Wentao Guo

Incoming CS PhD student @ Princeton

Princeton University

Biography

Wentao Guo is an incoming CS PhD student at Princeton University. His research interests include improving model and data efficiency in ML algorithms, and generally building an efficient, accessible, and reliable machine learning system. His research is advised by Prof. Beidi Chen, Prof. Christopher De Sa, and Prof. Thorsten Joachims.

He was a former developer lead for the Pathways project and a backend developer and tester lead for the CMSX team. He obtained his master’s and bachelor’s degrees in Computer Science (Magna Cum Laude) from Cornell University.

Interests

Efficient and Scalable ML algorithms
Machine Learning Systems

Education

Ph.D. in Computer Science (incoming)
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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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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Wentao Guo, Andrew Wang, Bradon Thymes, Thorsten Joachims (0001). Ranking with Slot Constraints.

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Research Experience

Research Assistant

Prof. Beidi Chen, Carnegie Mellon University

June 2023 – May 2024 Remote

I mainly worked on potential applications of zeroth-order optimization methods on memory-efficient LLM finetuning.

Research Assistant

Prof. Christopher De Sa, Cornell University

June 2021 – May 2023 Ithaca, NY

I mainly 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 mainly worked on ranking with slot constraints problem.

Engineering Experience

Developer Lead

Pathways project, Cornell University

June 2021 – May 2023 Ithaca, NY

I designed search algorithms that provided diverse suggestions on course enrollment choices, constructed the backend codebase with Flask and MongoDB, and iterated search algorithms from students’ feedback. I deployed and maintained the Pathways website to serve 3000 Cornell students.

CMSX Backend Developer & Tester Lead

CMSX Project, Cornell University

September 2019 – May 2022 Ithaca, NY

I fixed tens of production system bugs in Java and MySQL, contributed more than 11,000 lines of code, reviewed 76 peer’s pull requests, and supervised new members and held weekly meetings to manage the team. The CMSX website serves more than 8000 students in over 100 courses in Cornell University.