Research Collaborators
Department of Mechanical, Automotive & Materials Engineering,
Department of Mathematics & Statistics,
University of Windsor
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Dr. Ron Barron is Professor Emeritus in the Department of Mathematics & Statistics and an Adjunct Professor in the Department of Mechanical, Automotive & Materials Engineering, University of Windsor. He holds BA and MSc degrees in Mathematics from University of Windsor, PhD degree in Mathematics from Carleton University and MSc in Engineering from Stanford University.
His research spans across several disciplines, notably applied mathematics, mechanical engineering, civil engineering, computer science and physics, focusing on Computational Fluid Dynamics (CFD) and Numerical Heat Transfer (NHT), with special interest in software development and industrial applications. Industrial collaborations include joint research projects in the automotive, oil and gas, solar, food processing, greenhouse, manufacturing, electronics cooling and injection mold sectors. Recently, he has supported two research projects involving machine learning and fluid flow predictions.
He has supervised approximately 80 graduate students and postdoctoral researchers, and mentored more than 50 undergraduate research students from mathematics, physics, computer science, mechanical engineering, aerospace engineering and electrical engineering. He has published more than 300 journal and conference papers, 17 technical reports and holds several patents.
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School of Computer Science, University of Windsor
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Dr. Samet is a faculty member at the School of Computer Science, University of Windsor, and an adjunct professor at the e-Health Research Unit, Faculty of Medicine, Memorial University, where he was an assistant professor from 2012 to 2017.
His research interests and activities are in privacy-preserving and security aspects of various applications, especially in health sector, and health informatics. Prior to that, he was a Post-Doctoral Fellow at the e-Health Information Laboratory at the Children Hospital of Eastern Ontario Research Institute from 2010 to 2012. During his post-doc fellowship, he designed and developed several secure protocols for various health applications.
He received his Ph.D. in Computer Science from the University of Ottawa in 2010 and his thesis title was "Privacy-Preserving Data Mining", in which he proposed and designed some protocols on privacy-preserving methods for standard data mining and machine learning techniques.
School of Computer Science, University of Windsor
Dr. Gras is Professor at the School of Computer Science of the University of Windsor and Chief Science Officer at Movyl Technologies and MVYL Associates (San Francisco). He holds a Canada Research Chair in Learning and Simulation for Theoretical Biology from 2007 to 2017. He was Invited Senior Scientist at the INRIA, France, in 2005-06 and he was senior scientist, from 1998 to 2004, at the Swiss Institute of Bioinformatics, Geneva Switzerland. Dr. Gras earned a Ph.D. in computer science at the University of Rennes, France, in 1997 and a Habilitation a Diriger la Recherche in 2004 at the same institution. From 2000 to 2002 he also was consultant for GeneProt Inc. and Geneprot S.A., Geneva, Switzerland.
Dr. Gras research interests involve artificial intelligence, deep learning, machine learning, natural language processing, artificial life, theoretical biology, ecological modelling, bioinformatics, and combinatorial optimization. He has published over 100 articles in top tier journals/conferences.
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