Latest Updates
To know the details for B.Tech. (Hons.) seat allotment schedule under JEE Main Quota, please click here | Ph.D. Admissions 2026 Now Open | Full-Time and Part-Time | Apply Before 10 April 2026 – Apply Now | Information submitted to UGC for inspection purpose | UGC Public Self Disclosure | CET Code: E285 | CET Code: E285 / MBA – CET Code – B413 / M.Tech – CET Code – T615

Dr. S. Thiruselvan

Dr. S. Thiruselvan

Associate Professor

About

Dr. S. Thiruselvan is an Associate Professor in the School of Computer Science and Engineering at RV University, Bengaluru. He brings over a decade of rich experience spanning academia, research, and industry, with a deep commitment to advancing computer science and fostering interdisciplinary innovation.

He earned his Ph.D. in Computer Science from the National Institute of Technology, Tiruchirappalli, where his research focused on cloud service evaluation and selection in federated cloud environments. His broader research interests include Cloud Computing, Data Science, Optimization, and Decision Science. He has published widely in reputed international journals and conferences and actively collaborates on applied and cross-disciplinary research projects.

Dr. Thiruselvan has contributed to several impactful initiatives, including projects in quantum-inspired computing, intelligent systems, urban mobility solutions, and cloud pricing models. He is also a granted patent holder in the domain of smart environmental control systems.

In his academic career, he has held faculty positions at GITAM University, Presidency University, and Vignan’s Foundation for Science, Technology & Research. He also brings industry experience from his role as a Software Engineer at Softeon Inc. His teaching approach emphasizes the integration of theory and practice, mentoring students in areas such as computational thinking, smart technologies, and applied analytics.

Dr. Thiruselvan is committed to driving innovation through interdisciplinary research and collaborative problem-solving that addresses real-world challenges.

Life doesn’t have an end-point, let it be an endless journey of discovery and continuous learning

Bhagawati, R. ., & Subramanian, T. . (2024). A Clustering Approach for Information Retrieval Using A Quantum-Based Computation Technique. International Journal of Intelligent Systems and Applications in Engineering, 12(14s), 488–497. (Scopus)
Bhagawati, R., & Subramanian, T. (2023). An approach of a quantum-inspired document ranking algorithm by using feature selection methodology. International Journal of Information Technology, 15(8), 4041-4053. (Scopus)
Dipali, D., Subramanian, T., Kumaran, G. S., & Koppala, G. (2023). Design and simulation of fuzzy logic-based automatic environmental controller for oyster mushroom cultivation. European Chemical Bulletin, 12(4), 3973-3985.
Dipali, D., Subramanian, T., & Kumaran, G. S. (2023). A smart oyster mushroom cultivation using automatic fuzzy logic controller. Journal of Discrete Mathematical Sciences and Cryptography, 26(3), 601-615. (Scopus, WoS)
Bhagawati, Rupam, and Thiruselvan Subramanian. (2023). ""Quantum-aided feature selection model–A quantum machine learning approach."" Journal of Discrete Mathematical Sciences and Cryptography, 26(3), 641-655. (Scopus, WoS)
Sasi, A., & Subramanian, T. (2023). Forecasting stochastic consumer portability visitation pattern in fair price shops of India. Journal of Information and Optimization Sciences. 44(3), 439–454. (WoS, C in ABDC)
Poornima, S., & Subramanian, T. (2023, March). Effective feature extraction via n-skip gram instruction embedding model using deep neural network for designing anti-malware application. In 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS) (Vol. 1, pp. 2118-2123). IEEE. (Scopus)
Dipali, D., Subramanian, T., & Kumaran, G. S. (2023). A Novel Approach for an Outdoor Oyster Mushroom Cultivation using a Smart IoT-based Adaptive Neuro Fuzzy Controller. International Journal of Advanced Computer Science and Applications, 14(5). (Scopus, WoS)
Sasi, M. A., Subramanian, T., & Ravichandran, S. K. (2023). QUEUEING SYSTEM IN FAIR PRICE SHOP OF KERALA TO MITIGATE WAITING TIME AND OPTIMIZATION OF SERVERS. Indian Journal of Computer Science and Engineering, 14(1), 214-224.
Sasi, A., & Subramanian, T. (2022). Comparative analysis of ARIMA and double exponential smoothing for forecasting rice sales in fair price shop. Journal of Statistics and management Systems, 25(7), 1601-1619. (WoS, C in ABDC)
Poornima, S., & Subramanian, T. (2022). Evolution of Deep Quantum Learning Models Based on Comprehensive Survey on Effective Malware Identification and Analysis. Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network, 83-105.
Subramanian, T., Dhyani, A., Kumar, A., & Gill, S. S. (Eds.). (2022). Artificial Intelligence, machine learning and blockchain in quantum satellite, drone and network. CRC Press.
Renukaradhya, S., Bhagawati, R., & Subramanian, T. (2022). A Brief Study on Quantum Walks and Quantum Mechanics. In Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network (pp. 15-34). CRC Press.
Bhagawati, R., Subramanian, T., & Pitchai, A. (2022). A Keen Study on Quantum Information Systems. In Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network (pp. 35-45). CRC Press.
Sasi, A., Subramanian, T., & Kumar Ravichandran, S. (2022, January). Systematic literature review on industry revolution 4.0 to enhance supply chain operation performance. In Proceedings of the 2022 5th International Conference on Computers in Management and Business (pp. 173-179). (Scopus)
Subramanian, T., & Savarimuthu, N. (2016). Cloud service evaluation and selection using fuzzy hybrid MCDM approach in marketplace. International Journal of Fuzzy System Applications (IJFSA), 5(2), 118-153. (Scopus)
Subramanian, T., & Savarimuthu, N. (2016). Application based brokering algorithm for optimal resource provisioning in multiple heterogeneous clouds. Vietnam Journal of Computer Science, 3, 57-70.
Subramanian, T., & Savarimuthu, N. (2015). A study on optimized resource provisioning in federated cloud. arXiv preprint arXiv:1503.03579.
Subramanian, T., & Savarimuthu, N. (2014, November). EFfective Tariff Selection On Cloud Services: A consumer perspective. In 2014 International Conference on Contemporary Computing and Informatics (IC3I) (pp. 326-330). IEEE. (Scopus, WoS)

Dr. S. Thiruselvan’s research spans multiple interdisciplinary domains within computer science, with a primary focus on cloud computing, optimization, quantum-inspired algorithms, smart systems, and decision science. His scholarly work combines theoretical models with practical applications, addressing real-world challenges in resource provisioning, intelligent systems, and data-driven decision-making.

His early research, including his doctoral work, centered around cloud service evaluation and brokering in federated cloud environments, where he developed hybrid multi-criteria decision-making (MCDM) frameworks and pricing optimization models. These contributions offered cost-efficient and scalable solutions for service selection and migration in heterogeneous cloud infrastructures.

In recent years, his focus has expanded into quantum-inspired computation and machine learning. He has co-developed novel algorithms for document clustering, feature selection, and ranking, utilizing quantum computing principles to enhance information retrieval and pattern recognition tasks.

Another notable line of work lies in smart agriculture and IoT-enabled control systems. Dr. Thiruselvan has designed and simulated fuzzy logic-based controllers for automated environmental management in mushroom cultivation, leading to impactful applications in precision farming. This research also culminated in a granted Indian patent for an intelligent temperature and humidity control system.

Additionally, his contributions to urban mobility optimization, supply chain analytics, and anti-malware systems using deep learning highlight his versatility and ability to work across domains.

Dr. Thiruselvan’s research is consistently aimed at bridging theoretical innovation with societal impact, with a strong inclination towards collaborative, applied, and interdisciplinary problem-solving.

Research Interests

Cloud Computing

Optimization Techniques

Decision Science

Urban Mobility

Ph.D. Supervision

Successfully guided 3 Ph.D. scholars at Presidency University, Bengaluru, in areas including optimization, intelligent systems, and data-driven decision science.

Granted Patent

An Automatic Fuzzy Logic Controller System for Temperature and Humidity Maintenance in an Outdoor Farm – Patent No: 550952 (2024)

Dr. S. Thiruselvan

Associate Professor

Ph.D

School of Computer Science and Engineering

1