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Abhishek Srivastava

Assistant Professor, IT Systems & Analytics

Abhishek is currently working as Assistant Professor in the area of IT Systems & Analytics at IIM Jammu. He has a rich and diverse professional experience of working in Fortune 500 companies, startups and independent consulting, with successful delivery of multiple projects in the area of product development, policy making, AI and IT consulting, vendor management, startup community curation, fundraising, international collaborations, academic and industrial research.


  • Srivastava, A., Bala, P. K. & Kumar, B. (2020). New Perspectives on Gray Sheep Behavior in E-Commerce Recommendations. Journal of Retailing and Consumer Services 53, (ABDC), DOI : https://doi.org/10.1016/j.jretconser.2019.02.018
  • Ray, A., Bala, P., Dasgupta, S. & Srivastava, A. (2020). Understanding the Factors Influencing Career Choices in India: From the Students Perspectives.. International Journal of Indian Culture and Business Management., (ABDC), DOI : https://doi.org/10.1504/IJICBM.2020.10023811
  • Srivastava, A., Bala, P. K. & Kumar, B. (2017). Transfer Learning for Resolving Sparsity Problem in Recommender Systems: Human Values Approach.. Journal of Information Systems and Technology Management , 323-337. (ABDC), DOI : https://doi.org/10.4301/S1807-17752017000300002
  • Kumar, B., Bala, P. K. & Srivastava, A. (2016). Cosine Based Latent Factor Model for Precision Oriented Recommendation.. International Journal Of Advanced Computer Science And Applications, 451-457 DOI : https://doi.org/10.14569/IJACSA.2016.070161
  • Srivastava, A. (2018). Diffusing Indian Vedic Philosophy for transfer learning in Artificial Intelligence systems for more personalised recommendations. International Conference on Business Analytics and Intelligence, IISc Bangalore, India
  • Srivastava, A. (2016). Gray Sheep, Influential Users, User Modeling and Recommender System Adoption by Startups. ACM Conference on Recommender Systems, MIT / IBM Research, USA
  • Srivastava, A. (2015). A Framework for Simple, Secure and Cost Effective Online Voting System. European Conference on e-Government, University of Portsmouth, UK
  • Srivastava, A. (2015). Enhancing Recommender systems accuracy by using user-items latent features similarity. WEI International Academic Conference, Harvard, Boston, USA
  • Srivastava, A. (2015). An Improvised Latent Factor Model For More Efficient Recommender Systems. International Conference for Business and Economics, Harvard, Boston, USA

Business Analytics

AICTE ATAL Online Five days FDP (Augus 2021)