Dr. Atanu Dey is an Assistant Professor in the Information Systems area at the Indian Institute of Management Sambalpur. He completed both his MS and PhD from the Indian Institute of Technology (IIT) Kharagpur. He brings a blend of academic insight and industry experience, shaped through nearly nine years in the technology sector. Prior to joining IIM Sambalpur, he spent around seven years at HP Inc., where he progressed into the role of "Expert Data Scientist IV". In this capacity, he led data-driven initiatives, collaborated across multidisciplinary teams, and worked closely on translating analytical capabilities into strategic business outcomes.
His technical expertise spans Natural Language Processing (NLP), Sentiment Analysis, Data Science, Machine Learning (ML), and Deep Learning (DL). He has been involved in impactful research-oriented initiatives, including contributing to the development of a UKIERI-SPARC Project proposal. The long-term objective of this project was to create algorithms, tools, and dashboards to support organizations and governments in mitigating the environmental impact of electronic waste and fostering a more circular and sustainable economy. This experience reflects his commitment to applying advanced analytics for societal benefit.
Dr. Dey has published some research articles in the areas of NLP, ML, DL and Information Systems, focusing on how intelligent technologies can extract meaningful insights from unstructured data and support better decision-making. He continues to build on this intersection of research and practice, aspiring to contribute to the academic community, mentor emerging scholars, and engage with industry partners to advance data-driven innovation.
1. Foundation of Algorithm and Machine Learning (MBA BA)
2. Data Science for Business (MBA WP)
3. Fundamentals of Programming (BS MPP)
4. Business Analytics for Managerial Decision (MBA)
5. Data Visualization and Business Storytelling (MBA)
Journals (Published):
- Dey, A., Jenamani, M., & De, A. (2025). Consumer Sentiment-Driven Product Ranking Using a Feature-Level Deep Learning Approach: The Case of New and Refurbished Laptops. IEEE Transactions on Engineering Management, 73, 510-526. https://doi.org/10.1109/TEM.2025.3633709 (ABDC - A, IF: 6.2, ABS - 3, CiteScore – 13)
- Dey, A., & Jenamani, M. (2024). Aspect based sentiment analysis of consumer reviews using unsupervised attention neural framework. Applied Soft Computing, 167, 112259.https://doi.org/10.1016/j.asoc.2024.112259 (ABDC – C, IF: 6.6, CiteScore – 14.5)
- Dey, A., & Jenamani, M. (2024). A framework for analyzing consumer satisfaction using deep learning and expectation–confirmation theory: with illustration of refurbished laptops. International Journal of Data Science and Analytics, 20(3), 2811–2831.https://doi.org/10.1007/s41060-024-00646-2 (IF: 2.8)
- Dey, A., Jenamani, M., & Thakkar, J. J. (2019). Cross-D-vectorizers: a set of feature-spaces for cross-domain sentiment analysis from consumer review. Multimedia Tools and Applications, 78(16), 23141–23159.https://doi.org/10.1007/s11042-019-7553-0(IF: 3.6)
- Dey, A., Jenamani, M., & Thakkar, J. J. (2018). Senti-N-Gram: An n-gram lexicon for sentiment analysis. Expert Systems with Applications, 103, 92–105.https://doi.org/10.1016/j.eswa.2018.03.004ABDC – C, IF: 7.5, CiteScore – 15)
Conferences (Published) :
- Dey, A., Jenamani, M., & De, A. (2024, June). An Unsupervised Deep Learning Model for Aspect Retrieving Using Transformer Encoder. In Science and Information Conference (pp. 303-317). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-62277-9_18
- Dey, A., Jenamani, M., & De, A. (2023, December). An Efficient Approach for Findings Document Similarity Using Optimized Word Mover’s Distance. In International Conference on Pattern Recognition and Machine Intelligence (pp. 3-11). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-45170-6_1
- Dey, A., Jenamani, M., & Thakkar, J. J. (2017, November). Lexical TF-IDF: An n-gram feature space for cross-domain classification of sentiment reviews. In International Conference on Pattern Recognition and Machine Intelligence (pp. 380-386). Cham: Springer International Publishing. (Best Paper Award)https://doi.org/10.1007/978-3-319-69900-4_48
- Dey, A., Jenamani, M., & Thakkar, J. J. (2017, December). Sentiment wEight of N-grams in Dataset (SEND): A Feature-set for Cross-domain Sentiment Classification. In 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR) (pp. 1-6). IEEE.https://doi.org/10.1109/ICAPR.2017.8593172
- Hasnat, A., Bhattacharyya, T., Dey, A., Halder, S., & Bhattacharjee, D. (2017, March). A fast FPGA based architecture for computation of square root and Inverse Square Root. In 2017 Devices for Integrated Circuit (DevIC) (pp. 383-387). IEEE.https://doi.org/10.1109/DEVIC.2017.8073975
- Hasnat, A., Dey, A., Hoque, M. A., Halder, S., & Bhattacharjee, D. (2017, March). A novel unit circle approach for computation of sine function. In 2017 Devices for Integrated Circuit (DevIC) (pp. 570-573). IEEE.https://doi.org/10.1109/DEVIC.2017.8074015
- Dey, A., Bhattacharjee, S., & Samanta, D. (2016, May). Recognition of motor imagery left and right hand movement using EEG. In 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 426-430.IEEE.https://doi.org/10.1109/RTEICT.2016.7807856
1. Management Development Programme (MDP) on Artificial Intelligence (AI) and Machine Learning (ML) for MCL and SECL Executives
Role: Programme Director
Serving as the Programme Director for the Management Development Programmes on Artificial Intelligence (AI) and Machine Learning (ML) conducted for executives of Mahanadi Coalfields Limited (MCL) and South Eastern Coalfields Limited (SECL).
Teaching Responsibilities:
Introduction to Artificial Intelligence (AI): Fundamentals of AI, its evolution, key concepts, and applications in industry.
Hands-on with AI Tools: Practical sessions on contemporary AI tools, demonstrating their application in improving productivity, decision-making, and business processes.
2. Workshop on Data Science and Machine Learning
Conducted an online workshop on "Data Science and Machine Learning" through the NPTEL Plus platform. The workshop covered the fundamentals of data science, key machine learning concepts, practical applications, and emerging industry trends, providing participants with both theoretical understanding and practical insights.
