He has a PhD from the Indian Institute of Management Mumbai. He has completed a Master’s in Industrial Engineering and Management and a B.Tech in Mechanical Engineering from JNTU Hyderabad. He has 2+ years of industry experience in India and abroad. Previously, he worked with SR University, Warangal, Institute of Management Technology, Hyderabad, and ICFAI Business School, Hyderabad. Dr Rajan Kumar also served as a visiting faculty at DoMS, NALSAR University of Law, Hyderabad, School of Innovation and Management, Hyderabad. He is an Editorial Board Member at Humanities and Social Sciences Communications.

His research work is broadly in the area of integration of Machine learning techniques with core operations management research problems. Dr Rajan is curious about exploring the concurrent topics include Agentic AI, Virtual Reality, and Big Data Analytics. His teaching interest includes Machine Learning, Big Data Analytics, Management Information Systems, Blockchain, Data Visualisation and Modelling, Research Methodology, Project Management, and Supply Chain Management.

Journals

• Agrawal, A., Adishree, A., Tarei, P. K., & Gangadhari, R. K. (2025). Analysing performance barriers to the large-scale adoption of green hydrogen in the Indian landscape. International Journal of Productivity and Performance Management, 1-27. (ABDC - B category, Q1, impact factor 2.8, SCI, Scopus)
• Tarei, P. K., Gangadhari, R. K., & Gumte, K. (2024). Is driving an electric two-wheeler (E2W) safe? Analysing safety risk factors of E2W considering the quality and reliability criteria. International Journal of Quality & Reliability Management. (ABDC - B category, Q2, impact factor 2.8, SCI, Scopus)
• Gangadhari, R. K., Tarei, P. K., Chand, P., Rabiee, M., & Delen, D. (2024). Navigating the New Normal: Redefining N95 Respirator Design with an Integrated Text Mining and Quality Function Deployment-Based Optimization Model. Computers & Industrial Engineering, 109962. (ABDC - A category, Q1, impact factor 8, SCI, Scopus), https://doi.org/10.1016/j.cie.2024.109962
• Gangadhari, R. K., Rabiee, M., Khanzode, V., Murthy, S., & Tarei, P. K. (2024). From unstructured accident reports to a hybrid decision support system for occupational risk management: The consensus converging approach. Journal of safety Research (ABDC - A category, Q1, impact factor 4.1, SCI, Scopus), https://doi.org/10.1016/j.jsr.2024.02.006
• Chand, P., Tarei, P. K., Gangadhari, R. K., & Mikalef, P. (2023). IoT Capabilities in Regaining Travelers’ Confidence Through Touchless Travel: An Empirical Study for the Revival of the Airline Sector. IEEE Transactions on Engineering Management. (ABDC - A category, Q1, cite score 5.8, Scopus), doi: 10.1109/TEM.2023.3276779
• Gangadhari, R. K., Khanzode, V., Murthy, S., & Dennehy, D. (2023). Modelling the relationships between the barriers to implementing machine learning for accident analysis: the Indian petroleum industry. Benchmarking: An International Journal, 30(9), 3357-3381. (ABDC - B category, Q1, cite score 5.0, Scopus). https://doi.org/10.1108/BIJ-03-2022-0161
• Gangadhari, R. K., Shivalingam, V., Tarei, P. K., & Cherukuri, S. (2023). Modeling Perceptions About Destination Images and Intention to Re-Visit: A Mediating-Moderated Model of Tourists’ Behavior. International Journal of Hospitality & Tourism Administration, 1-27. (ABDC - B category, Q2, cite score 3.5, Scopus). DOI: 10.1080/15256480.2023.2235702
•  Gangadhari, R. K, Tarei, P. K., (2021). Qualitative investigation of the influential factors behind unsafe trucking behaviors in India. Transportation Research Record, 2675(1), 67-78. (ABDC - B category, Q2, impact factor 1.56, Scopus, SCI). https://doi.org/10.1177/0361198120964724
• Gangadhari, R. K., Murty, S., & Khanzode, V. (2021). Analysis of accidents involving petroleum tankers and their consequences in India. Process Safety Progress, 40(1), e12154. (Q2, impact factor 1.34, SCI, Scopus). https://doi.org/10.1002/prs.12154
• Wang, K., Zhao, Y., Gangadhari, R. K., & Li, Z. (2021). Analyzing the adoption challenges of the Internet of things (IoT) and artificial intelligence (ai) for smart cities in China. Sustainability, 13(19), 10983. (Q1, impact factor 3.25, SCI, Scopus). https://doi.org/10.3390/su131910983
• Tavana, M., Shaabani, A., Raeesi Vanani, I., & Gangadhari, R. K. (2022). A review of digital transformation on supply chain process management using text mining. Processes, 10(5), 842. (Q2, impact factor 2.84, SCI, Scopus). https://doi.org/10.3390/pr10050842
• Gangadhari, R. K., Karadayi‐Usta, S., & Lim, W. M. (2023). Breaking barriers toward a net‐zero economy. In Natural Resources Forum, 30. (Q2, Cite score 4.6, Scopus, SCI). https://doi.org/10.1111/1477-8947.12378
• Gangadhari, R. K., Khanzode, V., & Murthy, S. (2022). Application of rough set theory and machine learning algorithms in predicting accident outcomes in the Indian petroleum industry. Concurrency and Computation: Practice and Experience, 34(26), e7277. (Q2, cite score 4.2, Scopus),
• Verma, V. K., Gangadhari, R. K., & Pandey, P. K. (2023). A re-examination of the space debris problem using systems thinking, Space Mission Planning & Operations, 2, 28-43. https://doi.org/10.20517/smpo.2022.05

• Gangadhari, R. K., Khanzode, V., & Murthy, S. (2021, December). Disaster impacts analysis using social media data. In 2021 International Conference on Maintenance and Intelligent Asset Management (ICMIAM) (pp. 1-6). IEEE. Doi: 10.1109/ICMIAM54662.2021.9715186