A. Asudeh is an Associate Professor of Computer Science at the University of Illinois Chicago and the director of Innovative Data Exploration Laboratory (InDeX Lab).
His research focus is on Algorithm Design for Data and AI problems. He designs efficient, accurate, and responsible solutions that leverage Approximation, Randomized, and Computational Geometry Algorithms. His research interests include the interplay of Data/Algorithms/AI, Responsible Data Science, and Ranking and Approximate Nearest Neighbor Problems, among others.
Asudeh is a senior member of ACM and a senior member of IEEE. He serves as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering (TKDE), is a regular PC member of Data Management and AI flagship venues, and served as a VLDB Ambassador and the VLDB Endowment's Liaison to NSF.
His research is supported by NSF and has received recognitions, including the Communications of the ACM's (CACM) Research Highlight, Google's Research Scholar Award, SIGMOD 2019 Research Highlight Award, “Best of VLDB” 2020 (the special issue of VLDBJ), and SIGMOD 2017 Reproducibility Award.

Every year, I look for a small number of motivated, smart, and hard-working PhD students. In particular, I look for students with a strong background in Algorithms who are interested in finding algorithmic solutions for data problems and AI (recently LLMs and Foundation Models have enabled an exceptional phenomenon for such research). You also need to have outstanding programming skills. If you are interested, check our lab page and our recent publications. If interested and qualified, please apply here and mention my name in your application.
Due to the large number of emails, I may not be able to respond to them all. If you email me, please use ``Prospective PhD Student'' as the subject and attach your CV and transcripts. Describe your skills, interests, research experience, and how those may fit InDeX Lab.