EDTConf 2024
Mon 23 - Tue 24 September 2024 Linz, Austria
co-located with MODELS 2024
Marouane Kessentini

Registered user since Wed 27 Mar 2019

Name:Marouane Kessentini
Bio:

Dr. Marouane Kessentini is currently a full professor and Dean of the College of Computing at Grand Valley State University in Michigan and director of the NSF IUCRC center on Pervasive AI; Michigan Site. He received his Ph.D. from the University of Montreal in Canada in 2012. Dr. Kessentini is a recipient of the prestigious 2018 President of Tunisia distinguished research award, the University distinguished teaching award, the University distinguished digital education award, the College of Engineering and Computer Science distinguished research award, 4 best paper awards including an IEEE 10 Year Most Influential Paper award in Program Comprehension (2011-2021), and his AI-based software refactoring invention, licensed and deployed by Fortune 500 companies, and selected as one of the Top 8 inventions at the University of Michigan for 2018 among over 500 inventions, by the UM Technology Transfer Office. He received various grants from both industry and federal agencies and published over 160 papers in top journals and conferences. Dr. Kessentini has extensive collaborations with the industry on different areas related to refactoring, software engineering intelligence, search-based software engineering, Edge AI, AI/MLOps, AI and cyber-physical systems, intelligent software bots, etc. He is the co-founder of many workshops, General Chair of SSBSE16 and ASE22, and PC chair of MODELS19, SANER 2021, GECCO, etc. He served as a keynote speaker at various venues including ICSR, SSBSE, GECCO, WCCI, etc. He graduated 15+ Ph.D. students and served as associate editor in 7 journals and PC member of over 150 conferences.

Country:United States
Affiliation:Grand Valley State University
Personal website: https://kessentini.net/
Research interests:Software Engineering Intelligence, Refactoring, Search-based Software Engineering, Software Maintenance and Evolution, Model-Driven Engineering

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