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  9. Dr. Tejas M. Modi

Dr. Tejas M. Modi

Designation: Assistant Professor

Biography:

Dr. Tejas M. Modi is an Assistant Professor in the Department of Computer Science and Engineering at Adani University. He holds a Ph.D. from NIT Goa and has academic experience at IIIT Surat and MBIT. His research focuses on Software Defined Networks, Artificial Intelligence, Machine Learning, Deep Learning, and interdisciplinary applications. Dr. Modi has published extensively in reputed SCI and Scopus-indexed journals, including Computer Science Review, The Journal of Supercomputing, and CCPE. He has presented at international conferences, contributed to book chapters, and holds a granted patent in EEG signal optimization. He also serves peer reviewer in more than 15 Springer Nature Journals.

  • Ph.D. Computer Science and Engineering (NIT Goa-2023)
  • M.E. Information Technology (GTU-2015)
  • B.E. Computer Engineering (GTU-2013)

  • Asst. Professor at Department of CSE, Adani University Since January 2024.
  • Asst. Professor (Contractual) at Department of CSE, Indian Institute of Information Technology Surat from April 2023 to December 2023 .
  • Teaching Assistant at Department of CSE, Indian Institute of Information Technology Surat from January 2023 to April 2023.
  • Asst. Professor (Contractual) at Department of CSE, MBIT (Previously MBICT), Anand, Gujarat from June 2015 to October 2017.

  • Software Defined Network
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Inter-disciplinary Research

SCI Publications:

  1. Tejas M. Modi, Kuna Venkateswararao, Pravati Swain. “Integration of SDN into UAV, Edge Computing, & Blockchain: A Review, Challenges, & Future Directions”, Computer Science Review, Volume 58, 2025. (Elsevier,IF:12.7)
  2. Tejas M. Modi, Pravati Swain. “Hybrid Deep LearningModels and Link Probability Based Routing in Software Defined-DCN”, The Journal of Supercomputing, Volume 79, Pages: 9771–9794, 2023. (Springer, IF: 2.7)
  3. Tejas M. Modi, Pravati Swain. “Enhanced Routing Using Recurrent Neural Networks in Software-Defined Data Center Network”, Concurrency and Computation: Practice and Experience (CCPE), Volume 35 (5), pages: e7557, 2023. (Wiley, IF: 1.5)
  4. Tejas M. Modi, Pravati Swain. “Intelligent routing using convolutional neural network in software-defined data center network”, The Journal of Supercomputing, Volume 78, Pages: 13373–13392, 2022. (Springer, IF:2.7)

Scopus Publications:

  1. Kuna Venkateswararao, Tejas M. Modi, Pravati Swain, Srinivasa Rao Bendi. “Traffic Adaptive Small Cell Planning in HeterogeneousNetworks”, International Journal of ComputerNetwork and Information Security (IJCNIS), Volume 17 (2), pp.88-100, 2025, MECS Press.
  2. Tejas M. Modi, Kuna Venkateswararao, Pravati Swain. “Deep Learning Based Traffic Management in Knowledge Defined Network”, International Journal of Intelligent Systems and Applications (IJISA), Volume 16 (6), Pages: 73–83, 2024, MECS Press.

  1. Kuna Venkateswararao, Saaketh Choudarapu, Tejas M. Modi,TMNVamsi, I Sundara Siva Rao, J. N.V.R. Swarup Kumar.”Eco Harvesting Using 5G Technology”, In Proceedings of International Conference on Computing Technologies & Data Communication (ICCTDC), pp. 01-08, 2025.
  2. Khatsuria Yash Vijaybhai, Kuna Venkateswararao, Tejas Modi, Pravati Swain. “A Novel Optimization Strategy for Computation Offloading in the UAV-assisted Edge Computing”, In Proceedings of OITS International Conference on Information Technology (OCIT), pp. 463-468, 2022.
  3. Pravati Swain, Uttam Kamalia, Raj Bhandarkar,Tejas Modi. “CoDRL: Intelligent packet routing in SDN using convolutional deep reinforcement learning”, In Proceedings of the IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pp. 1-6, 2019.
  4. Tejas Modi, Pravati Swain. “FlowDCN: Flow scheduling in software defined data center networks”, In Proceedings of the 3rd IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), pp. 1-5, 2019.

  1. Vishal K. Pandey, Tejas M. Modi, Harnessing AI: The Role of Vision Transformers, GANs, and Hybrid Models in Modern Healthcare, in Next Generation Deep Learning in Healthcare Systems and Biomedical Engineering Modern Healthcare, CRC Press (Accepted, Under Production)

  1. Title: A System and Method for Obtaining Balanced Electroencephalography (EEG) Signals Based on an Optimization Technique. (Joint Inventor), Application No.:202306945, Application Date: 10/07/2023, Granted on: 28/02/2024, Republic of South Africa

  1. Expert Speaker in SikshaVid FDP organised at ADANI University in July 2025.

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