713-348-4749 aaz@rice.edu

Publications

Journal Publications

Over 400 journal and conference publications with over 27,500 citations; h-index of 55; 39 papers each with over 100 citations; 4 papers with over 1000 citations.

 

A. Banta, A.R. Phillips, R D’Ambrosio, E. Golanov, A. Regnier-Golanov, C. Karmonik, F. Shaib, G. Britz, B. Aazhang (2023) “A High-Accuracy, Non-Invasive, and Portable Method to Measure Cerebrospinal Fluid Flow in the Cerebral Aqueduct,” submitted to IEEE Transactions on Medical Imaging.

B. Fan, W. Goodman, R.Y. Cho, S.A. Sheth, R.R. Bouchard, B. Aazhang (2023) “Computational modeling and minimization of unintended neuronal excitation in a LIFU stimulation,” Nature Scientific Reports, Vol. 13, Issue 1, 13403, August 2023, https://doi.org/10.1038/s41598-023-40522-w

F. Ahsan, T. Chi, R. Cho, S.A. Sheth, W. Goodman, B. Aazhang (2022) “EMvelop stimulation: minimally invasive deep brain stimulation using temporally interfering electromagnetic waves,” Journal of Neural Engineering, Volume 19, Issue 4, July 2022, https://doi.org/10.1088/1741-2552/ac7894

Y. Zhao, Y. Zhang, Y. Fu, X. Ouyang, C. Wan, S. Wu, A. Banta, and B. Aazhang (2022) “e-G2C: A 0.14-to-8.31 µJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM,” IEEE Symposium on VLSI Technology and Circuits, doi: 10.1109/VLSITechnologyandCir46769.2022.9830335.

J. Hellar, N. Erfanian, and B. Aazhang (2022) “Epileptic Electroencephalography Classification using Embedded Dynamic Mode Decomposition,” Journal of Neural Engineering, Volume 19, Issue 3, June 2023, https://doi.org/10.1088/1741-2552/ac7256

J. Hellar, R. Cosentino, M. M. John, A. Post, S. Buchan, M. Razavi, and B. Aazhang (2022) “Manifold Approximating Graph Interpolation of Cardiac Local Activation Time” IEEE Transactions on Biomedical Engineering, https://ieeexplore.ieee.org/document/9755048  April 11, doi: 10.1109/TBME.2022.3166447

D. E.P. Moghaddam, S. A. Sheth, Z. Haneef, J. Gavvala, and B. Aazhang (2022) “Epileptic Seizure Prediction Using Spectral Width of The Covariance Matrix” Journal of Neural Engineering, https://doi.org/10.1088/1741-2552/ac6063

B. Fan, W. Goodman, R. Y. Cho, S. A. Sheth, R. R. Bouchard, and B. Aazhang (2022) “On Development of Beamforming with High Spatial Resolution in Low-Intensity Focused Ultrasound Neuromodulation” revised and resubmitted to Journal of Neural Engineering.

Jia and B. Aazhang (2020) “Reversing the Curse of Densification in mmWave Networks Through Spatial Multiplexing” submitted to IEEE Transactions on Wireless Communications, https://arxiv.org/abs/2012.07207.

Cosentino, R. Balestriero, R. Baraniuk, and B. Aazhang “Deep Autoencoders: From Understanding to Generalization Guarantees” in Mathematical and Scientific Machine Learning (MSML) 2021, EPFL Campus, Lausanne, Switzerland, Aug 16-19th 2021

Schmid, Y. Fan, T. Chi, E. Golanov, A. Regnier-Golanov, R. Austerman, S. Schodrof, K. Podell, P. Cherukuri, T. Bentley, C. Steele, B. Aazhang, G. Britz “Review of Wearable Technologies and Machine Learning Methodologies for Systematic Detection of Mild Traumatic Brain Injuries” in Journal of Neural Engineering, 2021, https://doi.org/10.1088/1741-2552/ac1982.

Su, W-T. Tan, X. Zhu, R. Liston, H. Wildfeuer, and B. Aazhang (2021) “Motion-Aware Optimizations for Downlink MU-MIMO in 802.11ax Networks” in IEEE Transactions on Network and Service Management, October 2021, doi: 10.1109/TNSM.2021.3117596

John, A. Banta, A. Post, S. Buchan, B. Aazhang, and M. Razavi “Machine Learning in Cardiac Electrophysiology” in Texas Heart Institute Journal, vol. 48, issue 5, October 2021.

Banta, R. Cosentino, M. M. John, A. Post, S. Buchan, M. Razavi, and B. Aazhang “Nonlinear Regression with a Convolutional Encoder-Decoder for Remote Monitoring of Surface Electrocardiograms” Artificial Intelligence in Medicine, vol. 118, pp. 102-135, August 1, 2021.

Sultan, K. G. Seddik, Z. Han, and B. Aazhang “Joint Transmitter-Receiver Optimization and Self-interference Suppression in Full-Duplex MIMO Systems” IEEE Transactions on Vehicular Technology, vol. 70, no. 7, pp. 6913-6929, July 2021.

Zhang, A. Banta, Y. Fu, M. M. John, A. Post, M. Razavi, B. Aazhang, J. Cavallaro, and Y. Lin “RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms” ACM Journal of Emerging Technologies in Computing Systems, 2021, https://doi.org/10.1145/1122445.1122456

Young, R. Homma, and B. Aazhang “Addressing Indirect Frequency Coupling via Partial Generalized Coherence” Nature Scientific Reports, Vol. 1, Issue 1, pp. 1-16, March 2021.

Young, C. Neveu, J. H. Byrne, and B. Aazhang “Inferring Functional Connectivity through Graphical Directed Information” Journal of Neural Engineering, vol 18, no 4. March 30, 2021.

S. Yellapantula, K. Forseth, N. Tandon, and B. Aazhang (2020) “NetDI: Methodology Elucidating the Role of Power and Dynamical Brain Network Features that Underpin Word Production” in eNeuro.

L. Luan, J. Robinson, B. Aazhang, T. Chi, K. Yang, X. Li, H. Rathore, A. Singer, S. Yellapantula, Y. Fan, Z. Yu, and C. Xie (2020) “Recent Advances in Electrical Neural Interfaces: Minimal Invasiveness, Longevity and Scalability” invited review paper in Neuron.

J. Young, V. Dragoi, and B. Aazhang “Precise Measurement of Correlations Between Frequency Coupling and Visual Task Performance” Nature Scientific Reports, 10, 17372, October 2020.

R. Cosentino, R. Balestriero, R. G. Baraniuk, and B. Aazhang (2020) “Universal Frame Thresholding” IEEE Signal Processing Letters, vol. 27, no. 6, pp. 1115–1119, June 2020.

R. Cosentino and B. Aazhang “Learnable Group Transform for Time-Series” Thirty-seventh International Conference on Machine Learning (ICML), pages 2164–2173, Vienna, Austria, 2020.

View a complete list of publications on Google Scholar.

Presentations

“Episode- and Patient-Specific Wireless Multisite Pacing of Diseased Human Hearts” (PDF)

“Can we predict and prevent the onset of seizures?” (PDF)

“An Introduction to the Rice Neuroengineering Initiative” (PDF)

Short Courses

“Learning from Sensor Data: Set I” (PDF)

“Learning from Sensor Data: Set II” (PDF)