Dr. Rahul Thakur

Brief Profile:

Dr. Rahul Thakur is an Assistant Professor in the Department of Electronics and Communication Engineering at Delhi Technological University (DTU), Delhi, since July 2020. He received his Ph.D. from DTU (2025), M.Tech. from NSUT East Campus (2017), and B.Tech. from Guru Gobind Singh Indraprastha University (2015). His research interests include Machine Learning, Deep Learning, Digital Image Processing, Image Forensics, and Computer Vision. He has an h-index of 6 with over 235 citations and received the Research Excellence Award (2021) at DTU. He qualified UGC-NET (JRF & Assistant Professor) and GATE in Electronics and Communication Engineering and is a member of IEEE, ISTE, IETE, and CSI. He has also contributed to academic development by organizing short-term courses, workshops, and a Faculty Development Programme, and by leading training programmes on advances in Computer Vision, while undertaking various academic and administrative responsibilities at departmental and university levels.

Research Profile:

• h- index: 06; i-10 index: 03; Citations: 255
• Orcid ID: 0000-0002-2672-6067; Scopus ID: 57216845790
• Web of Science Researcher ID: KRP-8282-2024
• Google Scholar: https://scholar.google.com/citations?user=e51fOvMAAAAJ&hl=en&oi=sra
• Webpage: https://sites.google.com/view/rahulthakur/home

• Optical Communication  (UG)
• Wireless Communication  (UG)
• Machine Learning (UG)
• Data Analytics (PG)
• Digital Electronics (UG)
• Soft Computing (UG)
• Machine Learning in VLSI Design (PG)

• Life Member of the Indian Society for Technical Education (ISTE).

• Lifetime member of the Computer Society of India (CSI).

• Fellow of the Institution of Electronics and Telecommunication Engineers (IETE).

• IEEE Member.

Recent Publications:

• Jayasinghe, J.K., Kulathunga, G.P. & Thakur, R. MOCRN-A Novel Physics-Guided Fault Modeling and Multimodal Neural Network for Fault Identification and Degradation Estimation in Analog Circuits. Circuits Syst Signal Process (2026). https://doi.org/10.1007/s00034-026-03590-7
• Thakur, R., Kavindu Jayasinghe, J.P.T. & Mehta, P. Interpretable and robust multimodal fake news detection with evidence fusion and reliable reasoning. Int J Data Sci Anal 22, 4 (2026). https://doi.org/10.1007/s41060-025-00895-9.

• K. Bindra, H. Gupta, D. Bhattacharya, and R. Thakur, “HyperSwin: preventing deepfake proliferation with swin-efficient fusion in a hyperledger ecosystem,” Signal, Image and Video Processing, vol. 19, no. 8, May 2025, doi: https://doi.org/10.1007/s11760-025-04183-8.

• R. Thakur and R. Rohilla, “An effective framework based on hybrid learning and kernel principal component analysis for face manipulation detection,” Signal, Image and Video Processing, Apr. 2024, doi: https://doi.org/10.1007/s11760-024-03117-0.

• R. Thakur and R. Rohilla, "LFRViT: Laplacian Filter Residual-based Vision Transformer for Multiple Image Forgery Detection," 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kamand, India, 2024, pp. 1-5, doi: 10.1109/ICCCNT61001.2024.10724100.
• R. Thakur, A. K. Samanta, Amrit and D. Garg, "DeepFake Detection using Transfer Learning," 2023 World Conference on Communication & Computing (WCONF), RAIPUR, India, 2023, pp. 1-6, doi: 10.1109/WCONF58270.2023.10234965.
• P. Agarwal, N. Yadav, R. Kumar, and R. Thakur, “Convolutional Neural Network for COVID-19 Detection,” in Proceedings of International Conference on Data Science and Applications, 2023, pp. 557–569. Lecture Notes in Networks and Systems, vol 552. Springer, Singapore. https://doi.org/10.1007/978-981-19-6634-7_39.
• R. Thakur, S. Raj, S. Pandey, and others, “Driver Drowsiness Detection System Using Machine Learning,” in Advanced Production and Industrial Engineering, IOS Press, 2022, pp. 31–38. DOI: 10.3233/ATDE220718.
• R. Thakur, H. Singh, C. S. Narula, and Harsh, “An Efficient Deep Neural Network-Based Framework for Building an Automatic Attendance System,” in Proceedings of the International Conference on Paradigms of Communication, Computing and Data Sciences, 2022, pp. 611–619. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-5747-4_52.
• T. Bhagat and R. Thakur, "Miller Compensation using CMOS OPAMP employing Current Buffer," 2022 3rd International Conference for Emerging Technology (INCET), Belgaum, India, 2022, pp. 1-5, doi: 10.1109/INCET54531.2022.9824739.
• T. Bhagat and R. Thakur, "Automatic Recognition of License Plates," 2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), Hyderabad, India, 2021, pp. 118-122, doi: 10.1109/ICETCI51973.2021.9574072.
• R. Thakur and R. Rohilla, “Recent advances in digital image manipulation detection techniques: A brief review,” Forensic Sci. Int., vol. 312, p. 110311, 2020, doi: 10.1016/j.forsciint.2020.110311.
• R. Thakur and R. Rohilla, "Copy-Move Forgery Detection using Residuals and Convolutional Neural Network Framework: A Novel Approach," 2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC), Greater Noida, India, 2019, pp. 561-564, doi: 10.1109/PEEIC47157.2019.8976868.

For more details, please visit my webpage: https://sites.google.com/view/rahulthakur/home

• Research Excellence Award at Delhi Technological University (DTU), Delhi.

• Qualified for JRF & Assistant Professor, UGC NET (Electronic Science).

• Qualified, GATE (Electronics and Communication).

• Co-Principal Investigator (Co-PI) of the DTU-sponsored research project titled “AI-based Prediction Model for Myopia Progression in Children”, sanctioned under the CCDR/Koshika Foundation.

• Mr. Sudhir Kumar (Continuing)