Jitendra K Tugnait

James B Davis Professor
Department of Electrical and Computer Engineering
Auburn University

Contact

313 Broun Hall, Auburn AL 36849-5201
Tel: (334) 844-1846
Fax: (334) 844-1809
tugnajk@auburn.edu

Current Research Interests

Statistical Signal Processing Conditional independence graphs of random vectors and matrices, and multivariate time series; Improper/non-circular complex-valued random signal processing; Robust signal processing
Machine Learning for Signal Processing Graphical modeling of random vectors and matrices, and multivariate time series; Differential (dependency) graphical modeling

Past Research Interests

Wireless Physical & Secure Communications Physical layer security; Massive MIMO; Cognitive radio
Multisensor Multitarget Tracking

► csauthors.net ► dblp ► Google Scholar ► Semantic Scholar

Some recent papers

J.K. Tugnait, "Multi-attribute graph estimation with sparse-group non-convex penalties," IEEE Access, vol. 13, pp. 80174-80190, 2025.

J.K. Tugnait, "Learning multi-attribute differential graphs with non-convex penalties," IEEE Access, vol. 13, pp. 67065-67078, 2025.

J.K. Tugnait, "Estimation of multi-attribute differential graphs with non-convex penalties," in Proc. 2025 IEEE Intern. Conf. Acoustics, Speech & Signal Processing (ICASSP 2025), pp. 1-5, Hyderabad, India, April 6-11, 2025.

J.K. Tugnait, "On sparse high-dimensional graph estimation from multi-attribute data," in Proc. 58th Asilomar Conference on Signals, Systems and Computers (ASILOMAR 2024), pp. 1053-1057, Pacific Grove, CA, Oct. 27-30, 2024.

J.K. Tugnait, "Conditional independence graph estimation from multi-attribute dependent time series," in Proc. IEEE International Workshop on Machine Learning for Signal Processing (MLSP-2024), pp. 1-6, London, UK, Sept. 22-25, 2024.

J.K. Tugnait, "Learning sparse high-dimensional matrix-valued graphical models from dependent data," IEEE Trans. Signal Processing, vol. 72, pp. 3363-3379, 2024. [pdf]

J.K. Tugnait, "Delay embedding for matrix graphical model learning from dependent data," in Proc. 2024 IEEE Intern. Conf. Acoustics, Speech & Signal Processing (ICASSP 2024), pp. 6180-6184, Seoul, South Korea, April 14-19, 2024.

J.K. Tugnait, "Learning high-dimensional differential graphs from multi-attribute data," IEEE Trans. Signal Processing, vol. 72, pp. 415-431, 2024. [pdf]

Link to our graduate program.

Date of latest revision: mon may 12 2025