Journals and Conference Papers:
Arshia Afzal, Grigorios Chrysos, Volkan Cevher, Mahsa Shoaran, “REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates”, International Conference on Machine Learning (ICML), 2024 (accepted)
Cong Ding, Mingxiang Gao, Anja K. Skrivervik, Mahsa Shoaran, “A 3mm2, Energy-Efficient, Multi-Data-Rate, FDMA Transmitter with On-Chip Antenna for Next-Generation Neural Implants”, IEEE European Solid-State Electronics Research Conference (ESSERC), 2024 (accepted)
Cong Ding, Mingxiang Gao, Anja K. Skrivervik, Mahsa Shoaran, “A 49.8mm2 Fully Integrated, 1.5m Transmission-Range, High-Data-Rate IR-UWB Transmitter for Brain Implants”, IEEE Custom Integrated Circuits Conference (CICC), 2024 (accepted)
Mohammad Kalbasi, Mohammad Ali Shaeri, Vincent Mendez, Solaiman Shokur, Silvestro Micera, and Mahsa Shoaran, “A Hardware-Efficient EMG Decoder with an Attractor-based Neural Network for Next-Generation Hand Prostheses”, IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2024 (accepted)
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Lin Yao, Jonathan Baker, Jae-Wook Ryou, Nicholas Schiff, Keith Purpura, Mahsa Shoaran, “Mental Fatigue Prediction from Multi-Channel ECoG Signal”, 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, 2020
Bingzhao Zhu, Milad Taghavi, Mahsa Shoaran, “Cost-Efficient Classification for Neurological Disease Detection,” IEEE Biomedical Circuits and Systems Conference (BioCAS), Nara, Japan, 2019
Lin Yao and Mahsa Shoaran, “Enhanced Prediction of Individual Finger Movements with Temporal Dynamics of ECoG,” 53rd Asilomar Conference on Signals, Systems and Computers, 2019
Bingzhao Zhu and Mahsa Shoaran, “Hardware-Efficient Seizure Detection,” 53rd Asilomar Conference on Signals, Systems and Computers, 2019
Bingzhao Zhu, Gianluca Coppola, Mahsa Shoaran, “Migraine Classification using Somatosensory Evoked Potentials,” Cephalalgia, 39(9):1143-1155, 2019
Milad Taghavi and Mahsa Shoaran, “Hardware Complexity Analysis of Deep Neural Networks and Decision Tree Ensembles for Real-time Neural Dara Classification,” IEEE EMBS Conference on Neural Engineering (IEEE NER), San Francisco, 2019
A Wolff, L Yao, J Gomez-Pilar, M Shoaran, N Jiang, G Northoff, “Neural variability quenching during decision-making: Neural individuality and its prestimulus complexity,” 192: 1-14, NeuroImage, 2019
Lin Yao, Peter Brown, Mahsa Shoaran, “Resting Tremor Detection in Parkinson’s Disease with Machine Learning and Kalman Filtering,” IEEE Biomedical Circuits and Systems Conference (IEEE BioCAS), Cleveland, Ohio, 2018
Mahsa Shoaran, Benyamin A. Haghi, Milad Taghavi, Masoud Farivar, Azita Emami, “Energy-Efficient Classification for Resource-Constrained Biomedical Applications” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (IEEE JETCAS), vol. 8, no. 4, pp. 693-707, 2018
Cosimo Aprile, Kerim Ture, Luca Baldassarre, Mahsa Shoaran, Gurkan Yilmaz, Franco Maloberti, Catherine Dehollain, Yusuf Leblebici, Volkan Cevher, “Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants,” IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), vol. 65, no. 11, pp. 3929-3941, 2018
Milad Taghavi, Benyamin A. Haghi, Masoud Farivar, Mahsa Shoaran, Azita Emami, “A 41.2 nJ/class, 32- Channel On-Chip Classifier for Epileptic Seizure Detection,” International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, 2018
Taige Wang, Mahsa Shoaran, Azita Emami, “Towards Adaptive Deep Brain Stimulation in Parkinson’s Disease: LFP-based Feature Analysis and Classification,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, 2018
Mahsa Shoaran, Benyamin A. Haghi, Masoud Farivar, Azita Emami, “Efficient Feature Extraction and Classification Methods in Neural Interfaces,” Winter Bridge on Frontiers of Engineering, National Academy of Engineering (NAE), , vol. 47, no. 4, 2017
Mahsa Shoaran, Masoud Farivar, Azita Emami, “Low-power and Miniaturized Seizure Control Devices for Epilepsy,” International Conference for Technology and Analysis of Seizures (ICTALS), Minneapolis, MN, 2017 (best paper award)
Mahsa Shoaran, Masoud Farivar, Azita Emami, “Hardware-Friendly Seizure Detection with a Boosted Ensemble of Shallow Decision Trees,” International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, Florida, Aug. 2016
Mahsa Shoaran, Claudio Pollo, Kaspar Schindler, Alexandre Schmid, “A Fully-Integrated IC with 0.85-µW/Channel Consumption for Epileptic iEEG Detection,” IEEE Transactions on Circuits and Systems II: Express Briefs (IEEE TCAS-II), vol. 62, no. 2, pp. 114-118, 2015
Mahsa Shoaran, Armin Tajalli, Massimo Alioto, Alexandre Schmid, Yusuf Leblebici, “Analysis and Characterization of Variability in Subthreshold Source-Coupled Logic Circuits,” IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), vol. 62, no. 2, pp. 458-467, 2015
Huichu Liu, Mahsa Shoaran, Xueqing Li, Suman Datta, Alexandre Schmid, Vijaykrishnan Narayanan, “Tunnel FET-Based Ultra-Low Power, Low-Noise Amplifier Design for Bio-signal Acquisition,” International Symposium on Low Power Electronics and Design (ISLPED), La Jolla, CA, USA, 2014
Mahsa Shoaran and Alexandre Schmid, “System and Circuit Design for High-Density iEEG Recording and Epileptic Seizure Detection,” Workshop on Biomedical Microelectronics and Translational Systems Research, Switzerland, 2014
Book Chapters and Patents:
Mahsa Shoaran, Benyamin A. Haghi, Masoud Farivar, Azita Emami, “Efficient Feature Extraction and Classification Methods in Neural Interfaces,” Chapter in Frontiers of Engineering: Reports on Leading-Edge Engineering, the National Academy Press, 2017
Mahsa Shoaran and Alexandre Schmid, “A Power-Efficient Compressive Sensing Platform for Cortical Implants,” Chapter in Advances in Analog Circuit Design, edited by Kofi Makinwa, Andrea Baschirott, and Pieter Harpe, Springer, 2016
Mahsa Shoaran, Mahdad Hosseini Kamal, Alexandre Schmid, “Compact Low-Power Cortical Recording Architecture for Compressive Multichannel Data Acquisition,” US Patent, P2763US00
Huichu Liu, Ramesh Vaddi, Vijaykrishnan Narayanan, Suman Datta, Moon Seok Kim, Xueqing Li, Alexandre Schmid, Mahsa Shoaran, Unsuk Heo, “Low Power Nanoelectronics,” US Patent 20150333534