Resume
Academic Achievements
- Learning Fast and Slow for Online Time Series Forecasting, ICLR-2023
- Continual Normalization: Rethinking Batch Normalization for Online Continual Learning, ICLR-2022
- TATL: Task Agnostic Transfer Learning for Skin Attributes Detection, MIA (IF=13.828)
- DualNet: Continual Learning, Fast and Slow, NeurIPS-2021
- Contextual Transformation Networks for Online Continual Learning, ICLR-2021
- Online Deep Learning: Learning Deep Neural Networks on the Fly, IJCAI-2018
Research Experience
- Currently a research scientist at the Machine Intelligence department, Institute for Infocomm Research (I2R), A*Star.
Education
- Received his Ph.D. from the School of Computing and Information Systems, Singapore Management University, under the supervision of Prof. Steven Hoi.
Background
- Research interests include continual learning, time series forecasting, meta learning, domain adaptation.
Miscellany
- Regularly serves as a reviewer for prestigious conferences and journals in AI and ML; Useful links: Google Scholar, Github, Linkedin