A. Asudeh is an assistant professor of Computer Science at the University of Illinois Chicago and the director of Innovative Data Exploration Laboratory (InDeX Lab). He serves as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering (TKDE) and is a regular PC member of Data Management flagship conferences. He is a a senior member of ACM, senior member of IEEE, VLDB Ambassador, and the VLDB Endowment's Liaison to NSF.
His research encompasses various aspects of Data problems, for which he develops efficient, accurate, and scalable solutions by leveraging Approximation and Randomized Algorithms, and Computational Geometry. His research is supported by two NSF-IIS grants and a Google Research Scholar Award. Algorithmic Fairness and Data-centric Responsible AI are his major focus in research. His research interests also include Ranking algorithms and indices, LLMs and Foundation Models, Social Networks, Machine Learning, and Misinformation Detection. His work has received awards and recognitions, including the Communications of the ACM's Research Highlight Award, SIGMOD 2019 Research Highlight, and SIGMOD 2017 Reproducibility Award, and “Best of VLDB” -- the special issue of VLDBJ,.

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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 Algorthims 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.