Rohan Mukherjee

About

Dr. Rohan Mukherjee is an Associate Professor of Management Information Systems and Analytics at IMI Kolkata. He has completed his MS and PhD from Indian Institute of Technology Kharagpur in the domain of visual information processing and system design. He has also post-doctoral research experience in cutting-edge approaches of Machine Learning and AI. Prior to joining IMI Kolkata, he has worked at IIM Bodh Gaya, IIM Jammu and Goa Institute of Management. Rohan has published consistently in reputed journals and IEEE conferences in his area of expertise. His current research interest includes artificial intelligence and machine learning and their application in business. Apart from regular teaching and research, Rohan works closely with industry in several consulting projects and Professional Development Programs.

Employment

• IMI Kolkata Associate Professor
  2023 - Present
• IIM Bodh Gaya Assistant Professor
  2021 - 2023
• IIIM Assistant Professor
  2020 - 2021
• Goa Institute of Management Assistant Professor
  2019 - 2020

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (41)

• Metaverse-enabled crisis management for logistics and supply chains: a socio-technical framework
  Journal of Enterprise Information Management 2026 DOI: 10.1108/JEIM-12-2025-1320
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• Digital innovation, digital transformation and operational performance: a thematic analysis
  The TQM Journal 2026 DOI: 10.1108/TQM-03-2026-0181
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• Can Flexible Machine Learning Examine the Housing Features in Urban Housing Market Systems? A Study from the Indian Consumer Perspective in a Multi-city Context
  Global Journal of Flexible Systems Management 2026 DOI: 10.1007/s40171-025-00475-7
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• Can Deep-Learning Models Predict Behavior of Treasury Bond Yields
  Computational Economics 2026 DOI: 10.1007/s10614-025-10947-8
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• Hardware-Algorithm Co-design for Iterative Half-Pixel Motion Estimation Using Inter-Level Systolic Array
  Circuits, Systems, and Signal Processing 2026 DOI: 10.1007/s00034-026-03649-5
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• “I quit because…”: A psychological interpretation of push-pull dynamics of employee attrition informed by explainable machine learning
  Acta Psychologica 2026 DOI: 10.1016/j.actpsy.2026.106869
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• The Evolution of Global Smart Systems and Future Technologies in Human Resource Management Systems
  Journal of Global Information Management 2025 DOI: 10.4018/JGIM.366390
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• FeL-MAR: Federated learning based multi resident activity recognition in IoT enabled smart homes
  Future Generation Computer Systems 2025 DOI: 10.1016/j.future.2024.107552
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• Stack-HAR: Complex Human Activity Recognition With Stacking-Based Ensemble Learning Framework
  IEEE Sensors Journal 2025 DOI: 10.1109/jsen.2025.3549311
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• Exploring predictive prowess of ensemble machine learning models in banking stocks: A technical, fundamental, and macroeconomic analysis
  IIMB Management Review 2025 DOI: 10.1016/j.iimb.2025.100570
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