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Steven Fernandes

Steven Fernandes is an Assistant Professor of Computer Science at Creighton University, where he teaches and mentors students in computer science, data science, and health informatics since joining in July 2020. His research focuses on developing advanced deep learning models for computer vision, medical imaging, and natural language processing applications. Before his current role, he completed postdoctoral research at the University of Central Florida in the Department of Computer Science from September 2018 to June 2020, contributing to DARPA, NSF, and RBC-funded projects in the areas of deep learning and computer vision. He also conducted postdoctoral research at the University of Alabama at Birmingham in the Department of Electrical and Computer Engineering from July 2017 to August 2018, working on NIH-funded projects in deep learning and medical image processing. Steven Fernandes earned his Ph.D. in Electronics and Communication Engineering from the Karunya Institute of Technology and Sciences, focusing on computer vision and machine learning. He holds an M.Tech in Microelectronics from the Manipal Institute of Technology and a B.E. in Electronics and Communication Engineering from Visvesvaraya Technological University. 

Selected 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, 2022. Systems and methods for dynamic passphrases. U.S. Patent 11,429,712

  • Pannu, J.S., Raj, S., Fernandes, S., 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., 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

Teaching

  • CSC 221 - Introduction to Programming - Fall 2020, Spring 2021, Fall 2021, Spring 2022

  • CSC 222 - Object Oriented Programming - Fall 2021, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Fall 2024

  • DSC 366 - Machine Learning - Spring 2023, Spring 2024, Spring 2025

  • CSC 414 - Introduction to Computer Organization - Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025

  • CSC 497 - Directed Independent Research - Fall 2024, Spring 2025

  • CSC 499 – Independent Study - Summer 2022

  • CSC 548 - Software Engineering - Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024

  • DSC 565 - Building Generative AI Applications - Fall 2025

  • CSC 590 - Neural Networks and Deep Learning - Spring 2021 (Special Topics)

  • CSC 590 - Cyberinfrastructure - Spring 2025 (Special Topics) 

  • DSC 599 - Data Science Senior Capstone - Fall 2023, Fall 2024

  • HIF 603 -  Introduction to Analytics in Health Informatics - Fall 2024

  • HIF 605 - Advanced Analytics in Health Informatics - Spring 2025

  • RSP 101 - Fall 2022, Spring 2022, Fall 2023, Spring 2024 

Professional Membership

  • Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) 

Email

  • steven.fernandes@ieee.org