Welcome to Yingtao’s Homepage!

Biography

My name is Yingtao Luo (Ying-Tao Luo, 罗颖韬). I am a third-year Ph.D. student in joint Machine Learning and Public Policy program (with Heinz College and Machine Learning Department) at Carnegie Mellon University. I am mainly advised by Prof. Rema Padman, with the guidance and help from Prof. Reza Skandari at Imperial College London, Prof. Bryan Wilder at CMU, and Dr. Arman Kilic at MUSC, on research that combines methodological innovation in sequential decision-making agents with real-world applications in heart transplantation decision-making. Before joining CMU, I primarily work with Prof. Jun Zhu at Tsinghua University, Prof. Qiang Liu at CASIA and many other wonderful people. I also worked at Damo Academy of Alibaba and Microsoft Research Asia for research intern.

I am very grateful for my collaborators and all the other great people from whom I learn a lot and get a lot of support. Their impacts have really shaped and transformed who I am now.

Methodology Interest

Decision-Making: Designing intelligent agents capable of adaptive reasoning, self-evolution through past failures, and meaningful collaboration with clinical experts in high-stakes environments.

Foundation Models: Advancing the use of large language and multimodal models to extract, integrate, and reason over diverse biomedical data, enabling more personalized, context-aware, and evidence-grounded decision support.

Domain Interest

AI for Health, AI for Science (scientific basis for health).

Statement

I am more attracted to the real-world impact of research and how people’s lives can be improved directly. I am generally open to collaboration who share the same interest and enjoy working with talented people I have met so far.

Skillset

Mostly about core ML (statistics, convex optimization, graphical model, reinforcement learning, etc.) and coding with Pytorch and CUDA, but also have the pleasure to learn human decision bias, healthcare informatics to aid my research.