling. In NeurIPS'22.

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Tao Yu, Wentao Guo, Jianan Canal Li, Tiancheng Yuan, Christopher De Sa (2022). MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point. In HAET workshop at ICML'22.

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Yann Hicke, Abhishek Masand, Wentao Guo, Tushaar Gangavarapu (2021). Assessing the efficacy of large language models in generating accurate teacher responses.

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Research Experience

Research Assistant

Prof. Beidi Chen, Carnegie Mellon University

June 2023 – May 2024 Remote

I worked on efficient sparse fine-tuning of LLMs with zeroth-order optimization methods.

Research Assistant

Prof. Christopher De Sa, Cornell University

June 2021 – May 2023 Ithaca, NY

I worked on (distributed) example orderings that produced the CD-GraB and GraB paper, and efficient high-precision floating-point arithmetic for hyperbolic representation learning as MCTensor and HTorch.

Research Assistant

Prof. Thorsten Joachims, Cornell University

June 2022 – February 2023 Ithaca, NY

I worked on the ranking with slot constraints problem.