Jitendra K Tugnait
James B Davis Professor Contact313 Broun Hall, Auburn AL 36849-5201 |
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Opening for a Post-Doctoral Research Position
A Post-Doc Research Position in Machine Learning for Signal Processing is available immediately. Will be supported by NSF Grant CCF-2308473, CIF: Small: Learning Sparse Vector and Matrix Graphs from Time-Dependent Data, PI: J.K. Tugnait. The position requires a strong background in (or willingness and ability to learn) statistical signal processing, optimization, (high-dimensional) statistics and graph signal processing.Interested persons should contact Prof. Tugnait at tugnajk@auburn.edu AND apply through https://www.auemployment.com/postings/49294 (college of engineering postdoc pool 2024-2025: HR requirement).
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 processingMachine 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 radioMultisensor Multitarget Tracking
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Some recent papers
J.K. Tugnait, "On conditional independence graph learning from multi-attribute Gaussian dependent time series," IEEE Open Journal of Signal Processing , vol. 6, pp. 705-721, 2025. [pdf]
J.K. Tugnait, "Multi-attribute graph estimation with sparse-group non-convex penalties," IEEE Access, vol. 13, pp. 80174-80190, 2025. [pdf]
J.K. Tugnait, "Learning multi-attribute differential graphs with non-convex penalties," IEEE Access, vol. 13, pp. 67065-67078, 2025. [pdf]
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]
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