Research

At GLOW.AI, we are interested in learning and optimization on data-centric AI, collaborative AI, automated AI, and AI for science problems, their applications to LLMs & MLLMs, among others. See below for the research themes we work on.

Data-Centric AI

Data selection, data valuation, knowledge distillation, data attribution, machine unlearning, data ownership, domain generalization

Agents in ML

Federated learning, collaborative ML, incentives, reinforcement learning

Automated AI

Active learning, Bayesian & zeroth-order optimization, neural architecture search, meta-learning

AI for Science

Experimental design, physics-informed ML, quantum ML, precision agriculture

Recent News

See the list of our publications here.

  • Jul 2024 Our AI Visiting Professorship Proposal (~S$4M for 3 years) on Data-Centric Machine Learning at Scale with Pang Wei Koh is accepted! Read more here.
  • Jun 2024 Presented AutoAI and PINNACLE in Adaptive Experimentation Workshop @ Meta NYC. Read more here.
  • May 2024 Presented our works on Data-Centric AI in the Age of LLMs (FreeShap, WASA, and INSTINCT) in the Data-Centric AI workshop at The Web Conference 2024. Read more here.
  • May 2024 Bryan served as an Area Chair of ICLR 2024, AISTATS 2024, ICML 2024, NeurIPS 2024 & AAAI 2025, and SPC of AAMAS 2025 & IJCAI 2024.