Matthew Nokleby

Assistant Professor
Department of Electrical and Computer Engineering
Wayne State University
Detroit, MI

e-mail: matthew (dot) nokleby (at) wayne (dot) edu
office: 3115 ENGG

I am an assistant professor in the Department of Electrical and Computer Engineering at Wayne State University. I am the director of the Information Processing Lab, where we study information theory and signal processing with emphasis on machine learning, wireless communication, and sensor fusion in wireless networks.

My Curriculum Vitae, ResearchGate profile, and Google Scholar profile.

News:

  • "Multi-scale Spectrum Sensing in Small-Cell mm-Wave Cognitive Wireless Networks" accepted to IEEE International Conference on Communications, May 2017. Joint work with Nicolo Michelusi at Purdue, Urbashi Mitra at USC, and Robert Calderbank at Duke.
  • Presented work with PhD student Ishan Jindal and collaborator Xuewen Chen (professor of CS at WSU) at the IEEE International Conference on Data Mining in Barcelona, Dec. 2016: "Learning Deep Networks from Noisy Labels with Dropout Regularization" [slides].
  • "Low-Dimensional Shaping for High-Dimensional Lattice Codes" accepted to IEEE Transactions on Wireless Communications.
  • Two papers presented at the IEEE International Symposium on Information Theory in Barcelona: "Voronoi Constellations for High-dimensional Lattice Codes," with Nuwan Ferdinand and Behnaam Aazhang [slides], and "Rate-distortion Bounds on Bayes Risk in Supervised Learning," with Ahmad Beirami and Robert Calderbank [slides].
  • New journal paper submitted to IEEE Transactions on Information Theory: "Rate-distortion Bounds on Bayes Risk in Supervised Learning," with Ahmad Beirami and Robert Calderbank [preprint].
  • "Cooperative Compute-and-Forward" published in Jan. 2016 issue of IEEE Transactions on Wireless Communications.

Prospective graduate students: I welcome applications from prospective Ph.D. students. If you are interested, email me a CV that includes relevant coursework, grades, and GRE/TOEFL scores as well as a short cover letter describing your research ambitions. I seek indepentent, motivated students with knowledge of linear algebra, probability theory, and optimization. I particularly encourage students of color, women, and students from other underrepresented groups to apply.

I am also interested in working with graduate and undergraduate students for short-term directed study projects related to machine learning and wireless communications. Please contact me if you are interested.