Bhupender Som
Also known as: Dr Soam
GNIOT Institute of Management Studies (GIMS), Jagan Institute of Management Studies, Kurukshetra University, Fortune Institute of International Business
About
A Ph.D. from Kurukshetra university from the department of statistics and operational research in stochastic models. The research interests include, stochastic queuing systems, data analytics and statistics. Possess over 18 years of experience in teaching and research. Have more than 100 publications/paper presentations in the journals and conferences of international repute. Completed consulting assignments related to primary and secondary data base research.
Employment
-
GNIOT Institute of Management Studies (GIMS) Director2023 - Present
-
Jagan Institute of Management Studies Dean, Professor2022 - 2033
-
Fortune Institute of International Business Deputy Director2021 - 2022
-
Lloyd Business School Director/Professor2019 - 2022
-
Jagan Institue of Management Studies Associate Professor2014 - 2019
Education
-
Kurukshetra University P.hD.2009 - 2014
Projects & Funding
Projects & funding information is unavailable.
Publications (41)
- Metacognition and Machines: Exploring AI’s Path to Consciousness Save
- The Predictive Power of Macroeconomic Variables on the Indian Stock Market Utilizing an Ann Model Approach: An Empirical Investigation Based on BSE Sensex Save
- Effectiveness of Organizational Justice on Workplace Deviance, with Job Satisfaction as a Mediating Driver Among Nurses and Healthcare Workers -A Sensitive Analysis Save
- A Study on Impact of Big Five Personality on Investment Decisions of Mutual Fund Investors: Mediation by Risk Save
- Applications of Mathematical Modeling, Machine Learning, and Intelligent Computing for Industrial Development Save
- Stock market prediction, COVID-19 pandemic and neural networks: an SCG algorithm application Save
- Queuing system with customers' impatience, retention, and feedback Save
- A meta-analysis of the application of artificial neural networks in accounting and finance Save
- Transient Solution of a Heterogeneous Queuing System with Balking and Catastrophes Save
- An M/M/2 Heterogeneous Service Markovian Feedback Queuing Model with Reverse Balking, Reneging and Retention of Reneged Customers Save