Advisory Board and Editors Artificial Intelligence
Thomas Stützle
Research Director of the Belgian F.R.S.-FNRS (tenured research professor position) working at the Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle (IRIDIA), Université libre de Bruxelles, Brussels, Belgium. His research interests range from stochastic local search (SLS) algorithms, automated design of algorithms, large scale experimental studies, multi-objective optimization to applications of SLS algorithms.
Cédric Sueur
Cédric Sueur is Full Professor at the University of Strasbourg, specializing in the study of animal behavior with a primary focus on the dynamics of social networks and the mechanisms of collective decision-making within social groups. He holds leadership roles in academic programs, serving as co-director of both the Master's program in Ecology, Ecophysiology, and Ethology, and the Master's program in Animal Ethics, highlighting his dedication to advancing knowledge in both ecological and ethical domains. His distinguished contributions to his field have earned him membership in the prestigious Institut Universitaire de France and recognition from the Royal Academy of Science, Letters and Fine Arts of Belgium, where he was honored with an award.
Tamara Sumner
I lead an interdisciplinary research and development lab that studies how computational tools - combining cognitive science, machine intelligence, and interactive media - can improve teaching practice, learning outcomes and learner engagement. Inquiry Hub, formerly known as Digital Learning Sciences, is a mission-centered, research-practice partnership involving faculty and students from the University of Colorado Boulder, scientific and technical staff from the University Corporation for Atmospheric Research (UCAR), and educators and administrators from Denver Public Schools. Our research and development team combines expertise in cognitive science, learning sciences, science education, user-centered design and evaluation, digital content management, software engineering, educational data mining, and machine learning/natural language processing.
I am also a Professor at the University of Colorado, with a joint appointment between the Institute of Cognitive Science and the Department of Computer Science. I am currently serving as the Director of the Institute of Cognitive Science. My research and teaching interests include personalized learning, learning analytics, cyber learning environments, educational digital libraries, scholarly communications, human centered computing, and interdisciplinary research methods for studying cognition. I have written 140 articles on these topics, including over 80 peer-reviewed scholarly publications.
Easter S Suviseshamuthu
Dr. Suviseshamuthu is an Associate Research Scientist at the Human Performance and Engineering Research Lab, Kessler Foundation, West Orange, NJ, U.S.A., since Dec. 2015.
He received the B.E. degree in Electronics and Communication Engineering from the Government College of Engineering, Tirunelveli, India (1988), the M.E. degree in Applied Electronics from Bharathiar University, Coimbatore, India (2001), and the Ph.D. in Multispectral Satellite Image Analysis from the Laboratoire des Sciences de l’Information et des Systèmes, Université de la Méditerranée, Marseille, France (2007). He was Post-Doctoral Fellow at the Bioimaging and Biostructure Institute, Italian National Research Council, Naples, Italy, (2008 to 2010), the Department of Mathematical Engineering, Université catholique de Louvain, Louvain-la-Neuve, Belgium, (2010 to 2014), and the GIPSA-Lab, Université Joseph Fourier, Grenoble, France (2014 to 2015).
His research focus encompasses statistical signal processing, blind source separation, medical imaging, optimization on matrix manifolds, machine learning, biomedical signal analysis, and bio-inspired computing. He serves as Associate Editor of IEEE Access.
Sándor Szénási
Sándor Szénási has earned his MSc degree in 2004 from Faculty of Informatics of Eötvös Loránd University, Budapest. He has received his PhD in 2013 from Doctoral School of Applied Informatics (GSAI) of Óbuda University, Budapest.
Currently, he is an associate professor in the Institute of Applied Informatics of John von Neumann Faculty of Informatics, Óbuda University, Budapest. He is the leader of the local CUDA Teaching Center.
His research areas are (data) parallel algorithms, GPU programming and medical image processing. He engages both in theoretical fundamentals and in algorithmic issues with respect to realization of practical requirements and given constraints.
He is the member of the John von Neumann Computer Society and IEEE, and also a reviewer of several conferences and journals.
Steven John Thompson
Former faculty at Johns Hopkins University, Dartmouth College, UC Davis. I have been teaching college students for over 25 years. My research expertise is in Internet phenomena: access, addiction, agency, control, dependency, governance, and policy; and engineering ethics in Science, Technology, and Society (STS) merging the Internet with physical bodies. I am the Editor for Machine Law, Ethics and Morality in the Age of Artificial Intelligence (2021); Androids, Cyborgs, and Robots in Contemporary Culture and Society (2017); and, Global Issues and Ethical Considerations in Human Enhancement Technologies (2014).
Yi-Hsuan Tsai
Yi-Hsuan Tsai is the Director of AI at Phiar, leading the AI team to conduct cutting-edge research for real-world AR navigation. He was a senior researcher at NEC Laboratories America, working on fundamental computer vision/deep learning research. He received his PhD at University of California, Merced, honored with the Graduate Dean's Dissertation Fellowship. Prior to that, he received his MS at University of Michigan, Ann Arbor and BS at National Chiao Tung University, Taiwan. He is the recipient of the Best Student Paper Honorable Mention award for ACCV'18. He has various research interests in computer vision and machine learning, with a focus on scene understanding, video analysis, fairness of AI, and representation learning.
Ivor W Tsang
Ivor W Tsang is a Professor of Artificial Intelligence, at University of Technology Sydney (UTS). He is also the Research Director of the UTS Flagship Research Centre for Artificial Intelligence (CAI) with more than 30 faculty members and 180 PhD students. His research focuses on transfer learning, feature selection, crowd intelligence, big data analytics for data with extremely high dimensions in features, samples and labels. He has more than 180 research papers published in top-tier journal and conference papers. According to Google Scholar, he has more than 13,000 citations and his H-index is 54. In 2009, Prof Tsang was conferred the 2008 Natural Science Award (Class II) by Ministry of Education, China, which recognized his contributions to kernel methods. In 2013, Prof Tsang received his prestigious Australian Research Council Future Fellowship for his research regarding Machine Learning on Big Data. In addition, he had received the prestigious IEEE Transactions on Neural Networks Outstanding 2004 Paper Award in 2007, the 2014 IEEE Transactions on Multimedia Prize Paper Award, and a number of best paper awards and honors from reputable international conferences, including the Best Student Paper Award at CVPR 2010. He serves as an Associate Editor for the IEEE Transactions on Big Data, the IEEE Transactions on Emerging Topics in Computational Intelligence and Neurocomputing. He serves as an Area Chair/Senior PC for NeurIPS, AISTATS, AAAI and IJCAI.
Md Zia Uddin
DR. MD ZIA UDDIN received his bachelor’s degree in computer science and engineering from International Islamic University Chittagong, Bangladesh, in 2004. He then completed his MS Leading to PhD degree in Biomedical Engineering from Kyung Hee University, South Korea, in 2011. Currently, he is a senior research scientist
in the human-computer interaction group at SINTEF Digital, Oslo, Norway, where he continues contributing to his research field. His research primarily focuses on data and feature analysis, physical and mental healthcare, human-machine interaction, pattern recognition, deep learning, and artificial intelligence. His innovative work has been published in prestigious journals such as Information Fusion, IEEE Transactions on Consumer Electronics, and Future Generation Computer Systems, showcasing his peers’ high regard for his research. His research outcomes have earned him best/outstanding paper awards at several peer-reviewed international conferences. He received a Gold Medal Award in 2008 for academic excellence in his undergraduate studies. He was also awarded the Korean Government IT Scholarship and the Kyung Hee University President Scholarship from March 2007 to February 2011 to pursue his PhD. He has extensive teaching experience, having taught more than 20 computer science-related courses at various academic levels, from bachelor’s to PhD, and supervised many students’ research works at these levels as well. He is a senior member of IEEE. He has been editors any several prestigious journals such as PLOS One, Sensors, IEEE Access, and the International Journal of Computers and
Applications, Frontiers in Human Neuroscience, and a keynote speaker at various international conferences. Dr. Zia has over 170 research publications (around half as the leading author), including international journals, conferences, book chapters, and single-authored books. His Google Scholar citations are more than 6000. He has led work packages and tasks in many national and international research projects. His significant contributions
have earned him recognition in the World’s Top 2% Scientists (career-long and single-year-based), a list by Stanford University and Elsevier BV.
Leonilde Varela
The main research interests of Leonilde Varela rely on the Manufacturing Management domain: Production Planning, Control and Optimization and in Collaborative Paradigms, Networks and Decision Making Models, Methods and Tools, and Systems, Web Applications and Services for supporting Engineering and Production Management. She focuses on exploring international scientific collaborations, mainly in terms of joint publications, projects, and special issues proposals, with colleagues from several institutions. She is an active member in the organizing and scientific committees of several internationa conferences and integrates several research networks and organizations, such as: Euro Working Group of Decision Support Systems (EWG-DSS); Institute of Electrical and Electronics Engineers (IEEE); Industrial Engineering Network (IE Network); Institute of Industrial and Systems Engineers (IISE); Machine Intelligence Research Labs, Scientific Network for Innovation and Research Excellence (MirLabs).
Eleni Vasilaki
I am Professor of Bioinspired Machine Learning at the Faculty of Engineering, University of Sheffield and the head the Machine Learning group. Prior to my Academic appointment in Sheffield, I was Scientific Collaborator in the groups of Prof. Wulfram Gerstner at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and Prof. Walter Senn at the University of Bern. I hold a PhD in Computer Science and Artificial Intelligence (University of Sussex), a Masters in Microelectronics (University of Athens) and a Bachelors degree (with distinction) in Informatics & Telecommunications (University of Athens). I am a Chartered Engineer, registered with the Engineering Council UK in membership of the Institution of Engineering and Technology.
Shravan Vasishth
Professor of Psycholinguistics at the Department of Linguistics, University of Potsdam, Germany. Specialization in computational models of sentence comprehension; sentence processing in aphasia; working memory and language comprehension; Bayesian statistics.