Todd P. Coleman

Assistant Professor
Coordinated Science Laboratory
Dept. of Electrical and Computer Engineering
University of Illinois at Urbana-Champaign

also affiliated with:

Contact Info:
c o l e m a n t A T you eye you see D O T e d u

(note the "t" after my last name)

  • CSL office:
    118 Coordinated Science Laboratory, 217-333-0880

    • Fax: 217-244-1642

    Campus Mail Code: MC-228

    University of Illinois at Urbana-Champaign

    1308 W. Main

    Urbana, IL 61801


  • Beckman office/lab:
    2143 Beckman Institute, 217-333-0880 (office)

    • 2440 Beckman Institute, 217-333-9125 (lab)

    Campus Mail Code: MC-251

    University of Illinois at Urbana-Champaign

    405 N. Mathews Avenue

    Urbana, IL 61801


    Education:


    Teaching:

    Research Interests:

    • Information Theory, Communications, Message-Passing Algorithms, Stochastic Control, Operations Research, Security & Information Forensics, Statistical Signal Processing, Computational Neuroscience
    • Publications

    Research Areas:

    Information Theory:
    • Developing theoretical limits of reliable communication in multiterminal settings for wireless applications, with an emphasis on the desirable properties of optimal architectures
    • Developing algebraic codes and low-complexity message-passing algorithms for reliable communication in multiterminal and point process channels with performance approaching theoretical boundaries

    Statistical Inference:
    • Performing provably good nonparametric statistical inference with low-complexity methods
    • Characterizing the statistical structure of point processes with likelihood methods, using state-space and convex optimization approaches

    Computational Neuroscience:
    • Modeling dynamic representations between stimuli and neural activity in a canonical way, with measures of accuracy that can be quantified statistically

    • Developing practical information fusion algorithms for mixed-modality, varying time-scale neural signal analysis

    • Developing new design methodologies and signal processing algorithms for neural interfaces and prosthetics applications

    Students:

    Graduate Students:
    • Avon Fernandes, MS candidate, Dept of ECE (co-supervised by Maxim Raginsky)

      • Low-Complexity Universal Architectures for Distributed Rate-Constrained Nonparametric Statistical Learning in Sensor Networks
    • Julian Jarzebowski, MS candidate, Dept of ECE

      • Applications of Stochastic Control and Information Theory to Enhance the Performance of Neural Communication Prostheses
    • Matt Sharrock, MD/PhD candidate, Neuroscience Program

      • Computational Neuroscience Modeling with Applications to Designing Novel Neurally Controlled Devices
    • Andrea Trevino, MS candidate, Dept of ECE

      • Statistical Point Process Analysis of Auditory Nerve Spiking with Applications to Improving Speech Recognition in Auditory Prostheses
    • Siva Kumar Gorantla , MS candidate, Dept of ECE

      • Multiterminal Information Theory
    Undergraduate Students:
    • Cyrus Omar, Depts of CS and Mollecular & Cellular Biology

      • Software Development and Signal Processing Algorithm Design for Neurally Controlled Devices
    • Katie Snell, Dept of ECE

      • Software Development and Signal Processing Algorithm Design for Neurally Controlled Devices
    • David Rockwood, Dept of ECE

      • Software Development and Signal Processing Algorithm Design for Neurally Controlled Devices
    • Arshdeep Singh ( summer ITI intern from Indian Institute of Technology )

      • Statistical Point Process Analysis of Keystroke Data for Network Security Applications

    Current Research Collaborators:

    Links:

    Todd P. Coleman