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. With his guidance, 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 computer-vision-in-the-wild 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
Experiences
I have been fortunately collaborating and doing research at/with
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Nov. 2022 - Present: Microsoft Research, Redmond
Collaborate with Dr. Chunyuan Li’s team, to explore foundation models emerging abilities and deep mysteries of intelligence.
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Sep. 2020 - Dec. 2021: Microsoft Research, Shanghai
Supervised by Dr. Dongsheng Li in the beautiful and relaxing WestBud office, with chill and smart colleagues.
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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. Doing front-tier research in nice bay-area weather. Go Cal and Roll on your Golden Bears!
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Jan 2020 - Nov 2022: Dr. Tong Che, MILA/Nvidia Research
Great appreciation on guiding me in many fascinating ML topics.
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May 2020 - Dec. 2021: Prof. Han Zhao, UIUC
Learn to write a paper with machine learning taste.
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May 2018 - Oct. 2019: DiDi Visual Perception Team, Beijing
First internship and two papers there.
Selected Publications
- [8]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. - [6]Invariant information bottleneck for domain generalization
AAAI 2022, In Proceedings of the AAAI Conference on Artificial Intelligence.[code] - [5]Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
ICCV 2021, In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).[code] - [4]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] - [3]MADAN: multi-source adversarial domain aggregation network for domain adaptation
IJCV 2021, International Journal of Computer Vision. - [2]Rethinking distributional matching based domain adaptation
- [1]Multi-source domain adaptation for semantic segmentation
NeurIPS 2019, In Neural Information Processing Systems.[code]
Professional Services
Conference Reviewer / Program Committee:
ICCV (2021), NeurIPS (2022), BMVC (2023), AAAI (2023), CVPR (2022,2023), AISTATS (2023).
Journal Reviewer: Pattern Recognition (PR), Transactions on Multimedia (TMM), Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Slab@NTU: Cluster Management (70+ users, 400+ GPUs)
Awards and Fellowships
- AISG Fellowship 2022
- Microsoft Starbridge Program 2020
- Silver Medal, China Collegiate Programming Competition (CCPC), ACM Regional, 2017
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.