đź‘‹ I'm a Ph.D. candidate diving deep into the world of AI and ML with years of hands-on experience. My expertise spans machine learning, deep learning, computer vision, and more.
🔍 My research focuses on low-resource data-efficient learning, hyperparameter optimization, secure learning, and efficient learning in AI systems. I'm also passionate about generative AI (large language models (LLMs), and diffusion models), Multimodal Foundation Models and probabilistic graphic models.
🎓 Currently pursuing my Ph.D. at the University of Texas at Dallas under Prof. Feng Chen's guidance.
🚀 I will be a Research Scientist Intern at Meta AI this summer. Now on the lookout for a full-time role (Research Scientist/Engineer, Post-doc, etc) in 2024.
Changbin Li, Kangshuo Li, Yuzhe Ou, Lance Kaplan, Audun Jøsang, Jin-hee Cho, Dong-hyun Jeong and Feng Chen.
International Conference on Learning Representations (ICLR), 2024
Changbin Li*, Suraj Kothawade*, Feng Chen, Rishabh Iyer.
International Conference on Machine Learning (ICML), 2022
Krishnateja Killamsetty*, Changbin Li*, Chen Zhao, Rishabh Iyer, Feng Chen. (* equal contribution)
AAAI Conference on Artificial Intelligence (AAAI), 2022
Conference: CVPR '24, ICLR '24, ICML '22 '24, NeurIPS '21 '23, AAAI '23-'24, KDD '20-'24, SDM '22, AISTATS '21, UAI '21, AutoML '21
Journal: Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Transactions on Knowledge Discovery from Data (TKDD), Big Data Research