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Endowed Chair and Professorships Titles
Julian T. Hightower Chair
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Christopher J. Rozell received a B.S.E. degree in Computer Engineering and a B.F.A. degree in Music in 2000 from the University of Michigan, received M.S. and Ph.D. degrees in Electrical Engineering in 2002 and 2007 from Rice University, and was a postdoctoral scholar at the Redwood Center for Theoretical Neuroscience at the University of California, Berkeley.

Dr. Rozell's research interests are in computational neuroengineering, an intersection of neuroscience, data science, neurotechnology and computational modeling that advances the understanding of brain function and the design of effective interventions. His research has a particular focus on exploiting closed-loop interactions between biological and artificial intelligence to create precision models and algorithms, with a clinical focus on psychiatric disorders such as treatment resistant depression.

His scholarly activity also includes research and creative work that advances our understanding of the societal impacts of emerging technologies such as neurotechnology and AI.

Dr. Rozell is proud to be a first-generation scholar who is committed to accessibility in our scientific communities. He is a co-founder and member of the Board of Directors of Neuromatch, Inc., a global nonprofit increasing access to scientific knowledge.

  • Computational neuroengineering
  • Machine learning & AI
  • Computational psychiatry
  • Neurotechnology & neuromodulation
  • Societal impacts & public engagement
Distinctions & Awards
  • The Neuro – Irv and Helga Cooper Foundation Open Science International Prize to Neuromatch, Inc. (2022)
  • Class of 1940 W. Howard Ector Outstanding Teacher Award (2019)
  • James S. McDonnell Foundation 21st Century Science Initiative Award (2014)
  • National Science Foundation CAREER Award (2014)
  • CETL/BP Junior Faculty Teaching Excellence Award (2013)
  • S. Alagapan, S. Heisig, K Choi, P. Riva-Posse, A. Crowell, V. Tiruvadi, M. Obatusin, A. Veerakumar, A. Waters, R. Gross, S. Quinn, L. Denison, M. O’Shaughnessy, M. Connor, G. Canal, J. Cha, R. Hershenberg, T. Nauvel, F. Isbaine, M. Afzal, M. Figee, B. Kopell, R. Butera, H. Mayberg, and C. Rozell. Cingulate dynamics track depression recovery with deep brain stimulation. Nature, September 2023.
  • M. O’Shaughnessy, W.G. Johnson, L. Tournas, C. Rozell, and K. Rommelfanger. Neuroethics guidance documents: Principles, analysis, and implementation strategies. Journal of Law and the Biosciences, July 2023.
  • M. O’Shaughnessy, D Schiff, L. Varshney, C. Rozell, and M. Davenport. What governs attitudes toward artificial intelligence adoption and governance? Science and Public Policy, 50(2):161–176, April 2023.
  • G. Canal, Y. Diaz-Mercado, M. Egerstedt, and C. Rozell. A low-complexity brain-computer interface for high-complexity robot swarm control. IEEE in Transactions on Neural Systems & Rehabilitation Engineering, 31:1816, March 2023.
  • M. O’Shaughnessy, G. Canal, M. Connor, M. Davenport, and C. Rozell. Generative causal explanations of black-box classifiers. In Neural Information Processing Systems (NeurIPS), December 2020.
  • G. Canal, S. Fenu, and C. Rozell. Active ordinal tuplewise querying for similarity learning. In AAAI Conference on Artificial Intelligence (AAAI), New York, NY, February 2020.
  • A. Eftekhari, H.L. Yap, M.B. Wakin, and C.J. Rozell. Stabilizing embedology: Geometry-preserving delay-coordinate maps. Physical Review E, 97(2):022222, February 2018.
  • A.S. Charles, A. Balavoine, and C.J. Rozell. Dynamic filtering of time-varying sparse signals via L1 minimization. IEEE Transactions on Signal Processing, 64(21):5644–5656, November 2016.
  • M. Zhu and C.J. Rozell. Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system. PLoS Computational Biology, 9(8):e1003191, August 2013.
  • A. Balavoine, J. Romberg, and C.J. Rozell. Convergence and rate analysis of neural networks for sparse approximation. IEEE Transactions on Neural Networks and Learning Systems, 23(9):1377–1389, September 2012.
  • A.S. Charles, B.A. Olshausen, and C.J. Rozell. Learning sparse codes for hyperspectral imagery. IEEE Journal of Selected Topics in Signal Processing, 5(5):963–978, September 2011.
  • C.J. Rozell, D.H Johnson, R.G. Baraniuk, and B.A. Olshausen. Sparse coding via thresholding and local competition in neural circuits. Neural Computation, 20(10):2526–2563, October 2008.