Exploring Principled Learning and Optimization Research

I am looking for self-motivated research assistants and interns. We may work on the following topics or other exciting topics that attract you. If you are interested, please send your CV and transcripts to [email protected].

Optimization for LLMs

(1) Data Optimization, e.g., data generation, data selection, data mixture, etc. (2) Efficient Training, e.g., memory-efficient optimizers, compute-efficient optimizers, etc. (3) Inference-Time Scaling, e.g., in-context learning, test-time training, LLM routing, RAG, hyper-parameter optimization, etc. (4) Efficient Deployment, e.g., quantification, distillation, etc. (5) Learning Paradigms, e.g., reinforcement learning, continuous learning, learning from partial feedback, etc.

LLMs for Optimization

(1) Learn to Optimize and Make Decisions (2) Optimization in the Language Space (3) Agentic AI using LLMs