- PhD (2022) Carnegie Mellon University (Operations Research)
- BS (2017) Georgia Institute of Technology (Applied Mathematics; Business Administration)
My research interests are broadly related to fairness and ethics of artificial intelligence. Currently, I work on modeling fairness and equity in optimization, outcome-centric social welfare perspectives of fair machine learning, human-centric aspects of ethical AI with a focus on modeling and inferring moral preferences. Along these directions, I am interested in applications from healthcare, infrastructure systems and supply chain.
- Search committee for Tenure Track Position in Analytics Member
- INFORMS Education Strategy Committee
Honors and Awards
Jack Howe Fellowship, Stevens Institute of Technology. September 2022- August 2025.
- POMS – Production and Operations Management Society Member
- INFORMS – The Institute for Operations Research and the Management Sciences Member
Grants, Contracts and Funds
National Science Foundation CMMI-2309668. Collaborative Research: Advancing Fairness for Emerging Infrastructure Systems with High Operational Dynamics. July 2023-June 2026.
- Chen, V.; Williams, J.; Leben, D.; Heidari, H. (2023). Local Justice and Machine Learning: Modeling and Inferring Dynamic Ethical Preferences toward Allocations. No. AAAI Conference on Artificial Intelligence (5 ed., vol. 37, pp. 5956-5964). Association for the Advancement of Artificial Intelligence.
- Chen, V.; Hooker, J. (2020). A Just Approach Balancing Rawlsian Leximax Fairness and Utilitarianism. No. AIES 20: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (pp. 221-227). Association for Computing Machinery.
- Chen, V.; Hooker, J. (2023). A Guide to Formulating Equity and Fairness in an Optimization Model. No. Annals of Operations Research (vol. 326, pp. 581-619). Springer.
- Chen, V.; Hooker, J. (2022). Combining leximax fairness and efficiency in a mathematical programming model. No. European Journal of Operational Research (1 ed., vol. 299, pp. 235-248). ScienceDirect.
MIS637 - Data Analytics and Machine Learning