Curriculum Vitae
I am a Ph.D. candidate specializing in memory architectures, memory evaluation, and decision-making for AI agents, with experience designing multimodal memory systems, evaluation systems, and tool-use workflows.
Education
Sep 2024–present
Columbia University
M.S., Computer Science
University of Michigan, Ann Arbor
B.S., Computer Science and Physics
Research experience
University of Notre Dame · Sep 2024–present
Ph.D. Candidate, advised by Prof. Yiyu Shi
- MemEye: visual-centric evaluation of multimodal agent memory.
- HM-RRG: hierarchical memory for generation from long clinical contexts.
- Agent Last Doubt: risk-aware tool use and agent decision-making.
- Seeing, Maintaining, and Learning: multimodal agent memory survey.
- Node-as-Agent: training-free graph agentic reasoning.
- MediQ-GAN: medical image generation from limited data.
Research details → · Publications →
Technical skills
Machine learning & AI
Agentic AI, large language models, multimodal large language models, generative modeling, medical AI, and robot learning and control.
Programming & systems
Python, C++, C, Java, MATLAB, SQL, PyTorch, NumPy, and SciPy.
Software & tooling
Linux, Git, Hugging Face, CUDA, and cloud and HPC environments.