Prof. Mesrob Ohannessian
Prof. Ohannessian’s research interests are broadly in machine learning, statistics, and information theory, and their applications. He strives to draw the most benefit from the smallest amount of data while addressing the statistical, computational, and societal aspects of modern data analysis. He is currently interested in two main problems: designing learning algorithms that adapt to structure in data and making non-discriminatory algorithmic decisions both computationally feasible and aware of their long-term societal impact. Prior to joining UIC as an Assitant Professor, he was a Research Assistant Professor at the Toyota Technological Institute at Chicago (TTIC), a postdoc at UC San Diego with Alon Orlitsky, a visiting scholar at the Simons Institute at UC Berkeley, a postdoc at MSR-Inria with Laurent Massoulié, and an ERCIM Marie Curie Fellow at the Université Paris-Sud with Stéphane Boucheron and Elisabeth Gassiat. He earned his PhD from MIT, with Munther Dahleh and Sanjoy Mitter, at the Laboratory for Information and Decision Systems (LIDS).
Prof. Ohannessian is honored and grateful to be an NSF CAREER Awardee (No. 2146334) and a co-PI of an NSF-Amazon Fairness in AI grant (No. 1939743).
Usama Muneeb
Usama Muneeb is a 5th year PhD Candidate in the department of Electrical and Computer Engineering at UIC. His research lies in more deeply understanding what is possible to do with machine learning algorithms, both theoretically and practically. Some of his recent work includes analyzing competitive learning algorithms and designing principled data augmentation methods, with applications in natural language processing. Before coming to UIC, Usama earned his Bachelors in Electrical Engineering with a minor in Computer Science from LUMS School of Science and Engineering in Lahore, Pakistan. He has extensive experience teaching, in particular a Neural Networks TA.
Jingyi Yang
Jingyi Yang is a 2nd year PhD Candidate in the department of Electrical and Computer Engineering at UIC. She works on fair machine learning and is also interested in fairness in sociotechnical systems that evolve. Her current project is on fusing multiple data sets, to assess and guarantee fairness in algorithmic decisions. Jingyi earned her Bachelors in Electronics from Chang’an University in Xi’An, China, and simultaneously her Masters Degree in ECE at UIC, through the joint exchange program. Jingyi enjoys teaching; at UIC, she was the TA of the Probability and Random Process for Engineers course.
Kenya Andrews
Kenya Andrews is a 2nd year PhD Student in the department of Electrical and Computer Engineering at UIC. She researches justice, ethics, and bias in machine learning. Her current project is looking at fairness in the allocation of COVID-19 Vaccines amongst vulnerable populations. She is a GEM Fellow and a recipient of the Bill and Melinda Gates Millennium Scholarship and NSF Bridge to Doctorate Fellowship. Kenya is a native of Macon, Georgia, and is a proud graduate of the Dual Degree Engineering Program with Spelman College where she earned a Bachelors of Science in Computer Science and Auburn University where she earned a Bachelors of Computer Engineering. In her spare time, she mentors several students and connects them with scholarship opportunities.
Zahra Rahimi Afzal
Zahra Rahimi Afzal is a third-year Ph.D. candidate in the Department of Electrical and Computer Engineering at UIC. Her research focuses on the intersection of Natural Language Processing (NLP) and Machine Learning (ML), both from a theoretical and practical standpoint. Before joining UIC, Zahra obtained her second Masters in Computer Science from Kansas State University, where she gained expertise in neural network verification and control. Moreover, she enjoys assisting students and contributing to their understanding of the subject matter while serving as a Teaching Assistant for the Probability and Random Process course.
Shayan Vassef
Shayan Vassef is a first-year Ph.D. candidate in the Department of Electrical and Computer Engineering at UIC. His research focuses on the intersection of Natural Language Processing (NLP) and Machine Learning (ML). Specifically, he aims to explain the reasoning behind AI models’ performance and use this reasoning to address challenges during the training and tuning phases. Before joining UIC, Shayan earned his bachelor’s degree in Electrical Engineering, majoring in Control Engineering, from the University of Tehran. His recent works include social media analysis and multi-task learning in the context of natural language. Outside of academics, he enjoys creating informative content on YouTube and sharing his passion for learning new tools in the field of AI.