I am a fourth-year Ph.D. candidate in the Department of Computer Science at Rutgers University, advised by Prof. Dimitris N. Metaxas. My research broadly lies at the intersection of large language models, retrieval-augmented generation and information retrieval. I am particularly interested in building reliable retrieval and reasoning frameworks for knowledge-intensive AI systems.
Before joining Rutgers, I received my M.S. degree in Computer Science from Syracuse University in 2022 and my B.Eng. degree from Jilin University in 2020.
I am currently seeking intern/full-time Research Scientist, Applied Scientist, or Machine Learning Engineering opportunities starting in 2026 or early 2027.
Education
Ph.D. Candidate in Computer Science
M.S. in Computer Science
B.Eng. in Logistics Engineering
Experience
Research Assistant
- Set-level optimization for relevance-aware diverse retrieval.
- Agentic GraphRAG for robust reasoning over noisy and incomplete KGs.
- Pooling & Semantic Shift: A formal theory of long-text embedding retrieval failure.
- Confidence-guided multimodal Q&A with complementary evidence selection.
Research Intern
- Works with Yangmin Ding & Shaobo Han.
- Efficient GraphRAG for Domain-Specific QA.
Research Assistant
- Advisor: Sucheta Soundarajan
Selected Publications
Pooling and Semantic Shift: the Fundamental Challenge in Long Text Embedding and Retrieval.
In arXiv,
2026.
CLIMB: Confidence-Guided Complementary Evidence for Multimodal Retrieval-Augmented Generation.
In arXiv,
2026.
A-MEM: Agentic Memory for LLM Agents.
In NeurIPS,
2025.
Task-Aligned Tool Recommendation for Large Language Models.
In IJCNLP-AACL (Oral),
2025.
Vector Retrieval with Similarity and Diversity: How Hard Is It?.
In arXiv,
2024.
INMS: Memory Sharing for Large Language Model based Agents.
In arXiv,
2024.
2k-Vertex Kernels for Cluster Deletion and Strong Triadic Closure.
In Journal of Computer Science and Technology,
2023.
Contact
- hanggao [dot] gh [at] gmail [dot] com
- 617 Bowser Rd, Piscataway, NJ 08854