Plenary and Keynote Speakers

Dr. Dalila B. Megherbi
University of Massachusetts Lowell, USA
Keynote Speaker

Dalila B. Megherbi obtained her Diplome Ingenieur d’Etat in Computer Engineering from the Ecole Nationale Polytechnique with the highest honors, received the Sc.M in Computer Engineering, the Sc.M in Applied Mathematics, and the Ph.D. in Electrical and Computer Engineering from Brown University. After working in the industry, including in the defense industry, she joined academia and joined the Department of Electrical and Computer Engineering at the University of Massachusetts Lowell, where she is currently a tenured faculty and the Director of the Research Center for Computer Machine/Human Intelligence Networking and Distributed Systems (CMINDS) that she founded, (https://www.uml.edu/Research/CMINDS/). Her research is internationally recognized. She holds more than >140 refereed peer-reviewed publication articles, including in the IEEE and the prestigious Nature Biotechnology. She holds US patent. 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/Oracle, Altera Inc., and Sky Computers Inc. She graduated more than 42 UML graduate Ph.D. and MS thesis option students. She serves as associate editor and member of the editorial boards and reviewer for a dozen of journals, including IEEE transactions. She was invited to serve as a General Chair for the 2018 IEEE CIVEMSA International Conference. She has been invited to organize/TPC/session chair and to speak (keynote speaker) at several national and international conferences. She has been invited to serve on national and international peer review boards, including NSF, NIH, NASA, National Science Foundation of Ireland, and Czech Science Foundation Research. She has been the recipient of numerous 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 Best Paper Award at the IEEE international conference CIVEMSA, 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 of several UML Annual Research and Scholarship Recognition Awards, in recognition of faculty with an 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 Times for her expertise in big data facial recognition for homeland security applications. Major national and international news agencies contacted her 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. She is an invited member of several honorary Societies, including Sigma Xi, Brown Chapter, New York Academy of Science, and the American Society for the Advancement of Science. Her primary research interests are Computational Machine Intelligence, Machine and Deep Learning, Digital Image processing & Computer Vision, “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 understanding 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: The importance of Integration of AI, Brain Neuro-Imaging Machine Vision, Peripheral Blood Gene Expressions, and Genomics for Better Prognosis and Diagnosis Predictions of Alzheimer's Disease
Keynote Abstract