Yi Ding (丁熠)

Hi there! I'm a PhD student at Purdue University , Department of Computer Science, advised by Dr. Ruqi Zhang. I obtained my B.S. degree at the School of Mathematics, Tianjin University . Previously, I worked as a research assistant in the MLDM Lab's Multimodal Vision Processing (MVP) Group, under the guidance of Dr. Bing Cao.

My research interests lie in developing reliable machine learning algorithms and frameworks for real-world applications, with a particular focus on the alignment of Large Foundation Models (LLMs and VLMs) and the generalization of multimodal learning algorithms.

My research focuses on developing reliable and efficient post-training algorithms for foundation models, with an emphasis on improving the general intelligence and safety awareness of LLMs. I am particularly interested in how models can learn and self-evolve from limited, noisy, or imperfect supervision.

• LLM/VLM Post-Training

  Reinforcement Learning, On-Policy Distillation, Reasoning, Self-Correction, and Self-Evolving.

• Alignment and Reliability

  Preference Alignment, Safety Alignment, Reliable Supervision, and Robustness.