Professional Summary
Motivated Ph.D. student in Computer Science and Engineering specializing in deep learning, large language models, and multimodal representation learning. Experienced in designing and scaling machine learning pipelines on large, noisy datasets for financial prediction and biomedical discovery.
Education
University at Buffalo, SUNY
PhD student in Computer Science and Engineering
Fudan University
Bachelor of Engineering, majoring in Electrical Engineering
Second-class Scholarship (Top 5%) at graduation
Work Experience
Harvard University
02/2025-05/2025Visiting Researcher
MBZUAI
08/2024-01/2025Visiting Researcher
GALASPORTS CO.
06/2023-08/2023Machine Learning Engineer Summer Intern
University at Buffalo
09/2022-NowPh.D Teaching/Research Assistant
Research Experience
LLM empowered Financial News Topic Extraction & Market Prediction
Ongoing Work
- Developed LLM-driven pipeline to extract financial themes from 40+ years of news data
- Created attention scores that improved stock market prediction (15.2% annual return)
A Probability Contrastive Learning Framework for Graph Representation Learning
NeurIPS 2024
- Solved False Pairs problem in graph contrastive learning via Bayesian modeling
- Achieved state-of-the-art results on MoleculeNet and QM9 benchmarks
A Unified Biomedical Knowledge Model for Molecule-Protein Interaction Prediction
Ongoing Work
- Integrated multi-modal biological data using optimal transport
- Improved accuracy and zero-shot generalization for interaction prediction
Other Works
Learning Unnormalized Statistical Models via Compositional Optimization (MECO)
ICML 2023 poster
KidSpeak: A General Multi-Purpose LLM for Kids' Speech Recognition and Screening
Arxiv
SE-3 Equivariant Mamba for Molecular Representation Learning
Arxiv
Prompt tuning based adapter for vision-language model adaptation
Ongoing Work