MVML 2018 will be held in Madrid, Spain on August 21 - 23, 2018.
Best Paper Award:
Two best paper awards will be conferred to author(s) of the papers that receive the highest rank during the peer-review and by the respected session chairs. Please visit Paper Submission for more information.
Become a Sponsor or an Exhibitor
MVML attracts a wide range of researchers in the field of biomedical engineering and systems. As a prominent company in the field of biomedical engineering and systems, we would like to offer you an exhibit at MVML. Please visit Sponsors for more information.
We are very happy to announce the following keynote speakers for the 4th International Conference on Machine Vision and Machine Learning (MVML'18):
University of Ottawa, Canada
University of Massachusetts, Lowell, USA
University of British Columbia, Canada
Dr. Robert Laganière
Robert Laganière is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa. He is also a Faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content-based video analysis, visual surveillance, driver-assistance, object detection and tracking. Robert authored the OpenCV Computer Vision Application Programming Cookbook (Packt pub. 3rd ed. 2017) and co-authored Object Oriented Software Development (McGraw Hill 2001). He co-founded Visual Cortek in 2006, an Ottawa-based video analytics startup that was later acquired in 2009 by iWatchLife.com, a cloud-based video monitoring company. He is also a consultant in computer vision and has been Chief Scientist in a number of startups companies such as Cognivue Corp, an embedded vision semiconductors company acquired by NXP in 2016. In 2016, Robert founded Tempo Analytics, a startup company proposing retail analytics solutions. Robert has a Bachelor of Electrical Engineering degree from Ecole Polytechnique in Montreal (1987) and M.Sc. and Ph.D. degrees from INRS-Telecommunications, Montreal (1996).
Topic of Keynote: Putting Machine Vision and Machine Learning at Work in Human Monitoring Applications
Dr. Dalila B. Megherbi
Dr. Dalila B. Megherbi received the Sc.M in Electrical and Computer Engineering, the Sc.M in Applied Mathematics, and the Ph.D in Electrical and Computer Engineering from Brown University, Providence, RI, USA. Dr. Megherbi is a faculty of Electrical and Computer Engineering at the University of Massachusetts, Lowell. She is the founder and Director of the research Center for Computer Machine/Human Intelligence Networking and Distributed Systems (CMINDS). Her research is internationally recognized. Since joining UMass Lowell, Dr. Megherbi holds more than 110 refereed peer-reviewed publication articles, including in the IEEE and the prestigious Nature Biotechnology (impact factor 41.667). She holds US patent. At UMass Lowell, she has been the recipient of numerous research grants and contracts, as the primary lead principal investigator, from several federal agencies and the industry, including, DoD AFRL/WPAB, NSF, US FDA, NIH, Raytheon Air Missile Defense Systems, Xilinx Inc., Structural Dynamics Research Corporation, SUN Microsystems, Altera Inc., and Sky Computers Inc. She graduated more than 30 graduate students Ph.D. and MS students with a thesis option. She serves as associate editor and member of the editorial boards and reviewer for a dozen of journals, including IEEE transactions. She has been invited to organize/TPC/session chair, and to speak at several national and international conferences. She has been invited to serve on national and international peer review boards including, NSF, NIH, NASA, and National Science Foundation of Ireland. She has been the recipient of several research and teaching awards, including the recipient of the Best Paper Award of all conference tracks at the IEEE International Conference on Homeland Security, the recipient of the IEEE Control Systems Society CDC Best Paper Finalist Award, the recipient of the Best Paper Award at the IEEE international conference ROMA, the recipient of the Top Professor Award for Outstanding Academic Integrity Leadership and Service to the students, the recipient of several university of Massachusetts Lowell Outstanding Teaching Excellence Awards, the recipient, each year since this recognition award was initiated in 2010, of 6 UMass Lowell Annual Research and Scholarship Recognition Awards, in recognition of faculty with extensive scholarship during that year. She has been a member of an international project consortium led by the US FDA. She was invited, interviewed and quoted in the New York Times for her expertise in big data facial recognition for homeland security applications. She was contacted by major national and international news agencies for her work and expertise in big data and facial recognition for homeland security. She was invited, interviewed and featured by the Science News Radio Network for her expertise in Artificial Intelligence and Big Data technologies applied to Weapons of Mass Destruction. Her primary current research interests are in computational machine vision and intelligence, deep learning, “Big data” analytics, knowledge extraction/representation, and adaptive learning systems in distributed computing systems and networks, with applications to homeland security and the life sciences (high throughput meta-genomics). Her main research goal is the understanding of and building sensor-based machines that can be made to exhibit intelligence. The idea is to build intelligent machines/sensors and to understand certain aspects of human and animal biological intelligence.
Topic of Keynote: Machine Learning Based Analysis of the Effects of Image Transformation and Partial Information on Face Recognition with Time-Varying Expressions for Homeland Security Applications.Keynote Abstract
Dr. Zheng Liu
Dr. Zheng Liu received his first doctorate in engineering from Kyoto University (Japan) in 2000 and earned a second Ph.D. in electrical engineering from the University of Ottawa in 2007. From 2000 to 2001, he was a research fellow with the control and instrumentation division of Nanyang Technological University, Singapore. He joined the Institute for Aerospace Research of National Research Council Canada (NRCC, Ottawa) as an NSERC governmental laboratory visiting fellow in 2001. From 2002 to 2012, he served as a research officer for NRCC. From 2012 to 2015, Dr. Liu worked for the Toyota Technological Institute (Nagoya, Japan) as a full professor. In 2015 fall, he returned to Canada and joined the University of British Columbia Okanagan and established the “Intelligent Sensing, Diagnostics, and Prognostics Research Lab.” He is currently an associate professor at the School of Engineering.
Dr. Liu is serving the editorial boards for five peer-reviewed journals, including IEEE Transactions on Instrumentation and Measurement, IEEE Instrumentation and Measurement Magazine, Information Fusion, Machine Vision and Applications, and Intelligent Industrial Systems. He also served as a reviewer for numerous funding agencies, journals, conferences, and publishers. He is a senior member of IEEE and member of SPIE and holds the professional engineer license in both British Columbia and Ontario.
Dr. Liu’s research focuses on data/information fusion, computer vision, machine learning, sensor techniques, structural health monitoring, non-destructive inspection, and prognostic health management. He received three best conference paper awards and participated numerous research projects with government agencies, industries, academic units, and research organizations.
Topic of Keynote: Information Fusion for Environmental Perception and Situation AwarenessKeynote Abstract