The NSF-Simons National Institute for Theory and Mathematics in Biology comprises a wide array of investigators driving innovation at the interface of mathematics and biology. NSF-Simons NITMB Affiliate Members bring unique perspectives vital for developing new mathematics and inspiring biological discovery. One such NITMB Affiliate Member leveraging artificial intelligence and machine learning for discovery across disciplines is Jingrui He.
Jingrui He is a Professor in the School of Information Sciences and Program Director of the MS in Information Management at the University of Illinois Urbana-Champaign. Her research focuses on heterogeneous machine learning, active learning, neural bandits, and self-supervised learning, with applications in sustainability, agriculture, social network analysis, healthcare, and finance. Professor He’s lab, the iDEA-iSAIL Joint Laboratory, co-founded with fellow NITMB Faculty Member Hanghang Tong, pioneers full-stack research for big data and AI solutions.
We spoke with Jingrui He to learn more about her work with AI, the impactful applications of her research, and how NITMB is helping He bridge the gap between her work and applications in other disciplines.
What is a big question you’ve been asking throughout your research?
“How to leverage mathematical tools to formulate and address problems that originate from high-impact applications.”
What disciplines does your research integrate?
“AI, machine learning, and sustainability”
Where do you find inspiration?
“I find inspiration from real-world successes (e.g., the successful development of large language models and their applications in multiple domains) and failures (e.g., the limited practical use of climate foundation models as compared to traditional numerical weather prediction). They both provide unique perspectives as to what types of research would have long-lasting impacts.”
What aspects of your work could be interesting to mathematicians or applied to biology?
“Leveraging world knowledge (e.g., through pre-trained large models) to help solve challenging mathematical problems (e.g., combinatorial optimization).”
What excites you about NITMB?
“NITMB’s mission to ‘generate new mathematical results and uncover the rules of life through theories, data-informed mathematical models, and computational and statistical tools’ is particularly appealing to me. I have participated in multiple activities sponsored by NITMB (e.g., graph neural network workshops). These activities brought together researchers from both academia and industry with diverse backgrounds. The interaction among these researchers helped bridge the gap between theory and applications, potentially leading to impactful research motivated by industrial needs (e.g., the pain points in obtaining frontier industrial models).”
What career achievement are you most proud of?
“Being able to make real impacts in collaboration with industry (e.g., IBM, Amazon) in addition to publications and patents.”
Outside of your research, what other interests do you have?
“I’m a yoga practitioner. It helps me find peace and an anchor when facing uncertainty.”
What are you hoping to work on in the future?
“I hope to work on the intersection of AI and quantum computing, such as the use of AI for quantum error correction and the use of quantum processors to significantly speed up foundation model pre-training and post-training.”
More information on Professor He’s work is available on her website and on the iDEA-iSAIL Joint Laboratory website.
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