Panos P. Markopoulos, Ph.D.

  • Mailing address: 79 Lomb Memorial Drive, GLE-3081, Rochester Institute of Technology, Rochester, NY 14623

  • Tel.: +1 585-475-7917 - Fax: 585-475-5845

  • E-mail: panos [at]

  • Google Scholar - ResearchGate - Twitter


  • [Aug2020] New paper on Dynamic L1-norm Tucker Tensor decomposition, submitted to IEEE JSTSP.

  • [Aug2020] New paper on L1-RESCAL accepted for publication to IEEE Asilomar CSSC.

  • [Jun2020] Joined US AFRL, Information Directorate, as Summer Visiting Research Faculty.

  • [Oct2019] Excited and thankful to receive the AFOSR YIP award.


I am a tenure-track Assistant Professor with the department of Electrical and Microelectronic Engineering (EME) at Rochester Institute of Technology, where I direct the Machine Learning Optimization and Signal Processing (MILOS) Lab. I am also on the extended faculty of RIT's Ph.D. Program in Computing and Information Sciences and Ph.D. Program in Mathematical Modeling. In the Summers of 2018 and 2020, I was a Visiting Research Faculty at the U.S. Air Force Research Laboratory (AFRL), Information Directorate. I obtained the Ph.D. degree in Electrical Engineering from University at Buffalo, The State University of New York, in August 2015, advised by Professor Dimitris A. Pados.

My research is theory and optimization algorithms for machine learning and data analysis. In these areas, I have co-authored multiple journal and conference articles. My research sponsors include the US National Science Foundation (NSF), the US National Geo-Spatial Intelligence Agency, the US Air Force Office of Scientific Research (AFOSR), and the Air Force Research Laboratory (AFRL). In October 2019, I received the Young Investigator Program (YIP) Award, from the AFOSR.

I have co-organized and chaired a large number of international meetings and conferences, including the 2019 IEEE International Workshop on Machine Learning for Signal Processing (IEEE MLSP 2019) and the Symposium on Tensor Methods for Signal Processing and Machine Learning at IEEE GlobalSIP 2018 and IEEE GlobalSIP 2019. I have also received multiple awards from the RIT Kate Gleason College of Engineering for exemplary performance in research and teaching.

Professional Positions


Research Areas

Together with my students and collaborators, I conduct research on theory and algorithms for optimization for machine learning and data analysis. Topics of interest include:

  • Theory/algorithms for Lp-norm subspace data analysis.

  • Inference and learning in adversarial environments.

  • Tensor decompositions and analysis of big and multi-modal data.

  • Mathematical understanding and enhancement of deep neural networks.


Selected Awards and Distinctions

  • Young Investigator Program (YIP) Award, Air Force Office of Scientific Research (AFOSR), 2020.

  • Exemplary Performance in Research, Kate Gleason College of Engineering, RIT, 2019, for the research proposals submitted in 2018.

  • Exemplary Performance in Teaching, Kate Gleason College of Engineering (KGCOE), RIT, 2019.

  • Exemplary Performance in Research, Kate Gleason College of Engineering, RIT, 2018, for the research proposals submitted in 2017.

  • Runner-up Poster Award, IEEE Western New York Image and Signal Processing Workshop, 2018, for the paper "Gait recognition based on tensor analysis of acceleration data from wearable sensors."

  • Student Travel Grant Award, SPIE Defense and Commercial Sensing, 2017, for the paper "Adaptive sparse-binary waveform design for all-spectrum channelization."

  • Exemplary Reviewer, IEEE Communications Society, 2017. "For contributions made in furthering the objectives of the Society as Exemplary Reviewer of IEEE Wireless Communications Letters, 2016."

  • Student Travel Grant Award, SPIE Defense, Security, and Sensing, 2014, for the paper "Direction finding with L1-norm subspaces."

  • Best Paper Award in Physical Layer Communications and Signal Processing, IEEE/VTS/EURASIP International Symposium on Wireless Communication Systems, 2013, for the paper "Some options for L1-subspace signal processing."

Professional Memberships

  • IEEE Signal Processing, Computer, and Communication Societies.

  • SIAM.

  • SPIE.

  • American Society for Engineering Education (ASEE).