Dr. Debbrota Paul Chowdhury

deb_profile
Assistant Professor – Grade II
Email: dchowdhury[at]cse.nits.ac.in
Date of Joining: 16.11.2023
Academic Experience: 04+
Google Scholar: Click Here

 

 

 

 

 

 

Academic Qualifications

  • Ph.D. from National Institute of Technology Rourkela
  • M.Tech  from Indian Institute of Information Technology Bhubaneswar
  • B.Tech from University Institute of Technology Burdwan

 

Area of Interest

  • Biometric Security
  • Image processing
  • Computer Vision
  • Machine Learning
  • Deep Learning

 

Short Biographical Sketch

Dr. Debbrota Paul Chowdhury is currently working as an Assistant Professor in the Department of Computer Science and Engineering at National Institute of Technology Silchar, Assam. He also served as an Assistant Professor in the Department of Computer Science & Engineering  at Sister Nivedita University (SNU), Kolkata, India, and at Kalinga Institute of Industrial Technology Bhubaneswar, India. He worked as an Adhoc faculty at the National Institute of Technology Warangal, India. He earned his Ph.D. degree in Computer Science & Engineering from the National Institute of Technology Rourkela, India in 2021. He completed his master’s in Computer Science & Engineering from the International Institute of Information Technology Bhubaneswar, India in 2016. He completed his bachelor’s degree in Computer Science and Engineering from the University Institute of Technology, Burdwan, India in 2014. His area of interest includes Biometric Security, Computer Vision, Machine Learning, Deep Learning, Image/Video Processing.

 

 Teaching at NIT Silchar

  • CS205 – Computer Architecture & Organization (UG) [current]
  • CS207 – Signals and Data Communication (UG) [current]
  • CS212 – Object Oriented Programming Laboratory (UG) [current]
  • CS214 – Signals and Data Communication Laboratory (UG) [current]

 

Publications

J = Journal, C = Conference

[J05] D. P. Chowdhury, S. Bakshi, C. Pero, G. Olague, and P. K. Sa. Privacy Preserving Ear Recognition System Using Transfer Learning in Industry 4.0. IEEE Transactions on Industrial Informatics, 2022, DOI: 10.1109/TII.2022.3196343.

[J04] D.P. Chowdhury, R. Kumari, S. Bakshi, M.N. Sahoo, and A. Das. Lip as Biometric and Beyond: A Survey. Multimedia Tools and Applications, 2021.

[J03] D.P. Chowdhury, S. Bakshi, P.K. Sa, and B. Majhi. Semantic Ear Feature Reduction for Source Camera Identification. Multimedia Tools and Applications, 2019, DOI: 10.1007/s11042-019-7665-6.

[ J02] D. P. Chowdhury, S. Bakshi, P.K. Sa, and B. Majhi. Wavelet energy feature based source camera identification for ear biometric images. Pattern Recognition Letters, Elsevier, 2018, DOI: 10.1016/j.patrec.2018.10.009.

[J01] D. P. Chowdhury, S. Bakshi, G. Guo and P.K. Sa. On Applicability of Tunable Filter Bank Based Feature for Ear Biometrics: A Study from Constrained to Unconstrained. Journal of Medical Systems, Springer, 2018, 42(1), p.11, DOI: 10.1007/s10916-017-0855-8.

 

[C01] Z. Emersic, A. Kumar S.V., B.S. Harish, W. Gutfeter, J.N. Khiarak, A. Pacut, E. Hansley, M. Pamplona Segundo, S. Sarkar, H. Park, G. Pyo Nam, I.J. Kim, S.G. Sangodkar, U. Kacar, M. Kirci, L. Yuan, J. Yuan, H. Zhao, F. Lu, J. Mao, X. Zhang, D. Yaman, F.I. Eyiokur, K. B. Ozler, H.K. Ekenel, D.P. Chowdhury, S. Bakshi, P.K. Sa, B. Majhi, P. Peer, V. Struc, The Unconstrained Ear Recognition Challenge 2019 in 12th IAPR International Conference on Biometrics (ICB), 2019.