Join us for the first part of the INFORMS Minority Issues Forum (MIF) Summer Webinar Competition! In this session, we explore a range of cutting-edge topics. These include explainable machine learning methods used to predict depression severity in medical students, which promises to provide insights into mental health monitoring and support. We will also delve into data-driven analytics aimed at improving social justice systems, with a focus on breaking the vicious cycle in the criminal justice system. Another fascinating area is the use of Markov chain models to manage security risks in election systems, an essential topic in ensuring the integrity of voting processes. Additionally, we will hear about metrics for environmental sustainability in strategic mine planning, which is crucial for balancing economic development with ecological preservation. Finally, the session will cover the innovator's advantage in competitive technology adoption, exploring how enhancing profit and reducing food waste can be achieved through supply transparency. Join us for an inspiring session of research and engaging presentations. Register now to secure your spot!
About the competition:
This event is designed to provide student MIF members in PhD programs with a unique platform to showcase their work outside the INFORMS Annual Meeting. We aim to increase student participation within the MIF community and highlight their innovative research.
Any student MIF member enrolled in a PhD program was eligible to apply. The Programs Committee has selected ten outstanding participants to advance in the competition. Five of these participants will present their work (the other five will present in an upcoming session. Each presenter will have ten minutes to impress the judges with their research. Academic and industry professionals will evaluate the presentations. Criteria include research topic and impact, visual appeal, organization, and presentation quality. The winner(s) will receive an honorarium at the next INFORMS Annual Meeting, equivalent to the cost of a student registration. All participants will receive a certificate of participation.
.
Speakers:
.
Zequn Chen is a second-year PhD in the Thayer School of Engineering at Dartmouth College. His research lies at the intersection of fair machine learning and fair optimization, with applications in healthcare. He also received a M.Sc. degree in Operations Research from University of Michigan, Ann Arbor.
.
Xiaoquan Gao
Xiaoquan Gao is a Ph.D. candidate in Industrial Engineering at Purdue University, focusing on socially responsible operations in healthcare and criminal justice. She holds a B.S. in Theoretical and Applied Mechanics from Peking University and will join Singapore Management University as an assistant professor of operations management in January 2025.
.
Carmen Haseltine
Carmen A. Haseltine is a Ph.D. candidate in Electrical Engineering at the University of Wisconsin-Madison, specializing in dynamic risk analysis of critical infrastructure. With a robust background in power systems and cybersecurity, Carmen's research focuses on improving the resilience of societal networks.
.
Raymond Kudzawu-D'pherdd
Raymond Kudzawu-D'Pherdd is a Ph.D. student in Operations Research with Engineering at the Colorado School of Mines, advised by Professor Alexandra Newman. He holds M.S. degrees in Industrial Finance and Investment from KNUST and in Petroleum Geoscience from the University of Ghana, Legon. His research focuses on environmental metrics for sustainable operations.
.
Chenghuai Li
Chenghuai Li is a Ph.D. candidate from Fuqua School of Business, Duke University. His research studies innovative technologies in operations with social responsibility and environmental concerns. The topics span from management of digital supply chains with an emphasis on food waste to improving electric vehicle adoption in ride-hailing platforms.