VALID: Custom ASIC Verification and FPGA Education Platform. - Patrick Murphy; J. Patrick Frantz; Erik Welsh; Ricky Hardy; Tinoosh Mohsenin; Joseph R. Cavallaro (MSE, 2003)

Hardware and applications of AsAP: An asynchronous array of simple processors. - Bevan M. Baas; Zhiyi Yu; Michael J. Meeuwsen; Omar Sattari; Ryan W. Apperson; Eric W. Work; Jeremy W. Webb; Michael A. Lai; Daniel Gurman; Chi Chen; Jason Cheung; Dean Truong; et al. (Hot Chips Symposium, 2006)

Split-Row: A Reduced Complexity, High Throughput LDPC Decoder Architecture. - Tinoosh Mohsenin; Bevan M. Baas (ICCD, 2006)

An asynchronous array of simple processors for dsp applications. - Zhiyi Yu; Michael J. Meeuwsen; Ryan W. Apperson; Omar Sattari; Michael A. Lai; Jeremy W. Webb; Eric W. Work; Tinoosh Mohsenin; Mandeep Singh; Bevan M. Baas (ISSCC, 2006)

High-Throughput LDPC Decoders Using A Multiple Split-Row Method. - Tinoosh Mohsenin; Bevan M. Baas (ICASSP (2), 2007)

AsAP: A Fine-Grained Many-Core Platform for DSP Applications. - Bevan M. Baas; Zhiyi Yu; Michael J. Meeuwsen; Omar Sattari; Ryan W. Apperson; Eric W. Work; Jeremy W. Webb; Michael A. Lai; Tinoosh Mohsenin; Dean Truong; Jason Cheung (IEEE Micro, 2007)

A Scalable Dual-Clock FIFO for Data Transfers Between Arbitrary and Haltable Clock Domains. - Ryan W. Apperson; Zhiyi Yu; Michael J. Meeuwsen; Tinoosh Mohsenin; Bevan M. Baas (IEEE Trans. Very Large Scale Integr. Syst., 2007)

A thresholding algorithm for improved Split-Row decoding of LDPC codes. - Tinoosh Mohsenin; Pascal Urard; Bevan M. Baas (ACSCC, 2008)

AsAP: An Asynchronous Array of Simple Processors. - Zhiyi Yu; Michael J. Meeuwsen; Ryan W. Apperson; Omar Sattari; Michael A. Lai; Jeremy W. Webb; Eric W. Work; Dean Truong; Tinoosh Mohsenin; Bevan M. Baas (IEEE J. Solid State Circuits, 2008)

Architecture and Evaluation of an Asynchronous Array of Simple Processors. - Zhiyi Yu; Michael J. Meeuwsen; Ryan W. Apperson; Omar Sattari; Michael A. Lai; Jeremy W. Webb; Eric W. Work; Tinoosh Mohsenin; Bevan M. Baas (J. Signal Process. Syst., 2008)

An Improved Split-Row Threshold Decoding Algorithm for LDPC Codes. - Tinoosh Mohsenin; Dean Truong; Bevan M. Baas (ICC, 2009)

Multi-Split-Row Threshold Decoding Implementations for LDPC Codes. - Tinoosh Mohsenin; Dean Nguyen Truong; Bevan M. Baas (ISCAS, 2009)

A 167-Processor Computational Platform in 65 nm CMOS. - Dean Nguyen Truong; Wayne H. Cheng; Tinoosh Mohsenin; Zhiyi Yu; Anthony T. Jacobson; Gouri Landge; Michael J. Meeuwsen; Christine Watnik; Anh Thien Tran; Zhibin Xiao; Eric W. Work; Jeremy W. Webb; et al. (IEEE J. Solid State Circuits, 2009)

A Low-Complexity Message-Passing Algorithm for Reduced Routing Congestion in LDPC Decoders. - Tinoosh Mohsenin; Dean Nguyen Truong; Bevan M. Baas (IEEE Trans. Circuits Syst. I Regul. Pap., 2010)

A Split-Decoding Message Passing Algorithm for Low Density Parity Check Decoders. - Tinoosh Mohsenin; Bevan M. Baas (J. Signal Process. Syst., 2010)

A reduced routing network architecture for partial parallel LDPC decoders. - Houshmand Shirani-mehr; Tinoosh Mohsenin; Bevan M. Baas (ACSCC, 2011)

Low power LDPC decoder with efficient stopping scheme for undecodable blocks. - Tinoosh Mohsenin; Houshmand Shirani-mehr; Bevan M. Baas (ISCAS, 2011)

A many-core platform implemented for multi-channel seizure detection. - Jordan Bisasky; Darin Chandler; Tinoosh Mohsenin (ISCAS, 2012)

High performance compressive sensing reconstruction hardware with QRD process. - Jérôme L. V. M. Stanislaus; Tinoosh Mohsenin (ISCAS, 2012)

An efficient & reconfigurable FPGA and ASIC implementation of a spectral Doppler ultrasound imaging system. - Adam Page; Tinoosh Mohsenin (ASAP, 2013)

Low-complexity FPGA implementation of compressive sensing reconstruction. - Jérôme L. V. M. Stanislaus; Tinoosh Mohsenin (ICNC, 2013)

A 64-core platform for biomedical signal processing. - Jordan Bisasky; Houman Homayoun; Farhang Yazdani; Tinoosh Mohsenin (ISQED, 2013)

LDPC Decoder with an Adaptive Wordwidth Datapath for Energy and BER Co-Optimization. - Tinoosh Mohsenin; Houshmand Shirani-mehr; Bevan M. Baas (VLSI Design, 2013)

Deep Belief Networks Used on High Resolution Multichannel Electroencephalography Data for Seizure Detection. - J. T. Turner; Adam Page; Tinoosh Mohsenin; Tim Oates 001 (AAAI Spring Symposia, 2014)

Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods. - Adam Page; J. T. Turner; Tinoosh Mohsenin; Tim Oates 001 (FLAIRS, 2014)

Reconfigurable STT-NV LUT-based functional units to improve performance in general-purpose processors. - Adarsh Reddy Ashammagari; Hamid Mahmoodi; Tinoosh Mohsenin; Houman Homayoun (ACM Great Lakes Symposium on VLSI, 2014)

A parallel and reconfigurable architecture for efficient OMP compressive sensing reconstruction. - Amey M. Kulkarni; Houman Homayoun; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2014)

Energy-efficient mapping of biomedical applications on domain-specific accelerator under process variation. - Mohammad Khavari Tavana; Amey M. Kulkarni; Abbas Rahimi; Tinoosh Mohsenin; Houman Homayoun (ISLPED, 2014)

Polarization-insensitive phase-transmultiplexing of CSRZ-OOK and RZ-BPSK to RZ-QPSK via XPM in a PCF. - Brice M. Cannon; Tanvir Mahmood; William Astar; Paul Boudra; Tinoosh Mohsenin; Gary M. Carter (OFC, 2014)

Live demonstration: Towards an ultra low power on-board processor for Tongue Drive System. - Ali Jafari; Nathanael Buswell; Adam Page; Tinoosh Mohsenin; Md. Nazmus Sahadat; Maysam Ghovanloo (BioCAS, 2015)

A low power seizure detection processor based on direct use of compressively-sensed data and employing a deterministic random matrix. - Ali Jafari; Adam Page; Chris Sagedy; Emily Smith; Tinoosh Mohsenin (BioCAS, 2015)

Utilizing deep neural nets for an embedded ECG-based biometric authentication system. - Adam Page; Amey M. Kulkarni; Tinoosh Mohsenin (BioCAS, 2015)

An ultra low power feature extraction and classification system for wearable seizure detection. - Adam Page; Siddharth Pramod; Tim Oates 001; Tinoosh Mohsenin (EMBC, 2015)

Accelerating compressive sensing reconstruction OMP algorithm with CPU, GPU, FPGA and domain specific many-core. - Amey M. Kulkarni; Tinoosh Mohsenin (ISCAS, 2015)

A Flexible Multichannel EEG Feature Extractor and Classifier for Seizure Detection. - Adam Page; Chris Sagedy; Emily Smith; Nasrin Attaran; Tim Oates 001; Tinoosh Mohsenin (IEEE Trans. Circuits Syst. II Express Briefs, 2015)

Toward an Ultralow-Power Onboard Processor for Tongue Drive System. - Sina Viseh; Maysam Ghovanloo; Tinoosh Mohsenin (IEEE Trans. Circuits Syst. II Express Briefs, 2015)

Application of Compressive Sensing to Gravitational Microlensing Experiments. - Asmita Korde-Patel; Richard K. Barry; Tinoosh Mohsenin (Astroinformatics, 2016)

CS-Based Secured Big Data Processing on FPGA. - Amey M. Kulkarni; Ali Jafari; Colin Shea; Tinoosh Mohsenin (FCCM, 2016)

FPGA-Based Reduction Techniques for Efficient Deep Neural Network Deployment. - Adam Page; Tinoosh Mohsenin (FCCM, 2016)

Low Energy Sketching Engines on Many-Core Platform for Big Data Acceleration. - Amey M. Kulkarni; Tahmid Abtahi; Emily Smith; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2016)

Low-Power Manycore Accelerator for Personalized Biomedical Applications. - Adam Page; Nasrin Attaran; Colin Shea; Houman Homayoun; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2016)

Adaptive real-time Trojan detection framework through machine learning. - Amey M. Kulkarni; Youngok K. Pino; Tinoosh Mohsenin (HOST, 2016)

A low-power multi-physiological monitoring processor for stress detection. - Nasrin Attaran; Justin Brooks; Tinoosh Mohsenin (IEEE SENSORS, 2016)

Sketching-based high-performance biomedical big data processing accelerator. - Amey M. Kulkarni; Ali Jafari; Chris Sagedy; Tinoosh Mohsenin (ISCAS, 2016)

Wearable seizure detection using convolutional neural networks with transfer learning. - Adam Page; Colin Shea; Tinoosh Mohsenin (ISCAS, 2016)

SVM-based real-time hardware Trojan detection for many-core platform. - Amey M. Kulkarni; Youngok K. Pino; Tinoosh Mohsenin (ISQED, 2016)

Architecture Exploration for Energy-Efficient Embedded Vision Applications: From General Purpose Processor to Domain Specific Accelerator. - Maria Malik; Farnoud Farahmand; Paul Otto; Nima Akhlaghi; Tinoosh Mohsenin; Siddhartha Sikdar; Houman Homayoun (ISVLSI, 2016)

Real-Time Anomaly Detection Framework for Many-Core Router through Machine-Learning Techniques. - Amey M. Kulkarni; Youngok K. Pino; Matthew French; Tinoosh Mohsenin (ACM J. Emerg. Technol. Comput. Syst., 2016)

An embedded FPGA accelerator for a stand-alone dual-mode assistive device. - Ali Jafari; Maysam Ghovanloo; Tinoosh Mohsenin (BioCAS, 2017)

LESS: Big data sketching and Encryption on low power platform. - Amey M. Kulkarni; Colin Shea; Houman Homayoun; Tinoosh Mohsenin (DATE, 2017)

Big vs little core for energy-efficient Hadoop computing. - Maria Malik; Katayoun Neshatpour; Tinoosh Mohsenin; Avesta Sasan; Houman Homayoun (DATE, 2017)

A Scalable FPGA-Based Accelerator for High-Throughput MCMC Algorithms. - Morteza Hosseini; Rashidul Islam; Amey M. Kulkarni; Tinoosh Mohsenin (FCCM, 2017)

A Real-Time Embedded FPGA Processor for a Stand-Alone Dual-Mode Assistive Device. - Ali Jafari; Maysam Ghovanloo; Tinoosh Mohsenin (FCCM, 2017)

Accelerating convolutional neural network with FFT on tiny cores. - Tahmid Abtahi; Amey M. Kulkarni; Tinoosh Mohsenin (ISCAS, 2017)

An EEG artifact identification embedded system using ICA and multi-instance learning. - Ali Jafari; Sunil Gandhi; Sri Harsha Konuru; W. David Hairston; Tim Oates 001; Tinoosh Mohsenin (ISCAS, 2017)

PACENet: Energy efficient acceleration for convolutional network on embedded platform. - Adwaya Kulkarni; Tahmid Abtahi; Colin Shea; Amey M. Kulkarni; Tinoosh Mohsenin (ISCAS, 2017)

SPARCNet: A Hardware Accelerator for Efficient Deployment of Sparse Convolutional Networks. - Adam Page; Ali Jafari; Colin Shea; Tinoosh Mohsenin (ACM J. Emerg. Technol. Comput. Syst., 2017)

Low Overhead Architectures for OMP Compressive Sensing Reconstruction Algorithm. - Amey M. Kulkarni; Tinoosh Mohsenin (IEEE Trans. Circuits Syst. I Regul. Pap., 2017)

Energy Efficient Convolutional Neural Networks for EEG Artifact Detection. - Mohit Khatwani; Morteza Hosseini; Hirenkumar Paneliya; Tinoosh Mohsenin; W. David Hairston; Nicholas R. Waytowich (BioCAS, 2018)

BiNMAC: Binarized neural Network Manycore ACcelerator. - Ali Jafari; Morteza Hosseini; Adwaya Kulkarni; Chintan Patel; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2018)

MC3A: Markov Chain Monte Carlo ManyCore Accelerator. - Lahir Marni; Morteza Hosseini; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2018)

Low Power and Trusted Machine Learning. - Avesta Sasan; Qi Zhu 002; Yanzhi Wang; Jae-sun Seo; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2018)

SCALENet: A SCalable Low power AccELerator for Real-time Embedded Deep Neural Networks. - Colin Shea; Adam Page; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2018)

A Real-Time Wearable FPGA-based Seizure Detection Processor Using MCMC. - Lahir Marni; Morteza Hosseini; Jennifer Hopp; Pedram Mohseni; Tinoosh Mohsenin (ISCAS, 2018)

Denoising Time Series Data Using Asymmetric Generative Adversarial Networks. - Sunil Gandhi; Tim Oates 001; Tinoosh Mohsenin; W. David Hairston (PAKDD (3), 2018)

A Scalable and Low Power DCNN for Multimodal Data Classification. - Ali Jafari; Morteza Hosseini; Houman Homayoun; Tinoosh Mohsenin (ReConFig, 2018)

MPT: Multiple Parallel Tempering for High-Throughput MCMC Samplers. - Morteza Hosseini; Rashidul Islam; Lahir Marni; Tinoosh Mohsenin (SoCC, 2018)

Heterogeneous HMC+DDRx Memory Management for Performance-Temperature Tradeoffs. - Mohammad Hossein Hajkazemi; Mohammad Khavari Tavana; Tinoosh Mohsenin; Houman Homayoun (ACM J. Emerg. Technol. Comput. Syst., 2018)

Energy-efficient acceleration of MapReduce applications using FPGAs. - Katayoun Neshatpour; Maria Malik; Avesta Sasan; Setareh Rafatirad; Tinoosh Mohsenin; Hassan Ghasemzadeh 001; Houman Homayoun (J. Parallel Distributed Comput., 2018)

A Low-Power Wearable Stand-Alone Tongue Drive System for People With Severe Disabilities. - Ali Jafari; Nathanael Buswell; Maysam Ghovanloo; Tinoosh Mohsenin (IEEE Trans. Biomed. Circuits Syst., 2018)

Embedded Low-Power Processor for Personalized Stress Detection. - Nasrin Attaran; Abhilash Puranik; Justin Brooks; Tinoosh Mohsenin (IEEE Trans. Circuits Syst. II Express Briefs, 2018)

Low Overhead CS-Based Heterogeneous Framework for Big Data Acceleration. - Amey M. Kulkarni; Colin Shea; Tahmid Abtahi; Houman Homayoun; Tinoosh Mohsenin (ACM Trans. Embed. Comput. Syst., 2018)

Accelerating Convolutional Neural Network With FFT on Embedded Hardware. - Tahmid Abtahi; Colin Shea; Amey M. Kulkarni; Tinoosh Mohsenin (IEEE Trans. Very Large Scale Integr. Syst., 2018)

An Energy-Efficient Programmable Manycore Accelerator for Personalized Biomedical Applications. - Adwaya Kulkarni; Adam Page; Nasrin Attaran; Ali Jafari; Maria Malik; Houman Homayoun; Tinoosh Mohsenin (IEEE Trans. Very Large Scale Integr. Syst., 2018)

SENSE: Sketching Framework for Big Data Acceleration on Low Power Embedded Cores. - Amey M. Kulkarni; Tinoosh Mohsenin (Security and Fault Tolerance in Internet of Things, 2019)

XPPE: cross-platform performance estimation of hardware accelerators using machine learning. - Hosein Mohammadi Makrani; Hossein Sayadi; Tinoosh Mohsenin; Setareh Rafatirad; Avesta Sasan; Houman Homayoun (ASP-DAC, 2019)

Learning Behaviors from a Single Video Demonstration Using Human Feedback. - Sunil Gandhi; Tim Oates 001; Tinoosh Mohsenin; Nicholas R. Waytowich (AAMAS, 2019)

On the Complexity Reduction of Dense Layers from O(N2) to O(NlogN) with Cyclic Sparsely Connected Layers. - Morteza Hosseini; Mark Horton; Hiren Paneliya; Uttej Kallakuri; Houman Homayoun; Tinoosh Mohsenin (DAC, 2019)

2SMaRT: A Two-Stage Machine Learning-Based Approach for Run-Time Specialized Hardware-Assisted Malware Detection. - Hossein Sayadi; Hosein Mohammadi Makrani; Sai Manoj Pudukotai Dinakarrao; Tinoosh Mohsenin; Avesta Sasan; Setareh Rafatirad; Houman Homayoun (DATE, 2019)

Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. - Bharat Prakash; Mohit Khatwani; Nicholas R. Waytowich; Tinoosh Mohsenin (FLAIRS, 2019)

On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. - Bharat Prakash; Mark Horton; Nicholas R. Waytowich; William David Hairston; Tim Oates 001; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2019)

ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications. - Maria Malik; Hassan Ghasemzadeh 001; Tinoosh Mohsenin; Rosario Cammarota; Liang Zhao 002; Avesta Sasan; Houman Homayoun; Setareh Rafatirad (ICPP, 2019)

Minimizing Classification Energy of Binarized Neural Network Inference for Wearable Devices. - Morteza Hosseini; Hirenkumar Paneliya; Utteja Kallakuri; Mohit Khatwani; Tinoosh Mohsenin (ISQED, 2019)

Learning from Observations Using a Single Video Demonstration and Human Feedback. - Sunil Gandhi; Tim Oates 001; Tinoosh Mohsenin; Nicholas R. Waytowich (CoRR, 2019)

Heterogeneous Scheduling of Deep Neural Networks for Low-power Real-time Designs. - Colin Shea; Tinoosh Mohsenin (ACM J. Emerg. Technol. Comput. Syst., 2019)

Big vs little core for energy-efficient Hadoop computing. - Maria Malik; Katayoun Neshatpour; Setareh Rafatirad; Rajiv V. Joshi; Tinoosh Mohsenin; Hassan Ghasemzadeh 001; Houman Homayoun (J. Parallel Distributed Comput., 2019)

SensorNet: A Scalable and Low-Power Deep Convolutional Neural Network for Multimodal Data Classification. - Ali Jafari; Ashwinkumar Ganesan; Chetan Sai Kumar Thalisetty; Varun Sivasubramanian; Tim Oates 001; Tinoosh Mohsenin (IEEE Trans. Circuits Syst. I Regul. Pap., 2019)

Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. - Bharat Prakash; Nicholas R. Waytowich; Ashwinkumar Ganesan; Tim Oates 001; Tinoosh Mohsenin (SafeAI@AAAI, 2020)

Mitigating Cache-Based Side-Channel Attacks through Randomization: A Comprehensive System and Architecture Level Analysis. - Han Wang 020; Hossein Sayadi; Tinoosh Mohsenin; Liang Zhao 002; Avesta Sasan; Setareh Rafatirad; Houman Homayoun (DATE, 2020)

StealthMiner: Specialized Time Series Machine Learning for Run-Time Stealthy Malware Detection based on Microarchitectural Features. - Hossein Sayadi; Yifeng Gao; Hosein Mohammadi Makrani; Tinoosh Mohsenin; Avesta Sasan; Setareh Rafatirad; Jessica Lin 001; Houman Homayoun (ACM Great Lakes Symposium on VLSI, 2020)

Energy-Efficient Hardware for Language Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Nitheesh Kumar Manjunath; Houman Homayoun; Avesta Sasan; Nicholas R. Waytowich; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2020)

Comprehensive Evaluation of Machine Learning Countermeasures for Detecting Microarchitectural Side-Channel Attacks. - Han Wang 020; Hossein Sayadi; Avesta Sasan; Setareh Rafatirad; Tinoosh Mohsenin; Houman Homayoun (ACM Great Lakes Symposium on VLSI, 2020)

Compressive Sensing Based Data Acquisition Architecture for Transient Stellar Events in Crowded Star Fields. - Asmita Korde-Patel; Richard K. Barry; Tinoosh Mohsenin (I2MTC, 2020)

Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks. - Farnaz Behnia; Ali Mirzaeian; Mohammad Sabokrou; Sai Manoj P. D.; Tinoosh Mohsenin; Khaled N. Khasawneh; Liang Zhao 002; Houman Homayoun; Avesta Sasan (ISQED, 2020)

A Low-Power LSTM Processor for Multi-Channel Brain EEG Artifact Detection. - Hasib-Al Rashid; Nitheesh Kumar Manjunath; Hirenkumar Paneliya; Morteza Hosseini; W. David Hairston; Tinoosh Mohsenin (ISQED, 2020)

CSCMAC - Cyclic Sparsely Connected Neural Network Manycore Accelerator. - Hirenkumar Paneliya; Morteza Hosseini; Avesta Sasan; Houman Homayoun; Tinoosh Mohsenin (ISQED, 2020)

An Energy-Efficient Low Power LSTM Processor for Human Activity Monitoring. - Arnab Neelim Mazumder; Hasib-Al Rashid; Tinoosh Mohsenin (SoCC, 2020)

End-to-end Scalable and Low Power Multi-modal CNN for Respiratory-related Symptoms Detection. - Haoran Ren; Arnab Neelim Mazumder; Hasib-Al Rashid; Vandana Chandrareddy; Aidin Shiri; Nitheesh Kumar Manjunath; Tinoosh Mohsenin (SoCC, 2020)

Learning Diverse Latent Representations for Improving the Resilience to Adversarial Attacks. - Ali Mirzaeian; Mohammad Sabokrou; Mohammad Khalooei; Jana Kosecka; Houman Homayoun; Tinoosh Mohsenin; Avesta Sasan (CoRR, 2020)

Cluster-Based Partitioning of Convolutional Neural Networks, A Solution for Computational Energy and Complexity Reduction. - Ali Mirzaeian; Masoud PourReza; Mohammad Sabokrou; Ashkan Vakil; Tinoosh Mohsenin; Houman Homayoun; Avesta Sasan (CoRR, 2020)

Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information. - Morteza Hosseini; Haoran Ren; Hasib-Al Rashid; Arnab Neelim Mazumder; Bharat Prakash; Tinoosh Mohsenin (CoRR, 2020)

CoughNet: A Flexible Low Power CNN-LSTM Processor for Cough Sound Detection. - Hasib-Al Rashid; Arnab Neelim Mazumder; Utteja Panchakshara Kallakuri Niyogi; Tinoosh Mohsenin (AICAS, 2021)

An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Bharat Prakash; Arnab Neelim Mazumder; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (AICAS, 2021)

Evaluation of Machine Learning-based Detection against Side-Channel Attacks on Autonomous Vehicle. - Han Wang 020; Soheil Salehi; Hossein Sayadi; Avesta Sasan; Tinoosh Mohsenin; Sai Manoj P. D.; Setareh Rafatirad; Houman Homayoun (AICAS, 2021)

Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks. - Ali Mirzaeian; Jana Kosecka; Houman Homayoun; Tinoosh Mohsenin; Avesta Sasan (ISQED, 2021)

2021 Roadmap on Neuromorphic Computing and Engineering. - Dennis V. Christensen; Regina Dittmann; Bernabé Linares-Barranco; Abu Sebastian; Manuel Le Gallo; Andrea Redaelli; Stefan Slesazeck; Thomas Mikolajick; Sabina Spiga; Stephan Menzel; Ilia Valov; Gianluca Milano; et al. (CoRR, 2021)

Interactive Hierarchical Guidance using Language. - Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2021)

Automatic Goal Generation using Dynamical Distance Learning. - Bharat Prakash; Nicholas R. Waytowich; Tinoosh Mohsenin; Tim Oates 001 (CoRR, 2021)

QS-NAS: Optimally Quantized Scaled Architecture Search to Enable Efficient On-Device Micro-AI. - Morteza Hosseini; Tinoosh Mohsenin (IEEE J. Emerg. Sel. Topics Circuits Syst., 2021)

A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference. - Arnab Neelim Mazumder; Jian Meng; Hasib-Al Rashid; Utteja Kallakuri; Xin Zhang 025; Jae-Sun Seo; Tinoosh Mohsenin (IEEE J. Emerg. Sel. Topics Circuits Syst., 2021)

Guest Editorial Cross-Layer Designs, Methodologies, and Systems to Enable Micro AI for On-Device Intelligence. - Tinoosh Mohsenin; Inna Partin-Vaisband; Houman Homayoun; Jae-Sun Seo; Xin Zhang 025 (IEEE J. Emerg. Sel. Topics Circuits Syst., 2021)

Binary Precision Neural Network Manycore Accelerator. - Morteza Hosseini; Tinoosh Mohsenin (ACM J. Emerg. Technol. Comput. Syst., 2021)

A Flexible Multichannel EEG Artifact Identification Processor using Depthwise-Separable Convolutional Neural Networks. - Mohit Khatwani; Hasib-Al Rashid; Hirenkumar Paneliya; Mark Horton; Nicholas R. Waytowich; W. David Hairston; Tinoosh Mohsenin (ACM J. Emerg. Technol. Comput. Syst., 2021)

An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning. - Nitheesh Kumar Manjunath; Aidin Shiri; Morteza Hosseini; Bharat Prakash; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Open J. Circuits Syst., 2021)

Adaptive Performance Modeling of Data-intensive Workloads for Resource Provisioning in Virtualized Environment. - Hosein Mohammadi Makrani; Hossein Sayadi; Najmeh Nazari; Sai Manoj Pudukotai Dinakarrao; Avesta Sasan; Tinoosh Mohsenin; Setareh Rafatirad; Houman Homayoun (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2021)

Cyclic Sparsely Connected Architectures for Compact Deep Convolutional Neural Networks. - Morteza Hosseini; Nitheesh Kumar Manjunath; Bharat Prakash; Arnab Neelim Mazumder; Vandana Chandrareddy; Houman Homayoun; Tinoosh Mohsenin (IEEE Trans. Very Large Scale Integr. Syst., 2021)

An Optimization Framework for Efficient Vision-Based Autonomous Drone Navigation. - Mozhgan Navardi; Aidin Shiri; Edward Humes; Nicholas R. Waytowich; Tinoosh Mohsenin (AICAS, 2022)

E2EdgeAI: Energy-Efficient Edge Computing for Deployment of Vision-Based DNNs on Autonomous Tiny Drones. - Mozhgan Navardi; Edward Humes; Tinoosh Mohsenin (SEC, 2022)

Neuromorphic-Enabled Security for IoT. - Soheil Salehi; Tyler David Sheaves; Kevin Immanuel Gubbi; Sayed Arash Beheshti; Sai Manoj P. D.; Setareh Rafatirad; Avesta Sasan; Tinoosh Mohsenin; Houman Homayoun (NEWCAS, 2022)

A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting. - Arnab Neelim Mazumder; Tinoosh Mohsenin (CoRR, 2022)

TinyM2Net: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices. - Hasib-Al Rashid; Pretom Roy Ovi; Aryya Gangopadhyay; Tinoosh Mohsenin (CoRR, 2022)

Towards an Interpretable Hierarchical Agent Framework using Semantic Goals. - Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2022)

Automatic Detection of Respiratory Symptoms Using a Low-Power Multi-Input CNN Processor. - Arnab Neelim Mazumder; Haoran Ren; Hasib-Al Rashid; Morteza Hosseini; Vandana Chandrareddy; Houman Homayoun; Tinoosh Mohsenin (IEEE Des. Test, 2022)

A Hardware Accelerator for Language-Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Houman Homayoun; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Des. Test, 2022)

Efficient Language-Guided Reinforcement Learning for Resource-Constrained Autonomous Systems. - Aidin Shiri; Mozhgan Navardi; Tejaswini Manjunath; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Micro, 2022)

2022 roadmap on neuromorphic computing and engineering. - Dennis V. Christensen; Regina Dittmann; Bernabé Linares-Barranco; Abu Sebastian; Manuel Le Gallo; Andrea Redaelli; Stefan Slesazeck; Thomas Mikolajick; Sabina Spiga; Stephan Menzel; Ilia Valov; Gianluca Milano; et al. (Neuromorph. Comput. Eng., 2022)

E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Uttej Kallakuri; Hasib-Al Rashid; Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (ACM Trans. Design Autom. Electr. Syst., 2022)

HAC-POCD: Hardware-Aware Compressed Activity Monitoring and Fall Detector Edge POC Devices. - Hasib-Al Rashid; Tinoosh Mohsenin (BioCAS, 2023)

Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach. - Arnab Neelim Mazumder; Niall Lyons; Ashutosh Pandey; Avik Santra; Tinoosh Mohsenin (EUSIPCO, 2023)

MLAE2: Metareasoning for Latency-Aware Energy-Efficient Autonomous Nano-Drones. - Mozhgan Navardi; Tinoosh Mohsenin (ISCAS, 2023)

ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents. - Tejaswini Manjunath; Mozhgan Navardi; Prakhar Dixit; Bharat Prakash; Tinoosh Mohsenin (CoRR, 2023)

LLM Augmented Hierarchical Agents. - Bharat Prakash; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2023)

Squeezed Edge YOLO: Onboard Object Detection on Edge Devices. - Edward Humes; Mozhgan Navardi; Tinoosh Mohsenin (CoRR, 2023)

Reg-TuneV2: A Hardware-Aware and Multiobjective Regression-Based Fine-Tuning Approach for Deep Neural Networks on Embedded Platforms. - Arnab Neelim Mazumder; Tinoosh Mohsenin (IEEE Micro, 2023)

MetaE2RL: Toward Meta-Reasoning for Energy-Efficient Multigoal Reinforcement Learning With Squeezed-Edge You Only Look Once. - Mozhgan Navardi; Edward Humes; Tejaswini Manjunath; Tinoosh Mohsenin (IEEE Micro, 2023)

Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors. - Bharat Prakash; Tim Oates 001; Tinoosh Mohsenin (FLAIRS, 2024)

Resource-Aware Saliency-Guided Differentiable Pruning for Deep Neural Networks. - Uttej Kallakuri; Edward Humes; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2024)

TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices. - Hasib-Al Rashid; Argho Sarkar; Aryya Gangopadhyay; Maryam Rahnemoonfar; Tinoosh Mohsenin (CoRR, 2024)

TinyM2Net-V3: Memory-Aware Compressed Multimodal Deep Neural Networks for Sustainable Edge Deployment. - Hasib-Al Rashid; Tinoosh Mohsenin (CoRR, 2024)

Energy-Aware FPGA Implementation of Spiking Neural Network with LIF Neurons. - Asmer Hamid Ali; Mozhgan Navardi; Tinoosh Mohsenin (CoRR, 2024)

Reg-Tune: A Regression-Focused Fine-Tuning Approach for Profiling Low Energy Consumption and Latency. - Arnab Neelim Mazumder; Farshad Safavi; Maryam Rahnemoonfar; Tinoosh Mohsenin (ACM Trans. Embed. Comput. Syst., 2024)

TinyM2Net-V2: A Compact Low-power Software Hardware Architecture for Multimodal Deep Neural Networks. - Hasib-Al Rashid; Utteja Kallakuri; Tinoosh Mohsenin (ACM Trans. Embed. Comput. Syst., 2024)

MetaTinyML: End-to-End Metareasoning Framework for TinyML Platforms. - Mozhgan Navardi; Edward Humes; Tinoosh Mohsenin (IEEE Embed. Syst. Lett., 2024)

GenAI at the Edge: Comprehensive Survey on Empowering Edge Devices. - Mozhgan Navardi; Romina Aalishah; Yuzhe Fu; Yueqian Lin; Hai Li 001; Yiran Chen 001; Tinoosh Mohsenin (AAAI Spring Symposia, 2025)

ATLASv2: LLM-Guided Adaptive Landmark Acquisition and Navigation on the Edge. - Mikolaj Walczak; Uttej Kallakuri; Tinoosh Mohsenin (AAAI Spring Symposia, 2025)

MambaLiteSR: Image Super-Resolution with Low-Rank Mamba Using Knowledge Distillation. - Romina Aalishah; Mozhgan Navardi; Tinoosh Mohsenin (ISQED, 2025)

Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning. - Ziyuan Bao; Eiman Kanjo; Soumya Banerjee; Hasib-Al Rashid; Tinoosh Mohsenin (CoRR, 2025)

RAFT: Robust Augmentation of FeaTures for Image Segmentation. - Edward Humes; Xiaomin Lin; Uttej Kallakuri; Tinoosh Mohsenin (CoRR, 2025)

Multi-RAG: A Multimodal Retrieval-Augmented Generation System for Adaptive Video Understanding. - Mingyang Mao; Mariela M. Perez-Cabarcas; Utteja Kallakuri; Nicholas R. Waytowich; Xiaomin Lin; Tinoosh Mohsenin (CoRR, 2025)

EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment. - Mikolaj Walczak; Romina Aalishah; Wyatt Mackey; Brittany Story; David L. Boothe; Nicholas R. Waytowich; Xiaomin Lin; Tinoosh Mohsenin (CoRR, 2025)

Enabling On-Device Medical AI Assistants via Input-Driven Saliency Adaptation. - Uttej Kallakurik; Edward Humes; Rithvik Jonna; Xiaomin Lin; Tinoosh Mohsenin (CoRR, 2025)

ViT-Reg: Regression-Focused Hardware-Aware Fine-Tuning for ViT on TinyML Platforms. - Md Ragib Shaharear; Arnab Neelim Mazumder; Tinoosh Mohsenin (IEEE Des. Test, 2025)