Li Sun

        [CV]


Contact:

lisun [at] bu [dot] edu

About Me

I am an Applied Scientist at AWS AI. Prior to that, I received my Ph.D. degree in Computer Engineering from Boston University, advised by Prof. Kayhan Batmanghelich. Previously, I received my M.S. degree in Intelligent Systems from University of Pittsburgh, and B.S. degree in Bioinformatics from Southern University of Science and Technology, China, where I did my undergraduate thesis with Prof. Wei Chen.

My research interests lie in self-supervised learning and multi-modal learning.

Selected Publications

* indicates equal contribution

From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding
Li Sun, Florian Luisier, Kayhan Batmanghelich, Dinei Florencio, Cha Zhang
ACL 2023 (Best Papers Honorable Mention) / Paper / Code
DocAgent: An Agentic Framework for Multi-Modal Long-Context Document Understanding
Li Sun, Liu He, Shuyue Jia, Yangfan He, Chenyu You
EMNLP 2025 / Paper / Code
Multi-Modal Large Language Models are Effective Vision Learners
Li Sun, Chaitanya Ahuja, Peng Chen, Matt D'Zmura, Kayhan Batmanghelich, Philip Bontrager
WACV 2025 / Paper / Code
Can Contrastive Learning Avoid Shortcut Solutions?
Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
NeurIPS 2021 / Paper / Code / News
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images
Li Sun*, Ke Yu*, Kayhan Batmanghelich
AAAI 2021 / Paper / Code
MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images
Yanwu Xu*, Li Sun*, Wei Peng*, Shuyue Jia, Katelyn Morrison, Adam Perer, Afrooz Zandifar, Shyam Visweswaran, Motahhare Eslami, Kayhan Batmanghelich
IEEE Transactions on Medical Imaging / Paper / Code / Project
Hierarchical Amortized GAN for 3D High Resolution Medical Image Synthesis
Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, Kayhan Batmanghelich
IEEE Journal of Biomedical and Health Informatics / Paper / Code
DrasCLR: A Self-supervised Framework of Learning Disease-related and Anatomy-specific Representation for 3D Lung CT Images
Ke Yu*, Li Sun*, Junxiang Chen, Maxwell Reynolds, Tigmanshu Chaudhary, Kayhan Batmanghelich
Medical Image Analysis / Paper / Code
Brain Tumor Segmentation and Survival Prediction Using Multimodal MRI Scans with Deep Learning
Li Sun, Songtao Zhang, Hang Chen, Lin Luo
Frontiers in Neuroscience / Paper
Knowledge Distillation via Constrained Variational Inference
Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-wei H. Lehman
AAAI 2022 / Paper

Work Experience

  • Research Scientist Intern, Meta • May - Sep, 2023
    Worked on large multi-modal models.
  • Research Intern, Microsoft • Jun - Aug, 2022
    Worked on large language models.
  • Research Intern, Microsoft • Mar - Aug, 2019
    Worked on medical image analysis and reinforcement learning.

Academic Service

  • Invited reviewer for NeurIPS, CVPR, IJCAI, MICCAI, IEEE TMI, IEEE J-BHI
  • Teaching assistant for CS523 Deep Learning, EC500 Medical Imaging with AI at Boston University

Honors and Awards

Honors

  • Best Papers Honorable Mention, The 61st Annual Meeting of the Association for Computational Linguistics • 2023
  • China National Scholarship, Ministry of Education of P.R. China • 2018
  • Magna cum laude Graduates, SUSTech • 2019

Challenges

  • 2nd Place in MICCAI Multimodal Brain Tumor Segmentation Challenge (BraTS), survival prediction task • 2018