publications

Refereed Papers | Conference Abstracts | Book Chapters | Other Publications

Refereed Papers

	Affective bias predicts changes in depression during deep brain stimulation therapy B. Cui, M.M. Mocchi, B.A. Metzger, P. Kalva, J. Magnotti, J.G. Fiedorowicz, A.C. Waters, C. Kovach, Y.Y. Reed, R.K. Mathura, C. Steger, B.R. Pascuzzi, K. Kanja, A. Veerakumar, V. Tiruvadi, A. Crowell, L. Denison, C. Rozell, N. Pouratian, W. Goodman, P. Riva Posse, H.S. Mayberg and K.R. Bijanki. Frontiers In Human Neuroscience, vol. Volume 19 - 2025, March 2025. [bibtex] [url] [doi]
	Online Machine Teaching under Learner Uncertainty: Gradient Descent Learners of a Quadratic Loss B. Martin Urcelay, C.J. Rozell and M. Bloch. SIAM Journal on Mathematics of Data Science (SIMODS), March 2025. In press [bibtex]
	Proceedings of the 12th Annual Deep Brain Stimulation Think Tank: Cutting Edge Technology meets Novel Applications A.E. Martinez-Nunez, C.J. Rozell, S. Little, H. Schmidt S.L. Tan, W.M. Grill, M. Pajic, D. Turner, C. de Hemptinne, A. Machado, A. Becker, R.S. Raike, M. Malekmohammadi, Y. Pathak, L. Himes, D. Greene, L. Krinke, M. Arlotti, L. Rossi, J.T. Robinson, B.H. Bahners, V. Litvak, L. Milosevic, S. Ghatan, F. Schaper, M.D. Fox, N.M. Gregg, C. Kubu, J.J Giordano, N.G. Cascella, Y.-H. Nho, C. Halpern, H.S. Mayberg, K.S. Choi, H.N. Song, J. Cha, S. Alagapan, N. Dosenbach, E.M. Gordon, J. Ren, H. Liu, L.V. Kalia, D.M. Kusyk, A. Ramirez-Zamora, K.D. Foote, M.S. Okun and J.K. Wong. Frontiers in Human Neuroscience, January 2025. [bibtex] [url]
	Modeling Latent Dynamics of the Autonomic Nervous System in Response to Trauma Recall and Non-Invasive Vagus Nerve Stimulation A.H. Gazi, S. An, J.A. Sanchez-Perez, M. Chan, M. Nikbakht, D.J. Lin, S. Natarajan, K.A. Johnsen, J.D. Bremner, J. Hahn, O.T. Inan and C.J. Rozell. IEEE Transactions on Biomedical Engineering, January 2025. Under review [bibtex]
	Remote monitoring of cardiovascular autonomic dysfunction in synucleinopathies with a wearable chest patch J.A. Berkebile, A.H. Gazi, M. Chan, T.D. Albarran, C.J. Rozell, O.T. Inan and P.A. Beach. IEEE Sensors Journal, 25(4), pp. 7250-7262, January 2025. [bibtex] [url] [doi]
	Brain Biomarkers for Pain Sensitivity P. Shirvalkar and C.J. Rozell. JAMA Neurology, January 2025. [bibtex] [url] [doi]
	An application-based taxonomy for brain–computer interfaces J.T. Robinson, S.L. Norman, M.R. Angle, T.G. Constandinou, T Denison, J.P. Donoghue, R.M. Field, A. Forsland, S. Kouider, J. del R. Millán, J.A. Michaels, A. Orsborn, C. Pandarinath, J.A. Pruszynski, C.J. Rozell, N.P. Shah, M.M. Shanechi, M. Shoaran, S.A. Sheth, S.D. Stavisky, E. Trautmann, N. Vachicouras and C. Xie. Nature Biomedical Engineering, December 2024. [bibtex] [url]
	Enhancing Human-in-the-Loop Learning for Binary Sentiment Word Classification B. Urcelay, C. J. Rozell and M. Bloch. In IEEE Conference on Decision and Control (CDC), December 2024. [bibtex]
	Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics Y. Chen, N. Mudrick, K. Johnsen, S. Alagapan, A.S. Charles and C. Rozell. In Neural Information Processing Systems (NeurIPS), December 2024. (Acceptance rate 26%) [bibtex] [url]
	Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed K.A. Johnsen, N.A. Cruzado, Z.C. Menard, A.A. Willats, A.C. Charles, J. Markowitz and C. J. Rozell. November 2024. Under review. [bibtex] [url]
	Learning Internal Representations of 3D Transformations from 2D Projected Inputs M. Connor, B. Olshausen and C. Rozell. Neural Computation, 36(11), pp. 2505–2539, November 2024. [bibtex] [url]
	Neural Interoceptive Processing is Modulated by Deep Brain Stimulation to Subcallosal Cingulate Cortex for Treatment Resistant Depression E. Xu, S. Pitts, J. Dahill-Fuchel, S. Scherrer, T. Nauvel, J.G. Overton, P. Riva-Posse, A. Crowell, M. Figee, S. Alagapan, C.J. Rozell, K.S. Choi, H. Mayberg and A. Waters. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, November 2024. In press. [bibtex] [url] [doi]
	StressFADS: Learning Latent Autonomic Factors of Stress in the Context of Trauma Recall and Neuromodulation A.H. Gazi, M. Hsu H.-L. Chan, J.D. Bremner, C.J. Rozell and O.T. Inan. In International Conference on Body Sensor Networks (BSN), October 2024. [bibtex]
	LINOCS: Lookahead Inference of Networked Operators for Continuous Stability N. Mudrick, E. Yezerets, Y. Chen, C. Rozell and A.S. Charles. Transactions on Machine Learning Research, September 2024. [bibtex] [url]
	Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics N. Mudrick, Y. Chen, E. Yezerets, C. Rozell and A.S. Charles. Journal of Machine Learning Research, 25(59), pp. 1–44, April 2024. [bibtex] [html]
	Subcallosal Cingulate Deep Brain Stimulation Evokes Two Distinct Cortical Responses via Differential White Matter Activation A. Seas, M.S. Noor, K.S. Choi, A. Veerakumar, M. Obatusin, J. Dahill-Fuchel, V. Tiruvadi, E. Xu, P. Riva-Posse, C.J. Rozell, H.S. Mayberg, C.C. McIntyre, A.C. Waters and B. Howell. Proceedings of the National Academy of Sciences, 121(14), pp. e2314918121, March 2024. [bibtex] [url] [doi]
	Cortical signatures of sleep are altered following effective deep brain stimulation for depression J.J. van Rheede, S. Alagapan, T. Denison, P. Riva-Posse, C. Rozell, H. Mayberg, A.C. Waters and A. Sharott. Translational Psychiatry, 14(1), pp. 103, February 2024. [bibtex] [url]
	Manifold Contrastive Learning with Variational Lie Group Operators K. Fallah, A. Helbling, K.A. Johnsen and C.J. Rozell. Transactions on Machine Learning Research, February 2024. [bibtex] [url]
	Cingulate dynamics track depression recovery with deep brain stimulation 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. Nature, vol. 622, pp. 130–138, October 2023. [bibtex] [url] [doi]
	Neuroethics guidance documents: Principles, analysis, and implementation strategies M. O'Shaughnessy, W.G. Johnson, L. Tournas, C. Rozell and K. Rommelfanger. Journal of Law and the Biosciences, 10(2), pp. lsad025, October 2023. [bibtex] [url] [doi]
	Distance preservation in state-space methods for detecting causal interactions in dynamical systems M. O'Shaughnessy, M. Davenport and C. Rozell. August 2023. Under review. [bibtex] [url]
	Leveraging Physiological Markers to Quantify the Transient Effects of Traumatic Stress and Non-Invasive Neuromodulation A.H. Gazi, J.A. Sanchez-Perez, S. Natarajan, M. Chan, M. Nikbakht, D.J. Lin, J.D. Bremner, J. Hahn, O.T. Inan and C.J. Rozell. In International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), July 2023. \textbfSelected for oral presentation. [bibtex]
	What governs attitudes toward artificial intelligence adoption and governance? M. O'Shaughnessy, D Schiff, L. Varshney, C. Rozell and M. Davenport. Science and Public Policy, 50(2), pp. 161–176, April 2023. [bibtex] [url] [doi]
	Active Learning of Ordinal Embeddings: A User Study on Football Data C. Loeffler, K. Fallah, S. Fenu, D. Zanca, B. Eskofier, C.J. Rozell and C. Mutschler. Transactions on Machine Learning Research, April 2023. [bibtex] [url]
	Exploration of Acute Effects of Stimulation Frequency on Subcallosal Cingulate Dynamics in SCC DBS E.C. Fitoz, S. Alagapan, A. Waters, V. Tiruvadi, A. Veerakumar, M. Obatusin, K.S. Choi, A. Crowell, P. Riva-Posse, R. Butera, H. Mayberg and C.J. Rozell. In 2023 11th International IEEE/EMBS Conference on Neural Engineering (NER), April 2023. [bibtex]
	A low-complexity brain-computer interface for high-complexity robot swarm control G. Canal, Y. Diaz-Mercado, M. Egerstedt and C. Rozell. IEEE in Transactions on Neural Systems & Rehabilitation Engineering, vol. 31, pp. 1816–1825, March 2023. [bibtex] [url] [doi]
	Learning Identity-Preserving Transformations on Data Manifolds M. Connor, K. Fallah and C. Rozell. Transactions on Machine Learning Research, March 2023. [bibtex] [url]
	Pain is Reduced by Transcutaneous Cervical Vagus Nerve Stimulation and Correlated with Cardiorespiratory Variability Measures in the Context of Opioid Withdrawal A. H. Gazi, A. B. Harrison, T. P. Lambert, A. Nawar, M. Obideen, E.G. Driggers, V. Vaccarino, A. J. Shah, C. J. Rozell, M. Biokson, J. W. Welsh, O. T. Inan and D. J. Bremner. Frontiers in Pain Research, vol. 3, pp. 1031368, November 2022. [bibtex]
	Transcutaneous Cervical Vagus Nerve Stimulation Reduces Respiratory Variability in the Context of Opioid Withdrawal A. H. Gazi, A. B. Harrison, T. P. Lambert, M. Obideen, J. W. Welsh, V. Vaccarino, A. J. Shah, S. E. Back, C. J. Rozell, D. J. Bremner and O. T. Inan. In IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), September 2022. [bibtex]
	Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate E.E. Smith, K.S. Choi, A. Veerakumar, M. Obatusin, B. Howell, A. Smith, V. Tiruvadi, A.L. Crowell, P. Riva-Posse, S. Alagapan, C. Rozell, H.S. Mayberg and A.C. Waters. Frontiers in Human Neuroscience, vol. 16, August 2022. [bibtex] [url]
	Passively Captured Interpersonal Social Interactions and Motion from Smartphones Predicts Decompensation in Heart Failure: An Observational Cohort Study A. Cakmak, E. Alday, S. Densen, G. Najarro, P. Rout, C. J. Rozell, O.T. Inan, A.J. Shah and G.D. Clifford. JMIR Formative Research, 6(8), pp. e36972, August 2022. [bibtex]
	Variational Sparse Coding with Learned Thresholding K. Fallah and C. Rozell. In International Conference on Machine Learning (ICML), July 2022. \textbfSelected for oral presentation. (Acceptance rate 22%) [bibtex] [url]
	Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy and Traumatic Brain Injury J.K. Wong, H. Bergman, M. Muthuraman, S. Groppa, S.A. Sheth, H.M. Bronte-Stewart, K.B. Wilkins, M.N. Petrucci, E. Lambert, Y. Kehnemouyi, P. Starr, S. Little, J. Anso, R. Gilron, L. Poree, G.P. Kalamangalam, G. Worrell, K.J. Miller, N.D. Schiff, C.R. Butson, J. Henderson, J.W. Judy, A. Ramirez-Zamora, K.D. Foote, G. Deuschl, R. Wolke, P.A. Silburn, L. Li, G. Oyama, H. Kamo, S. Sekimoto, N. Hattori, J.J. Giordano, D. DiEuliis, J. Shook, D.D. Dougherty, A.S. Widge, H.S. Mayberg, J. Cha, K.S. Choi, S. Heisig, M. Obatusin, E. Opri, S.B. Kaufman, P Shirvalkar, C.J. Rozell, S. Alagapan, R.S. Raike, H. Bokil, D. Greene and M.S. Okun. Frontiers in Human Neuroscience, vol. 16, March 2022. [bibtex] [url]
	Constrained brain volume in an efficient coding model explains the fraction of excitatory and inhibitory neurons in sensory cortices A. Alreja, I. Nemenman and C. Rozell. PLOS Computational Biology, 18(1), pp. e1009642, January 2022. [bibtex] [url] [doi]
	Infrared Search and Track with Unbalanced Optimal Transport Dynamics Regularization N. Bertrand, J. Lee, K. Prussing, S. Shapero and C.J. Rozell. IEEE Geoscience and Remote Sensing Letters, 18(12), pp. 2072–2076, December 2021. [bibtex] [doi]
	Harnessing the Manifold Structure of Cardiomechanical Signals for Physiological Monitoring during Hemorrhage J. Zia, J. Kimball, C.J. Rozell and O.T. Inan. IEEE Transactions on Biomedical Engineering, 68(6), pp. 1759-1767, June 2021. [bibtex] [url] [doi]
	Towards Democratizing and Automating Online Conferences: Lessons from the Neuromatch Conferences T. Achakulvisut, T. Ruangrong, P. Mineault, T.P. Vogels, M. Peters, P. Poirazi, C. Rozell, B. Wyble, D. Goodman and K.P. Kording. Trends in Cognitive Sciences, 25(4), pp. 265-268, April 2021. [bibtex] [url] [doi]
	Variational Autoencoder with Learned Latent Structure M. Connor, G. Canal and C. Rozell. In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2021. (Acceptance rate 30%) [bibtex] [url]
	Feedback Coding for Active Learning G. Canal, M. Bloch and C. Rozell. In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2021. (Acceptance rate 30%) [bibtex] [url]
	A 17.8 MS/s Compressed Sensing Radar Accelerator Using a Spiking Neural Network P. Brown, M. O'Shaughnessy, C.J. Rozell, J. Romberg and M. Flynn. IEEE Journal of Solid State Circuits, 56(3), pp. 834–843, March 2021. [bibtex] [doi]
	State-space optimal feedback control of optogenetically driven neural activity M.F. Bolus, A.A. Willats, C.J. Rozell and G.B. Stanley. Journal of Neural Engineering, 18(3), pp. 036006, March 2021. [bibtex] [url] [doi]
	Generative causal explanations of black-box classifiers M. O'Shaughnessy, G. Canal, M. Connor, M. Davenport and C. Rozell. In Neural Information Processing Systems (NeurIPS), December 2020. (Acceptance rate 20%) [bibtex] [url]
	Learning sparse codes from compressed representations with biologically plausible local wiring constraints K. Fallah, A. Willats, N. Liu and C. Rozell. In Neural Information Processing Systems (NeurIPS), December 2020. (Acceptance rate 20%) [bibtex] [url]
	Unbalanced Optimal Transport Regularization for Imaging Problems J. Lee, N. Bertrand and C.J. Rozell. IEEE Transactions on Computational Imaging, vol. 6, pp. 1219-1232, July 2020. [bibtex] [url]
	Efficient Tracking of Sparse Signals via an Earth Mover's Distance Dynamics Regularizer N. Bertrand, A. Charles, J. Lee, P. Dunn and C.J. Rozell. IEEE Signal Processing Letters, vol. 27, pp. 1120-1124, June 2020. [bibtex] [url]
	An unbiased efficient sleep-wake detection algorithm for a population with sleep disorders: Change Point Decoder A. Cakmak, G. Da Poian, A. Willats, A. Haffar, R. Abdulbaki, Y. Ko, A. Shah, V. Vaccarino, D. Bliwise, C.J. Rozell and G. Clifford. Sleep, February 2020. [bibtex] [url]
	Active ordinal tuplewise querying for similarity learning G. Canal, S. Fenu and C. Rozell. In AAAI Conference on Artificial Intelligence (AAAI), February 2020. \textbfSelected for oral presentation. (Acceptance rate 20%). [bibtex] [url]
	Representing Closed Transformation Paths in Encoded Network Latent Space M. Connor and C. Rozell. In AAAI Conference on Artificial Intelligence (AAAI), February 2020. \textbfSelected for spotlight presentation. (Acceptance rate 20%). [bibtex] [url]
	Sparse Bayesian Learning with Dynamic Filtering for Inference of Time-Varying Sparse Signals M. O'Shaughnessy, M. Davenport and C. Rozell. IEEE Transactions on Signal Processing, 68(1), pp. 388–403, December 2019. [bibtex] [url]
	Hierarchical Optimal Transport for Multimodal Distribution Alignment J. Lee, M. Dabagia, E. Dyer and C.J. Rozell. In Neural Information Processing Systems (NeurIPS), December 2019. (Acceptance rate 21%) [bibtex] [url]
	Sparse Coding Using the Locally Competitive Algorithm on the TrueNorth Neurosynaptic System K.L. Fair, D.R. Mendat, A.G. Andreou, C.J. Rozell, J. Romberg and D.V. Anderson. Frontiers in Neuroscience, vol. 13, pp. 754, July 2019. [bibtex] [url]
	Sub-second Dynamics of Theta-Gamma Coupling in Hippocampal CA1 L. Zhang, J. Lee, C.J. Rozell and A.C. Singer. eLife, vol. 8, pp. e44320, July 2019. [bibtex] [url]
	Active embedding search via noisy paired comparisons G. Canal, A. Massimino, M. Davenport and C. Rozell. In International Conference on Machine Learning (ICML), June 2019. (Acceptance rate 23%) [bibtex] [pdf]
	PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices I. Kolb, C. Landry, M. Yip, C. Lewallen, W. Stoy, J. Lee, A. Felouzis, B. Yang, E.S. Boyden, C.J. Rozell and C.R. Forest. Journal of Neural Engineering, 16(4), pp. 046003, May 2019. [bibtex] [url]
	Unsupervised learning of manifold models for neural coding of physical transformations in the ventral visual pathway M. Connor and C. Rozell. In Conference on Cognitive Computational Neuroscience, September 2018. [bibtex]
	Short-term Sequence Memory: Compressive effects of Recurrent Network Dynamics A. Charles, H.L. Yap, D. Yin and C. Rozell. In Conference on Cognitive Computational Neuroscience, September 2018. [bibtex]
	Matched Filtering for Heart Rate Estimation on Compressive Sensing ECG Measurements G. Da Poian, C.J. Rozell, R. Bernardini, R. Rinaldo and G.D. Clifford. IEEE Transactions on Biomedical Engineering, 65(6), pp. 1349–1358, June 2018. [bibtex] [url]
	Controlling high-complexity robotic swarms with low-complexity EEG brain-computer interfaces G. Canal, Y. Diaz-Mercado, M. Egerstedt and C. Rozell. In International BCI Meeting, May 2018. [bibtex]
	Cell Membrane Tracking in Living Brain Tissue using Differential Interference Contrast Microscopy J. Lee, I. Kolb, C. Forest and C.J. Rozell. IEEE Transactions on Image Processing, pp. 1847–1861, April 2018. [bibtex] [url]
	Stabilizing Embedology: Geometry-Preserving Delay-Coordinate Maps A. Eftekhari, H.L. Yap, M.B. Wakin and C.J. Rozell. Physical Review E, 97(2), pp. 022222, February 2018. [bibtex] [url] [doi]
	Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo M.F. Bolus, A.A. Willats, C.J. Whitmire, C.J. Rozell and G.B. Stanley. Journal of Neural Engineering, 15(2), pp. 026011, January 2018. [bibtex] [url]
	Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks A.S. Charles, D. Yin and C.J. Rozell. Journal of Machine Learning Research, 18(7), pp. 1-37, 2017. [bibtex] [pdf]
	Rank Learning by Ordinal Gerrymandering S. Fenu and C.J. Rozell. In Proceedings of the IEEE International Conference On Machine Learning And Applications (ICMLA), December 2017. [bibtex] [url]
	Neuromorphic computation: Sparse codes from memristor grids B.A. Olshausen and C.J. Rozell. Nature Nanotechnology, 12(8), pp. 722–723, August 2017. [bibtex] [url]
	Efficient coding with biophysical constraints can explain properties of networks and neural responses In Computational and Systems Neuroscience (COSYNE) Workshop on New Methods for Understanding Neural Dynamics and Computation, February 2017. Invited talk. [bibtex]
	Dynamic Filtering of Time-Varying Sparse Signals via L1 Minimization A.S. Charles, A. Balavoine and C.J. Rozell. IEEE Transactions on Signal Processing, 64(21), pp. 5644–5656, November 2016. [bibtex] [url]
	Moving toward in vivo closed-loop optogenetic control of neural activity In American Control Conference (ACC) Workshop on Modeling, Estimation and Control Across Scales in Neuroscience, July 2016. Invited talk. [bibtex]
	Outcome measures based on classification performance fail to predict the intelligibility of binary-masked speech A.A. Kressner, T. May and C.J. Rozell. Journal of the Acoustical Society of America, 139(6), pp. 3033–3036, June 2016. [bibtex] [url]
	Exploiting the low-dimensional structure of dynamical system attractors In Computational and Systems Neuroscience (COSYNE) Workshop on Dimensionality reduction for the analysis and interpretation of high-dimensional neural datasets, February 2016. Invited talk [bibtex]
	Cochlear implant speech intelligibility outcomes with structured and unstructured binary mask errors A.A. Kressner, A. Westermann, J. Buchholz and C.J. Rozell. Journal of the Acoustical Society of America, 139(2), pp. 800–810, February 2016. [bibtex] [url]
	Electrical and optical activation of mesoscale neural circuits with implications for coding D. Millard, C. Whitmire, C.A. Gollnick, C.J. Rozell and G.B Stanley. Journal of Neuroscience, 35(47), pp. 15702–15715, November 2015. [bibtex] [url]
	Modeling Inhibitory Interneurons in Efficient Sensory Coding Models M. Zhu and C.J. Rozell. PLoS Computational Biology, 11(7), pp. e1004353, July 2015. [bibtex] [url]
	Discrete and Continuous-time Soft-Thresholding with Dynamic Inputs A. Balavoine, C.J. Rozell and J. Romberg. IEEE Transactions on Signal Processing, 63(12), pp. 3165–3176, June 2015. [bibtex] [pdf]
	Structure in time-frequency binary masking errors and its impact on speech intelligibility A.A. Kressner and C.J. Rozell. Journal of the Acoustical Society of America, 137(4), pp. 2025–2035, April 2015. [bibtex] [url]
	The Restricted Isometry Property for Random Block Diagonal Matrices A. Eftekhari, H.L. Yap, C.J. Rozell and M.B. Wakin. Applied and Computational Harmonic Analysis, 38(1), pp. 1–31, January 2015. [bibtex] [pdf]
	Optimal Sparse Approximation With Integrate and Fire Neurons S. Shapero, M. Zhu, P. Hasler and C.J. Rozell. International Journal of Neural Systems, 24(05), pp. 1440001, August 2014. [bibtex] [url]
	Correction to "Convergence and Rate Analysis of Neural Networks for Sparse Approximation" A. Balavoine, J. Romberg and C.J. Rozell. IEEE Transactions on Neural Networks and Learning Systems, 25(8), pp. 1595–1596, August 2014. [bibtex]
	Short Term Memory Capacity in Networks via the Restricted Isometry Property A.S. Charles, H.L. Yap and C.J. Rozell. Neural Computation, 26(6), pp. 1198–1235, June 2014. [bibtex] [pdf]
	Spectral Super-Resolution of Hyperspectral Imagery Using Re-Weighted L1 Spatial Filtering A.S. Charles and C.J. Rozell. IEEE Geoscience and Remote Sensing Letters, 11(3), pp. 602–606, March 2014. [bibtex] [pdf]
	On the move: Dynamical systems for modeling, measurement and inference in compressed sensing In Matheon Workshop on Compressed Sensing and its Applications, December 2013. Invited talk. [bibtex]
	Configurable Hardware Integrate and Fire Neurons for Sparse Approximation S. Shapero, C.J. Rozell and P. Hasler. Neural Networks, vol. 45, pp. 134–143, September 2013. Special issue on Neuromorphic Engineering: from Neural Systems to Brain-Like Engineered Systems. [bibtex] [url]
	Convergence Speed of a Dynamical System for Sparse Recovery A. Balavoine, C.J. Rozell and J. Romberg. IEEE Transactions on Signal Processing, 61(17), pp. 4259–4269, September 2013. [bibtex] [pdf]
	Stable Manifold Embeddings with Structured Random Matrices H.L. Yap, M.B. Wakin and C.J. Rozell. IEEE Journal of Selected Topics in Signal Processing, 7(4), pp. 720–730, August 2013. Special issue on Differential Geometry in Signal Processing. [bibtex] [pdf]
	Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system M. Zhu and C.J. Rozell. PLoS Computational Biology, 9(8), pp. e1003191, August 2013. [bibtex] [url]
	Tracking time-varying sparse signals In Advanced Modem Technology Forum, Qualcomm Technologies, Inc., May 2013. Invited talk. [bibtex]
	Evaluating the generalization of the Hearing Aid Speech Quality Index (HASQI) A.A. Kressner, D.V. Anderson and C.J. Rozell. IEEE Transactions on Audio, Speech and Language Processing, 21(2), pp. 407–415, February 2013. [bibtex] [pdf]
	A Common Network Architecture Efficiently Implements a Variety of Sparsity-based Inference Problems A.S. Charles, P. Garrigues and C.J. Rozell. Neural Computation, 24(12), pp. 3317–3339, December 2012. [bibtex] [pdf]
	Convergence and Rate Analysis of Neural Networks for Sparse Approximation A. Balavoine, J. Romberg and C.J. Rozell. IEEE Transactions on Neural Networks and Learning Systems, 23(9), pp. 1377–1389, September 2012. [bibtex] [pdf]
	Low Power Sparse Approximation on Reconfigurable Analog Hardware S. Shapero, A.S. Charles, C. Rozell and P. Hasler. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2(3), pp. 530–541, September 2012. Special issue on Circuits, Systems and Algorithms for Compressive Sensing. [bibtex] [pdf]
	Spectral Super-Resolution of Hyperspectral Images In SIAM Conference on Imaging Science, May 2012. Invited talk. [bibtex]
	Recursive estimation of dynamic signals with sparsity models via re-weighted L1 minimization In Janelia Farm Conference on Machine Learning, Statistical Inference, and Neuroscience, May 2012. [bibtex]
	Concentration of Measure for Block Diagonal Matrices with Applications to Compressive Signal Processing J.Y. Park, H.L. Yap, C.J. Rozell and M.B. Wakin. IEEE Transactions on Signal Processing, 59(12), pp. 5859–5875, December 2011. [bibtex] [pdf]
	Stable Takens' Embeddings for Linear Dynamical Systems H.L. Yap and C.J. Rozell. IEEE Transactions on Signal Processing, 59(10), pp. 4781–4794, October 2011. [bibtex] [pdf]
	Learning Sparse Codes for Hyperspectral Imagery A.S. Charles, B.A. Olshausen and C.J. Rozell. IEEE Journal of Selected Topics in Signal Processing, 5(5), pp. 963–978, September 2011. [bibtex] [pdf]
	Sparse coding via thresholding and local competition in neural circuits C.J. Rozell, D.H Johnson, R.G. Baraniuk and B.A. Olshausen. Neural Computation, 20(10), pp. 2526–2563, October 2008. \textbfSelected for Faculty of 1000 Biology (now H1 Connect). [bibtex] [pdf]
	Analog and Digital Sparse Approximation with Applications to Compressed Sensing In 2008 SIAM Conference on Imaging Science, July 2008. Invited talk. [bibtex]
	Neural architectures for sparse approximation In Information Theory and Applications Workshop, January 2008. Invited talk. [bibtex]
	Power Scheduling for Wireless Sensor and Actuator Networks C.J. Rozell and D.H. Johnson. In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN), pp. 470–478, April 2007. (Acceptance rate 22%) [bibtex] [pdf]
	All-optical nanoscale pH meter S.W. Bishnoi, C.J. Rozell, C.S. Levin, M.K. Gheith, B.R. Johnson, D.H. Johnson and N.J Halas. Nano Letters, 6(8), pp. 1687–1692, August 2006. [bibtex] [url]
	Analyzing the robustness of redundant population codes in sensory and feature extraction systems C.J. Rozell and D.H. Johnson. Neurocomputing, 69(10–12), pp. 1215–1218, June 2006. [bibtex] [pdf]
	Evaluating local contributions to global performance in wireless sensor and actuator networks C.J. Rozell and D.H. Johnson. Lecture Notes in Computer Science, vol. 4026, pp. 1–16, June 2006. it Proceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS), San Francisco, CA, June 2006 [bibtex] [pdf]
	Examining methods for estimating mutual information in spiking neural systems C.J. Rozell and D.H. Johnson. Neurocomputing, vol. 65–66C, pp. 429–434, June 2005. [bibtex] [pdf]
	Measuring information transfer in crayfish sustaining fiber spike generators C.J. Rozell, D.H. Johnson and R.M. Glantz. Biological Cybernetics, 90(2), pp. 89–97, February 2004. [bibtex] [pdf]
	Information processing during transient responses in the crayfish visual system C.J. Rozell, D.H. Johnson and R.M. Glantz. Neurocomputing, vol. 52–54, pp. 53–58, June 2003. [bibtex] [pdf]

Conference Abstracts

	Advancing the Mechanistic Understanding of Subcallosal Cingulate Deep Brain Stimulation Through Biophysical Modeling P. Sarikhani, E.C. Fitoz, H. Mayberg, R. Butera, C.J. Rozell and S. Alagapan. May 2025. [bibtex]
	Decoding depression recovery with deep brain stimulation using explainable AI C.J. Rozell. May 2025. Invited talk. [bibtex]
	Advancing Cognitive Science with AI: Decoding depression recovery with AI C.J. Rozell. April 2025. Invited talk. [bibtex]
	Biophysical modeling of subcallosal cingulate cortex to advance deep brain stimulation for treatment-resistant depression P. Sarikhani, C. Fitoz, R. Butera, C. Rozell and S. Alagapan. March 2025. [bibtex]
	Human Anterior Cingulate Dynamics During Effortful Walking T. Albarran, C. May, K. Kerr, K. Herrin, J. Leestma, T. Harvey, A. Young, G. Sawicki, C.J. Rozell and S. Alagapan. March 2025. [bibtex]
	Circuit deficits in treatment resistant depression and repair with deep brain stimulation C. Rozell. November 2024. Invited talk. [bibtex]
	Anterior cingulate dynamics during effortful walking in humans T. May C. Albarran, K. Herrin, J. Leestma, T. Harvey, A. Young, G. Sawicki, C. Rozell and S. Alagapan. October 2024. [bibtex]
	Understanding Depression Recovery with Deep Brain Stimulation Using Explainable AI C. Rozell. September 2024. Invited talk. [bibtex]
	Decomposed Linear Dynamical Systems (dLDS) for identifying the latent dynamics underlying high-dimensional time-series N. Mudrik, Y. Chen, E. Yezerets, C. Rozell and A. Charles. July 2024. [bibtex]
	Developing and Validating Marker of Treatment Response for Subcallosal Cingulate Deep Brain Stimulation C. Rozell. May 2024. Invited talk. [bibtex]
	Decomposed dynamics: toward discovering latent brain factors underlying depression and recovery C.J. Rozell. January 2024. Invited talk. [bibtex]
	A Novel Subcallosal Cingulate Biomarker of Deep Brain Stimulation Mediated Stable Depression Recovery S. Alagapan, S. Heisig, K.S. Choi, A. Waters, A. Veerakumar, V. Tiruvadi, M. Obatusin, T. Nauvel, J. Cha, A. Crowell, M. Figee, P. Riva Posse, R. Butera, H. Mayberg and C. Rozell. 93(9), pp. S271, 2023. Proceedings of Society of Biological Psychiatry Annual Meeting [bibtex]
	Decomposed linear dynamical systems for C. elegans functional connectivity E. Yezerets, N. Mudrik, Y. Chen, A. Charles and C. Rozell. November 2023. [bibtex]
	Enhancing the Cleo experiment simulation testbed to support all-optical control, multi-channel optogenetics, and easier integration into data analysis pipelines K. Johnsen, N. Cruzado, A. Charles and C.J. Rozell. November 2023. [bibtex]
	Validation of local field potential marker of subcallosal cingulate deep brain stimulation mediated depression recovery in an independent cohort S. Alagapan, E. Fitoz, M. Figee, T. Nauvel, K. Choi, M. Obatusin, S. Heisig, J. Cha, A. Waters, R. Butera, P. Riva Posse, H.M. Mayberg and C.J. Rozell. November 2023. [bibtex]
	Longitudinal effects of subcallosal cingulate deep brain stimulation on the resting electroencephalogram in treatment-resistant depression T. Nauvel, S. Alagapan, M. Obatusin, S. Heisig, J. Dahill-Fuchel, C.J. Rozell, A. Waters and H.M. Mayberg. November 2023. [bibtex]
	Characterizing the Stress-Reducing Effects of Non-Invasive Vagus Nerve Stimulation A. H. Gazi, D Bremner, J. Hahn, C. J. Rozell and O. T. Inan. October 2023. Special session on Enabling Closed-Loop Technologies for Mental Health: Biobehavioral Sensor Informatics and Just-in-Time Interventions [bibtex]
	Decomposed linear dynamical systems for C. elegans functional connectivity E. Yezerets, N. Mudrik, Y. Chen, C. Rozell and A. Charles. March 2023. [bibtex]
	CLOCTools: A library of tools for closed-loop neuroscience A. Willats, M.F. Bolus, K. Johnsen, G.B. Stanley and C.J. Rozell. November 2022. [bibtex]
	Bridging model and experiment with CLEOsim: a testbed for in-silico prototyping of complex neuroscience experiments K. Johnsen, N. Cruzado, A. Willats and C.J. Rozell. November 2022. [bibtex]
	A novel subcallosal cingulate biomarker of deep brain stimulation mediated stable recovery S. Alagapan, S. Heisig, K.S. Choi, A. Waters, A. Veerakumar, V. Tiruvadi, M. Obatusin, T.J. Nauvel, J. Cha, M. Figee, A.L. Crowell, P. Riva-Posse, R.J. Butera, H.S. Mayberg and C.J. Rozell. November 2022. [bibtex]
	Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics N. Mudrik, Y. Chen, E. Yezerts, C.J. Rozell and A. Charles. November 2022. New Orleans, LA. [bibtex]
	A novel subcallosal cingulate biomarker of deep brain stimulation mediated stable recovery S. Alagapan, S. Heisig, K.S. Choi, A. Waters, A. Veerakumar, V. Tiruvadi, M. Obatusin, T.J. Nauvel, J. Cha, M. Figee, A.L. Crowell, P. Riva-Posse, R.J. Butera, H.S. Mayberg and C.J. Rozell. October 2022. [bibtex]
	Exploration of acute effects of stimulation frequency on subcallosal cingulate dynamics in SCC DBS E.C. Fitoz, S. Alagapan, S. Heisig, K.S. Choi, A. Waters, A. Veerakumar, V. Tiruvadi, M. Obatusin, T.J. Nauvel, J. Cha, M. Figee, A.L. Crowell, P. Riva-Posse, R.J. Butera, H.S. Mayberg and C.J. Rozell. October 2022. [bibtex]
	Latent State-Space Modeling of Physiological Responses to Non-Invasive Vagus Nerve Stimulation and Traumatic Stress A. H. Gazi, S. An, S. Natarajan, J. A. Sanchez-Perez, D Bremner, J. Hahn, O. T. Inan and C. J. Rozell. October 2022. [bibtex]
	CLOCTools: A library of tools for closed-loop neuroscience A. Willats, M.F. Bolus, K. Johnsen, N. Cruzado, G.B. Stanley and C.J. Rozell. October 2022. [bibtex]
	Cleo: a simulation testbed for bridging model and experiment in mesoscale neuroscience K. Johnsen, N. Cruzado, A. Willats and C.J. Rozell. October 2022. [bibtex]
	Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics N. Mudrik, Y. Chen, E. Yezerts, C.J. Rozell and A. Charles. September 2022. Virtual meeting. [bibtex]
	Latent State-Space Modeling of Physiological Responses to Non-Invasive Vagus Nerve Stimulation and Traumatic Stress A. H. Gazi, S. An, S. Natarajan, J. A. Sanchez-Perez, D Bremner, J. Hahn, C. J. Rozell and O. T. Inan. September 2022. [bibtex]
	Informing clinical decisions in psychiatric neuromodulation with AI C.J. Rozell. August 2022. Invited talk. [bibtex]
	Learning the Data Manifold for Reusable Augmentations K. Fallah, M. Connor and C. Rozell. June 2022. [bibtex]
	Electrophysiological Biomarkers to Optimize DBS for Depression V S. Alagapan, A. Aloysi, R. Butera, J. Cha, K. Choi, A. Crowell, M. Figee, R. Gross, S. Heisig, B. Kopell, H. Mayberg, T. Nauvel, M. Obatusin, S. O'Neill, P. Riva Posse, C. Rozell, A. Smith and A. Waters. June 2022. [bibtex]
	Closed-Loop Computational Neuroscience for Causally Dissecting Circuits III C. Rozell, G. Stanley, M. Bolus, A. Willats, K. Johnsen, A. Borsa and N. Cruzado. June 2022. [bibtex]
	Oracle Guided Image Synthesis with Relative Queries A. Helbling, C. Rozell, M. O'Shaughnessy and K. Fallah. April 2022. [bibtex] [url]
	Local dynamics changes accompanying stable recovery in subcallosal cingulate deep brain stimulation for treatment-resistant depression S. Alagapan, S. Heisig, P. Riva-Posse, H.S. Mayberg and C.J. Rozell. April 2022. [bibtex]
	Closed-Loop Computational Neuroscience for Causally Dissecting Circuits II C. Rozell, G. Stanley, M. Bolus, A. Willats and K. Johnsen. June 2021. [bibtex]
	Electrophysiological Biomarkers to Optimize DBS for Depression IV H. Mayberg, P. Riva Posse, C. Rozell, R. Butera, K. Choi, A. Waters, M. Figee, S. Alagapan, A. Crowell, R. Gross, S. Heisig, M. Obatusin, A. Smith, T. Nauvel and J. Cha. June 2021. [bibtex]
	Electrophysiological Biomarkers to Optimize DBS for Depression - supplement: Longitudinal study of the effects of subcallosal cingulate deep brain stimulation for treatment-resistant depression on the power spectrum of the resting electroencephalogram T. Nauvel, S. Alagapan, S. Heisig, C. Rozell, H. Mayberg and A. Waters. June 2021. [bibtex]
	State-space optimal feedback control of neural circuits M. Bolus, A. Willats, C. Whitmire, C. Rozell and G. Stanley. May 2021. [bibtex]
	When are open- and closed-loop control necessary for causal inference in neural circuits? A. Willats, M. O'Shaughnessy, K. Johnsen and C.J. Rozell. October 2020. [bibtex]
	Closed-Loop Computational Neuroscience for Causally Dissecting Circuits C. Rozell, G. Stanley, M. Bolus, A. Willats and K. Johnsen. June 2020. [bibtex]
	Electrophysiological Biomarkers to Optimize DBS for Depression III H. Mayberg, P. Riva Posse, C. Rozell, S. Alagapan, R. Butera, K. Choi, A. Crowell, B. Howell, B. Mahmoudi, M. Obatusin, R. Gross, M. Sendi, V. Tiruvadi, A. Veerakumar, A. Waters and P. Weiss. June 2020. [bibtex]
	The PICASSO algorithm for Bayesian localization via paired comparisons in a union of subspaces model G. Canal, M. Connor, J. Jin, N. Nadagouda, M. O'Shaughnessy, C. Rozell and M. Davenport. May 2020. [bibtex]
	Unsupervised learning of manifold models for coding physical transformations M. Connor and C.J. Rozell. March 2020. [bibtex]
	A 17.8 MS/s Neural-Network Compressed Sensing Radar Processor in 16nm FinFET CMOS P. Brown, M. O'Shaughnessy, C. Rozell, J. Romberg and M. Flynn. March 2020. [bibtex]
	A change point decoder for sleep/wake detection on memory constrained wearables A. Cakmak, G. Da Poian, A. Willats, A. Shah, V. Vaccarino, D. Bliwise, C.J. Rozell and G. Clifford. December 2019. [bibtex]
	Parallel Unbalanced Optimal Transport Regularization for Imaging J. Lee, N. Bertrand and C.J. Rozell. December 2019. Selected for Spotlight presentation. [bibtex]
	Hierarchical Optimal Transport for Multimodal Distribution Alignment J. Lee, M. Dabagia, E. Dyer and C.J. Rozell. December 2019. [bibtex]
	A General ADMM Framework for Optimal Transport Regularized Problems J. Lee, N. Bertrand and C.J. Rozell. December 2019. [bibtex]
	Joint Estimation of Trajectory and Dynamics from Paired Comparisons G. Canal, M. O'Shaughnessy, C. Rozell and M. Davenport. December 2019. [bibtex]
	Dynamical System Implementations of Sparse Bayesian Learning M. O'Shaughnessy, M. Davenport and C. Rozell. December 2019. [bibtex]
	Electrophysiological features of subcallosal cingulate cortex in patients with treatment-resistant depression S. Alagapan, V. Tiruvadi, M. Sendi, A. Waters, A. Veerakumar, M. Obatusin, A. Crowell, P. Riva Posse, R. Butera, H. Mayberg and C. Rozell. October 2019. [bibtex]
	Sub second dynamics of theta gamma coupling in hippocampal CA1 L. Zhang, J. Lee, C. Rozell and A. Singer. October 2019. [bibtex]
	Cluster-based Optimal Transport Alignment J. Lee, E. Dyer and C.J. Rozell. July 2019. Selected for oral presentation. [bibtex]
	Fast Numerical Methods for Convex Problems with Optimal Transport Regularization J. Lee and C.J. Rozell. July 2019. [bibtex]
	Robust Incorporation of Signal Predictions into the Sparse Bayesian Learning Framework M. O'Shaughnessy, M. Davenport and C. Rozell. July 2019. [bibtex]
	Active embedding search via noisy paired comparisons G. Canal, A. Massimino, M. Davenport and C. Rozell. July 2019. [bibtex]
	Natural Variation Transfer using Learned Manifold Operators M. Connor, J. Culpepper, H. Nguyen and C. Rozell. July 2019. [bibtex]
	Electrophysiological Biomarkers to Optimize DBS for Depression III H. Mayberg, P. Riva Posse, C. Rozell, S. Alagapan, R. Butera, K. Choi, A. Crowell, B. Howell, B. Mahmoudi, M. Obatusin, R. Gross, M. Sendi, V. Tiruvadi, A. Veerakumar, A. Waters and P. Weiss. June 2019. [bibtex]
	Interactive Object Segmentation With Noisy Binary Inputs G. Canal, S. Manivasagam, S. Liang and C.J. Rozell. November 2018. [bibtex]
	Rigorous guarantees on sequence memory capacity in recurrent neural networks using randomized dimensionality reduction A. Charles, H.L. Yap, D. Yin and C. Rozell. October 2018. [bibtex]
	Sparse Dynamic Filtering via Earth Mover’s Distance Regularization N. Bertrand, J. Lee, A. Charles, P. Dunn and C.J. Rozell. April 2018. [bibtex]
	State-aware control of neural activity: design & analysis A. Willats, M. Bolus, C. Whitmire, G. Stanley and C. Rozell. March 2018. [bibtex]
	An Optimal Transport Tracking Regularizer J. Lee, A. Charles, N. Bertrand and C. Rozell. December 2017. [bibtex]
	Earth-Mover's Distance as a Tracking Regularizer A. Charles, N. Bertrand, J. Lee and C.J. Rozell. December 2017. [bibtex]
	Controlling high-complexity robotic swarms with low-complexity EEG brain-machine interfaces G. Canal, Y. Diaz-Mercado, M. Egerstedt and C. Rozell. November 2017. [bibtex]
	Cell membrane tracking in live brain tissue with differential interference contrast (DIC) microscopy J. Lee, I. Kolb, C. Forest and C. Rozell. November 2017. [bibtex]
	The patcherBot: a Walk-away Automated Patch-clamp Electrophysiology System I. Kolb, J. Lee, A Felouzis, C. Landry, M. Yip, C. Lewallen, W. Stoy, C. Rozell and C. Forest. November 2017. [bibtex]
	Optimal E:I cell ratios in efficient coding models of V1 under volume constraints A. Alreja, I. Nemenmen and C. Rozell. November 2017. [bibtex]
	Closed loop optogenetic control of thalamocortical activity M. Bolus, A. Willats, C. Whitmire, C. Rozell and G. Stanley. November 2017. [bibtex]
	Fast ADMM Solver for Reweighted Total Variation Image Deconvolution and Inpainting J. Lee and C.J. Rozell. November 2017. [bibtex]
	Dynamic Filtering with Earth Mover’s Distance Regularization A. Charles, J. Lee, N. Bertrand and C. Rozell. June 2017. [bibtex]
	Compression of multiple input streams into recursive neural networks A. Charles, D. Yin and C. Rozell. June 2017. [bibtex]
	Stabilizing Embedology: Geometry-Preserving Delay-Coordinate Maps C. Rozell, M. Wakin, H.L. Yap and A. Eftekhari. June 2017. Selected for oral presentation. [bibtex]
	Active learning approaches for complex non-invasive brain-computer interfaces C. Rozell. June 2017. [bibtex]
	Stabilizing Embedology: When Do Delay-Coordinate Maps Preserve Geometry? A. Eftekhari, H.L. Yap, M.B. Wakin and C. Rozell. May 2017. Invited [bibtex]
	Closed-loop Optogenetic Control of Neural Circuits: Tracking dynamic trajectories of firing rate in vivo M. Bolus, A. Willats, C. Whitmire, C. Rozell and G. Stanley. April 2017. [bibtex]
	Precision Cell Boundary Tracking on DIC Microscopy Video for Patch Clamping J. Lee and C.J. Rozell. March 2017. [bibtex]
	Short-term Sequence Memory in Recurrent Networks A. Charles, H.L. Yap, D. Yin and C. Rozell. December 2016. [bibtex]
	Unsupervised learning of manifold models for neural coding of physical transformations in the ventral visual pathway M. Connor and C. Rozell. December 2016. [bibtex]
	Efficient Randomized Filtering for Dimensionality Reduction in Electrophysiology Data N. Bertrand, H.L. Yap, A. Charles and C. Rozell. December 2016. [bibtex]
	Closed Loop Optogenetic Control of Neural Circuits in vivo: Developing design principles for controlling patterns of neural firing rate M. Bolus, A. Willats, C. Whitmire, Z. Costello, M. Egerstedt, C. Rozell and G. Stanley. November 2016. [bibtex]
	Closed Loop Optogenetic Control of Neural Circuits in vivo: Developing Design Principles for Controlling Patterns of Neural Firing Rate M. Bolus, A. Willats, C. Whitmire, Z. Costello, M. Egerstedt, C. Rozell and G. Stanley. November 2016. [bibtex]
	Cortical communication via randomized dimensionality reduction with local synaptic connections C. Rozell and N. Liu. February 2016. [bibtex]
	Closed loop optogenetic control of neural circuits: Tracking dynamic trajectories of neural activity M. Bolus, A. Willats, C. Whitmire, Z. Costello, M. Egerstedt, C. Rozell and G. Stanley. February 2016. [bibtex]
	Learning manifold transport operators of 3D transformations from 2D imagery C. Rozell and M. Norko. January 2016. [bibtex]
	Closing the loop around firing rate: Following dynamic trajectories A. Willats, M. Bolus, C. Whitmire, C. Rozell and G. Stanley. October 2015. [bibtex]
	Learning a Dynamics Dictionary for Time-Varying Sparse Signals A. Charles and C. Rozell. July 2015. [bibtex]
	Restricting Vocabulary Size in Pediatric Augmentative and Alternative Communication A. Moreno, C.J. Rozell and A. Howard. June 2015. [bibtex]
	Convergence of Basis Pursuit De-noising with Dynamic Filtering A. Charles and C.J. Rozell. December 2014. [bibtex]
	Can Random Linear Networks Store Multiple Long Input Streams? A. Charles, D. Yin and C.J. Rozell. December 2014. [bibtex]
	A First Analysis of the Stability of Takens' Embedding H.L. Yap, A. Eftekhari, M.B. Wakin and C.J. Rozell. December 2014. [bibtex]
	The role of sparsity in visual perception C. Rozell, M. Zhu, A. Charles, H.L. Yap and M. Norko. November 2014. [bibtex]
	The influence of structure in binary mask estimation error on speech intelligibility A. Kressner and C. Rozell. August 2014. Selected for oral presentation. [bibtex]
	Sparsity Based Spectral Super-Resolution and Applications to Ocean Water Color A. Charles, C. Rozell and N. Tufillaro. July 2014. [bibtex]
	Iterative Soft-Thresholding for Time-Varying Signal Recovery A. Balavoine, C.J. Rozell and J.K. Romberg. May 2014. [bibtex]
	Coding consequences of activity propagation from sensory and artificial stimulation of neural circuits D.C. Millard, C. Rozell and G.B. Stanley. February 2014. [bibtex]
	Modeling single-trial V1 population response to dynamic natural scenes M. Zhu and C. Rozell. December 2013. [bibtex]
	How can Efficient Neural Coding be Exploited for Neural Interfacing? October 2013. Invited talk. [bibtex]
	Speech Understanding in Noise Provided by a Simulated Cochlear Implant Processor Based on Matching Pursuit A. Kressner and C.J. Rozell. October 2013. [bibtex]
	Convergence of a Neural Network for Sparse Approximation using the Nonsmooth Łojasiewicz Inequality A. Balavoine, C.J. Rozell and J.K. Romberg. August 2013. [bibtex] [pdf]
	Using compressed sensing to study sequence memory capacity in networked systems A. Charles, H.L. Yap and C. Rozell. July 2013. [bibtex]
	Stochastic Filtering via Reweighted-l1 A. Charles and C. Rozell. July 2013. [bibtex]
	Speech separation using Matching Pursuit for time-frequency masking A. Kressner and C. Rozell. July 2013. [bibtex]
	A sparse coding model of V1 produces surround suppression effects in response to natural scene A.P. Del Giorno, M. Zhu and C. Rozell. July 2013. [bibtex]
	Sparse coding model captures V1 population response statistics to natural movies M. Zhu, I. Stevenson, U. Koster, C. Gray, B. Olshausen and C. Rozell. July 2013. [bibtex]
	Compressed Sensing Radar Using Recurrent Neural Networks H.L. Yap, A. Charles and C. Rozell. June 2013. [bibtex]
	Causal binary mask estimation for speech enhancement using sparsity constraints A. Kressner, D.V. Anderson and C. Rozell. June 2013. [bibtex]
	Dynamic Filtering of Sparse Signals Using Reweighted L1 A. Charles and C. Rozell. May 2013. [bibtex] [pdf]
	A Novel Binary Mask Estimator Based on Sparse Approximation A. Kressner, D.V. Anderson and C. Rozell. May 2013. [bibtex]
	Sparse coding model and population response statistics to natural movies in V1 M. Zhu, I. Stevenson, U. Koster, C. Gray, B. Olshausen and C. Rozell. February 2013. [bibtex]
	Compressive LADAR Detector Noise Performance D. Sale, C.J. Rozell, J.K. Romberg and A.D. Lanterman. November 2012. [bibtex]
	The Restricted Isometry Property for Echo State Networks with Applications to Sequence Memory Capacity H.L. Yap, A. Charles and C.J. Rozell. August 2012. [bibtex] [pdf]
	Compressive LADAR in Realistic Environments D. Sale, C.J. Rozell, J.K. Romberg and A.D. Lanterman. August 2012. [bibtex]
	Biologically realistic excitatory and inhibitory cell properties emerge from a sparse coding network M. Zhu and C. Rozell. July 2012. [bibtex]
	The Restricted Isometry Property for Block Diagonal Matrices A. Eftekhari, H.L. Yap, C.J. Rozell and M.B. Wakin. June 2012. [bibtex]
	The Restricted Isometry Property for Echo State Networks with Applications to Sequence Memory Capacity H.L. Yap, A. Charles and C.J. Rozell. June 2012. [bibtex]
	Short-Term Memory Capacity in Recurrent Networks via Compressed Sensing A. Charles, H.L. Yap and C.J. Rozell. May 2012. [bibtex]
	Biophysically accurate non-classical and inhibitory interneuron properties in a sparse coding network M. Zhu and C.J. Rozell. May 2012. [bibtex]
	Biophysically accurate inhibitory interneuron properties in a sparse coding network M. Zhu, B. Olshausen and C. Rozell. February 2012. [bibtex]
	Short-Term Memory Capacity in Recurrent Networks via Compressed Sensing A. Charles, H.L. Yap and C.J. Rozell. February 2012. [bibtex]
	A Scalable Implementation of Sparse Approximation on a Field Programmable Analog Array S. Shapero, C. Rozell, A. Balavoine and P. Hasler. November 2011. [bibtex]
	Robustness of the Hearing Aid Speech Quality Index (HASQI) A. Kressner, D. Anderson and C. Rozell. October 2011. [bibtex] [pdf]
	Computational auditory models validate the intelligibility benefits of "efficient filters" A. Kressner, D. Anderson and C. Rozell. August 2011. [bibtex]
	Stable Embeddings of Time Series Data H.L. Yap and C. Rozell. July 2011. [bibtex]
	Concentration Inequalities and Isometry Properties for Compressive Block Diagonal Matrices H.L. Yap, J.Y. Park, A. Eftekhari, C.J. Rozell and M.B. Wakin. July 2011. [bibtex]
	Learning sparse codes for hyperspectral images A. Charles, B. Olshausen and C. Rozell. July 2011. [bibtex]
	Convergence and Rate Analysis of Neural Networks for Sparse Approximation A. Balavoine, J. Romberg and C.J. Rozell. July 2011. [bibtex]
	A compressive sensing LIDAR architecture D. Sale, C. Rozell, J. Romberg and A. Lanterman. July 2011. [bibtex]
	Recent evidence of sparse coding in neural systems C. Rozell and M. Zhu. June 2011. [bibtex]
	Concentration Inequalities and Isometry Properties for Compressive Block Diagonal Matrices H.L. Yap, J.Y. Park, A. Eftekhari, C.J. Rozell and M.B. Wakin. June 2011. [bibtex]
	A Hierarchical Re-weighted-l1 Approach for Dynamic Sparse Signal Estimation A. Charles and C. Rozell. June 2011. [bibtex]
	Stable Embeddings of Time Series Data H.L. Yap and C. Rozell. June 2011. [bibtex]
	Compressive LIDAR Conceptual Model and Simulation Results D. Sale, C. Rozell, J. Romberg and A. Lanterman. May 2011. [bibtex]
	Estimation and Dynamic Updating of Time-Varying Signals With Sparse Variations M.S. Asif, A. Charles, J. Romberg and C. Rozell. May 2011. [bibtex] [pdf]
	Stable Manifold Embeddings with Operators Satisfying the Restricted Isometry Property H.L. Yap, M.B. Wakin and C.J. Rozell. March 2011. [bibtex] [pdf]
	The Restricted Isometry Property for Block Diagonal Matrices H.L. Yap, A. Eftekhari, M.B. Wakin and C.J. Rozell. March 2011. [bibtex] [pdf]
	Sparsity Penalties in Dynamical System Estimation A. Charles, M.S. Asif, J. Romberg and C. Rozell. March 2011. [bibtex] [pdf]
	Sparse approximation on a network of locally competitive integrate and fire neurons S. Shapero, D. Brüderle, P. Hasler and C. Rozell. February 2011. [bibtex]
	Population characteristics and interpretations of nCRF effects emerging from sparse coding M. Zhu and C. Rozell. February 2011. [bibtex]
	Global Convergence of the Locally Competitive Algorithm A. Balavoine, C.J. Rozell and J.K. Romberg. January 2011. [bibtex]
	Causal sparse decomposition of audio signals A. Charles, A.A. Kressner and C.J. Rozell. January 2011. [bibtex]
	Stable Takens' Embedding for Linear Dynamical Systems H.L. Yap and C.J. Rozell. December 2010. Invited paper for session on \emphExploiting Sparsity and Compressive Sensing in System Identification. [bibtex]
	Analog Sparse Approximation for Compressed Sensing Recovery C.J. Rozell and P. Garrigues. November 2010. [bibtex]
	Sparse Coding for Spectral Signatures in Hyperspectral Images A. Charles and C.J. Rozell. November 2010. [bibtex]
	Compressed Sensing Design of LIDAR Sensors November 2010. Invited talk. [bibtex]
	Predicting speech quality using a computational auditory model A. Kressner, C. Rozell and D. Anderson. August 2010. [bibtex]
	Sparse coding models demonstrate some non-classical receptive field effects M. Zhu and C. Rozell. July 2010. \textbfSelected for oral presentation. [bibtex]
	Compressed Sensing Design of LIDAR Sensors June 2010. McLean, VA. [bibtex]
	Network Models of Sparse Coding and Nonclassical Receptive Field Effects April 2010. New York, NY. [bibtex]
	Concentration of Measure for Block Diagonal Measurement Matrices M.B. Wakin, J.Y. Park, H.L. Yap and C.J. Rozell. March 2010. [bibtex] [pdf]
	Concentration of Measure for Block Diagonal Matrices With Repeated Blocks C.J. Rozell, H.L. Yap, J.Y. Park and M.B. Wakin. March 2010. Invited paper [bibtex] [pdf]
	Exploring the statistical structure of large-scale neural recordings using a sparse coding model A. Khosrowshahi, J. Baker, R. Herikstad, S. Yen, C. Rozell and B. Olshausen. February 2010. [bibtex]
	Distributed processing in frames for sparse approximation C.J. Rozell. March 2008. Invited paper [bibtex] [pdf]
	Reconstruction of compressively sensed images via neurally plausible local competitive algorithms R.L. Ortman, C.J. Rozell and D.H. Johnson. pp. 476–479, March 2008. [bibtex]
	Locally competitive algorithms for sparse approximation C.J. Rozell, D.H. Johnson, R.G. Baraniuk and B.A. Olshausen. pp. 169–172, September 2007. [bibtex]
	Modeling sensor networks with fusion frames P. Casazza, G. Kutyniok, S. Li and C.J. Rozell. vol. 6701, pp. 67011M-1 – 67011M-11, August 2007. [bibtex] [pdf]
	Neurally plausible sparse coding via competitive algorithms C.J. Rozell, D.H. Johnson, R.G. Baraniuk and B.A. Olshausen. February 2007. [bibtex]
	Information Theory and Neuroscience: A Tutorial D.H. Johnson, C.J. Rozell and I.N. Goodman. November 2006. [bibtex]
	All-optical nanoscale pH meter: a plasmonic nanodevice with quantifiable output S.W. Bishnoi, C.S. Levin, C.J. Rozell, B.R. Johnson, D.H. Johnson and N.J Halas. October 2006. Invited paper [bibtex]
	Sparse Coding via Thresholding and Local Competition B.A. Olshausen, C.J. Rozell, D.H. Johnson and R.G. Baraniuk. August 2006. [bibtex]
	Information Theory and Neuroscience D.H. Johnson and C.J. Rozell. July 2006. [bibtex]
	Feature-based information processing with selective attention C.J. Rozell, I.N. Goodman and D.H. Johnson. May 2006. [bibtex] [pdf]
	Analysis of noise reduction in redundant expansions under distributed processing requirements C.J. Rozell and D.H. Johnson. pp. 185–188, March 2005. [bibtex] [pdf]
	To cooperate or not to cooperate: Detection strategies in sensor networks M.A. Lexa, C.J. Rozell, S. Sinanović and D.H. Johnson. pp. 841–844, May 2004. [bibtex] [pdf]
	Matched filter performance for unequal target and background covariance matrices C.J. Rozell and D. Manolakis. pp. 109–117, April 2004. [bibtex]
	A theoretical framework for electro-acoustic music M. Simoni, B. Broening, C. Rozell, C. Meek and G. Wakefield. 1999. [bibtex] [pdf]

Book Chapters

Information Theory and Systems Neuroscience
D.H. Johnson, I.N. Goodman and C.J. Rozell. Chapter in Analysis of parallel spike trains (S. Grün, S. Rotter, eds.), Springer-Verlag, 2010.
[bibtex]

Other Publications

	Using explainable AI to uncover neural dynamics, behavior changes and network microstructure underlying depression recovery with DBS C. Rozell. March 2024. Invited talk. [bibtex]
	New data-driven electrophysiology outcome measures and insights into SCC DBS for depression DBS Think Tank IX, August 2021. Invited talk. [bibtex]
	On the Relation between Block Diagonal Matrices and Compressive Toeplitz Matrices H.L. Yap and C.J. Rozell. Technical report, Georgia Institute of Technology, School of Electrical and Computer Engineering, October 2011. [bibtex] [pdf]
	Distributed redundant representations in man-made and biological sensing systems C.J. Rozell. Ph.D. thesis, Rice University, May 2007. [bibtex] [pdf]
	Analyzing dynamics and stimulus feature dependence in the information processing of crayfish sustaining fibers C.J. Rozell. M.S. thesis, Rice University, May 2002. [bibtex] [pdf]