CV

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Education

• Ph.D. in Machine Learning, Georgia Institute of Technology, 2023 - Present
  • Advisor: Professor Zsolt Kira
• B.S. in Statistics, Renmin University of China, 2019 - 2023

Internships

• 02/2023 - 07/2023: Research Intern
  • Microsoft Research AI4Science
  • Duties included: Virus sequence prediction, classification and annotation using Large Language Models.
  • Advisor: Doctor Chuan Cao

Research Experience

• 08/2023 - Present: Graduate Research Assistant
  • School of Electrical and Computer Engineering, Georgia Institute of Technology
  • Duties included: Led the project “Robust Fine-Tuning of Vision Language Foundation Models”.
  • Advisor: Professor Zsolt Kira
• 06/2022 - 09/2022: Remote Research Assistant
  • Department of Applied Mathematics & Statistics, Johns Hopkins University
  • Duties included: Performed comprehensive studies on 10 real-world graph benchmark datasets and simulated random graphs following the 2-block stochastic block models, with respect to different methods (spectral or message-passing), graph topology (homophily or heterophily), graph density, and number of layers of the methods.
  • Advisors: Professor Carey Priebe, Applied scientist Da Zheng, Ph.D. student Ningyuan (Teresa) Huang
• 02/2022 - 04/2023: Undergraduate Research Assistant
  • School of Statistics, Renmin University of China
  • Duties included: Improved the fusion process of 3 modalities (visual, acoustic, and textual) based on cross-modality attention mechanism, explored how information interchange on various modalities reflects users’ preferences.
  • Advisor: Professor Xiaoling Lu
• 06/2021 - 05/2022: Undergraduate Research Assistant
  • Gaoling School of Artificial Intelligence, Renmin University of China
  • Duties included: Resolved the modality-missing issue by proposing an implicit imputation method (AIMI) with multi-modal representation learning via auto-encoding, clustering based on CPM-Net, adversarial networks and a feedback loop.
  • Advisors: Professor Hongteng Xu, Professor Hailun Liang

Teaching Experience

• 08/2023 - 12/2023: Random Processes (ECE6601)
  • Graduate Teaching Assistant

Publications

Adversarial and Implicit Modality Imputation with Applications to Depression Early Detection

From Local to Global: Spectral-Inspired Graph Neural Networks

Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models

Directional Gradient Projection for Robust Fine-tuning of Foundation Models

FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering

Skills

• Python
  • Data processing packages including Numpy, Pandas
  • Proficient in PyTorch, Scikit-learn
• C/C++
  • Object oriented programming
  • Qt for desiging programs with GUI
• R
• LaTeX
• SQL