Assistant Professor
Email: quadri@ou.edu
Office: Devon Energy Hall 242
Phone: (405) 325-5237
Website
Education
Ph.D., Computer Science and Engineering
University of South Florida
M.S., Computer Science
University of South Florida
B.E., Computer Engineering
University of Mumbai
Research Focus
Experience and Awards
Bio:
Dr. Ghulam Jilani is an Assistant Professor in the Computer Science department at the Gallogly College of Engineering, University of Oklahoma. Prior to joining OU, he worked as a Postdoctoral Research Associate and CRA/CCC/NSF Computing Innovation Fellow working with Dr. Danielle Albers Szafir in the Department of Computer Science at the University of North Carolina-Chapel Hill. Ghulam received his Ph.D. in Computer Science & Engineering, advised by Dr. Paul Rosen at the University of South Florida in 2021. He holds an M.S. in Computer Science from the University of South Florida and a Bachelor in Computer Engineering from the University of Mumbai. His research interests lie at the intersection of Information Visualization, HCI, ML Models, and perception & cognition.
Dr. Quadri's primary goal is to create a perceptual and human-centered framework to optimize visualization design, improving decision-making quality and confidence while providing objective guidance for designers. In his work, he borrows approaches from InfoVis and perception & cognitive science and applies human-centered evaluation to measure, model, and theorize human perception of data and visual design. His dissertation research work in this space received the IEEE VGTC Best Dissertation award for contributing new ways to measure, model, and construct task-optimized visualizations. His postdoc research is supported by the NSF-CRA Computing Innovation 2021 Fellowship. Ghulam's research collaborations span various applications, including design-oriented perceptual research projects to create robust design choice models, perceptual variability, design optimization, and information accessibility. His recent work on perceptual variability received the Best Paper Honorable Mention Award for CLAMS at IEEE VIS 2023.