Jiewen Hu
Jiewen Hu

Master’s in Machine Learning

Carnegie Mellon University

About Me

I am a master’s student in the Machine Learning (MSML) program at Carnegie Mellon University, advised by Professor Sean Welleck. My research focuses on enhancing the logical reasoning capabilities of language models, with a particular emphasis on mathematical reasoning and interpretability. I aim to bridge the gap between human understanding and machine reasoning, enabling AI to excel in rigorous tasks like theorem proving, complex planning, and decision-making.

Previously, I completed an internship at Shanghai Jiao Tong University in summer 2023, advised by Professor Pengfei Liu, where I worked on improving reasoning and alignment in large language models for mathematical tasks.

I am also excited to explore new areas and have been fortunate to work with Professor Oana Carja on computational evolutionary biology, Professors Paul Liang and Louis-Philippe Morency on facial behavior analysis toolkits, and Professor Giovanni Leoni on real analysis research.

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Interests
  • Neural Theorem Proving
  • Interpretability
  • Model Reasoning Abilities
  • Reinforcement Learning
Education
  • MS Machine Learning

    Carnegie Mellon University

  • BSc Computer Science

    Carnegie Mellon University

Publications
(2024). miniCTX: Neural Theorem Proving with (Long-) Contexts. The 4th Workshop on Mathematical Reasoning and AI at NeurIPS'24.
(2024). Reformatted Alignment. Findings of the Association for Computational Linguistics: EMNLP 2024.