Houbing Herbert Song (M’12–SM’14) received the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in August 2012.
In August 2017, he joined the Department of Electrical Engineering and Computer Science, Embry-Riddle Aeronautical University, Daytona Beach, FL, where he is currently a Tenured Associate Professor and the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab, www.SONGLab.us). SONG Lab graduates work in a variety of companies and universities. Those seeking academic positions have been hired as tenure-track assistant professors at US universities like Auburn University, Bowling Green State University, and University of Tennessee. He has served as an Associate Technical Editor for IEEE Communications Magazine (2017-present), an Associate Editor for IEEE Internet of Things Journal (2020-present), IEEE Transactions on Intelligent Transportation Systems (2021-present), and IEEE Journal on Miniaturization for Air and Space Systems (J-MASS) (2020-present), and a Guest Editor for IEEE Journal on Selected Areas in Communications (J-SAC), IEEE Internet of Things Journal, IEEE Network, IEEE Transactions on Industrial Informatics, IEEE Sensors Journal, IEEE Transactions on Intelligent Transportation Systems, and IEEE Journal of Biomedical and Health Informatics. He is the editor of eight books, including Aviation Cybersecurity: Foundations, principles, and applications, Scitech Publishing, 2022, Smart Transportation: AI Enabled Mobility and Autonomous Driving, CRC Press, 2021, Big Data Analytics for Cyber-Physical Systems: Machine Learning for the Internet of Things, Elsevier, 2019, Smart Cities: Foundations, Principles and Applications, Hoboken, NJ: Wiley, 2017, Security and Privacy in Cyber-Physical Systems: Foundations, Principles and Applications, Chichester, UK: Wiley-IEEE Press, 2017, Cyber-Physical Systems: Foundations, Principles and Applications, Boston, MA: Academic Press, 2016, and Industrial Internet of Things: Cybermanufacturing Systems, Cham, Switzerland: Springer, 2016. He is the author of more than 100 articles and the inventor of 2 patents (US & WO). His research interests include cyber-physical systems/internet of things, cybersecurity and privacy, AI/machine learning/big data analytics, edge computing, unmanned aircraft systems, connected vehicle, smart and connected health, and wireless communications and networking. His research has been sponsored by federal agencies (including National Science Foundation, US Department of Transportation, Federal Aviation Administration, Air Force Office of Scientific Research, US Department of Defense, and Air Force Research Laboratory) and industry. His research has been featured by popular news media outlets, including IEEE GlobalSpec's Engineering360, Association for Uncrewed Vehicle Systems International (AUVSI), Security Magazine, CXOTech Magazine, Fox News, U.S. News & World Report, The Washington Times, New Atlas, Battle Space, and Defense Daily.
Dr. Song is a senior member of IEEE and ACM, and an ACM Distinguished Speaker. Dr. Song is a Highly Cited Researcher identified by Clarivate™ (2021) and a Top 1000 Computer Scientist identified by Research.com. Dr. Song was a recipient of the Best Paper Award from the 12th IEEE International Conference on Cyber, Physical and Social Computing (CPSCom-2019), the Best Paper Award from the 2nd IEEE International Conference on Industrial Internet (ICII 2019), the Best Paper Award from the 19th Integrated Communication, Navigation and Surveillance technologies (ICNS 2019) Conference, the Best Paper Award from the 6th IEEE International Conference on Cloud and Big Data Computing (CBDCom 2020), the Best Paper Award from the 15th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2020), the Best Paper Award from the 40th Digital Avionics Systems Conference (DASC 2021), the Best Paper Award from 2021 IEEE Global Communications Conference (GLOBECOM 2021) and the Best Paper Award from 2022 IEEE International Conference on Computer Communications (IEEE INFOCOM 2022).
Jerry Chun-Wei Lin currently serves as a full professor in the Department of Computer Science, Electrical Engineering and Mathematical Sciences at Western Norway University of Applied Sciences in Bergen, Norway. He has published more than 500 research papers in peer-reviewed journals (more than 70 ACM/IEEE journals) and international conferences. His research interests include data mining, soft computing, deep learning/machine learning, security and privacy, optimization, fintech, and IoT applications. He is Editor-in-Chief of the Data Science and Pattern Recognition (DSPR) journal, Associate Editor for 11 SCI journals including IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), IEEE Transactions on Cybernetics (IEEE TCYB), Information Sciences (INS) and others. He has served as a guest editor for more than 60 SCI journals, including some top-tier journals in ACM and IEEE, e.g., ACM TOIT, ACM TALLIP, ACM TMIS, ACM JDIQ, IEEE JBHI, IEEE TII, IEEE TFS and IEEE TITS. He is the co-leader of the well-known SPMF project, which provides more than 200 data mining algorithms and has been cited in many different applications (about 1000 citations). He was also recognized as the most cited Chinese researcher by Elsevier/Scopus in 2018, 2019, 2020, and 2021, and as a top-2% scientist in 2020 and 2021 by the report of the Stanford University. He was also recognized as one of the top-10 most productive researchers in Norway in 2021. He is a Fellow of IET (FIET), ACM Distinguished Scientist, and IEEE Senior Member.
Yaroslav D. Sergeyev is Distinguished Professor at the University of Calabria, Italy (professorship awarded by the Italian Government) and Head of Numerical Calculus Laboratory at the same university. He is also Member of the University International Council and Professor (part-time contract) at Lobachevsky Nizhniy Novgorod State University, Russia, Affiliated Researcher at the Institute of High Performance Computing and Networking of the Italian National Research Council, and Affiliated Faculty at the Center for Applied Optimization, University of Florida, Gainesville, USA.
He was awarded his Ph.D. (1990) from Lobachevski Gorky State University and his D.Sc. degree (1996) from Lomonosov State University, Moscow (this degree is Habilitation for the Full Professorship in Russian universities). In 2013, he was awarded Degree of Honorary Doctor from Glushkov Institute of Cybernetics of The National Academy of Sciences of Ukraine, Kiev.
His research interests include numerical analysis, global optimization (he was President of the International Society of Global Optimization, 2017-2021), infinity computing and calculus (the field that he has founded), philosophy of computations, set theory, number theory, fractals, parallel computing, and interval analysis. Prof. Sergeyev is included in the lists “Top Italian Mathematicians” and “Top Italian Computer Scientists”. He was awarded several research prizes (Khwarizmi International Award, 2017; Pythagoras International Prize in Mathematics, 2010; EUROPT Fellow, 2016; Outstanding Achievement Award from the 2015 World Congress in Computer Science, Computer Engineering, and Applied Computing, USA; Honorary Fellowship, the highest distinction of the European Society of Computational Methods in Sciences, Engineering and Technology, 2015; The 2014 Journal of Global Optimization (Springer) Best Paper Award; Lagrange Lecture, Turin University, Italy, 2010; MAIK Prize for the best scientific monograph published in Russian, Moscow, 2008, etc.). In 2020, he was elected corresponding member of Accademia Peloritana dei Pericolanti in Messina, Italy. In 2020 and 2021, he was included in the rating “Highly cited authors in Scopus”.
His list of publications contains more than 250 items (among them 6 books). He is a member of editorial boards of 12 international and 3 national journals and co-editor of 11 special issues. He delivered more than 70 plenary and keynote lectures at prestigious international congresses. He was (Co-)Chairman of 11 international conferences and a member of Scientific Committees of more than 60 international congresses. He is Coordinator of numerous national and international research and educational projects. Software developed under his supervision is used in more than 40 countries of the world. Numerous magazines, newspapers, TV and radio channels have dedicated a lot of space to his research.
Daniela Cardone obtained a Master's Degree in Biomedical Engineering at the La Sapienza
University of Rome in 2009. In 2013, she obtained the title of Ph.D. in Neuroscience and
Neuroimaging at the University "G. d’Annunzio "of Chieti-Pescara.
Since June 2021, she has the role of Research Fellow, Senior Research at the Department of
Engineering and Geology of the University of "G. d’Annunzio "of Chieti-Pescara.
Her research work mainly concerns the development of processing methods and analysis of
images and physiological signals, of various nature. Her main activity concerns, in particular,
thermal infrared (IR) imaging. In this context, she developed real-time tracking algorithms for
specific areas of interest and IR image morphing methods on anatomical templates. She also
dealt with the realization of image fusion algorithms between visible and thermal images.
More recently, her research has focused on affective computing and human-machine
interaction, with particular reference to the automotive research field and assistive robotics.
Robert Plana has been Professor at Paul Sabatier University in Toulouse and at the Institut Universitaire de France in the field of Internet of Things Technologies. He has occupied numerous top management positions at CNRS, National Research Agency and Ministry of higher education and research. In the private sector, he has been working with a startup (SiGe Microsystems) as Senior Technology Leader, with Alstom as Open Innovation Director and with GE as the CTO and Ecosystem Director of the GE Digital Services for Europe. He is now the Chief Technology Officer of ASSYSTEM Group in charge of the Innovation strategy and leading the program “Engineering Powered by digital services”. He is pioneering the convergence between Big Data, Artificial Intelligence and Advanced System Engineering for mission critical Infrastructures.
4x TEDx speaker, MIT alum, YouTube creator. Globally recognized corporate consultant and scientific
advisor at AgnisStibe.com. Offers an authentic science-driven STIBE method and practical tools for
hyper-performance. Artificial Intelligence Program Director and Professor of Transformation at EM
Normandie Business School. Paris Lead of Silicon Valley founded Transformative Technology
community. At the renowned Massachusetts Institute of Technology, he established research
on persuasive cities for sustainable wellbeing. His change method is helping millions to gain
confidence and build resilience against everyday circumstances. It will help you achieving stressless
hyper-performance at work and certainty in life. Within this vision, business acceleration and societal
wellbeing can be achieved through purposefully designed innovations that successfully blend
technological advancements with human nature.
David Perpetuini graduated in Biomedical Engineering from the Marche Polytechnic University of Ancona in 2012. In 2018, he obtained the title of Ph.D. in Neuroscience and Neuroimaging at the University "G. d'Annunzio" of Chieti-Pescara with a final dissertation entitled:" Complexity analysis of fNIRS signal: validation and clinical applications ". Part of the Ph.D.'s research work was carried out at the Department of Biomedical Engineering and Medical Physics of the University College of London (UCL) and at the Institute of Cognitive Neuroscience (ICN) in London. Since 2018 he has been a post-doctoral researcher at the Department of Neuroscience, Imaging and Clinical Sciences of the University "G. d’Annunzio " of Chieti-Pescara. His research work mainly concerns the study of brain activity through functional near-infrared spectroscopy (fNIRS), particularly in Alzheimer's disease patients, employing machine learning and artificial intelligence techniques. Moreover, he develops algorithms for the detection of the autonomic nervous system activity by means of functional thermal imaging and he investigates the state of vascular aging using photoplethysmography.
Malak BOURDOUANE studied a BBA in UMV in Morocco, passionate about customer relationship management, and with a decade of professional experience in different sectors, she has occupied numerous management positions in Morocco and Turkey in different international companies, managing international sales and business development from East to West with her multi languages capacities. She is currently working in one of the most famous Industrial IoT Companies that is based in the US as a Partnership Director where she learned and made her way in the IoT World by creating and managing the strong relationship with the company’s customers and partners, as she always said “ the best Marketing way it’s not only #Satisfied Customer But also a #Satisfied Partner because we should always support our partners in every term”
Within the IIoT World, she learned the efficiency of being agile, predictive, and monitoring in Industry 4.0 and how we can implement it in different industries.
Lecturer and researcher and algorithm developer in the fields of, artificial and business intelligence, computer vision, and big data. My inventions lie at the core current Artificial Intelligence systems and lead several projects from the industry. I’m senior lecturer at the Max Stern Yezreel Valley College.
My main research interests are data mining, big data, and business analytics, dealing mainly with clustering, non-parametric statistics, and algorithms for approximate nearest neighbor search.
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