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Prof. Dr. Altan ÇAKIR

Prof. Dr. Altan ÇAKIR

Istanbul Technical University

Prof. Dr. Altan Çakır, after receiving his bachelor's and master's degrees in Physics and Mathematics, completed his doctoral studies at the Karlsruhe Institute of Technology in Germany in 2010. During his doctoral studies, Prof. Çakır conducted significant research problems involving big data analytics and artificial intelligence-based data science studies at the Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN). Following his doctoral studies, he conducted postdoctoral research at the Deutsches Elektronen-Synchrotron (DESY) in Hamburg, Germany, and at CERN. As a postdoctoral researcher, Prof. Çakır participated in research at CERN and DESY for more than five years. Since 2016, he has been a faculty member at Istanbul Technical University. He currently leads the ITU-CMS research group responsible for research conducted at CERN. Additionally, in 2017, Prof. Çakır was invited as a visiting faculty member at the Fermi National Accelerator Laboratory (Fermilab) in Illinois, USA, where he continued his focus on large-scale data analytics and machine/deep learning techniques. Alongside his scientific research, Prof. Çakır conducts interdisciplinary studies ranging from big data synthesis to economic and industrial applications, providing consultancy to numerous national and international companies, and sharing his expertise on big data and artificial intelligence application technologies, strategies, skills, and competencies.

Prof. Altan Çakır teaches a variety of courses, primarily on big data and its applications, within the Big Data and Business Analytics program of the Industrial Engineering Department at Istanbul Technical University. He is also one of the faculty members of Big Data conferences and teaches in master's programs jointly created by Cambridge University, Madrid Polytechnic, Paris Technical, and Sorbonne Universities. Furthermore, as part of Turkey's CERN associate membership, Prof. Çakır represents the country as a member of the ECFA (European Committee for Future Accelerators) and RECFA (Restricted European Committee for Future Accelerators). Since 2019, he has been a Board Member of the ITU Artificial Intelligence and Data Science Research and Application Center, and since early 2021, he has served as Co-Chair of the Turkey Artificial Intelligence Platform ( and a Board Member of the Turkish Informatics Foundation as of 2023. Additionally, since May 2021, Prof. Dr. Altan Çakır has founded and served as the Dean of the Research Deanship (, responsible for planning, coordinating, and strategizing all research processes at Istanbul Technical University, the first of its kind in Turkey. He is also the co-founder and Chairman of the Board of Parton Big Data Analytics and Consultancy Inc., operating in ITU Technopark, and co-founder and CIO of Adin.Ai, an AI-based digital marketing and advertising optimization startup established in the United States in 2022. The Adin.Ai initiative, co-founded by Prof. Çakır, was recognized among the top 100 promising startups by Fast Company Turkey in 2023 and was recently listed among the most innovative companies.

The State of AI in Recent Years: The Breakthrough Year of Generative AI

The advent of the large data age has significantly expanded the scope of both science and many industries, creating challenging conditions for the development of information technologies and applications. Many companies are investing in AI to secure their future. Today, AI innovation becomes valuable when it enhances decision-making through the application of big data and advanced analytics, combined with human interaction on digital platforms. This talk explores the opportunity for cross-fertilization between generative artificial intelligence, big data, and advanced analytics within related disciplines. We will highlight the potential relationship between them in the context of digital business platforms. This discussion will focus on data-driven generative ai applications at various levels of data-driven automation maturity in industry.

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