Arijit Maji | Indian Institute of Management Bodh Gaya

Overview

Arijit Maji is working as an Assistant Professor at the Indian Institute of Management Bodh Gaya, India. He did his Bachelor’s degree in Power Engineering from the National Power Training Institute (Eastern Region), Durgapur, India, and his Master’s degree in Quality, Reliability & Operations Research from the Indian Statistical Institute, Kolkata, India. He completed his PhD from Shailesh J. Mehta School of Management, IIT Bombay. His research has been published in reputed leading journals, including the Journal of the Operational Research Society, Annals of Operations Research, International Journal of Production Research, and the International Journal of Quality & Reliability Management. His primary research interests include statistical & machine learning methods, quality engineering, industrial process analytics, and business analytics.

Academic Background

Ph.D., Indian Institute of Technology Bombay, Mumbai, India.

M.Tech., Quality, Reliability & Operations Research, Indian Statistical Institute, Kolkata, India.

B.Tech., Power Engineering, National Power Training Institute, Durgapur, India.

Experience

Assistant Professor, Birla Institute of Management Technology, Greater Noida, India.

Assistant Professor, Symbiosis Statistical Institute, Pune, India.

Business Analyst (Manager), Axis Bank Ltd., Bengaluru, India.

Associate Data Science Consultant, AXA Business Services Pvt. Ltd., Bengaluru, India.

Teaching Interest

Data Mining Machine Learning Text Mining Big Data Analytics Advanced Machine Learning Modelling (Supervised, Unsupervised, and One-Class Learning) Applied Optimization Techniques.

Research Interest

Machine Learning in Industrial Process Analytics Quality Analytics Industrial Business Analytics

Publications

Journal Articles

1.

Maji, A., Mukherjee, I., Tang, L.C. (2026). A Machine Learning-Based Statistical Process Control for Nonnormal Multivariate Data with Nonlinear Correlation Structure. Journal of the Operational Research Society. https://doi.org/10.1080/01605682.2026.2679041 (ABDC-A)

2.

Maji, A., Mukherjee, I., & Manatkar, R. (2025). An improved multivariate manufacturing process monitoring framework using one-class classifier support vector machines. Annals of Operations Research. https://doi.org/10.1007/s10479-025-06991-0 (ABDC-A)

3.

Maji, A., & Mukherjee, I. (2023). An efficient adaptive r-md multivariate single control chart for nonlinear multiple quality characteristics. International Journal of Production Research, 62(3), 784–822. https://doi.org/10.1080/00207543.2023.2173508 (ABDC-A)

4.

Maji, A., & Mukherjee, I. (2023). An unsupervised one-class-classifier support vector machine to simultaneously monitor location and scale of multivariate quality characteristics. International Journal of Quality and Reliability Management, 40(2), 419–454. https://doi.org/10.1108/IJQRM-09-2021-0316 (ABDC-B)

Conference Proceedings

1.

Maji, A., & Mukherjee, I. (2022). Performance evaluation of a one-class-classifier support vector machine-based control chart with varied hyperparameter selection strategies in real-life manufacturing processes , in Proceedings of the International Conference on Optimization, Learning and Analytics in Business (OLAB-2022), Heritage Institute of Technology, Kolkata, India, 2022.

2.

Maji, A., Amed, S., & Sen, T. (2021). Multivariate Missing Value Imputation using Weighted Cluster Softmax Technique. In Interdisciplinary Research in Technology and Management (pp. 128-133). CRC Press. https://doi.org/10.1201/9781003202240