Prof. Yao: Agentic AI systems in Computational Biology

School of Computing
Faculty Advisor
Qiuming Yao
Contact Email qyao3@unl.edu
Website
Advisor College:
Engineering
Potential Student Tasks
  • Come to in person meeting.
  • Do some programming work.
  • Read relevant materials.
  • Learn how to explore the unknown.
  • Learn how to be better than AI.
Student Qualifications

Be responsible, and be aware of the timeline. Have passion and true curiosity.
Training, Mentoring, and Workplace Community
  • In person teaching and learning.
  • Directly work with the professor.
  • Support to formulate your own project pathways.
  • Long term support in research and job hunting.
Available Positions
3

AI agent is most novel thing during the past year. This project explores the development of agentic AI systems for computational biology, focusing on autonomous and interactive AI agents that can assist with biological data analysis, knowledge retrieval, hypothesis generation, and scientific workflow management. We specifically will explore what can be done, what cannot be done, what is risky, and what is reliable. Currently we don't know the consequence and impact of these intelligent entities in life science and medical applications. Let's explore together.