About

I am a fifth year CS Ph.D. candidate at The University of North Carolina, Chapel Hill advised by Prof. Mohit Bansal. My research focuses on multimodal AI and agentic systems for understanding and reasoning across different modalities (especially videos). My goal is to develop effective and efficient systems that integrate perception and reasoning to solve complex real-world problems. I am a recipient of the Bloomberg Data Science Ph.D. Fellowship.

I am on the job market, looking for full-time Research Scientist positions starting Summer 2027. Feel free to reach out!

Research Interests

I build multimodal systems that perceive and reason over long and complex videos. My recent work follows three directions:

NewsRecent

  • Sep 2026Searching Videos as Trees accepted to NeurIPS 2026.
  • Jul 2026EgoMemReason accepted to COLM 2026.
  • Jun 2026Evidence-Backed Video Question Answering accepted to ECCV 2026.
  • Jun 2026Co-organized the Transformers for Vision (T4V) Workshop at CVPR 2026.
  • May 2026Joined Bloomberg in New York as a Research Intern, working on large-scale multimodal document understanding.
  • Apr 2026Multimodal Fact-Level Attribution for Verifiable Reasoning accepted to ICML 2026.
  • Mar 2026Received the Bloomberg Data Science Ph.D. Fellowship.
  • Feb 2026Active Video Perception accepted to CVPR 2026 Findings.
  • Jan 2026SiLVR accepted to TMLR.
  • Nov 2025TimeRefine accepted to WACV 2026.
  • Aug 2025Video-RTS accepted to EMNLP 2025 Main and MEXA to EMNLP 2025 Findings.
  • Jun 2025Co-organized the Transformers for Vision (T4V) Workshop at CVPR 2025.
  • May 2025Joined Salesforce AI Research in Palo Alto as a Research Intern, working on agentic long video understanding.
  • Feb 2025VideoTree accepted to CVPR 2025.
  • Oct 2024DAM accepted to WACV 2025.
  • Sep 2024LLoVi accepted to EMNLP 2024 Main.
  • May 2024Joined the Meta FAIR Perception team in Menlo Park as a Research Intern.
  • Jan 2024Unified Embeddings for Multimodal Retrieval via Frozen LLMs accepted to EACL 2024 Findings.
  • Jul 2023UCoFiA accepted to ICCV 2023.
  • May 2023Joined Amazon Alexa AI in Seattle as an Applied Scientist Intern.
  • 2022Language-Augmented Pixel Embedding for Generalized Zero-Shot Learning accepted to IEEE TCSVT.
  • Aug 2022Started my Ph.D. at UNC-Chapel Hill, advised by Prof. Mohit Bansal.
  • Aug 2021Region Semantically Aligned Network for Zero-Shot Learning accepted to CIKM 2021 (long oral).

Publications

Agentic video understanding
Efficient video reasoning with LLMs
Long-horizon memory and verifiable reasoning
Earlier work: retrieval and zero-shot learning
2026
2025
2024
2023
2022
  • Language-Augmented Pixel Embedding for Generalized Zero-shot Learning
    Language-Augmented Pixel Embedding for Generalized Zero-shot Learning
    Ziyang Wang, Yunhao Gou, Jingjing Li, Lei Zhu, Heng Tao Shen
    TCSVT 2022
2021

Experience

  • May 2026 — Aug 2026
    Research Intern · Bloomberg
    New York City, NY · Large-scale multimodal document understanding, with Dr. Debanjan Mahata and Dr. Daniel Preoțiuc-Pietro
  • May 2025 — Feb 2026
    Research Intern · Salesforce AI Research
    Palo Alto, CA · Agentic long video understanding, with Dr. Juan Carlos Niebles, Dr. Michael S. Ryoo, Dr. Junnan Li and Dr. Honglu Zhou
  • May 2024 — Dec 2024
    Research Intern · Meta FAIR Perception
    Menlo Park, CA · Video foundation encoders, with Dr. Ronghang Hu, Dr. Christoph Feichtenhofer, Dr. Po-Yao Huang and Dr. Daniel Bolya
  • May 2023 — Oct 2023
    Applied Scientist Intern · Amazon Alexa AI
    Seattle, WA · Multimodal retrieval with LLMs, with Dr. Heba Elfardy, Dr. Kevin Small and Dr. Markus Dreyer
  • Oct 2021 — May 2022
    Research Intern · Tsinghua AIR
    Beijing, China · Advised by Prof. Jingjing Liu

Education

  • 2022 — present
    Ph.D. in Computer Science
    UNC-Chapel Hill · Advised by Prof. Mohit Bansal
  • 2022 — 2024
    M.S. in Computer Science
    UNC-Chapel Hill · During Ph.D. study
  • 2018 — 2022
    B.Eng. in Software Engineering
    University of Electronic Science and Technology of China · Advised by Prof. Jingjing Li

Honors & Service

Honors

  • Bloomberg Data Science Ph.D. Fellowship, Bloomberg L.P., March 2026 — recognized for my research in long-context multimodal understanding and multimodal agents.

Service

I am a die-heart Arsenal and Tar Heel fan.