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Parag Kulkarni
パラグ クルカルニー

Machine Learning, Artificial Intelligence, and Innovation Strategy
  • ・B.E. - Wlachand College of Engineering, Sangli, India

  • ・M.E. - SGSITS, Indore, India

  • ・D.Sc. - UGSN Monarch, Switzerland

  • ・Ph.D. - IIT, Kharagpur, India

Parag Kulkarni

Biographical Statement

Parag is Professor of AI, Machine Learning and Innovation Strategy at TIU. He is an entrepreneur, Machine Learning researcher, an innovation strategist and author of best-selling Innovation Strategy and Data science books. Parag holds PhD from IIT Kharagpur (2001), management education from IIM and was conferred higher doctorate DSc by UGSM monarch, Switzerland (2010).

An avid reader, Parag is Director and Chief Scientist of iKnowlation Research Labs – a vibrant Machine Learning Product, research and Consulting initiative. Parag has published over 250+ research papers (in peer reviewed journals and conferences), invented over a dozen patents and authored 12 books. (
Parag has guided 15 PhD candidates. He has over 25 years of experience in technologies, product building and applications of AI and ML to different verticals. In the past, he headed research division of many companies including Siemens, IDeaS, Capsilon, etc. Parag is prolific speaker and is/was associated with many technical and B-schools of repute including IITs, IIMs, COEP, Pune University and Masaryk University, Brno – Czech Republic.

Parag’s machine learning ideas has resulted in pioneering products and have become commercially successful to produce unprecedented impact. He delivered over one thousand keynote addresses and 200+ tutorials across the globe. His work on Systemic Machine Learning published by IEEE is widely cited. Over 100 institutes and 100000+ professionals benefitted from Parag’s talks, research and systemic consultations. Parag helped underperforming professionals and students to transform into happy and passionate warriors. Fellow of the IET, IETE, and senior member IEEE, Parag is recipient of Oriental Foundation Scholarship and was nominated for prestigious Bhatnagar award in 2013 and 2014. His Book “Knowledge Innovation Strategy” is one of the best sellers while his book YD is adopted for major TV serial “YEAR DOWN”.

Parag has over half a dozen innovative products built around concepts of associative and systemic machine learning. As a consultant, he has contributed to success of over two-dozen organizations including start-ups and established companies. He is a pioneer in the concepts of Systemic Machine Learning, Reverse Hypothesis Machine Learning, Context Vector Machines and Deep Explorative Machine Learning. He is a core contributor to areas of AI, Machine learning and allied areas with focus on optimal and systemic learning. He has been helping organizations, research groups for identifying right innovation and Machine Learning opportunities, building ML models and embedding Creative Machine Learning in their operations, services and products.

Selected Publications by Parag Kulkarni


Kulkarni, P. (2017). Reverse hypothesis machine learning: A practitioner's perspective. Germany: Springer.

Kulkarni, P. (2015). Reinforcement and systemic machine learning for decision making. New Delhi India: Wiley.

Kulkarni, P. (2015). Knowledge innovation strategy: Why cats don’t take part in rat race. New Delhi, India: Bloomsbury.

Kulkarni, P., & Joshi, P. (2015). Artificial intelligence: Building intelligent systems. New Delhi, India: Prentice Hall India.

Kulkarni, P., & Brown et al, M. (2015). Mining unstructured data: A big data perspective. New Delhi, India: Prentice Hall India.

Kulkarni, P., Chande, P.K., & Jahirabadkar, S. (2012). E-business models. New Delhi, India: Oxford University Press.

Kulkarni, P. (2012). Reinforcement and systemic machine learning for decision making. New Jersey, USA: Wiley IEEE.

Kulkarni, P., & Chande, P.K. (2008). IT strategies-For business. New Delhi, India: Oxford University Press.

Kulkarni, P., & Kulkarni, M. (2007). Deliverance from success. Pune, India: CTC Publication.

Inventor of Patents

Malaney, S., Kulkarni, P., Viswanathan, K., Malaney, V., & Evans, J. (2005). U.S. Patent No. 8,176,004 B2. San Diego, CA: Capsilon Corp.

Malaney, S., Kulkarni, P., Viswanathan, K., & Malaney, V. (2005). US Patent No. 7,747,495 B2. San Diego, CA: Capsilon Corp.

Peer-reviewed Journal Articles

Velankar, M., Kulkarni, P. (2018). Melodic pattern recognition in Indian classical music for raga identification. Springer, International Journal of Information Technology. Retrieved from

Velankar, M., Kulkarni, P. (2018). Soft computing for music analytics. International Journal of Engineering Applied Sciences and Technology, 3(2), 35-40.

Sonawane, S., & Kulkarni, P. (2018). Extractive summarization using semi-graph (ESSg). Springer Evolving Systems. Retrieved from

Pise, N., & Kulkarni, P. (2017). Evolving learner’s behavior in data mining. Springer, Evolving Systems, 8(4), 243–259.

Munot, M., Joshi, P., Joshi, M., & Kulkarni, P. (2016). An incremental approach for efficient karyotyping systems. Journal of Medical Imaging and Health Informatics 6(1), 221-225.

Barve, S., & Kulkarni, P. (2014). Multi-agent reinforcement learning-based opportunistic routing and channel assignment for mobile cognitive radio ad hoc networks. Springer, Journal Mobile Networks and Applications, 19(6), 720-730.

Jahirabadkar, S., & Kulkarni, P. (2014). Adaptive determination of ε-distance parameter in density based clustering. Elsevier Journal on Expert Systems With Applications, 41(6), 2939-2946.

Mulay, P., & Kulkarni, P. (2013). Knowledge augmentation via incremental clustering. International Journal of Business Information Systems (IJBIS), 12(1), 68-87.

Lal, S., Kulkarni, P., & Singh, A. (2012). Instance based classification for decision making in network data. Journal of Intelligent Systems, 1(1), 334-1860.

Haribhakta, Y.V., & Kulkarni, P. (2011). Learning context for text categorization. International Journal of Data Mining & Knowledge Management Process (IJDKP), 1(6), 15–23.

Joshi, P., & Kulkarni, P. (2011). A novel approach for clustering based on pattern analysis. International Journal of Computer Applications, 4(8), 1-4.

Lal, S., Kulkarni, P., & Singh, A. (2010). Classification based on parametric partitioning of solution space. International Journal on Intelligent Systems, 19(21), 65-191.

Sengupta, N., & Kulkarni, P. (2007). Text classification for construction related documents. NICMA- Journal for Management, 01, 5-13.

Butalia, A., Ramani, A.K., & Kulkarni, P. (2010). Emotional recognition and towards context based decision. International Journal of Computer Applications, 3(8) 42-54.

Kulkarni, P., & SenGupta, I. (2005). Dual and multiple token based load balancing. International Journal of System Architecture, 51(1), 95-112.

Other journal articles can be found at:

News Appearances

Gupta, S. (2015, Aug 08). Book review: Knowledge innovation strategy is a must-read. Hindustan Times. Retrieved from:

Dharwadkar, J. (2017, Sep 25). Our current education system needs revamp, says Pune author Parag Kulkarni. Hindustan Times. Retrieved from: