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I am an associate professor in the Department of Electrical and Computer Engineering at . I received the BE degree in Telecommunications Engineering from , Karnataka, India in 2005, the MS degree and the PhD degree, both in Electrical Engineering from in 2007 and 2010, respectively. My research areas are Signal Processing, Machine Learning and Artificial Intelligence, and STEM �Ӱ���̳. I am a member of the Tau Beta Pi and the Eta Kappa Nu honor societies.

I am also the director of the

�Ӱ���̳ Background

Electrical Engineering Ph.D. - 2010 Arizona State University
Electrical Engineering M.S - 2007 Arizona State University
Telecommunications Engineering B.E. - 2005 Visvesvaraya Technological University

Courses Taught

• Digital Signal Processing
• Systems and Signal Processing
• Detection and Estimation Theory
• Adaptive Signal Processing
• Signal Processing and Applications
• Digital Control

Teaching Interests

Digital Signal Processing, digital and wireless communications, statistical and adaptive signal processing, signals and systems

Research Interests

Signal processing, machine learning, complex networks, and applications including cybersecurity, behavioral biometrics, and continuous authentication, STEM �Ӱ���̳

Awards

• �Ӱ���̳ Outstanding Advisor Award, 2019
• Outstanding Teaching Award - �Ӱ���̳ HKN - 2015-2016
• Graduate Teaching Excellence Award (awarded by the Graduate and Professional Students Association, Arizona State University): Nominated thrice; won for the year 2008-2009.

Patents

• M.K. Banavar, K. Mack, “Localization using wireless signals,” United States Patent 10,117,051, October 30, 2018.
• Maximum Likelihood Localization in the Presence of Channel Uncertainties, U.S. Patent Grant No. US9507011B2, Publication 2016-11-29 (X. Zhang, C. Tepedelenlioglu, M.K. Banavar, A. Spanias,applicants).
• Energy-Efficient Distributed Estimation using Nonlinear Amplifiers, U.S. Patent Grant No. US9461676B2, Publication 2016-10-04, (R. Santucci, C. Tepedelenlioglu, A. Spanias, M.K. Banavar, applicants).

Publications

• J. Križaj, R. O. Plesh, M. Banavar, S. Schuckers, and V. Štruc, "Deep Face Decoder: Towards understanding the embedding space of convolutional networks through visual reconstruction of deep face templates," Engineering Applications of Artificial Intelligence, vol. 132, pp. 107941, 2024.
• C. Sahu, M. Banavar and S. Schuckers, “A novel non-linear transformation based multi-user identification algorithm for fixed text keystroke behavioral dynamics,” IEEE Transactions on Biometrics, Behavior, and Identity Science, 2022.
• P. Sattigeri, J. Thiagarajan, K. Ramamurthy, A. Spanias, M. Banavar, A. Dixit, J. Fan, M. Malu, K. Jaskie, S. Rao, U. Shanthamallu, V. Narayanaswamy, S. Katoch, “Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors,” International Journal of Virtual and Personal Learning Environments (IJVPLE), vol. 12, no. 1, pp. 1-17, 2022.
• M.K. Banavar, S. Wickramasinghe, M. Achalla, J. Sun, "Ordinal UNLOC: Target Localization With Noisy and Incomplete Distance Measures," in IEEE Internet of Things Journal, vol. 8, no. 23, pp. 17111-17119, Dec. 2021.
• M.K. Banavar, S. Rivera, B. Ayotte, K.V. Mack, D. Barry, A. Spanias, C. Sahu, T. Yang, “Teaching Signal Processing Applications using an Android Echolocation App,” Computers in �Ӱ���̳ Journal, vol. 12, no. 1, 2021.
• B. Ayotte, M. Banavar, D. Hou and S. Schuckers, "Fast Free-text Authentication via Instance-based Keystroke Dynamics," in IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), 2020.
• D.M. Barry, H. Kanematsu, N. Ogawa, K. Nakahira, M. Banavar, S. Rivera, “STEM activities for exploring Mars using innovative e-learning,” Procedia Computer Science, vol. 159, pp. 1126-1134, 2019.
• X. Zhang, C. Tepedelenlioglu, M.K. Banavar, A. Spanias, G. Muniraju, “Location Estimation and Detection in Wireless Sensor Networks in the Presence of Fading,” Physical Communications (PHYCOM), vol. 32, pp. 62-74, February 2019.
• J. Sun, T. Yang, K.V. Mack, M.K. Banavar, “UNLOC: Optimal unfolding localization from noisy distance data,” Sampling Theory in Signal and Image Processing, vol. 17, no. 2, pp. 183-195, 2018.