Speakers
Razvan Andonie
Computer Science Department, Central Washington University, USA
Răzvan Andonie received the MS degree in mathematics/computer science from University of Cluj-Napoca, Romania, and the PhD degree from University of Bucharest, Romania. His PhD advisor was Solomon Marcus. He was Group Leader of the Image Processing Research Group, Research Institute of Computer Techniques, Brasov, Romania (1984-1992). In 1992 he moved to the Department of Electronics and Computers, Transylvania University of Brașov, Romania, as an Associate Professor/Full Professor. He was a visiting professor at various universities and research institutions: Wayne State University (USA), University of Texas at San Antonio (USA), University of Ulster (Northern Ireland, UK), Dublin City University (Ireland), Autonomous University of Barcelona (Spain), Paris 13 University (France), Technische Hochschule Ingolstadt (Germany), Nanjing University of Aeronautics and Astronautics (China), Dalle Molle Institute for Artificial Intelligence (Switzerland), University of Ottawa (Canada), National University of Ireland (Ireland), University of Luxembourg (Luxemburg), Old Dominium University (USA), University of Lübeck (Germany), University of Bristol (UK), King’s College (UK), Uppsala University (Sweden). Since 2003 he is an Associate Professor/Full Professor with the Computer Science Department, Central Washington University, USA. He has authored (co-authored) +150 papers. His main research interests are computational intelligence, machine learning, parallel and distributed computing, data mining, and quantum machine learning. He has received several times a Best Research Presentation Award, gave many invited lectures, and was involved in organizing a significant number of international conferences. He is supervising PhD candidates in computational intelligence and machine learning.
Guénaël Cabanes
Laboratoire d'Informatique de Paris Nord, Université Sorbonne Paris Nord, France
Guénaël Cabanes is an academic researcher at Sorbonne Paris Nord University, France, member of the Machine Learning research team of the LIPN laboratory. He received his PhD in computer science from the University of Sorbonne Paris Nord in 2010. His main research interests are in data mining, more specifically in unsupervised learning adapted to dynamic and complex data, with applications to image and text mining, data stream analysis and complex systems modeling. He has participated in several research projects in cooperation with various national and international research teams and companies, and has published about 20 papers in peer-reviewed journals and 35 in international conferences, in addition to two book chapters. Guénaël Cabanes has co-supervised 6 PhD students and supervises 1 or 2 Master 2 internships each year. He is also director of the first year of the computer science Master at the Galileo Institute and is in charge of the certification of digital skills at the Institute./span>
Nistor Grozavu
ETIS Laboratory, CYU Cergy Paris University, France
Nistor Grozavu received his HdR (Ability to direct research) degree from Sorbonne Paris Nord University in 2020 and PhD degree in Unsupervised Machine Learning in 2009 from Paris 13 University. He is currently Full Professor in Computer Science at CY Cergy Paris University. His research is with the MIDI team from ETIS Laboratory. His research interests include Unsupervised Learning, Transfer Learning, Dimensionality reduction, Collaborative Learning, Machine Learning by Matrix Factorization and content-based information retrieval, Quantum Machine Learning. These researches are applied in different applications for text mining, visual information retrieval, recommendation systems, fraud detection, etc. via ANR, FUI, PEPS CNRS, AUF projects. He is also a member of IEEE, INNS, and the co-founder of the INNS Autonomous Machine Learning group. Nistor is the co-author of a patent on visual information retrieval, published two book chapters, 12 peer-reviewed journal papers, and more than 40 international conference papers. Nistor Grozavu co-supervised 2 post-doctorants, 8 PhD students and supervises each year 1-2 Master2 internship.
Diana Inkpen
School of Electrical Engineering and Computer Science, University of Ottawa, Canada
Diana Inkpen received her Ph.D. in Computer Science from the University of Toronto, Canada, and her M.Sc. and B.Eng. in Computer Science and Engineering from the Technical University of Cluj-Napoca, Romania. She is currently a Professor at the University of Ottawa, in the School of Electrical Engineering and Computer Science. Her research is in applications of Natural Language Processing and Text Mining. She is the editor-in-chief of the Computational Intelligence journal and the associate editor for the Natural Language Engineering journal. She published a book on Natural Language Processing for Social Media (Morgan and Claypool Publishers, Synthesis Lectures on Human Language Technologies, the third edition appeared in 2020), 10 book chapters, more than 35 journal articles, and more than 130 conference papers. She received many research grants, from which the majority include intensive industrial collaborations. She supervised 14 Ph.D. students and 25 M.Sc. students.
Boris Kovalerchuk
Dept. of Computer Science at Central Washington University, USA
Dr. Boris Kovalerchuk is a professor of Computer Science at Central Washington University, USA. His publications include three books "Data Mining in Finance" (Springer, 2000), "Visual and Spatial Analysis" (Springer, 2005), and "Visual Knowledge Discovery and Machine Learning" (Springer, 2018), chapters in the Data Mining/Machine learning Handbooks, and over 170 other publications. His research and teaching interests are in machine learning, visual analytics, visualization, uncertainty modeling, image and signal processing, and data fusion. Dr. Kovalerchuk has been a principal investigator of research projects in these areas, supported by the US Government agencies. He served as a senior visiting scientist at the US Air Force Research Laboratory, and as a member of expert panels at the international conferences, and panels organized by the US Government bodies. Prof. Kovalerchuk regularly teach classes on AI, Data Mining, Machine Learning, Information and Data Visualization, Visual Knowledge Discovery at Central Washington University. He also have been teaching these topics at several other Universities in the US and abroad. Dr. Kovalerchuk delivered relevant tutorials at IJCNN 2017, HCII 2018, KDD 2019, ODSC West 2019; WSDM 2020.
Basarab Matei
Laboratoire d'Informatique de Paris Nord, Université Sorbonne Paris Nord, France
Basarab Matei received his HdR (Ability to direct research) degree from Sorbonne Paris Nord University in 2011 and PhD degree in 2001 from Paris 6 University both in Applied Mathematics. He is currently Associate Professor in Computer Science at Sorbonne Paris Nord University. His research is with the A3 team from LIPN Laboratory. His research interests include Unsupervised Learning within Optimal Transport Theory, Transfer Learning, Dimensionality reduction, Representation Learning, Matrix Factorization and content-based information retrieval, Quantum Machine Learning. Basarab published 4 book chapters, 27 peer-reviewed journal papers and more than 30 international conference papers. Basarab Matei co-supervised 2 post-doctorants, 5 PhD students and supervises each year 1-2 Master2 internship.
Parisa Rastin
Department of Applied Mathematics, École nationale supérieure des mines, Nancy, France
Parisa Rastin received her Ph.D. in computer science from the University of Sorbonne Paris Nord. She is currently an associate professor at the University of Lorraine, École nationale supérieure des mines de Nancy. Her main research interests are in the area of data mining, more specifically in unsupervised learning adapted to dynamic and complex data, with applications to text mining, data flow analysis and recommendation systems. Parisa has published 2 papers in peer-reviewed journals and over 22 papers in international conferences. Parisa Rastin currently co-supervises 3 PhD students and supervises 3-4 engineering projects and 1 master internship each year.
Nicoleta Rogovschi
Laboratory of Informatics Paris Descartes (LIPADE), Paris Descartes University, France
Nicoleta Rogovschi received her Master of Computer Science degree from Paris 13 University in 2006 in Machine Learning. She is currently an Associate Professor in Computer Science at the Paris Descartes University. She completed her Ph.D. in Computer Science (Probabilistic Unsupervised Learning) in 2009 in the Computer Science Laboratory of Paris 13 University and the HdR (Ability to direct research) in 2021 at Sorbonne Paris Nord University. She’s research is with the Data Mining (GFD) Team. Her research interests include Probabilistic Learning, Unsupervised Learning, Clustering and Co-Clustering methods for different types of data in different contextes : anonymization, recommender system, opinion detection,... She is also a member of EGC, AFIA, IEEE, INNS, INNS AML group. Nicoleta Rogovschi codirected 5 PhD students and tens of Master Research students.
Lab Instructors
Bogdan Musat
Amazon, Romania and Transilvania University, Brasov, Romania
Bogdan Musat is an Applied Scientist at Amazon and a PhD student in the field of Artificial Intelligence at Transilvania University of Brasov. He received his B.Sc. and M.Sc. in Computer Science from Transilvania University of Brasov in 2015, respectively in 2017. His research interests drove his throughout the years into areas like time series analysis, natural language processing, computer vision, efficient neural network deployment and reinforcement learning.
Andrew Dunn
OpenEye, Spokane, Washington, USA
Andrew Dunn is a Software Engineer at OpenEye in Spokane, Washington, USA and is a Masters student at Central Washington University of Ellensburg. He received his B.Sc in Computer Science from Central Washington University in 2019. His research interests are in Machine Learning and Natural Language Processing.