Visiting Scholars

The Kohl Centre was delighted to host Rui Fan, assistant professor of economics at the School of Humanities, Arts, and Social Sciences (HASS) at Rensselaer Polytechnic Institute (RPI). Fan, who also holds a joint appointment as assistant professor of finance at the Lally School of Management and serves as an affiliated faculty member at the Center for Research toward Advancing Financial Technologies (CRAFT), visited the Centre from October 31 to November 3, 2024.

Fan’s research expertise spans a range of critical areas, including financial econometrics, causal inference, systemic risk, predictive analysis, and risk management. Her work aims to develop innovative and practical solutions to complex problems in economics and finance, aligning perfectly with the Kohl Centre’s mission to advance research that bridges theory and real-world applications.

During her visit, Fan actively participated in and presented at the Kohl Centre workshop on causality and machine learning/AI. This workshop, which brought together scholars from diverse fields, provided a platform for discussing cutting-edge research and fostering interdisciplinary collaboration. Fan’s presentation added depth to the discussions, showcasing her insights into causal inference and reinforcing the workshop’s focus on state-of-the-art data analytic methods.

Fan also collaborated with Le Wang at the Kohl Centre on two significant projects. The first project focuses on the development of new econometric causal inference methods for instrumental variables. The second project aims to create a Systemic Risk Indicator for U.S. agricultural commodities, addressing a crucial need for better predictive and risk management tools in the agricultural sector. Both projects are well-aligned with the Kohl Centre’s commitment to producing impactful, interdisciplinary research that benefits academia and industry alike.

Fan’s visit underscored the Centre’s dedication to fostering cross-disciplinary dialogue and collaboration. By engaging with experts like Fan, the Kohl Centre continues to build a vibrant research community that is equipped to tackle complex challenges in data analytics, economics, and finance. Her work, with its focus on practical and predictive analysis, exemplifies the Centre’s goal of developing innovative methodologies and delivering solutions that resonate across industries.

The Kohl Centre looks forward to future collaborations with Fan and other leading scholars as it continues to push the boundaries of research in data science, causal inference, and risk management.

The Kohl Centre recently had the pleasure of hosting Hengrui Cai, an accomplished young scholar and assistant professor in statistics at the Donald Bren School of Information and Computer Sciences at the University of California, Irvine, during her visit from October 31 to November 3, 2024.

Cai’s research spans various domains, including causal inference, reinforcement learning, graphical models, and their integration to develop reliable, powerful, and interpretable solutions to complex real-world challenges. Her current work focuses on topics such as individualized optimal decision-making with complex data, policy evaluation in reinforcement learning and bandits, natural language processing, explainable deep learning, and causal discovery for high-dimensional individual mediation analysis. These research areas have significant applications in fields like precision medicine, customized economics, personalized marketing, and modern epidemiology.

During her visit to the Kohl Centre, Cai taught a tutorial session on an introduction to causal machine learning, an emerging field that is making a significant impact in various industries. The session was well-attended, drawing a diverse group of faculty and students eager to gain insight into this frontier topic. The feedback from attendees highlighted the value of the tutorial, noting its relevance to both their academic research and potential career paths.

Cai also participated in and presented at the Kohl Centre workshop on causality and machine learning/AI, where she shared her expertise and engaged with scholars across disciplines. Her involvement in the workshop reinforced the Kohl Centre’s mission of fostering interdisciplinary collaboration and promoting state-of-the-art data analytic methods that address real-world applications.

Cai’s visit exemplified the Kohl Centre’s commitment to advancing research that bridges theory and practice, while equipping students and researchers with the knowledge and skills needed to thrive in data analytics and machine learning. Her work in causal inference and related fields aligns seamlessly with the Centre’s focus on impactful research and interdisciplinary learning, underscoring the importance of bringing together scholars from varied backgrounds to tackle complex problems.

The Kohl Centre looks forward to continuing collaborations with scholars like Cai and furthering its mission to foster innovation and cross-disciplinary dialogue in data science.