Steven Fernandes

Steven Fernandes began his postdoctoral research at the University of Alabama at Birmingham, where he worked on NIH-funded projects. He also conducted postdoctoral research at the University of Central Florida. This research included working on DARPA, NSF, and RBC funded projects. His publications include research articles in highly selective artificial intelligence venues. He received his Ph.D., M.Tech, and B.E. in Electronics and Communication Engineering from Karunya Institute of Technology and Sciences, Manipal Institute of Technology, and Visvesvaraya Technological University respectively. His current area of research is focused on using artificial intelligence techniques to extract useful patterns from big data. This includes robust computer vision and natural language processing applications using deep learning and computer-aided diagnosis using medical image processing.

Recent Publications

  • Ortiz, E.U., Shaikh, M.A., Salter, M.I., Wilkinson, S.R.W.Y., Pourtabatabaie, A., Vintila, I.M., Fernandes, S. and Jha, S.K., Royal Bank of Canada, 2021. Systems and methods for dynamic passphrases. U.S. Patent Application 17/129,631.

  • Pannu, J.S., Raj, S., Fernandes, S.L., Chakraborty, D., Rafiq, S., Cady, N. and Jha, S.K., 2020. Design and Fabrication of Flow-Based Edge Detection Memristor Crossbar Circuits. IEEE Transactions on Circuits and Systems (TCAS) II: Express Briefs, 67(5), pp.961-965.

  • Raj, S., Pannu, J.S., Fernandes, S.L., Ramanathan, A., Pullum, L.L. and Jha, S.K., 2020. Attacking NIST Biometric Image Software using Nonlinear Optimization. Pattern Recognition Letters (PRL), 131, pp.79-84.

  • Fernandes, S., Raj, S., Ewetz, R., Singh Pannu, J., Kumar Jha, S., Ortiz, E., Vintila, I. and Salter, M., 2020. Detecting Deepfake Videos using Attribution-Based Confidence Metric. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (pp. 308-309).

  • Jha, S., Raj, S., Fernandes, S., Jha, S.K., Jha, S., Jalaian, B., Verma, G. and Swami, A., 2019. Attribution-Based Confidence Metric For Deep Neural Networks. In Advances in Neural Information Processing Systems (NeurIPS) (pp. 11826-11837).

Research Interests

  • Deep Learning
  • Computer Vision
  • Natural Language Processing
  • Deep Reinforcement Learning


  • Fall 2022:
    • CSC 221 - Introduction to Programming
    • CSC 222 - Object-Oriented Programming
    • CSC 548 - Software Engineering