{"id":3586,"date":"2023-03-14T13:35:13","date_gmt":"2023-03-14T13:35:13","guid":{"rendered":"https:\/\/ieeecscai.wpengine.com\/2023\/?page_id=3586"},"modified":"2023-05-18T07:09:48","modified_gmt":"2023-05-18T07:09:48","slug":"uzay-kaymak","status":"publish","type":"page","link":"https:\/\/cai.ieee.org\/2023\/uzay-kaymak\/","title":{"rendered":"Uzay Kaymak"},"content":{"rendered":"\t\t
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Uzay Kaymak
\nProfessor of Information Systems, Eindhoven University of Technology, The Netherlands<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\"\"<\/p>

June 6, 3:00pm
Location: Santa Clara I<\/h5>

Panelist: Explainable AI: Current Challenges and Future Perspectives<\/a><\/span><\/h4>

This panel will discuss a wide range of aspects of Explainable AI that may include informativeness, trustworthiness, fairness, transparency, causality, transferability, reliability, accessibility, privacy, safety, verifiability and accountability. The topics discussed at the panel will cover aspects of Explainable AI that may include local and global scope, specific and agnostic models, as well as aspects of constructive, what-if, counterfactual and example-based explanations. Other potential topics may include recent developments related to real world bias of AI, how this bias is reflected in data bias, the encoding of data bias in algorithmic bias, its uncovering by Explainable AI, and how the latter can be used for closing the loop by mitigating real world bias of AI. The panel will also explore current challenges and future perspectives in Explainable AI that may include formalisation and evaluation of explanations, their adoption in industry, their potential for improving human machine collaboration and their ability to facilitate collective intelligence, responsibility, security and causality in AI.<\/p>

\"\"<\/a>Uzay Kaymak<\/strong> is a Full Professor and Chair of Information Systems in Health Care at Eindhoven University of Technology (TU\/e). His research focuses on intelligent decision support systems, data and process mining and computational modeling methods. He has worked on the development of computational intelligence methods for decision models in which linguistic information, represented either as declarative linguistic rules derived from experts or obtained through natural language processing, is combined with numerical information extracted from data by computational and machine learning methods. Fuzzy set theory is at the basis of such models. The resulting (adaptive) decision support systems have been used in various fields such as financial decision-making, economic analysis and clinical decision support. Uzay Kaymak received his MSc in electrical engineering (1992), Chartered Designer Degree in information technology (1995), and PhD in control engineering (1998) from Delft University of Technology. He has held various positions at Shell International Exploration and Production, Erasmus University Rotterdam, the Netherlands, and Salford University in United He has (co)-authored more than 250 scientific publications in the fields of intelligent systems, computerized decision support and computational intelligence. Uzay is a board member of the TU\/e Clinical Informatics study program (two-year post-master PDEng study) and a member of the program and\/or organization committee of multiple international conferences. He also holds a visiting professor position at the Zhejiang University, China.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Uzay Kaymak Professor of Information Systems, Eindhoven University of Technology, The Netherlands June 6, 3:00pmLocation: Santa Clara I Panelist: Explainable AI: Current Challenges and Future Perspectives This panel will discuss a wide range of aspects of Explainable AI that may include informativeness, trustworthiness, fairness, transparency, causality, transferability, reliability, accessibility, privacy, safety, verifiability and accountability. The […]<\/p>\n","protected":false},"author":5,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3586","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/pages\/3586","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/comments?post=3586"}],"version-history":[{"count":0,"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/pages\/3586\/revisions"}],"wp:attachment":[{"href":"https:\/\/cai.ieee.org\/2023\/wp-json\/wp\/v2\/media?parent=3586"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}