Innovations in Information and Communication Technologies

Prof. Neeraj Kumar (SMIEEE) (2019, 2020 highly-cited researcher from WoS) is working as a Full Professor in the Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology (Deemed to be University), Patiala (Pb.), India.  He is also adjunct professor at Asia University, Taiwan, King Abdul Aziz University, Jeddah, Saudi Arabia and Charles Darwin University, Australia. He has published more than 400 technical research papers in top-cited journals and conferences which are cited more than 18000 times from well-known researchers across the globe with current h-index of 74. He is highly cited researcher in 2019 in the list released by Web of Science (WoS). He has guided many research scholars leading to Ph.D. and M.E./M.Tech. His research is supported by funding from various competitive agencies across the globe.  His broad research areas are Green computing and Network management, IoT, Big Data Analytics, Deep learning and cyber-security. He hasalso edited/authored 10 books with International/National Publishers like IET, Springer, Elsevier, CRC. Security and Privacy of Electronic Healthcare Records: Concepts, paradigms and solutions (ISBN-13: 978-1-78561-898-7), Machine Learning for cognitive IoT, CRC Press,  Blockchain, Big Data and Machine learning, CRC Press,  Blockchain Technologies across industrial vertical, Elsevier, Multimedia Big Data Computing for IoT Applications: Concepts, Paradigms and Solutions (ISBN: 978-981-13-8759-3), Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019) (ISBN 978-981-15-3369-3). Probabilistic Data Structures for Blockchain based IoT Applications, CRC Press.  One of the edited text-book entitled, "Multimedia Big Data Computing for IoT Applications: Concepts, Paradigms, and Solutions” published in Springer in 2019 is having 3.5 million downloads till 06 June 2020. It attracts attention of the researchers across the globe.  He is serving as editors of ACM Computing Survey, IEEE Transactions on Sustainable Computing, IEEE Systems Journal, IEEE Network Magazine, IEEE Communication Magazine, Elsevier Journal of Networks and Computer Applications, Elsevier Computer Communication, Wiley International Journal of Communication Systems. Also, he has organized various special issues of journals of repute from IEEE, Elsevier, Springer.  He has been a workshop chair at IEEE Globecom 2018, IEEE Infocom 2020 and IEEE ICC 2020   and track chair of Security and privacy of IEEE MSN 2020. He is also TPC Chair and member for various International conferences such as IEEE MASS 2020, IEEE MSN2020. He has won the best papers award from IEEE Systems Journal and IEEE ICC 2018, Kansas-city in 2018. He won the best researcher award from parent organization every year from last eight consecutive years.Dr Rahat Iqbal is a senior academic with 20 years’ experience in industrial and academic roles. His main research interests lie in Big Data Analytics, Internet of Things (IoT), Information Retrieval, Artificial Intelligence and Energy Efficient Communication Protocols. He is leading the Research Group in Big Data and IoT in the Institute for Future Transport and Cities. Dr Iqbal has supervised to completion 17 PhD students.  He serves on programme committee and advisory committee of many international conferences and journals. He has published more 130 papers in international journals, conferences, book chapters and workshops.  He has also co-invented 5 patents relating to biologically inspired deep machine learning approaches for fault detection & isolation, route optimisation and monitoring driving. Dr Iqbal is a principle investigator on a 3.5-year PhD project (£104,892) titled "Urban flood monitoring and forecasting" funded by EIT Digital and UK Industrial partner (2021-2025). Dr Iqbal is a principle investigator on a 3.5-year PhD project (£104,892) titled "Passenger profiling for autonomous car using AI / machine learning" funded by EIT Digital and UK Industrial partner (2021-2025). Dr Iqbal is a principle investigator on a 2-year project (£105,310) titled “Digital Connected and Autonomous Vehicle Proving Ground (DIGICAV)”funded by Innovate UK in partnership with HORIBA MIRA (2019-2020).DIGICAV. Dr Iqbal is a principle investigator on a two-year project (£750,000) titled “Flood Ultra-Cognitive Dendrite (FLUD)” funded by Innovate UK and PlaTcom Venturs, Malaysia under the Technology Programme “Newton fund: UK-Malaysia urban Innovation Challenge 2017 Competition for funding. Dr Iqbal is a principle investigator for knowledge transfer partnership and spin-out company, a supplier of high-tech intelligent data-driven solutions. He is seconded to work as CEO at Interactive Coventry Limited. Dr Iqbal was principle investigator on a one-year project (2012-2013) “Driver’s intent prediction: self-learning car initiative” funded (£49,301) by Technology Strategy Board funded in collaboration with Jaguar Land Rover Ltd. From 2013 – 2015, Dr Iqbal worked on a number of Knowledge Exchange and Enterprise Network (KEEN) projects in collaboration with Infinity Wireless Ltd, Modus IT Ltd to develop high-tech solutions relating to data recovery apps and big data analytics for businesses. He was principle investigator on a two-year project (2011-2013) “Development of an innovation teaching tool using web/mobile and service oriented technologies” funded by Technology Strategy Board Project in collaboration with Currant limited. From 2009 - 2013, he was principle investigator for an EPSRC funded (£85,052) project titled “Task Sensitive Search Recommender System Based on Relevance Feedback”. The project was carried out in collaboration with Trinity Expert Systems. From 2007 – 2009, Dr Iqbal was involved in a number of projects to introduce novel teaching, learning and assessment methods. These projects were funded by Coventry University,CILASS: Centre for Inquiry-based Learning in the Arts and Social Sciences, University of Sheffield. Also over this period, he was involved in a number of industrial consultation activities. Dr Iqbal was also involved in the project management and development of the EU FP7 project CHIL (Computers in Human Interaction Loop) at the Technical University of Eindhoven, Netherlands. Suneet Kumar Gupta is a faculty in the Department of Computer Science Engineering at Bennett University, Gr. Noida. His current research interests are Wireless Sensor Network, Internet of Things, Natural Language Processing and Brain-Computer Interaction. Presently Dr.  Gupta is working on a Wireless Sensor Network based project funded by Department of Science and Technology, Uttar Pradesh. Dr. Gupta is the reviewer of many international journals i.e. Computer Network, Wireless Personal Communication, Information Science, IEEE Transactions etc. Dr. Gupta is also part of a project fundedby the Royal Academy of Science London entitled with Leadingindia.ai. Under this project, Dr. Gupta has organized 70 workshops on Deep Learning and Internet of Things (IoT). He has more than 50 research articles, authored 2 books and 2 book chapters in his account. Dr Deepak Garg is Director of leadingindia.ai  (Leading the Change in Institutions for Excellence); Chair, Computer Science and Engineering, Bennett University and Director, NVIDIA-Bennett Center of Research on Artificial Intelligence. He is leading the largest Development, Skilling and Research initiative in AI in India with more than 1000 institutional collaborators. He is a chief consultant for algorithmguru.in. He has done his Ph.D. in efficient algorithm design in 2006. He served as chair of IEEE Computer Society, India IEEE Education Society (2013-15). He has handled funding of around INR 700 million including RAENG, UK on MOOCs, Machine Learning and AI. He has 100+ publications with 850+ citations and Google h-index of 17. In his 20 years of experience he has delivered 300+ invited talks and conducted 100+ Workshops and 15+ Conferences across the country. He has Supervised 13 Ph.D. and 35 PG students. He is a blogger in Times of India named as breaking shackles.

• Deep Learning Model for Arrhythmia Classification with 2D Convolutional Neural Network.-  Related Works.- Materials and Methods.