Sadi Evren Şeker

Sadi Evren Seker is a Turkish computer scientist and data scientist. He is the first person to introduce the concept of "Computerized Argument Delphi Technique" in the literature, which is an enhancement to the Delphi method originally developed on Project RAND.

Career and research After obtaining a Ph.D. degree in computer engineering from Yildiz Technical University in 2010, Seker joined the faculty at Istanbul University in 2011 as an assistant professor. In recognition of his achievements, he was promoted to the rank of professor in the Department of Computer Engineering in 2020. Computer-implemented methods for selection of features in predictive data modeling A machine learning based prediction system and method

He currently serves as the Dean of the Computer and Information Technologies Faculty at Istanbul University. His researches involves the implementation of data science algorithms in various industries, including banking, geology, natural language processing and big data analytics He has published more than 200 scientific journals and books His work has been covered by local news agencies on several occasions.

Seker's research focuses on Responsible AI, Automated machine learning and explainable artificial intelligence. Seker, is the Turkish editor of the book Algorithms, originally written by Robert Sedgewick and Kevin Wayne GISQAF: MapReduce guided spatial query processing and analytics system, funded by the National Science Foundation under Award No. CNS 1229652 and the Air Force Office of Scientific Research under Award No. FA-9550-09-1-0468 Recurring and Novel Class Detection Using Class-Based Ensemble for Evolving Data Stream, in TKDE which is based on work supported by the AFOSR under awards FA9450-08-1-0260 and FA9950-10-1-0088 and by NASA under award 2008-00867-01. His author profile with his publications on IEEE is available on IEEE Xplore and his DBLP profile is available for online access. There are some news about his works on democratization of artificial intelligence for SMEs