Ph.D Student, Computer Science
Nanyang Technological University, Singapore
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).
- MIMIC-IT: Multi-modal In-Context Instruction Tuning
- Otter: A multi-modal model with in-context instruction tuning
- Coordinating Multiple Vision-Language Models for Visual Reasoning
NeurIPS 2023,In Conference on Neural Information Processing Systems.
- Invariant information bottleneck for domain generalization
AAAI 2022,In Proceedings of the AAAI Conference on Artificial Intelligence. [code]
- 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.
- Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
ICCV 2021,In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). [code]
- 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]
- MADAN: multi-source adversarial domain aggregation network for domain adaptation
IJCV 2021,International Journal of Computer Vision.
- Rethinking distributional matching based domain adaptation
- Multi-source domain adaptation for semantic segmentation
NeurIPS 2019,In Neural Information Processing Systems. [code]
I have been fortunately collaborating and doing research at/with
Sep. 2020 - Dec. 2021: Microsoft Research, Shanghai
Supervised by Dr. Dongsheng Li in the beautiful and relaxing WestBud office, with chill and smart colleagues.
Oct. 2019 - Aug. 2020 (remote till May 2021): Berkeley AI Research, CA, USA
Supervised by Prof. Kurt Keutzer and Prof. Sicheng Zhao, Prof. Xiangyu Yue, Prof. Shanghang Zhang and Dr. Colorado Reed. Enjoy the weather and front-tier research atmosphere. Go Cal and Roll on your Golden Bears!
Jan 2020 - Nov 2022: Dr. Tong Che, MILA/Nvidia Research
Great appreciation on guiding me to explore many fascinating ML topics.
May 2020 - Dec. 2021: Prof. Han Zhao, UIUC
Learn to write a paper with machine learning taste.
May 2018 - Oct. 2019: DiDi Visual Perception Team, Beijing
First internship and two papers there.
- Talk/Technical Sharing:
- Slab@NTU: Cluster Adminstrator (70+ users, 400+ GPUs)
- The AI Talk: Organizer
Conference Reviewer / Program Committee:
ICCV (2021,2023), NeurIPS (2022), BMVC (2023), AAAI (2023), CVPR (2022,2023), AISTATS (2023), ICML (2023).
Workshop: ICLR 2023 (DG)
- Pattern Recognition (PR)
- Transactions on Multimedia (TMM)
- Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- International Journal of Computer Vision (IJCV)
Awards and Fellowships
- AISG Fellowship 2022
- Microsoft Research Starbridge Program 2020
- Silver Medal, China Collegiate Programming Competition (CCPC), ACM Regional, 2017
- Deadlift: 100kg, 1-3RM
- Squat: 100kg, 1-3RM
- Bench Press: 80kg, 3RM
- 5KM Run: ~34 min
- 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.