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Parikshit Mahalle Profile

Parikshit Mahalle

Parikshit Mahalle

Biography

Dr Parikshit is a senior member IEEE and is Professor, Dean Academics at Vishwakarma Institute of Technology, Pune, India. Prior to this, he worked as a Dean - Research and Development at VIT, Dean - Research and Development and Head - Department of Artificial Intelligence and Data Science at Vishwakarma Institute of Information Technology, Pune, India and Professor, Head, Department of Computer Engineering at Sinhgad Institutes. He completed his Ph. D from Aalborg University, Denmark in 2013 and completed his Post Doctoral Research at CMI, Copenhagen, Denmark. He has 25 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, Member-BoS and academic council member at more than 30 Universities and autonomous colleges across India. He has 117 patents, 440+ research publications (Google Scholar citations-4400 plus, H index-29 and Scopus Citations are 2300 plus with H index -22, Web of Science citations are 585 with H index - 12) and authored/edited 75 books with Springer, CRC Press, Cambridge University Press, etc. He is editor in chief for Research Journal of Computer Systems and Engineering (RJCSE), Associate Editor for IGI Global - Journal of Affective Computing and Human Interfaces (JACHI), member-Editorial Review Board for IGI Global - International Journal of Ambient Computing and Intelligence and reviewer for various transactions, 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 IoT and machine learning and EIGHT students have successfully defended their PhD under his supervision from SPPU and Three students completed Postdoc under his mentorship from NTU, Taiwan. He is also the recipient of ?Best Faculty Award? by Sinhgad Institutes and Cognizant Technologies Solutions, International Level S4DS distinguished Researcher of the Year 2023 and State Level Meritorious Teacher Award and Distinguished Research Guide Award at IEEE ICTBIG 2024, organised by Symbiosis University of Applied Sciences (SUAS), Indore. He has delivered 400 plus lectures at national and international level. His book on Design and Analysis of algorithms is referred as Textbook in IIITs and NITs and his book on Data Analysis on Pandemic by CRC press has received two international awards in 2020. His edited title, 'Data Science: Techniques and Intelligent Applications', has been awarded the prestigious Choice Outstanding Academic Titles Award for 2024. He is also Certified ISO 27001:2022 Lead Auditor. He has also worked as an Invited Guest faculty at several international universities like UMA, Lima Peru in South America, National Taipei University Taiwan etc. He visited 24 countries till date for various academic and research collaborations. 

Research Interest

He completed his Ph. D from Aalborg University, Denmark in 2013 and completed his Post Doctoral Research at CMI, Copenhagen, Denmark. He has 25 years of teaching and research experience.

Abstract

Beyond Generative AI: Towards Next Generation AI Agents and Agentic Intelligence: The rapid advancement of generative artificial intelligence (AI) has transformed creativity, productivity, and automation across diverse domains. However, current generative models remain largely tool-centric, limited to content generation without autonomous reasoning or adaptive decision-making. This paper explores the transition from generative AI to the emerging paradigms of AI agents and agentic intelligence, which represent the next generation of AI evolution. AI agents extend generative capabilities with goal-oriented task execution, contextual memory, reasoning, and environment interaction. Agentic AI further advances this concept by enabling self-directed, adaptive, and collaborative systems that can operate in dynamic, multi-agent ecosystems with human alignment and ethical safeguards. The paper outlines the distinguishing features of these paradigms, highlights enabling technologies such as reinforcement learning, human-in-the-loop frameworks, and multi-agent coordination, and presents a roadmap for their integration into real-world applications. By charting this progression, the work provides insights into how AI can evolve from creative assistance to autonomous, trustworthy, and value-aligned intelligence shaping the future of industries and society.