Cognitive Computing for Machine Thinking

Dr. Makarand Velankar received Ph.D. degree in Computer Engineering from Savitribai Phule Pune University. He has 11 years of industry experience and is associated with MKSSS’S Cummins College of Engineering for women, Pune, Maharashtra, India since 2001. His research interests include machine learning, AI, information retrieval, algorithms, cognitive computing and computational musicology. He is member of various professional bodies such as Computer Society of India, ACM, Indian Institute of Engineers. He acted as reviewer for many journals and conferences such as IEEE transactions, Springer, Eurasip, Sadhna, UAAI, IGI Global and ISMIR. He is associated with International Society of Music Information Retrieval to promote research in computational music. He is also an entrepreneurship educator, trainer and approved mentor for start-ups. He received Gold Global Jury award for evaluating and guiding startups at global level. He has delivered talks and conducted sessions/ webinars ondifferent topics in startups, entrepreneurship and computing.Dr Parikshit is a senior member IEEE and is Professor, Dean Research and Development and Head - Department of Artificial Intelligence and Data Science at Vishwakarma Institute of Information Technology, Pune, India. He completed his Ph. D from Aalborg University, Denmark and continued as Post Doc Researcher at CMI, Copenhagen, Denmark. He has 23 + years of teaching and research experience. He is an ex-member of the Board of Studies in Computer Engineering, Ex-Chairman Information Technology, Savitribai Phule Pune University and various Universities and autonomous colleges across India. He has 15 patents, 200+ research publications (Google Scholar citations-2900 plus, H index-25 and Scopus Citations are 1400 plus with H index-18, Web of Science citations are 438 with H index - 10) and authored/edited 54 books with Springer, CRC Press, Cambridge University Press, etc. He is editor in chief for IGI Global –International Journal of Rough Sets and Data Analysis, Inter-science International Journal of Grid and Utility Computing, member-Editorial Review Board for IGI Global – International Journal of Ambient Computing and Intelligence and reviewer for various journals and conferences of the repute. His research interests are Machine Learning, Data Science, Algorithms, Internet of Things, Identity Management and Security. He is guiding 8 PhD students in the area of IoT and machine learning and SIX students have successfully defended their PhD under his supervision from SPPU. He is also the recipient of “Best Faculty Award” by Sinhgad Institutes and Cognizant Technologies Solutions. He has delivered 200 plus lectures at national and international level.Dr. Gitanjali R. Shinde has overall 15 years of experience, presently working as Head & Associate Professor in Department of Computer Science & Engineering (AI & ML), Vishwakarma Institute of Information Technology, Pune, India. She has done Ph.D. in Wireless Communication from CMI, Aalborg University, Copenhagen, Denmark on Research Problem Statement “Cluster Framework for Internet of People, Things and Services” – Ph. D awarded on 8th May 2018. She obtained M.E. (Computer Engineering) degree from the University of Pune, Pune in 2012 and B.E. (Computer Engineering) degree from the University of Pune, Pune in 2006. She has received research funding for the project “Lightweight group authentication for IoT” by SPPU, Pune. She has presented a research article in the World Wireless Research Forum (WWRF) meeting, Beijing China. She has published 50+ papers in National, International conferences and journals. She is author of 10+ books with publishers Springer and CRC Taylor & Francis Group and she is also editor of books. Her book "Data Analytics for Pandemics A COVID 19 Case Study” is awarded outstanding Book of year 2020.

• Chapter 1: Natural and Artificial Intelligence: Overview.- Chapter 2: AI and Cognitive Computing: Machine and Human Perspective.- Chapter 3: Internet of Behavior.- Chapter 4: Rethinking Machine Learning and Deep Learning.- Chapter 5: Machine Thinking: New Paradigm Shift.- Chapter 6: Cognitive Computing.- Chapter 7: Business Cases. - Chapter 8: Conclusions.