August 2026 MMLI Community Spotlight

A major focus of Le’s work with MMLI has been developing the Open Enzyme Database, a community resource designed to make enzyme data more accessible and useful for researchers. Working closely with the National Center for Supercomputing Applications (NCSA), Le helped transform enzyme data and research concepts into an accessible web platform for the enzyme research community. The resulting work was published in Nucleic Acids Research, with Le serving as first author and leading many aspects of the project’s research and development.

Before joining Illinois, Le earned his Ph.D. in Systems Biology from Chalmers University of Technology in Sweden, where he worked at the intersection of computational biology, synthetic biology, and machine learning. His research included developing deep-learning approaches to predict enzyme turnover numbers from protein sequences and substrate structures. This interdisciplinary background provides a strong foundation for his current work using AI to advance enzyme discovery and engineering. 

As of August, 2026: Two years, eight months.

I pursued my Ph.D. degree in the Department of Life Sciences at Chalmers University of Technology in Sweden, with a major in systems biology. During my Ph.D., I worked at the intersection of computational biology, synthetic biology, and machine learning, with a particular interest in understanding and predicting enzyme properties.

My research interests primarily focus on synthetic biology, enzyme engineering, and artificial intelligence (AI). In MMLI, I am mainly working on enzyme database development and AI-driven prediction of enzyme properties, with the goal of developing computational tools that can facilitate enzyme discovery and engineering.

I was drawn to MMLI by the world-leading research being conducted at the intersection of synthetic biology and AI. Prof. Huimin Zhao is a pioneer in synthetic biology, and I was excited to have the opportunity to work with him and further develop my research expertise during my postdoctoral training.

My favorite part of being a part of MMLI is the highly collaborative and interdisciplinary environment. MMLI brings together researchers with diverse expertise, from synthetic biology and chemical synthesis to machine learning and software development. I really enjoy working with people from different backgrounds and seeing how our ideas can be translated into practical tools and resources for the scientific community. These collaborations have also given me many opportunities to learn new things and expand my research perspectives.

One of the most fulfilling experiences I have had within MMLI was working on the development of the Open Enzyme Database. This project gave me the opportunity to work closely with the NCSA team to transform our research ideas and enzyme data into an accessible and user-friendly web platform for the enzyme research community. I really enjoyed this collaboration and was impressed by the NCSA team’s expertise and professionalism in web development. Seeing the project grow from an initial idea into a comprehensive resource, and eventually having our work published in Nucleic Acids Research, was especially rewarding. This experience showed me how close collaboration between researchers and software developers can turn scientific ideas into practical resources with broader impact.

In my free time, I enjoy traveling and exploring new places, trying different foods, and spending time with friends.

Recently, I have been watching a lot of cooking and restaurant exploration videos. I enjoy learning new cooking techniques from these videos. I have been trying to improve my cooking skills, and it is always fun to experiment with new dishes in my free time.

More information about my work can be found on my Google Scholar profile.

Shivank joined the Shukla Group in 2025, drawn to its integration of AI-based modeling, experimental assays, and physics-based simulations to study protein function. More recently, in the Shukla Group, Shivank has worked on research that applies machine learning to identify potential modulators of HIV latency and functional residues crucial to proteins transporting sugars in plants. He also served as a graduate mentor for MMLI’s MATRIX-Uni program on a project using AI and high-throughput experiments to engineer proteins.

Before beginning his Ph.D. at Illinois, Shivank earned a master’s degree in bioinformatics from Georgia Tech following undergraduate training in computer science. His previous research spans natural language processing, computational genomics, proteomics, protein-property prediction, and large language model fine-tuning, providing a multidisciplinary foundation for applying computational approaches across biological and chemical research.

As of August, 2026: One Year.

My undergraduate background was in computer science, after which I pursued a masters in bioinformatics at Georgia Tech in Atlanta. During this time, I was engaged in multiple projects and internships in natural language processing, computational genomics, and proteomics across academia and the IS and biotech industries, with an emphasis on efficient LLM finetuning techniques and protein property prediction.

At MMLI, I have been affiliated with a seed grant on redox polymer design, where I’m training machine learning models to predict oxidation potentials and engineer novel organic polymers as battery electrode materials. I also work on enhancing catalytic efficiency for plant enzymes using AI methods as part of Thrust 2.

What drew me to the Shukla group was its impressive integration of AI-based modeling, experimental assays, and physics-based simulation and sampling techniques to comprehensively analyze protein function. The various thrusts of MMLI similarly had a strong track record of interdisciplinary collaborations which aligned well with my own parallel interests in computational techniques and the sciences.

My favorite thing about MMLI has been the regular opportunities and platforms it provides to interact with labs with very diverse research interests. This has made it an enriching experience for me to learn from different subject experts and borrow from their individual areas of expertise outside of my own.

I recently mentored an undergraduate student as part of MMLI’s first cohort of MATRIX-Uni interns over the summer. It was fun introducing curious minds to the kind of work we do, and simultaneously a great learning experience for me to improve on how we communicate our research and give back to the scientific community.

Outside of work, I like to listen to history podcasts, cook and bake, and try to keep my houseplants alive! I also like identifying local tree, reptile, and amphibian species wherever I’m staying.

I have an expansive knowledge of paleontology and ancient history from across Asia, and I’m fluent in three languages. I’m also tragically allergic to cats.

Three things in my bucket list would be trying out the best fried chicken places in every major city, backpacking across the Japanese countryside, and adopting a dog.

The best way to see what I’m working on with the Shukla Group would be to visit my team’s page.