Assistant Professor
Department of Health Data Science and Artificial Intelligence
Contact
Lishan Yu, PhD became an Assistant Professor at McWilliams School of Biomedical Informatics at UTHealth Houston in September of 2023. After earning her PhD, Yu worked as a postdoctoral fellow at Yau Mathematical Sciences Center, Tsinghua University. She has received extensive training in mathematics, statistics, computer science, and biomedical informatics. Dr. Yu is passionately dedicated to developing efficient methods to address challenges in biomedical informatics that arise from real-world situations.
Tell us about your research center and/or what research you are currently working on?
My research revolves around striving for optimal problem-solving in biomedical informatics. Currently, I am interested in the integration of the frontier AI methodologies into the realm of biomedical informatics, which involves the development and improvement of models. I am working on leveraging the capabilities of big models to advance approaches for addressing domain-specific challenges.
What type of student or Postdoctoral Fellow are you looking for to work in your center?
We are looking for highly motivated students or postdoctoral fellows who are passionate about biomedical informatics. They should have a willingness to learn the related frontier techniques in informatics and have practical skills to quickly implement research ideas. They should have the potential to evolve into innovative thinkers, capable of working both independently and collaboratively.
What does the future of biomedical informatics look like?
The future of biomedical informatics is expected to be marked by mutually beneficial relationships with the fields of medicine and healthcare, where they will continue to complement and drive each other's development. Biomedical informatics will play an increasingly vital role in the advancement of medicine and health care. For instance, biomedical informatics will greatly enhance the information management and automation of medical data, leading to improved data quality and quantity. This, in turn, will further drive the progress of biomedical informatics, significantly enhancing abilities including discovering new medical knowledge from healthcare data and building models for disease prediction.