Dr V N Rajesh, currently an Associate Professor in Data Science & Information Systems, is a seasoned Data Science and Business Analytics Professional with over 15 years of experience. His rich and diverse industry experience has involved him in various roles, including but not limited to analytics and data science project delivery, product and platform development, data science consulting & research, Business Analytics COE establishment, and pre-sales & business development activities.

He has designed and deployed analytical solutions for numerous clients across global markets, in domains as diverse as Banking & Financial Services, Insurance, Retail, Healthcare, Railroad, Hospitality and Manufacturing. He has worked with leading IT service providers, including Cognizant Technology Solutions, Hexaware, Wipro, GE Transportation and Tech Mahindra.

In his previous engagement with the Tamil Nadu e-Governance Agency, IT Department, Tamil Nadu State, he was involved in the design and implementation of cutting-edge analytical solutions and policies to foster data-driven decision-making in the Government sector.

In academia, Dr Rajesh has worked as an Assistant Professor at the IT & Systems Group of the Indian Institute of Management, Lucknow (IIML) and as Visiting Associate Professor, Industrial Engineering Group, Mechanical Engineering Area of Universidad Carlos III de Madrid (UC3M), in Madrid, Spain.

Dr Rajesh has been an active researcher and has contributed over 20 articles to leading international technical conferences (IEEE ICDM, IEEE IRI, etc) and refereed journals.

Primarily an engineer, Dr Rajesh holds a Bachelor’s degree in Electronics Engineering (BE (Honours)) from the University of Bombay, and has completed the Fellow Program in Management (FPM) from the Indian Institute of Management Bangalore (IIMB).

AI/ML, Data Mining & Knowledge Discovery in Databases, Responsible AI, Big Data Analytics and Blockchain

• Alfonso Duran, Rajesh Natarajan and Esmeralda Giraldo, “Sincronización de los ciclos de información y de gestión de infraestructuras de servicios hoteleros” (Synchronization of Information and Infrastructure Management Lifecycles in Hotel Services), Dirección y Organización, No. 45, pp. 38-45, December 2011.


• Rajesh Natarajan and B. Shekar, “Interestingness of Association Rules in Data Mining: Issues relevant to eCommerce,” Sadhana-Academy Proceedings in Engineering Sciences of The Indian Academy of Sciences, 30, 2&3, pp. 291-310, April/June 2005.


• Shekar and Rajesh Natarajan, “A Framework for Evaluating Knowledge-Based Interestingness of Association Rules,” Fuzzy Optimization and Decision Making, 3, pp.157 – 185, June 2004.


• Shekar and Rajesh Natarajan, “A Fuzzy Taxonomy-based Method to Assess Interestingness of Association Rules,” Fuzzy Systems and AI: Reports and Letters, 8, 1-3, pp.25-32, 2002.

• Rajesh Natarajan, Esmeralda Giraldo and Alfonso Duran, “Challenges in Data-driven Hotel Infrastructure Assignment Decisions,” Proceedings of the 6^th International Conference on Industrial Engineering and Industrial Management (CIO 2012), pp. 416-423, Vigo, Spain, July 18-20, 2012.


• Rajesh Natarajan and Alfonso Duran, “Aligning Hotel Data Management for Customer related Resource Assignment Decisions,” Proceedings of the 5t^h International Conference of Industrial Engineering and Industrial Management (CIO 2011), September 7-9, 2011, Cartagena, Spain, pp 157-164, Springer, London.


• Rajesh Natarajan and B. Shekar, “Tightness: A Novel Heuristic and a Clustering Mechanism to improve the Interpretation of Association Rules,” Proceedings of the 2008 IEEE International Conference on Information Reuse and Integration (IEEE IRI 2008), July 13-15, 2008, Las Vegas, USA, pp. 308-313.


• Shekar and Rajesh Natarajan, “Investigations into relatedness-based interestingness of association rules: A transaction-driven analysis,” Proceedings of the 2006 IEEE Intl. Conference on Information Reuse and Integration (IEEE IRI 2006), September 16-18, 2006, Waikoloa, Hawaii, USA, pp. 522-527.


• Rajesh Natarajan and B. Shekar, “Weakness of Association Rules: A Mechanism for Clustering,” Proceedings of the 17^th Information Resources Management Association International Conference (IRMA 2006), Washington D.C., U.S.A., May 2006, pp.435-437.


• Rajesh Natarajan and B. Shekar, “Tightness-based Clustering of Association Rules: An Aid to Chance Discovery in Data Mining,” 22^nd on Machine Learning (ICML 2005), Proc. of Workshop on Chance Discovery: from Data Interaction to Scenario, Bonn, Germany, August, 2005, pp.43-51.


• Rajesh Natarajan and B. Shekar, “A Relatedness-based Data-driven Approach to Determination of Interestingness of Association Rules,” Proceedings of the 20^th Annual ACM Symposium on Applied Computing (SAC 2005), Santa Fe, U.S.A., March 2005, pp. 551-552.


• Shekar and Rajesh Natarajan, “A Transaction-based Neighbourhood-driven Approach to Quantifying Interestingness of Association Rules,” Proceedings of the IEEE International Conference on Data Mining 2004 (IEEE ICDM 2004), Brighton, U.K., December 2004, pp. 194-201.


• Rajesh Natarajan and Shekar B., “A Taxonomy-based Approach to Determining Generic Interestingness of Association Rules,” of IEEE TENCON 2003 (IEEE Region 10 Technical Conf. on Convergent Technologies for the Asia-Pacific), Bangalore, India, October 14-17, 2003, pp. 701-707.


• Shekar and Rajesh Natarajan, “A Fuzzy-Graph-Based Approach to the Determination of Interestingness of Association Rules”, in Proc. of the 4^th Conf. on Practical Aspects of Knowledge Management, PAKM ’02, Eds: D. Karagiannis and U. Reimer, LNAI 2569, Springer-Verlag, 2002, pp. 377-388.


• Shekar and Rajesh Natarajan, “A Fuzzy Relatedness Measure for determining Interestingness of Association Rules”, in Proc. of the Second Intl. Conf. on Hybrid Intelligent Systems , Dec. 01-04, 2002, Universidad de Chile, Chile, AOS Press, pp. 95-104.


• Rajesh Natarajan and Shekar B., “Data Mining for CRM: Some Relevant Issues,” in Proc. of the 1^st International Conf. on Customer Relationship Management in India held at MDI Gurgaon (Nov.’00), “Customer Relationship Management: Emerging Concepts, Tools and Applications” Eds: Sheth J.N., Parvatiyar A. and Shainesh G., Tata McGraw Hill Ltd, New Delhi, 2001, pp. 81-90.

• Rajesh Natarajan, AI Regulation: Imperatives, Challenges and a Supporting Framework, 2021


• Rajesh Natarajan, Challenges in Big Data Analytics Implementation: A Government Perspective, 2021

• Rajesh Natarajan and B. Shekar, “Understandability of Association Rules: A Heuristic Measure to enhance Rule Quality,” Quality Measures in Data Mining (QMDM), Series: Studies in Computational Intelligence, Vol. 43, Guillet, Fabrice; Hamilton, Howard J. (Eds.) , Springer-Verlag, pp 179-206, 2007.


• Rajesh Natarajan and B. Shekar, “Interesting Knowledge Patterns in Databases,” Encyclopaedia of Knowledge Management, (Edited by David Schwartz, Bar-Ilan University, Israel), Idea Group Inc., U.S.A., pp 297-304, 2005.

• Vidyashankar, Rajesh Natarajan and Subhrangshu Sanyal, “Mine Your Way to Combat Money Laundering – Part 2,” DM Review Special Report, October, 2007


• Vidyashankar, Rajesh Natarajan and Subhrangshu Sanyal, “Mine Your Way to Combat Money Laundering – Part 1,” DM Review Special Report, October, 2007

• Rajesh Natarajan, Review of “The Political Mapping of Cyberspace, by Jeremy Crampton, The University of Chicago Press, 2003” in ACM SIGACT News, Vol. 38, No. 3, 2007.


• Rajesh Natarajan, Review of “Graphics of Large Datasets: Visualizing a Million, by Unwin, Anthony, Martin Theus and Heike Hofmann, Springer, New York, 2006,” in Interfaces, Vol. 37, No. 5, September-October 2007, pp. 488-496.

• “Post-processing in data mining: Interestingness measures for Association Rule Mining,” Tutorial presented at ACM Compute 2008, Bangalore, India, January, 2008.

• “A Transaction-based Neighbourhood-driven Approach to Quantifying Interestingness of Association Rules,” IEEE International Conference on Data Mining 2004, Brighton, U.K., November, 2004.


• “A Taxonomy-based Approach to Determining Generic Interestingness of Association Rules,” IEEE TENCON 2003 (IEEE Region 10 Technical Conference on Convergent Technologies for the Asia-Pacific), Bangalore, India, October 14-17, 2003.


• “A Fuzzy-Graph-Based Approach to the Determination of Interestingness of Association Rules,” 4^th International Conference on Practical Aspects of Knowledge Management, PAKM ’02, Vienna, Austria, December 2-3, 2002.


• “Data Mining for CRM: Some Relevant Issues,” 1^st International Conference on Customer Relationship Management in India held at MDI Gurgaon, November, 2000.

• “The Movement Planner System for Dispatching Trains in Railroad Networks – A Practical Perspective,” Key Note Address in Indian Institute of Technology Madras, Department of Management Studies, Research Symposium 2019, held at IIT Madras, 2nd November, 2019.


• “Business Applications of Advanced Analytics,” Key Note Address at JK Group Engineering Conference, J K Paper Mills, Rayagada, Odisha, 25th-27th November, 2015.

• Text Mining Workshop 2014 organised by ACM Student Chapter, ISI Kolkata and Indian Statistical Institute, Kolkata at Indian Statistical Institute, Kolkata from 6 – 8 January, 2014


• ISO 31000:2009 Risk Management Principles and Guidelines Implementation Course conducted by BSI at Wipro, Bangalore on 21–22 January, 2013

• Listed in Marquis Who’s Who in the World, 2007


• National Merit Scholarship awarded by the Maharashtra Board of Secondary and Higher Secondary Education for performance in the H.S.C. examination, 1991

• Data Science
• Data Mining and Knowledge Discovery in Databases
• Artificial Intelligence
• Machine Learning
• Big Data Analytics
• Blockchain for Management
• Data Management
• Responsible AI and Public Policy