Farshad Badie
Berlin School of Business and Innovation GmbH, Germany
Farshad Badie
Berlin School of Business and Innovation GmbH, Germany
Farshad Badie holds a PhD in Human-Centered Communication & Informatics, with a special focus on logic, information science, and learning/cognitive science in human-human-machine interaction systems. He obtained his doctoral degree from Aalborg University (AAU) in Denmark in 2017. Dr. Badie's research primarily revolves around semi-formal conceptual/logical languages as well as their applications in semantic/terminological knowledge modelling. More specifically, his research frameworks lie in the logical, ontological, and semantic analysis of the fundamental components of meaning and cognition within cognitive/knowledge agents' interactions. Moreover, in organisational and human-centred contexts, he analytically explores the existential, conceptual and logical aspects of the concepts of "change" and "innovation”. Dr. Badie also serves as an editorial board member and reviewer for numerous journals covering computer science, formal languages, theory of artificial intelligence, cybernetics, decision/learning sciences, and management sciences. Additionally, he has participated as an organising and scientific committee member in over 160 conferences and workshops held in Europe, America, Australia, Asia, and Africa.
Farshad Badie holds a PhD in Human-Centered Communication & Informatics, with a special focus on logic, information science, and learning/cognitive science in human-human-machine interaction systems. He obtained his doctoral degree from Aalborg University (AAU) in Denmark in 2017. Dr. Badie’s research primarily revolves around semi-formal conceptual/logical languages as well as their applications in semantic/terminological knowledge modelling. More specifically, his research frameworks lie in the logical, ontological, and semantic analysis of the fundamental components of meaning and cognition within cognitive/knowledge agents’ interactions. Moreover, in organisational and human-centred contexts, he analytically explores the existential, conceptual and logical aspects of the concepts of “change” and “innovation”. Dr. Badie also serves as an editorial board member and reviewer for numerous journals covering computer science, formal languages, theory of artificial intelligence, cybernetics, decision/learning sciences, and management sciences. Additionally, he has participated as an organising and scientific committee member in over 160 conferences and workshops held in Europe, America, Australia, Asia, and Africa.
Gabriella Punziano
University of Naples Federico II, Italy
Gabriella Punziano
University of Naples Federico II, Italy
Gabriella Punziano, PhD in Sociology and Social Research is Associate Professor in Sociology and Methodology of Social Sciences at the Department of Social Sciences of the University of Naples Federico II, where she hold advanced digital research and methodological courses. Since 2018 she is the director of the Paideia association for culture and advanced training in human and social sciences and of the Summer School on method and social research. Her research interests include: the new analytical frontiers and the challenges introduced by the digital, new data, mixed and integrated and digital perspectives on public, institutional and political communication phenomena, social policies and welfare regimes, risk communication analysis on social and digital platforms. She is the author of more than 100 publications among articles, book chapters, edited books, handbook, on methodological issues.
Gabriella Punziano, PhD in Sociology and Social Research is Associate Professor in Sociology and Methodology of Social Sciences at the Department of Social Sciences of the University of Naples Federico II, where she hold advanced digital research and methodological courses. Since 2018 she is the director of the Paideia association for culture and advanced training in human and social sciences and of the Summer School on method and social research. Her research interests include: the new analytical frontiers and the challenges introduced by the digital, new data, mixed and integrated and digital perspectives on public, institutional and political communication phenomena, social policies and welfare regimes, risk communication analysis on social and digital platforms. She is the author of more than 100 publications among articles, book chapters, edited books, handbook, on methodological issues.
Jürgen Pilz
Emeritus, Alpen Adria University (AAU) of Klagenfurt, Austria
Jürgen Pilz
Emeritus, Alpen Adria University (AAU) of Klagenfurt, Austria
Jürgen Pilz is Emeritus Professor at the Department of Statistics, Alpen Adria University (AAU) of Klagenfurt, Austria. He received his PhD and DSc degrees from TU Mining Academy Freiberg, Germany. From 1994 – 2020 he was Professor and Chair of Applied Statistics at AAU Klagenfurt, Austria, from 2007-2015 and 2018-2019 he served as (Founding) Head of the Dept. of Statistics at AAU Klagenfurt. He held guest professorships at Charles University Prague (Czech Rep.), University of Augsburg (Germany), Purdue University (USA), University of British Columbia, Vancouver (Canada) and University of Canterbury, Christchurch (New Zealand).
Jürgen Pilz is Emeritus Professor at the Department of Statistics, Alpen Adria University (AAU) of Klagenfurt, Austria. He received his Ph.D. and DSc degrees from TU Mining Academy Freiberg, Germany. From 1994 – 2020 he was Professor and Chair of Applied Statistics at AAU Klagenfurt, Austria, from 2007-2015 and 2018-2019 he served as (Founding) Head of the Dept. of Statistics at AAU Klagenfurt. He held guest professorships at Charles University Prague (Czech Rep.), University of Augsburg (Germany), Purdue University (USA), University of British Columbia, Vancouver (Canada), and the University of Canterbury, Christchurch (New Zealand).
His major areas of interest include Bayesian Statistics, Spatial Statistics, Design of Experiments, Bayesian Epidemiology, and Bayesian Statistical Learning. He has published over 200 papers in international journals and conference proceedings. He has supervised more than 80 Master theses and 40 Ph.D. theses. He is the author of seven books from renowned publishers including Wiley, Springer, Chapman & Hall, the latest one being „Applied Statistics – Theory and Problem Solutions with R“ published by J. Wiley and Sons, Oxford 2020. He is an elected member of the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS), and on editorial boards of several international statistics journals.
Sanda Martincic-Ipsic
University of Rijeka, Croatia
Sanda Martincic-Ipsic
University of Rijeka, Croatia
Sanda Martinčić-Ipšić obtained her B.Sc. degree in Computer Science from the University of Ljubljana Faculty of Computer Science and Informatics, and her M.Sc. degree in informatics from the University of Ljubljana, Faculty of Economy. In 2007 she obtained a Ph.D degree in Computer Science from the University of Zagreb, Faculty of Electrical Engineering and Computing. Dr. Martinčić-Ipšić currently works as full professor of Computer Science at the University of Rijeka, Faculty of Informatics and Digital Technologies.
Dr. Martinčić-Ipšić currently works as full professor of Computer Science at the University of Rijeka, Faculty of Informatics and Digital Technologies. She is a leader of Language Networks research group, and the head of Laboratory for Natural Speech and Language processing at Center for Artificial Intelligence and Cybersecurity at University of Rijeka. Currently, she serves as a director of PhD study in informatics at Faculty of Informatics and Digital Technologies. Her research interests include natural language processing, complex networks, data science and data analytics. She has published more than 100 scientific papers and books.
Vladan Devedzic
University of Belgrade, Serbia
Vladan Devedzic
University of Belgrade, Serbia
Vladan Devedzic is a Professor of Computer Science and Software Engineering at the University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia. Since 2021, he is a Corresponding Member of the Serbian Academy of Sciences and Arts (SASA).
His long-term professional objective is to bring close together ideas from the broad fields of Artificial Intelligence / Intelligent Systems and Software Engineering. His current professional and research interests include artificial intelligence, intelligent software systems, programming education, software engineering, and technology-enhanced learning (TEL).
Vladan Devedzic is a Professor of Computer Science and Software Engineering at the University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia. Since 2021, he is a Corresponding Member of the Serbian Academy of Sciences and Arts (SASA).
His long-term professional objective is to bring close together ideas from the broad fields of Artificial Intelligence / Intelligent Systems and Software Engineering. His current professional and research interests include artificial intelligence, intelligent software systems, programming education, software engineering, and technology-enhanced learning (TEL).
Alina Vladescu
National Institute for Optoelectronics, Romania
Alina Vladescu
National Institute for Optoelectronics, Romania
Alina Vladescu (Dragomir) has PhD in Materials Science from University Politehnica of Bucharest (UPB) (2011). She works at National Institute for Optoelectronics INOE2000, Department for Advanced Surface Processing and Analysis by Vacuum Technologies (since 2002). She is also associate professor in Surface Engineering at UPB. Expertise: Functional coatings (metals, nitrides, carbides, oxides and oxynitrides) deposited by magnetron sputtering and cathodic arc techniques, especially for optics, optoelectronics, mechanical/tribological applications, but also with special properties, such as corrosion resistant and biomaterials. She has 140 ISI papers, and over 250 presentations, 17 patents, 7 books, 16 awards at Invention Exhibitions. Hirsh score is 25.
Alina Vladescu (Dragomir) has PhD in Materials Science from University Politehnica of Bucharest (UPB) (2011). She works at National Institute for Optoelectronics INOE2000, Department for Advanced Surface Processing and Analysis by Vacuum Technologies (since 2002). She is also associate professor in Surface Engineering at UPB. Expertise: Functional coatings (metals, nitrides, carbides, oxides and oxynitrides) deposited by magnetron sputtering and cathodic arc techniques, especially for optics, optoelectronics, mechanical/tribological applications, but also with special properties, such as corrosion resistant and biomaterials. She has 140 ISI papers, and over 250 presentations, 17 patents, 7 books, 16 awards at Invention Exhibitions. Hirsh score is 25.
Christos Katris
Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece
Christos Katris
Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece
Christos Katris is a Customs Officer (Statistician) at the Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece. He has worked as an Adjunct Lecturer at the University of Patras, as a Postdoctoral Researcher at the Athens University of Economics and Business (AUEB), as a Statistician and/or Econometrician at various jobs, and as a Statistical Researcher in projects from the University of Patras and of AUEB. He holds a BSc. in Statistics and Economics, an MSc. in "Computer Mathematics and Decisions" and a Ph.D. in Applied Statistics. He has research publications in scientific journals and conferences and his scientific interests are mainly in time series and forecasting, applied statistics, and applied econometrics.
Christos Katris is a Customs Officer (Statistician) at the Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece. He has worked as an Adjunct Lecturer at the University of Patras, as a Postdoctoral Researcher at the Athens University of Economics and Business (AUEB), as a Statistician and/or Econometrician at various jobs, and as a Statistical Researcher in projects from the University of Patras and of AUEB. He holds a BSc. in Statistics and Economics, an MSc. in “Computer Mathematics and Decisions” and a Ph.D. in Applied Statistics. He has research publications in scientific journals and conferences and his scientific interests are mainly in time series and forecasting, applied statistics, and applied econometrics.
Yuri Demchenko
University of Amsterdam
Yuri Demchenko
University of Amsterdam
Yuri Demchenko is a Senior Researcher at the Complex Cyber Infrastructure Research Group of the University of Amsterdam. He graduated from the National Technical University of Ukraine "Kyiv Polytechnic Institute" where he also received his Ph.D. degree. His main research areas include Data Science and Data Management, Big Data Infrastructure, and Technologies for Data Analytics, DevSecOps, and general security architectures
He was involved in many European projects such as EGEE, GEANT4, and SLICES-DS where he developed elements of cloud-based infrastructures for scientific research. He is currently contributing to building the SLICES-RI for Digital Infrastructure technology experimentation. He actively researches on the architectural and design aspects of data management infrastructures for experimental research reproducibility and FAIR data sharing and processing.
Yuri Demchenko is a Senior Researcher at the Complex Cyber Infrastructure Research Group of the University of Amsterdam. He graduated from the National Technical University of Ukraine “Kyiv Polytechnic Institute” where he also received his Ph.D. degree. His main research areas include Data Science and Data Management, Big Data Infrastructure, Technologies for Data Analytics, DevSecOps, and general security architectures. He was involved in many European projects such as EGEE, GEANT4, and SLICES-DS where he developed elements of cloud-based infrastructures for scientific research. He is currently contributing to building the SLICES-RI for Digital Infrastructure technologies experimentation. He actively researches on the architectural and design aspects of data management infrastructures for experimental research reproducibility and FAIR data sharing and processing.
Dr. Alexander Borusan
Technische Universität Berlin
Dr. Alexander Borusan
Technische Universität Berlin
Dr. Alexander Borusan is Deputy Operations of the Database Systems and Information Management group at the Technische Universität Berlin. Prior to his work in Berlin, he worked at the Kyiv Polytechnical Institute and as a visiting professor in the Department of Computer Science at the University of Hamburg. Alexander worked in various national and international research projects and in projects on behalf of industry in the Ukraine, USA, France, and Germany. His research interests include Petri Nets Technology for Systems Development and Data stream management in Automotive, Avionics, and Aerospace Applications. In addition to his activities at the university, Alexander was chair of the department, chair of the Berlin Branch at the Fraunhofer-Institute ISST, and is currently a Senior Scientist at the System Quality Center at the Fraunhofer-Institute FOKUS.
Dr. Alexander Borusan is Deputy Operations of the Database Systems and Information Management group at the Technische Universität Berlin. Prior to his work in Berlin, he worked at the Kyiv Polytechnical Institute and as a visiting professor in the Department of Computer Science at the University of Hamburg. Alexander worked on various national and international research projects and in projects on behalf of industry in the Ukraine, USA, France, and Germany. His research interests include Petri Nets Technology for Systems Development and Data stream management in Automotive, Avionics, and Aerospace Applications. In addition to his activities at the university, Alexander was chair of the department, chair of the Berlin Branch at the Fraunhofer-Institute ISST, and is currently a Senior Scientist at the System Quality Center at the Fraunhofer-Institute FOKUS.
Ben Auffarth
Hastings Direct, London
Ben Auffarth
Hastings Direct, London
Ben Auffarth is a seasoned data science leader with a background and Ph.D. in computational neuroscience. Ben has analyzed terabytes of data, simulated brain activity on supercomputers with up to 64k cores, designed and conducted wet lab experiments, built production systems processing underwriting applications, and trained neural networks on millions of documents. He’s highly regarded in the London data science community and the best-selling author of the books Generative AI with LangChain, Machine Learning for Time Series, and Artificial Intelligence with Python Cookbook.
Ben Auffarth is a seasoned data science leader with a background and Ph.D. in computational neuroscience. Ben has analyzed terabytes of data, simulated brain activity on supercomputers with up to 64k cores, designed and conducted wet lab experiments, built production systems processing underwriting applications, and trained neural networks on millions of documents. He’s highly regarded in the London data science community and the best-selling author of the books Generative AI with LangChain, Machine Learning for Time Series, and Artificial Intelligence with Python Cookbook.
Dr. Kassim Mwitondi
Senior Lecturer & Researcher at Sheffield Hallam University
Dr. Kassim Mwitondi
Senior Lecturer & Researcher at Sheffield Hallam University
Kassim obtained his PhD in Statistical Data Mining from the School of Mathematics of the University of Leeds, in 2003. His interdisciplinary work on Big Data Modelling of Sustainable Development Goals (BDMSDG), with Machine Learning (ML) applications in Agri-Food, Environment, Health and Education, is well–documented. His research work focuses on ML applications in modeling non-orthogonal real-life phenomena and promotes academia–industry partnerships and collaboration across disciplines and continents. He is a regular presenter at a number of international conferences on data science and related fields across the world, and he has published extensively in those areas. He sits on the editorial and advisory boards of several international bodies.
Kassim obtained his PhD in Statistical Data Mining from the School of Mathematics of the University of Leeds, in 2003. His interdisciplinary work on Big Data Modelling of Sustainable Development Goals (BDMSDG), with Machine Learning (ML) applications in Agri-Food, Environment, Health, and Education, is well–documented. His research work focuses on ML applications in modeling non–orthogonal real–life phenomena and promotes academia–industry partnerships and collaboration across disciplines and continents. He is a regular presenter at a number of international conferences on data science and related fields across the world, and he has published extensively in those areas. He sits on the editorial and advisory boards of several international bodies.
Mounim A. El-Yacoubi
Professor at Institute Polytechnique de Paris
Mounim A. El-Yacoubi
Professor at Institute Polytechnique de Paris
Mounîm A. El-Yacoubi is a Professor at Institut Polytechnique de Paris. Prior to that, At SRTP, CENPARMI, and Parascript, LLC, he developed handwriting recognition software for mail sorting, bank check reading, and form processing, still running daily in automatic reading machines worldwide. He has been Program Co-Chair of ICPRAI 2022, IEEE SWC 2023, and ICCSI 2023, and is General Chair of the 15th International Conference on Human System Interaction (HSI), Paris, 2024. His research interests include AI, machine learning & deep learning, modeling human user data, especially behavioral signals like handwriting, voice, gesture, and activity recognition, with a special focus on e-health and sport, in particular the detection of neurodegenerative and chronic diseases.
Mounîm A. El-Yacoubi is a Professor at Institut Polytechnique de Paris. Prior to that, At SRTP, CENPARMI, and Parascript, LLC, he developed handwriting recognition software for mail sorting, bank check reading, and form processing, still running daily in automatic reading machines worldwide. He has been Program Co-Chair of ICPRAI 2022, IEEE SWC 2023, and ICCSI 2023, and is General Chair of the 15th International Conference on Human System Interaction (HSI), Paris, 2024. His research interests include AI, machine learning & deep learning, modeling human user data, especially behavioral signals like handwriting, voice, gesture, and activity recognition, with a special focus on e-health and sport, in particular the detection of neurodegenerative and chronic diseases.
Prof. Patrick Siarry
Professor at University Paris-Est Créteil (UPEC)
Prof. Patrick Siarry
Professor at University Paris-Est Créteil (UPEC)
Dr. Patrick Siarry is a professor at the University Paris-Est Créteil (UPEC) since 2010. His research area is relatively (since 1982) new “metaheuristic” optimization such as simulated annealing, which is indicated for the so-called problems of “hard optimization” because of their ability to avoid in principle, trapping in sub-optimal solutions. Much of his work is explicitly one or the other keywords – in particular, modeling, identification, learning rule bases (artificial intelligence), control,
nondestructive testing, and maintaining biological and medical engineering. Since 2009 he has served as a Director of Team Image Processing and Signal (TIS) at the Laboratory of Images, Signals, and Intelligent Systems.
Prof. Siarry has 12 frames at 100% of doctoral theses and scientific career, for 32 years, resulting in various publications. The scientific and research activities of Prof. P. Siarry confirm him as a leading scientist in the area of “metaheuristic” optimization.
Dr. Patrick Siarry is a professor at the University Paris-Est Créteil (UPEC) since 2010. His research area is relatively (since 1982) new “metaheuristic” optimization such as simulated annealing, which is indicated for the so-called problems of “hard optimization” because of their ability to avoid in principle, trapping in sub-optimal solutions. Much of his work is explicitly one or the other keywords – in particular, modeling, identification, learning rule bases (artificial intelligence), control, nondestructive testing, and maintaining biological and medical engineering. Since 2009 he has served as a Director of Team Image Processing and Signal (TIS) at the Laboratory of Images, Signals, and Intelligent Systems. Prof. Siarry has 12 frames at 100% of doctoral theses and scientific career, for 32 years, resulting in various publications. The scientific and research activities of Prof. P. Siarry confirm him as a leading scientist in the area of “metaheuristic” optimization.
Costas Vassilakis
University of the Peloponnese, Greece
Costas Vassilakis
University of the Peloponnese, Greece
Costas Vassilakis is a Professor in the Department of Informatics and Telecommunications of the University of the Peloponnese, in the area of Information Systems. He received his degree from the Department of Informatics, University of Athens in 1990 and his PhD from the same department in 1995. He has published more than 240 papers in international journals and conferences and has participated in more than 30 international and national R&D projects. His research interests include information systems, data science, software engineering, semantic web, as well as information presentation aspects.
Costas Vassilakis is a Professor in the Department of Informatics and Telecommunications of the University of the Peloponnese, in the area of Information Systems. He received his degree from the Department of Informatics, University of Athens in 1990 and his PhD from the same department in 1995. He has published more than 240 papers in international journals and conferences and has participated in more than 30 international and national R&D projects. His research interests include information systems, data science, software engineering, semantic web, as well as information presentation aspects.
Radoslaw Kita
Head of Data Science at Ringier Axel Springer Polska
Radoslaw Kita
Head of Data Science at Ringier Axel Springer Polska
"Radoslaw Kita works as Head of Data Science at Ringier Axel Springer Polska. He manages a team of several Data Scientists and MLOps. The team is responsible for building an environment enabling the use of AI, ad recommendation systems, and content recommendation systems.
Radoslaw has been involved in the analysis of large data sets for over 22 years. During this time, he worked for an internet portal, a bank, television, an e-commerce platform, a telecom, and ad tech."
“Radoslaw Kita works as Head of Data Science at Ringier Axel Springer Polska. He manages a team of several Data Scientists and MLOps. The team is responsible for building an environment enabling the use of AI, ad recommendation systems, and content recommendation systems.
Radoslaw has been involved in the analysis of large data sets for over 22 years. During this time, he worked for an internet portal, a bank, television, an e-commerce platform, a telecom, and ad tech.”
Gustavo M. de Almeida
Lappeenranta-Lahti University of Technology, Finland
Gustavo M. de Almeida
Lappeenranta-Lahti University of Technology, Finland
Gustavo M. de Almeida is a researcher at the Department of Energy Technologies, School of Energy Systems, Lappeenranta-Lahti University of Technology (LUT), Finland. He obtained his doctoral degree in Chemical Engineering from the University of São Paulo (USP), Brazil 2006, focusing on data analysis, signal processing, and industrial process monitoring. His research interests include machine learning, industrial statistics, and data visualization for Process Data Analytics (PDA) applications, focusing mainly on process monitoring, fault detection and diagnosis, and soft sensing in the continuous process industry. He has participated in national and international research projects and served as a reviewer in several journals and on scientific committees at international conferences covering process systems engineering, artificial intelligence, operations research, and related areas.
Gustavo M. de Almeida is a researcher at the Department of Energy Technologies, School of Energy Systems, Lappeenranta-Lahti University of Technology (LUT), Finland. He obtained his doctoral degree in Chemical Engineering from the University of São Paulo (USP), Brazil 2006, focusing on data analysis, signal processing, and industrial process monitoring. His research interests include machine learning, industrial statistics, and data visualization for Process Data Analytics (PDA) applications, focusing mainly on process monitoring, fault detection and diagnosis, and soft sensing in the continuous process industry. He has participated in national and international research projects and served as a reviewer in several journals and on scientific committees at international conferences covering process systems engineering, artificial intelligence, operations research and related areas.
Dr. Bernard Sinclair-Desgagné
Skema Business School
Dr. Bernard Sinclair-Desgagné
Skema Business School
Bernard Sinclair-Desgagné is a Professor of Economics and CSR at Skema Business School. Previously, he was for several years, and successively, Professor at INSEAD, the École Polytechnique de Montréal, and HEC Montréal. He holds a PhD in Management Science/Operations research from Yale University. His main research areas are the economics of incentives and organization, environmental economics and policy, risk management, and environmental innovation. His publications can be found in major journals such as Econometrica, Management Science, the Journal of Law, Economics and Organization, and the Journal of Environmental Economics and Management. His recent work focuses on incentive compensation and responsible business, CSR and artificial intelligence, and the measurement of innovation. In 2004, he was elected a Fellow of the European Economic Association. In 2006, he won (with co-author Pauline Barrieu of the LSE) the Finance and Sustainability European Research Award for the article “On Precautionary Policies” published in Management Science. From 2008 to 2019, he was a member of the Commission de l’éthique en Science et en Technologies (CEST), which advises the Government of Québec on ethical matters raised by the deployment of new technologies.
Bernard Sinclair-Desgagné is Professor of Economics and CSR at Skema Business School. Previously, he was for several years, and successively, Professor at INSEAD, the École polytechnique de Montréal and HEC Montréal. He holds a PhD in Management science/Operations research from Yale University. His main research areas are the economics of incentives and organization, environmental economics and policy, risk management, and environmental innovation. His publications can be found in major journals such as Econometrica, Management Science, the Journal of Law, Economics and Organization, and the Journal of Environmental Economics and Management. His recent work focuses on incentive compensation and responsible business, CSR and artificial intelligence, and the measurement of innovation. In 2004, he was elected a Fellow of the European Economic Association. In 2006, he won (with co-author Pauline Barrieu of the LSE) the Finance and Sustainability European Research Award for the article “On Precautionary Policies” published in Management Science. From 2008 to 2019, he was a member of the Commission de l’éthique en science et en technologie (CEST), which advises the Government of Québec on ethical matters raised by the deployment of new technologies.
Diego Cuadrado
Clintell Technology, Madrid, Spain
Diego Cuadrado
Clintell Technology, Madrid, Spain
Diego Cuadrado is a CEO of Clintell Technology. In addition to leading Clintell Technology, He's also a co-founder of two tech startups that have recently received significant funding and acclaim. Over the past ten years, he immersed himself in the world of data, a journey that's taken him across various industries and countries. His experience spans working with an array of companies, from innovative startups to major multinationals, including notable names like L'Oreal, Ryanair, Fairy, Dodot, Kiehl's, YSL, Ralph Lauren, Gillette, Head & Shoulders, Pantene, and many others.
Beyond his corporate engagements, he has also taken on the role of an educator, teaching at the
university level and sharing insights on platforms like TEDx and other significant business events. Six years ago, he embarked on an entrepreneurial journey, establishing a venture builder focused on the cutting edge of artificial intelligence. The mission at Clintell Technology is to develop advanced AI and machine learning models that cater to the unique needs of both corporations and tech startups. This innovative approach has not only set us apart in the industry but also attracted external investment.
Diego Cuadrado is a CEO of Clintell Technology. In addition to leading Clintell Technology, he’s also a co-founder of two tech startups that have recently received significant funding and acclaim. Over the past ten years, he immersed himself in the world of data, a journey that’s taken him across various industries and countries. His experience spans working with an array of companies, from innovative startups to major multinationals, including notable names like L’Oreal, Ryanair, Fairy, Dodot, Kiehl’s, YSL, Ralph Lauren, Gillette, Head & Shoulders, Pantene, and many others. Beyond his corporate engagements, he has also taken on the role of an educator, teaching at the university level and sharing insights on platforms like TEDx and other significant business events. Six years ago, he embarked on an entrepreneurial journey, establishing a venture builder focused on the cutting edge of artificial intelligence. The mission at Clintell Technology is to develop advanced AI and machine learning models that cater to the unique needs of both corporations and tech startups. This innovative approach has not only set us apart in the industry but also attracted external investment.
Michal Boni
University for Social Sciences and Humanities in Warsaw, Poland
Michal Boni
University for Social Sciences and Humanities in Warsaw, Poland
The first minister of Digital Affairs in Central Eastern Europe (2011-2013), one of the leaders of the consultations and work on GDPR from 2012. As a Member of the European Parliament (2014-2019), especially active in LIBE and ITRE Committees. Responsible for many reports: 5G Road Map and Gigabit Society Development, European Open Science Cloud, Re-use and Public Information directive, e-privacy solutions, reports of AI, and e-Health development. Currently: SWPS University
(University for Social Sciences and Humanities in Warsaw - Assistant Professor/ Department of New Technologies in Social Applications). In cooperation with Martens Centre (Brussels’ think tank - Senior Researcher Associate); SMEEurope and SMEConnect (Senator and moderator of public debates on digital topics).
The first minister of Digital Affairs in Central Eastern Europe (2011-2013), one of the leaders of the consultations and work on GDPR from 2012. As a Member of the European Parliament (2014-2019), especially active in LIBE and ITRE Committees. Responsible for many reports: 5G Road Map and Gigabit Society Development, European Open Science Cloud, Re-use and Public Information directive, e-Privacy solutions, reports of AI, and e-Health development. Currently: SWPS University
(University for Social Sciences and Humanities in Warsaw – Assistant Professor/ Department of New Technologies in Social Applications). In cooperation with Martens Centre (Brussels’ think tank – Senior Researcher Associate); SMEEurope and SMEConnect (Senator and moderator of public debates on digital topics).
Dr. Aziz Fellah
Northwest Missouri State University, USA
Dr. Aziz Fellah
Northwest Missouri State University, USA
Dr. Aziz Fellah is an Associate Professor at Northwest Missouri State University. He earned his B.Sc., M.Sc., and Ph.D. degrees in computer science. He has extensive computer science teaching and research experience at various institutions in the US and Canada. Dr. Fellah’s research interests and areas span both theoretical and practical computer science, including software engineering, algorithmic learning, programming languages, model checking, information flow control in machine learning, and distributed/parallel systems in which he has been academically active and published extensively. Dr. Fellah has served on many international scientific and research committees. He collaborated closely with academic communities and industry partners to promote students' educational learning experiences to which Dr. Fellah attaches great importance.
Dr. Aziz Fellah is an Associate Professor at Northwest Missouri State University. He earned his B.Sc., M.Sc., and Ph.D. degrees in computer science. He has extensive computer science teaching and research experience at various institutions in US and Canada. Dr. Fellah’s research interests and areas span both theoretical and practical computer science, including software engineering, algorithmic learning, programming languages, model checking, information flow control in machine learning, and distributed/parallel systems in which he has been academically active and published extensively. Dr. Fellah has served on many international scientific and research committees. He collaborated closely with academic communities and industry partners to promote students’ educational learning experiences to which Dr. Fellah attaches great importance.
From Last Edition Committee Board
Alexander Borusan
Technische Universitaet Berlin, Germany
Alexander Borusan
Technische Universitaet Berlin, Germany
Dr. Alexander Borusan is Deputy Operations of the Database Systems and Information Management group at the Technische Universität Berlin. His research interests include data streams management. Prior to his work in Berlin, he worked at the Kiev Polytechnical Institute and as a visiting professor in the department of computer science at the University of Hamburg. Alexander worked in various national and international research projects and in projects on behalf of industry in the Ukraine, USA, France, and Germany. He is currently the member of the Management Team of BIFOLD, the Berlin Institute for the Foundations of Learning and Data.
Dr. Alexander Borusan is Deputy Operations of the Database Systems and Information Management group at the Technische Universität Berlin. His research interests include data streams management. Prior to his work in Berlin, he worked at the Kiev Polytechnical Institute and as a visiting professor in the department of computer science at the University of Hamburg. Alexander worked in various national and international research projects and in projects on behalf of industry in the Ukraine, USA, France, and Germany. He is currently the member of the Management Team of BIFOLD, the Berlin Institute for the Foundations of Learning and Data.
Hichem Snoussi
University of Technology of Troyes, France
Hichem Snoussi
University of Technology of Troyes, France
Prof. Hichem Snoussi received the diploma degree in Electrical Engineering from the Ecole Supérieure d'Electricité (Supélec), Gif-sur-Yvette, France, in 2000. He also received the DEA degree and the Ph.D. in signal processing from the University of Paris-Sud, Orsay, France, in 2000 and 2003 respectively. Between 2003 and 2004, he was postdoctoral researcher at IRCCyN, Institut de Recherches en Communications et Cybernétiques de Nantes. He has spent short periods as visiting scientist at the Brain Science Institute, RIKEN, Japan and Olin Neuropsychiatry Research Center at the Institute of Living in USA. Between 2005 and 2009, he was associate professor at the University of Technology of Troyes, France. He has obtained the HDR degree from the University of Technology of Compiègne in 2009. Since 2010, he is Full Professor at the University of Technology of Troyes. His research interests include Bayesian techniques for source separation, information geometry, differential geometry, machine learning,etc. Since 2010, he has been in charge of the CapSec Plateform (Sensors for Security). He is the principal investigator of many research projects and industrial partnerships. Between 2016 and 2020, he has been manager of LM2S Lab in Charles Delaunay Institute. Since 2021, he is deputy director of LIST3N lab and team leader of M2S group. He co-founded 2 start-up: Aquilae (IA for videosurveillance) and Damavan Imaging (Compton cameras for nuclear inspection).
He has obtained the HDR degree from the University of Technology of Compiègne in 2009. Since 2010, he is Full Professor at the University of Technology of Troyes. His research interests include Bayesian techniques for source separation, information geometry, differential geometry, machine learning,etc. Since 2010, he has been in charge of the CapSec Plateform (Sensors for Security). He is the principal investigator of many research projects and industrial partnerships. Between 2016 and 2020, he has been manager of LM2S Lab in Charles Delaunay Institute. Since 2021, he is deputy director of LIST3N lab and team leader of M2S group. He co-founded 2 start-up: Aquilae (IA for videosurveillance) and Damavan Imaging (Compton cameras for nuclear inspection).
Chinmaya Dehury
University of Tartu, Estonia
Chinmaya Dehury
University of Tartu, Estonia
Chinmaya Kumar Dehury is an Assistant Professor of Distributed Systems at Mobile & Cloud Lab, Institute of Computer Science, University of Tartu, Estonia. He completed his Ph.D. in Computer Science and Information Engineering from Chang Gung University, Taiwan. He has attended many international meetings and was invited to talk at workshops and conferences. His research interest varies from Artificial Intelligence Technologies and Applications. He has been a Technical Committee Member in 2021 and is currently a PC member in ACS/IEEE,2022.
Chinmaya Kumar Dehury is an Assistant Professor of Distributed Systems at Mobile & Cloud Lab, Institute of Computer Science, University of Tartu, Estonia. He completed his Ph.D. in Computer Science and Information Engineering from Chang Gung University, Taiwan. He has attended many international meetings and was invited to talk at workshops and conferences. His research interest varies from Artificial Intelligence Technologies and Applications. He has been a Technical Committee Member in 2021 and is currently a PC member in ACS/IEEE,2022.
Chong Leong Gan
Micron Technology, Inc., United States
Chong Leong Gan
Micron Technology, Inc., United States
Dr. Chong Leong, Gan received the B.S. degree in Chemical Engineering from National University of Malaysia in 2000, M.S. degree in Chemical Instrumentation in 2003 from University Science Malaysia, and Ph.D. in Nanoelectronic Engineering from University Malaysia Perlis in 2015. Since 2006, he has been a Quality and Reliability Member of Technical Staff with Altera Corporation, Senior R&D Engineering Manager with Western Digital Inc, and recently as Package Characterization Director with Micron Technology Inc.
Dr. Chong Leong, Gan received a B.S. degree in Chemical Engineering from the National University of Malaysia in 2000, an M.S. degree in Chemical Instrumentation in 2003 from the University of Science Malaysia, and a Ph.D. in Nanoelectronic Engineering from the University Malaysia Perlis in 2015. Since 2006, he has been a Quality and Reliability Member of Technical Staff with Altera Corporation, Senior R&D Engineering Manager with Western Digital Inc, and recently as Package Characterization Director with Micron Technology Inc.
Giancarlo Cobino
Qvantia, Italy
Giancarlo Cobino
Qvantia, Italy
10+ years of experience in Data Science projects, from machine learning to Artificial intelligence, applied to real-world problems. Development and implementation of customers profiling, recommender systems and Churn algorithms. Extensive experience in managing heterogeneous teams of Software Developers, DevOps, data scientists, Sales and Marketing. Recently served as global leader of ML and MLOps for NTT DATA, he's now CTO of Qvantia (https://qvantia.com), a unified ML and AI platform, and founder of Huok (https://huok.tech), a consultancy firm helping enterprises to adopt Artificial Intelligence.
10+ years of experience in Data Science projects, from machine learning to Artificial intelligence, applied to real-world problems. Development and implementation of customers profiling, recommender systems and Churn algorithms. Extensive experience in managing heterogeneous teams of Software Developers, DevOps, data scientists, Sales and Marketing. Recently served as global leader of ML and MLOps for NTT DATA, he’s now CTO of Qvantia (https://qvantia.com), a unified ML and AI platform, and founder of Huok (https://huok.tech), a consultancy firm helping enterprises to adopt Artificial Intelligence.
Christos Katris
Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece
Christos Katris
Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece
Christos Katris is a Customs Officer (Statistician) at the Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece. He has worked as an Adjunct Lecturer at the University of Patras, as a Postdoctoral Researcher at the Athens University of Economics and Business (AUEB), as a Statistician and/or Econometrician at various jobs, and as a Statistical Researcher in projects from the University of Patras and of AUEB. He holds a BSc. in Statistics and Economics, an MSc. in "Computer Mathematics and Decisions" and a Ph.D. in Applied Statistics. He has research publications in scientific journals and conferences and his scientific interests are mainly in time series and forecasting, applied statistics, and applied econometrics.
Christos Katris is an Adjunct Lecturer at the Department of Mechanical Engineering and Aeronautics at the University of Patras and a Customs Officer (Statistician) at the Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece. He was a Postdoctoral Researcher at the Department of Accounting and Finance, Athens University of Economics and Business, and has worked as a Statistician/Econometrician in Alma Economics, as a Statistical Analyst at the Quality Assurance Unit (MO.DI.P.) of the University of Patras, and as Statistical Researcher in projects from the University of Patras and from the Athens University of Economics and Business. He holds Degrees in Statistics and Economics, a Master’s Degree in “Computer Mathematics and Decisions” and a Ph.D. (entitled “Stochastic Models for Data Analysis on the Internet”, from the University of Patras in the research area of Applied Statistics. His scientific interests are mainly in time series and forecasting, applied statistics, and applied econometrics.
Alessandro Bonaita
Generali Corporate Pension Fund, Italy
Alessandro Bonaita
Generali Corporate Pension Fund, Italy
Alessandro Bonaita is Group Head of Data Science at Generali Group, one of the largest global insurance and asset management providers, where he is responsible for developing the adoption of artificial intelligence in more than 50 countries. Previously Head of Analytics at American Express and RCS Mediagroup, where he also served as Deputy Privacy Officer, in the last years he focused his attention on the ethical and legal implications of AI, its responsible and sustainable adoption, and the related organizational impacts, becoming an advisor for several institutions and research centers, including Stanford University and the European insurance and reinsurance federation.
Alessandro Bonaita is Group Head of Data Science at Generali Group, one of the largest global insurance and asset management providers, where he is responsible for developing the adoption of artificial intelligence in more than 50 countries. Previously Head of Analytics at American Express and RCS Mediagroup, where he also served as Deputy Privacy Officer, in the last years he focused his attention on the ethical and legal implications of AI, its responsible and sustainable adoption, and the related organizational impacts, becoming an advisor for several institutions and research centers, including Stanford University and the European insurance and reinsurance federation.
Gianpaolo Di Bona
University of Cassino, Italy
Gianpaolo Di Bona
University of Cassino, Italy
Gianpaolo Di Bona is an Associate Professor at the University of Cassino. He earned a Ph.D. in Civil and Mechanical Engineering from the University of Cassino, and a Master's Degree in Civil Engineering from the University of Rome “La Sapienza”. He has been involved - as a team member and, more recently, as a scientific coordinator - in research projects of national and international importance. These projects are in the areas of Manufacturing, Quality Management and Operations Improvement, and Supply Chain Management. Since 2017, he has served on many international committees, as a member of editorial boards, and as a reviewer. Over 70 publications in relevant journals, scientific conferences, and books.
Gianpaolo Di Bona is an Associate Professor at the University of Cassino. He earned a Ph.D. in Civil and Mechanical Engineering from the University of Cassino, and a Master’s Degree in Civil Engineering from the University of Rome “La Sapienza”. He has been involved – as a team member and, more recently, as a scientific coordinator – in research projects of national and international importance. These projects are in the areas of Manufacturing, Quality Management and Operations Improvement, and Supply Chain Management. Since 2017, he has served on many international committees, as a member of editorial boards, and as a reviewer. Over 70 publications in relevant journals, scientific conferences, and books.
Jürgen Pilz
Alpen Adria Universität Klagenfurt- Institute of Statistics, Austria
Jürgen Pilz
Alpen Adria Universität Klagenfurt- Institute of Statistics, Austria
Professor Jürgen Pilz supervises Ph.D. students and postdoctoral researchers and teaches courses on statistics and data science. In 1988, he received his DSc from Germany. His major areas of interest include Bayesian Statistics, Spatial Statistics, Design of Experiments, Bayesian Epidemiology, and Bayesian Statistical Learning. Over 180 publications have been published in international journals and conference proceedings by him. Author of 8 books published by renowned publishers such as Wiley, Springer, Elsevier, Chapman & Hall from 2007-2015. Former Head of the Department of Applied Statistics at Alpen Adria University Klagenfurt - Emeritus Professor since October 1, 2020 - elected member of the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS) - on editorial boards of several international statistics journals.
Jürgen Pilz is Emeritus Professor at the Department of Statistics, Alpen Adria University (AAU) of Klagenfurt, Austria. He received his Ph.D. and DSc degrees from TU Mining Academy Freiberg, Germany. From 1994 – 2020 he was Professor and Chair of Applied Statistics at AAU Klagenfurt, Austria, from 2007-2015 and 2018-2019 he served as (Founding) Head of the Dept. of Statistics at AAU Klagenfurt. He held guest professorships at Charles University Prague (Czech Rep.), University of Augsburg (Germany), Purdue University (USA), University of British Columbia, Vancouver (Canada), and the University of Canterbury, Christchurch (New Zealand).
His major areas of interest include Bayesian Statistics, Spatial Statistics, Design of Experiments, Bayesian Epidemiology, and Bayesian Statistical Learning. He has published over 200 papers in international journals and conference proceedings. He has supervised more than 80 Master theses and 40 Ph.D. theses. He is the author of seven books from renowned publishers including Wiley, Springer, Chapman & Hall, the latest one being „Applied Statistics – Theory and Problem Solutions with R“ published by J. Wiley and Sons, Oxford 2020. He is an elected member of the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS), and on editorial boards of several international statistics journals.
Mike Williamson
Tradeshift, Denmark
Mike Williamson
Tradeshift, Denmark
Mike Williamson is the director of machine learning and data engineering at Tradeshift. Prior to Tradeshift, Mike worked at companies of all sizes, primarily in Silicon Valley, now living in the greater Copenhagen region. He began his career in semiconductor manufacturing and came to love the capability of statistics to deliver experimental success with less effort and cost. He made the jump to data science shortly thereafter, primarily working in SaaS companies. He focused on the “productionizing” of machine learning, elements such as MLOps, Infrastructure as Code, and CI/CD. Mike spent most of his career as an individual contributor, but has spent the last several years as an ML architect, professor, and currently as director of the ML and data engineering team at Tradeshift.
Mike Williamson is the director of machine learning and data engineering at Tradeshift. Prior to Tradeshift, Mike worked at companies of all sizes, primarily in Silicon Valley, now living in the greater Copenhagen region. He began his career in semiconductor manufacturing and came to love the capability of statistics to deliver experimental success with less effort and cost. He made the jump to data science shortly thereafter, primarily working in SaaS companies. He focused on the “productionizing” of machine learning, elements such as MLOps, Infrastructure as Code, and CI/CD. Mike spent most of his career as an individual contributor, but has spent the last several years as an ML architect, professor, and currently as director of the ML and data engineering team at Tradeshift.
Eric Peukert
ScaDS.AI, Leipzig University, Germany
Eric Peukert
ScaDS.AI, Leipzig University, Germany
Dr. Eric Peukert is the Administration Director of the National Data Science Center ScaDS.AI. He studied Media Informatics at the Dresden University of Technology and received a Ph.D. in SAP Research in the field of data integration within various BMBF and EU research projects. After completing his doctorate and two more years at SAP, Mr. Peukert moved to ScaDS at the University of Leipzig. Mr. Peukert coordinates the AI center's research activities with a special focus on industry cooperation and gives lectures at the University of Leipzig on big data and cloud data management. His research focuses on big data technologies, graph-based analysis, data integration, and machine learning-based methods.
Dr. Eric Peukert is the Administration Director of the National Data Science Center ScaDS.AI. He studied Media Informatics at the Dresden University of Technology and received a Ph.D. in SAP Research in the field of data integration within various BMBF and EU research projects. After completing his doctorate and two more years in at SAP, Mr. Peukert moved to ScaDS at the University of Leipzig. Mr. Peukert coordinates the AI center’s research activities with a special focus on industry cooperation and gives lectures at the University of Leipzig on big data and cloud data management. His research focuses on big data technologies, graph-based analysis, data integration, and machine learning-based methods.
Willi Sauerbrei
Medical Center - University of Freiburg, Germany
Willi Sauerbrei
Medical Center - University of Freiburg, Germany
Willi Sauerbrei is a senior statistician and professor in medical biometry. Since 1983, he has worked as an academic biostatistician with a main interest in various issues of model building and in cancer research. For 16 years, he was the head of a Clinical Trials Unit. With Patrick Royston, he has developed the multivariable fractional polynomial approach (MFP) and extensions of it. Methodological topics of interest include variable and function selection, model stability, treatment covariate interactions, meta-analysis, reporting of research findings, and high-dimensional data. He is the initiator and chair of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative.
Dr. Sauerbrei is a senior statistician and professor in medical biometry. Since 1983, he has worked as an academic biostatistician with a main interest in various issues of model building and in cancer research. For 16 years, he was the head of a Clinical Trials Unit. With Patrick Royston, he has developed the multivariable fractional polynomial approach (MFP) and its extensions of it. Methodological topics of interest include variable and function selection, model stability, treatment covariate interactions, meta-analysis, reporting of research findings, and high-dimensional data. He is the initiator and chair of the STRATOS (STRengthening Analytical Thinking for Observational Studies).
Scientific Committee Operator Event Reviewer
Rajsekhar works for Apple as an Engineering Manager for Data Platform and ML Infra focused on providing Lake House solutions for Machine Learning and Data Engineering use cases. Raj has over 18 years of experience in data space. One of the founding engineering members responsible for building large scale, multi-cloud and secure data/ML infrastructure at Apple. The platform runs at PB scale, over a trillion events ingestion daily. Adopters of open source technologies and responsible for designing, implementing and automating the managed services to deploy in various accounts.