Wentao Guo

Wentao Guo

Incoming CS PhD student @ Princeton

Princeton University

Biography

Wentao Guo is an incoming CS PhD student at Princeton University. His research is advised by Prof. Beidi Chen, Prof. Christopher De Sa, and Prof. Thorsten Joachims. 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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(2023). Coordinating Distributed Example Orders for Provably Accelerated Training. In NeurIPS'23.

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(2022). GraB: Finding Provably Better Data Permutations than Random Reshuffling. In NeurIPS'22.

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(2022). MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point. In HAET workshop at ICML'22.

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(2021). Assessing the efficacy of large language models in generating accurate teacher responses.

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(0001). Ranking with Slot Constraints.

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Research Experience

 
 
 
 
 
Prof. Beidi Chen, Carnegie Mellon University
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.
 
 
 
 
 
Prof. Christopher De Sa, Cornell University
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.
 
 
 
 
 
Prof. Thorsten Joachims, Cornell University
Research Assistant
Prof. Thorsten Joachims, Cornell University
June 2022 – February 2023 Ithaca, NY

Engineering Experience

 
 
 
 
 
Pathways project, Cornell University
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 Project, Cornell University
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.

Ongoing Projects

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HTorch - Hyperbolic Learning with MCTensor
We want to build all hyperbolic learning models (with manifolds as Halfspace, Lorentz, Poincare, etc.) on top of MCTensor algorithms.
HTorch - Hyperbolic Learning with MCTensor

Academic services

NeurIPS'23, ICLR'24, ICML'24, KDD'24, DMLR journal (upcoming) reviewer

Contact

Please feel free to contact me!