Faculty Spotlight: Jiawei Han
Jiawei Han is a computer scientist, focusing on data mining, machine learning and text mining. His group has been working on information extraction and text mining from scientific literature. He was drawn to MMLI by its interest in MMLI data/text mining from chemistry data, including chemistry science literature and says that his favorite part of being a part of MMLI is working with his students and other colleagues in chemistry on various research problems. In his free time, he likes to travel and reading broadly. [Click above to read more!]
Trainee Spotlight: Mohit Anand
Mohit Anand Mohit Anand is Ph.D candidate at Penn State University in the Maranas group, which explores metabolic modeling, protein design, and synthesis planning. His research focuses on developing computational tools for synthesis planning, recently investigating language models to predict synthetic pathways. Fascinated by the intersection of AI and chemistry, he was drawn to MMLI after watching a documentary on AlphaFold, which he believed would transform enzyme chemistry—a belief later validated by a Nobel Prize awarded to its creators. At MMLI, he values the freedom to explore innovative ideas and collaborate with talented individuals, gaining insights from speakers at symposiums and retreats. [Click above to read more!]
MMLI Staff Spotlight: Jiawei Han
What is your background and describe your current work/role/any exciting projects you want to share.
My research focuses on Natural Language Processing, especially on Multimedia Multilingual Information Extraction, Knowledge-enhanced Large Language Models and Vision-Language Models, AI for Science and Science-inspired AI.
What drew you to MMLI? What has been your favorite part of being a part of MMLI?
It’s the people. It’s a wonderful privilege to be able to work with wonderful chemists such as Profs. Martin Burke, Ying Diao and Huimin Zhao. They are extremely intelligent, open-minded, kind and generous, and have become my close collaborators and good friends.
How do you like to spend your free time? I regularly do yoga and Zumba indoor, and have been enjoying outdoor activities in the countryside, especially cycling and hiking in the forests. I have been traveling to 30+ countries in six continents.
Fun fact (or extremely average fact) about yourself. I’m very creative in terms of making dumplings.
MMLI Trainee Spotlight: Let’s meet Mohit Anand
What is your background and describe your current work/role/lab and the project you are most excited to be working on right now.
I earned an integrated Bachelor’s and Master’s degree in Chemical Engineering from the Indian Institute of Technology Delhi (IIT Delhi). Currently, I am pursuing a Ph.D. in the Chemical Engineering program at Penn State University, where I work in the Maranas group. The group explores diverse research areas, including metabolic modeling, protein design, and synthesis planning.
My research focuses on developing computational tools for synthesis planning, which aim to reduce the time and effort required for experimental work and predicts synthesis routes for desired molecules by leveraging encoded chemical knowledge. Recently, I began exploring the use of language models to predict synthetic pathways. Generative models hold immense potential, and if successful, this approach could lead to the development of a powerful computational tool for the field.
What drew you to your project and/or MMLI?
The combination of AI and chemistry has always fascinated me. AI has already had a profound impact and will continue to shape the future in transformative ways. I was eager to become part of this community, learn advanced techniques, and contribute meaningfully where possible. A few years ago, I watched a documentary on AlphaFold, and though its full potential wasn’t immediately clear to me, I sensed that it would be a game-changer in the field of enzyme chemistry. Fast forward to the present, the minds behind AlphaFold have been recognized with a Nobel Prize, further highlighting its significance. Being involved, even in a small way, in the intersection of AI and chemistry is incredibly exciting and motivating for me.
What has been your favorite part of being a part of MMLI?
What I appreciate most about MMLI is the freedom to explore innovative ideas while collaborating with incredible people. Additionally, I have gained valuable insights from listening to speakers from around the world who are invited to our symposium and retreat. These two events provide the community with fresh perspectives and much-needed motivation to continue working toward our shared goals.
How do you like to spend your free time? (or what would you do for fun if you had more free time!)
I enjoy playing team sports and frequently participate in volleyball, badminton, and soccer. If I had more time, I would be consistent with my gym workouts, devote more attention to practicing music and travel more which is something I currently don’t get to do as much as I’d like.
Fun fact (or extremely average fact) about yourself you would like to share.
I enjoy sharing memes and reels with friends—it’s a fun way to stay connected and have inside jokes.