Academic Year 2021-22 is Georgia Tech’s first cohort of its President’s Postdoctoral Fellow Program.

Darius Carter

Darius Carter hails from Richmond, Virginia, and is currently a President’s Postdoctoral Fellow at Georgia Institute of Technology. He has a Ph.D. in Mechanical & Aerospace Engineering at the University of Virginia (UVA). He graduated from Highland Springs High school in Henrico County, Virginia in 2013. He then enrolled at UVA, where he graduated with his B.S. in Mechanical Engineering with a Minor in Material Science in 2017. As a Ph.D. student, his research focuses on unmanned aerial vehicles and their safety when flying near boundaries. With his Postdoc he will be focusing on aerodynamic coupling between propellers and airfoils. He was the Co-President of Black Graduate and Professional Student Organization, Recruitment Chair for the Mechanical & Aerospace Graduate Student Board, Co-Chair for UVA’s Graduate Recruitment Initiative Team, Member of the search committee for the Dean of Engineering, and Academic Mentor with UVA Athletics. Outside of school and research, he is a dedicated member of Alpha Phi Alpha Fraternity, Inc. and the National Society of Black Engineers. He enjoys hanging out with friends, adventuring, traveling, and watching and playing sports, especially basketball. He desires to inspire the next generation of black engineering students. 

Katherine Graham

Katherine Graham is a postdoctoral fellow studying pathogens in the environment and how to track microbes in sewage to inform public health decision making. She earned her BSE in Chemical Engineering from the University of Michigan and MS and PhD in Environmental Science and Engineering at Stanford University. Her graduate studies focused on investigating sources of viruses in urban waters and the performance of nature-based infrastructure in improving water quality. As a postdoctoral fellow, she is focusing on developing methods and applying ‘omics tools to detect viruses in the environment to improve public health.

Eugene Ndiaye

Eugene Ndiaye is a postdoctoral fellow at the School of Industrial Systems Engineering (ISyE). He obtained his PhD in applied mathematics from Telecom ParisTech. His research interests focus on the interplay between machine learning and optimization, mainly to understand how a statistical learning algorithm can select particular information from data and how this selection bias affects its prediction abilities. Among other long-term objectives, it aims to provide quantifiable and implementable guarantees on the performance and limits of artificial intelligence methods as well as their impacts when they are deployed in society.

Jingyan Wang

Jingyan Wang is a Ronald J. and Carol T. Beerman President’s postdoctoral fellow in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. Her research interests lie in understanding and mitigating biases in decision making problems such as peer grading and peer review, using tools from statistics and machine learning. She is the recipient of the Best Student Paper Award at AAMAS 2019. She received her Ph.D. in the School of Computer Science from Carnegie Mellon University in 2021, advised by Nihar Shah. She received her B.S. in Electrical Engineering and Computer Sciences with a minor in Mathematics from the University of California, Berkeley in 2015.

Martin Zubeldia

Martin Zubeldia is a Postdoctoral Fellow in the Department of Industrial and Systems Engineering. Born in Montevideo, Uruguay, he received a B.S. degree in Electronics Engineering (2012) and a M.Sc. degree in Engineering (2014) from the Universidad ORT Uruguay, and a Ph.D. in Electrical Engineering (2019) from MIT. Before joining GaTech, he was a postdoc at the Eindhoven University of Technology, and at the University of Amsterdam, in the Netherlands. His research primarily focuses on the modeling, analysis, and control of large-scale stochastic decision systems, inspired by applications in computer networks and other service systems. He is particularly interested in the fundamental tradeoffs between performance and efficiency in such systems, with an emphasis on the role that information plays in these tradeoffs.