Ge Liu
Yunan Luo
NEW Faculty Spotlight: Ge Liu
Ge Liu is one of the new faculty who joined MMLI during our renewal. She is currently an assistant professor of the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign. She is interested in geometric DL and multi-modal flow matching & diffusion methods for computational design of functional and therapeutic molecules, including but not limited to antibody design, enzyme and catalyst design and drug discovery. [Click to read more]
What is your background/what did you do before your current role?
I received my PhD from MIT EECS department (CSAIL). Prior to joining UIUC, I spent an amazing year at the Institute for Protein Design as a postdoctoral researcher advised by Prof. David Baker.
What is your current position/short description of what you are working on right now with MMLI.
I am an assistant professor in CS. I work on geometry-aware and multimodal generative models (especially diffusion and flow-matching) for engineering and de novo design of functional molecules (proteins, small molecules). I’m excited to work with MMLI on new-to-nature enzyme/catalysis design and drug discovery with generative AI and LLMs. You can find out more about my lab here!
What drew you to MMLI (or your lab)?
I am drawn by the opportunity to collaborate with diverse experts in science (especially chemistry) and to work on frontier scientific research problems with real-world feedback.
What has been your favorite part of being a part of MMLI?
The collaborative spirit and deep scientific expertise.
How do you like to spend your free time?
Road trip, cooking, music.
Fun fact (or extremely average fact) about yourself you would like to share.
I want to improve my skills in using PyMOL.
NEW Faculty Spotlight: Yunan Luo
Yunan Luo is one of the four new faculty members who joined MMLI during our renewal. He is currently an assistant professor in the School of Computational Science and Engineering at Georgia Institute of Technology. Previously, he was a MMLI seed grantee, and had worked on MMLI projects during his PhD. He is broadly interested in computational biology and machine learning, with a focus on developing AI and data science methods to reveal core scientific insights into biology and medicine. [Click to read more]
What is your background/what did you do before your current role?
I received my Ph.D. in Computer Science from the University of Illinois Urbana–Champaign (UIUC) in 2021. My training has been in computer science throughout my degrees, and over time I developed a strong interest in interdisciplinary research, particularly at the interface of machine learning and the life sciences.
What is your current position/short description of what you are working on right now with MMLI?
I am an Assistant Professor in the School of Computational Science & Engineering in the College of Computing at Georgia Tech. Within MMLI, I work on AI-guided enzyme engineering, with an emphasis on developing methods that operate effectively in realistic experimental settings where data are sparse, noisy, and generated iteratively. You can find out more about my lab and research here!
What drew you to your project and/or MMLI?
MMLI’s vision closely aligns with the problems I am most passionate about: closing the loop between computation and experimentation to make molecular design more systematic and scalable. I was especially drawn to MMLI’s end-to-end approach to “molecule making,” where modeling decisions are informed by experimental realities and progress is driven by close collaboration across AI and chemistry teams.
What has been your favorite part of being a part of MMLI?
The people, and the collaborative culture they create. MMLI brings together researchers who think deeply about different parts of the pipeline, from experimental design and measurement to model building and deployment. I have especially appreciated how open and generous people are with ideas, feedback, and time, which makes collaborations both productive and enjoyable.
How do you like to spend your free time? (or what would you do for fun if you had more free time!)
When I have free time, I like to recharge with simple routines and a slower pace. If I had more uninterrupted time, I would happily spend it reading books that are as far away from my research as possible.
Fun fact (or extremely average fact) about yourself you would like to share.
I am probably one of the MMLI members who has held the most roles within the institute, spanning trainee, collaborator, seed grant awardee, and Thrust project PI. I was in the final year of my Ph.D. when MMLI 1.0 launched in 2020 and was supported by MMLI as a graduate research assistant during 2020–2021, co-mentored by my Ph.D. advisor, Dr. Jian Peng, and MMLI Director, Dr. Huimin Zhao. After starting my position at Georgia Tech, I continued close collaborations with Huimin’s lab and was fortunate to receive two MMLI Seed Grants (2022–2024) to explore new research directions early in my career. In MMLI 2.0, I have been honored to be included as a Thrust project PI. I am deeply grateful for the opportunities MMLI has provided, which have been pivotal in shaping my research trajectory, and I have truly enjoyed growing my career alongside MMLI.
