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Invited Speakers


Assoc. Prof. Ismail Bennis
University of Haute Alsace, France

Ismail Bennis earned in 2009 a bachelor’s degree in mathematics and computer science from the Université Mohammed V in Rabat, Morocco. 2011, he received a master’s degree in Computer Networks and Telecommunications from the same university. He completed his PhD in 2015 under joint supervision between the Université Mohamed V in Rabat, Morocco and the Université de Reims Champagne-Ardenne in France. From 2015 to 2017, he worked as a temporary professor for research and teaching (A.T.E.R) at the University of Reims. Between 2017 and 2020, he worked as an associate professor at La Rochelle University. His research interests include routing protocols with quality of service over wireless sensor networks, IoT and outlier detection. Since September 2020, he has worked as an associate professor at the University of Haute Alsace.

Speech Title: "Network Anomaly Detection in IoT: Challenges and Recent Approaches"

Abstract: Wireless Sensor Networks (WSNs), and more generally, the Internet of Things (IoT), are widely used to gather information and monitor the environment in various applications, such as medical, agricultural, manufacturing, and military. The goal is to transmit data from sensors to the base station. However, this data is susceptible to outliers, which can occur due to the sensor nodes themselves or the harsh environment in which they are deployed. Therefore, WSNs must detect outliers and take action to ensure data Quality of Service (QoS) in terms of reliability and accuracy, as well as prevent further degradation of application efficiency. This need has resulted in many research efforts to propose efficient outlier detection and classification solutions and improve the performance of existing ones. The challenge is detecting outliers and classifying them as errors to be ignored or important events requiring further action. This talk will discuss enhanced and effective outlier detection and classification approaches for WSNs. The enhancement tackles the clustering, outlier detection, and classification phases.



Assoc. Prof. Mario Konecki
University of Zagreb, Croatia

Associate Professor Mario Konecki, Ph.D. is a former special advisor to the rector of the University of Zagreb for Internet services and international cooperation, and coordinator of the Croatian Rectors' Conference for information technology. He teaches at the Faculty of Organization and Informatics in Croatia, and is the author or co-author of more than 100 scientific and professional papers. He has been awarded with 7 best paper awards, and has worked on a number of scientific and professional projects. He is active in the fields of education, computer games, virtual reality, augmented reality, artificial intelligence, programming, assistive technologies, design and entrepreneurship.

Speech Title: The Role of Virtual Reality, Artificial Intelligence and other New Technologies in Modern Society

Abstract: Society as a concept is experiencing everlasting change, and the latest one comes in the form of new technologies, such as virtual reality, artificial intelligence etc. At this point it is important to understand the technology that is available, and its role in modern society, as well as implications of consequential paradigm shifts. Various domains of new technology application need to be analyzed and consequent changes need to be understood.


Dr. Lovell Hodge
Munich Re, Canada

Dr. Lovell Hodge is currently the Vice President of Data and Adaptive Intelligence at Munich Re. As part of the North American Integrated Analytics team, Lovell's mandate includes the implementation of AI capabilities to support the Digital Transformation strategy of the North American Life and Health group. Lovell holds Bachelor and Masters Degrees in Computer Science and a Ph.D. in Systems Design Engineering, majoring in Artificial Intelligence, from the University of Waterloo. A former researcher and lecturer at the University of Waterloo, his areas of focus included Data and Knowledge Based Systems, Artificial Neural Networks, Intelligent Multi-Agent systems, Fuzzy Logic and Genetic Algorithms. Lovell has authored several papers in Journals such as IEEE Transactions on Systems, Man and Cybernetics, International Joint Conference on Neural Networks and the International Conference on Computer Science and Information Technology. He has over 25 years experiences in Information Technology and AI, spanning academia as well as the banking, insurance and health industries and is an experienced executive. He has developed several advanced AI solutions for fraud detection, pattern recognition, cancer recognition, customer profiling, multi agent coordination and medical rule- based decision support systems. Lovell has also implemented large scale data warehouses both on premises and cloud based for the financial and insurance industries and holds a US patent on a novel method for processing encrypted data with ML models.



Prof. Arti Arya
PES University, India

Dr. Arti Arya has completed her BSc (Mathematics Hons) in 1994 and MSc (Mathematics) in 1996 from Delhi University. She completed her MTech (CSE) from Allahabad Agricultural University and the Doctorate of Philosophy in Computer Science Engineering from Faculty of Technology and Engineering, Mahrishi Dayanand University, Rohtak, Haryana in 2009. She was working as Professor and Head of MCA dept in PESIT, Bangalore South Campus till Aug 2020 and currently serving as Professor in Computer Science Engg. Dept. in PES University since Aug 2020. She has 23+ years of experience in academics, out of which 17 yrs is of research as well. Her areas of interest include Spatial Data Mining, NLP, Machine Learning, Artificial Intelligence, Graph Neural Networks, Generative AI, Unstructured Data Management, Applied Numerical Methods, and Biostatistics. She is a Member of ACM, life member of CSI and Senior Member IEEE. She is on the reviewer board of many reputed International Journals like SNAM (Springer, Scopus indexed), IJCDS(Scopus indexed) to name a few. She has around 70+ publications in various reputed International Conferences and Journals. She has guided 2 PhDs in Machine Learning and Spatial Data mining and currently guiding 3 candidates in the area of NLP and Machine and Deep learning. Rest details can be found on https://



Assoc. Prof. Rajasekar Mohan
PES University, India

Assoc. Prof. Rajasekar Mohan is currently an Associate Professor in Dept of ECE, PES University, a private University in Bangalore, India. He is actively pursuing research in the domain of wireless communications. His keen interest lies in developing novel neural network models for predicting and optimizing performance of high-density wireless local area networks. His other research interests include embedded systems, IoT, robotics and application of ML in communication. He is alumnus of Indian Institute of Technology, Madras, India. He has served in the Indian Air Force for over 24 years in various technology roles in the field of communication. He has published several articles in Journals and conferences in the domains of IoT, Robotics and Wireless Communication.