General Instructions for Giving a Job Talk at LARK Lab At LARK Lab, we value engaging discussions, deep technical insights, and collaborative learning. A job talk is an opportunity for us to learn about your research, thought process, and how you approach problems.

We are excited to announce the launch of our Reinforcement Learning (RL) Seminar, a biweekly reading and discussion series focused on foundational RL concepts and applications. With several ongoing RL-related projects in our lab and a growing need for structured training among our trainees, we are introducing this seminar-style reading club to foster a deeper understanding of RL principles.

Dr. Yanjun Gao recently spoke at a campus conference on “Engaging with AI”, where she shared insights on the evolving role of AI in research, healthcare, and education. The talk explored how AI innovations, particularly large language models (LLMs), are transforming scientific discovery and decision-making.

We are thrilled to announce that our paper, “When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?” has been accepted to the Empirical Methods on Natural Language Processing (EMNLP) 2024 conference as a Findings paper!