Dr. Tolulope Fadina is an Assistant Professor in Actuarial Science and Risk Management at the University of Illinois at Urbana–Champaign.  With a strong commitment to bridging the gap between academic research and industry application, Dr. Fadina recently completed the Climate Risk Certificate Bundle: Life and Investment/Finance Track, a professional program offered by the Society of Actuaries (SOA). This training has further enhanced her ability to translate advanced climate risk and uncertainty models into actionable insights for insurers and asset managers. Dr. Fadina welcomes collaborative partnerships with industry stakeholders who are tackling complex challenges in climate risk, financial modeling, and risk measures. With regard to recognitions, in 2025, she was featured as a distinguished mathematician by Mathematically Gifted and Black. In 2022, she was named one of the Black Heroes of Mathematics by the International Centre for Mathematical Sciences.

Eric Icaza is an instructor of  actuarial science and former Sun Life actuarial analyst. My teaching and projects merge actuarial science with applied mathematics and data science. Courses include financial mathematics, linear algebra, regression modeling, loss models, and insurance regulation. Projects include Neural Networks from Scratch, Actuarial Applications of Machine Learning, Testing Portfolio Management Theories, and Introduction to Monte Carlo Simulation.

Xiaochen Jing is an Assistant Professor at the Department of Mathematics of the University of Illinois at Urbana-Champaign. He graduated from the University of Wisconsin-Madison with a Ph.D. in Actuarial Science, Risk Management & Insurance. He also completed his Master’s degree in Actuarial Science from the University of Illinois at Urbana-Champaign. His research mainly employs empirical methods and focuses on insurance product design and market behavior, with particular interests in variable annuities and decentralized insurance. In 2025, he received an Individual Grant Competition award from the Society of Actuaries.

Feng Liang is a Professor in the Department of Statistics at the University of Illinois at Urbana-Champaign (UIUC), where she also serves as the Director of the Actuarial Science and Risk Management Program. She received her Ph.D. in Statistics from Yale University and was previously an Assistant Professor at Duke University.

Dr. Liang has published in top statistical journals and AI conferences, advised 19 Ph.D. students, and served as Associate Editor for several leading statistical journals. Her research has been supported by the National Science Foundation (NSF), the Department of Energy (DOE), and other funding agencies.

Her research focuses on Bayesian methodology, machine learning, and information-theoretic approaches, with recent interests in the theoretical foundations and modern statistical inference in AI. Her recent work, in collaboration with Sandia National Laboratories, addresses the challenge of improving and assessing the quality of uncertainty quantification in deep learning. One of her recent papers—providing a mathematical foundation for score-based diffusion models, a class of generative AI models—was selected as a spotlight paper at the 2025 International Conference on Machine Learning (ICML), a highly competitive venue. She is also actively working on transfer learning via Bayesian approaches, with a focus on compressing, explaining, and transferring neural networks in a principled and interpretable manner.

Zhiyu (Frank) Quan is an Assistant Professor at the Program for Actuarial and Risk Management Sciences of the University of Illinois Urbana-Champaign, a Brad and Karen Smith Professorial Scholar of the College of Liberal Arts and Sciences, and a Finance and Insurance Sector Lead for Discovery Partners Institute. He holds a Ph.D. in Actuarial Science from the University of Connecticut. Before joining Illinois, he worked in a cutting-edge Insurtech company as a R & D data scientist developing data-driven solutions for major insurance companies. He has a broad spectrum of research interests in data science applications in insurance such as tree-based models, natural language processing, deep learning, and applies his actuarial expertise to build predictive models for claim research, rate making, etc. His research agenda is driven by real-life data and is inspired by collaborations with Insurtech and insurance companies. Besides, he is a director of the Illinois Risk Lab, which facilitates research activities that integrate academic training with practical problem-solving in real business settings. He has received the Arnold O. Beckman Research Award and has been awarded by the Society of Actuaries Research Institute and Casualty Actuarial Society.