Ph.D Student, Computer Science
Nanyang Technological University, Singapore

About

I am a first-year PhD student and luckily advised by the brilliant and kind researcher Prof. Ziwei Liu. I am passionate about deep learning research in the following topics:

(1) Foundation Models: Stable Diffusion, GPT, they are seemingly promising to put AI with real intelligence into pratical use.

(2) Embodied AI: an autonomous agent that learns to solve challenging tasks within environment through interaction and exploration.

These are moonshot wild dreams and also what I will focus on in the long run.

Currently I base my first step research topics on large-scale multi-mdoality models and emerging abilities in foundation models.

I am always grateful to those more senior who have a deep understanding of these topics for their advice. Besides, I am always willing to collaborate with people who are also interested in relevant issues, and provide corresponding guidance to younger students (undergrad or master).

Email: drluodian[at]gmail[dot]com

Selected Publications
  1. [12]
    Bo Li*, Peiyuan Zhang*, Jingkang Yang, Yuanhan Zhang, Fanyi Pu, Ziwei Liu OtterHD: A High-Resolution Multi-modality Model ArXiv Preprint. [code]
  2. [11]
    Bo Li*, Yuanhan Zhang*, Liangyu Chen, Jinghao Wang, Fanyi Pu, Jingkang Yang, Chunyuan Li, Ziwei Liu MIMIC-IT: Multi-modal In-Context Instruction Tuning ArXiv Preprint. [code]
  3. [10]
    Bo Li*, Yuanhan Zhang*, Liangyu Chen, Jinghao Wang, Jingkang Yang, Ziwei Liu Otter: A multi-modal model with in-context instruction tuning ArXiv Preprint. [code]
  4. [9]
    Liangyu Chen*, Bo Li*, Sheng Shen, Jingkang Yang, Chunyuan Li, Kurt Keutzer, Trevor Darrell, Ziwei Liu Coordinating Multiple Vision-Language Models for Visual Reasoning NeurIPS 2023, In Conference on Neural Information Processing Systems. Short version in ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation Models (ME-FoMo).
  5. [6]
    Bo Li, Yifei Shen, Yezhen Wang, Wenzhen Zhu, Dongsheng Li, Kurt Keutzer, Han Zhao Invariant information bottleneck for domain generalization AAAI 2022, In Proceedings of the AAAI Conference on Artificial Intelligence. [code]
  6. [8]
    Bo Li*, Yifei Shen*, Jingkang Yang, Yezhen Wang, Jiawei Ren, Tong Che, Jun Zhang, Ziwei Liu Sparse Mixture-of-Experts are Domain Generalizable Learners ICLR 2023 (Oral), In International Conference on Representation Learning 2023. [code] Short version in NeurIPS 2022 Workshop on Distribution Shift.
  7. [7]
    Yezhen Wang, Tong Che, Bo Li, Kaitao Song, Hengzhi Pei, Yoshua Bengio, Dongsheng Li Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One Under Review.
  8. [5]
    Yezhen Wang, Bo Li, Tong Che, Kaiyang Zhou, Ziwei Liu, Dongsheng Li Energy-Based Open-World Uncertainty Modeling for Confidence Calibration ICCV 2021, In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). [code]
  9. [4]
    Bo Li, Yezhen Wang, Shanghang Zhang, Dongsheng Li, Kurt Keutzer, Trevor Darrell, Han Zhao Learning invariant representations and risks for semi-supervised domain adaptation CVPR 2021, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. [code]
  10. [3]
    Sicheng Zhao, Bo Li, Pengfei Xu, Xiangyu Yue, Guiguang Ding, Kurt Keutzer MADAN: multi-source adversarial domain aggregation network for domain adaptation IJCV 2021, International Journal of Computer Vision.
  11. [2]
    Bo Li, Yezhen Wang, Tong Che, Shanghang Zhang, Yoshua Bengio, Kurt Keutzer Rethinking distributional matching based domain adaptation arXiv preprint arXiv:2006.13352.
  12. [1]
    Sicheng Zhao*, Bo Li*, Xiangyu Yue*, Yang Gu, Pengfei Xu, Runbo Hu, Hua Chai, Kurt Keutzer Multi-source domain adaptation for semantic segmentation NeurIPS 2019, In Neural Information Processing Systems. [code]
Experiences

I have been fortunately collaborating and doing research at/with

Professional Services
  • Talk/Technical Sharing:
  • Slab@NTU: Cluster Adminstrator (70+ users, 400+ GPUs)

  • Conference Reviewer / Program Committee:

    • ICCV (2021,2023), NeurIPS (2022), BMVC (2023), AAAI (2023), CVPR (2022,2023), AISTATS (2023), ICML (2023).

    • Workshop: ICLR 2023 (DG)

  • Journal Reviewer:

    • Pattern Recognition (PR)
    • Transactions on Multimedia (TMM)
    • Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
    • International Journal of Computer Vision (IJCV)
Awards and Fellowships

Personal

Exercise
  • Deadlift: 100kg, 1-3RM
  • Squat: 100kg, 1-3RM
  • Bench Press: 80kg, 3RM
  • 5KM Run: ~34 min
Life
  • Love watching a lot of Youtube videos and reading daily world news.
  • Enjoy participating meaningful social activities (connect with community).
  • Dream to be a film director.

Acknowledgements: this website builds on al-folio and Jiaming Song.