| 2026 | PAKDD | 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 |
| 2025 | ICCAD | Invited Paper: BitMedViT: Ternary-Quantized Vision Transformer for Medical AI Assistants on the Edge. | Mikolaj Walczak, Uttej Kallakuri, Edward Humes, Xiaomin Lin, Tinoosh Mohsenin |
| 2024 | FlAIRS | Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors. | Bharat Prakash, Tim Oates, Tinoosh Mohsenin |
| 2023 | ISCAS | MLAE2: Metareasoning for Latency-Aware Energy-Efficient Autonomous Nano-Drones. | Mozhgan Navardi, Tinoosh Mohsenin |
| 2020 | AAAI | Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. | Bharat Prakash, Nicholas R. Waytowich, Ashwinkumar Ganesan, Tim Oates, Tinoosh Mohsenin |
| 2020 | DATE | Mitigating Cache-Based Side-Channel Attacks through Randomization: A Comprehensive System and Architecture Level Analysis. | Han Wang, Hossein Sayadi, Tinoosh Mohsenin, Liang Zhao, Avesta Sasan, Setareh Rafatirad, Houman Homayoun |
| 2019 | ASPDAC | XPPE: cross-platform performance estimation of hardware accelerators using machine learning. | Hosein Mohammadi Makrani, Hossein Sayadi, Tinoosh Mohsenin, Setareh Rafatirad, Avesta Sasan, Houman Homayoun |
| 2019 | DAC | 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 |
| 2019 | DATE | 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 |
| 2019 | FlAIRS | Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. | Bharat Prakash, Mohit Khatwani, Nicholas R. Waytowich, Tinoosh Mohsenin |
| 2019 | ICPP | ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications. | Maria Malik, Hassan Ghasemzadeh, Tinoosh Mohsenin, Rosario Cammarota, Liang Zhao, Avesta Sasan, Houman Homayoun, Setareh Rafatirad |
| 2018 | ISCAS | A Real-Time Wearable FPGA-based Seizure Detection Processor Using MCMC. | Lahir Marni, Morteza Hosseini, Jennifer Hopp, Pedram Mohseni, Tinoosh Mohsenin |
| 2018 | PAKDD | Denoising Time Series Data Using Asymmetric Generative Adversarial Networks. | Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, W. David Hairston |
| 2017 | DATE | LESS: Big data sketching and Encryption on low power platform. | Amey M. Kulkarni, Colin Shea, Houman Homayoun, Tinoosh Mohsenin |
| 2017 | DATE | Big vs little core for energy-efficient Hadoop computing. | Maria Malik, Katayoun Neshatpour, Tinoosh Mohsenin, Avesta Sasan, Houman Homayoun |
| 2017 | FCCM | A Scalable FPGA-Based Accelerator for High-Throughput MCMC Algorithms. | Morteza Hosseini, Rashidul Islam, Amey M. Kulkarni, Tinoosh Mohsenin |
| 2017 | FCCM | A Real-Time Embedded FPGA Processor for a Stand-Alone Dual-Mode Assistive Device. | Ali Jafari, Maysam Ghovanloo, Tinoosh Mohsenin |
| 2017 | ISCAS | Accelerating convolutional neural network with FFT on tiny cores. | Tahmid Abtahi, Amey M. Kulkarni, Tinoosh Mohsenin |
| 2017 | ISCAS | An EEG artifact identification embedded system using ICA and multi-instance learning. | Ali Jafari, Sunil Gandhi, Sri Harsha Konuru, W. David Hairston, Tim Oates, Tinoosh Mohsenin |
| 2017 | ISCAS | PACENet: Energy efficient acceleration for convolutional network on embedded platform. | Adwaya Kulkarni, Tahmid Abtahi, Colin Shea, Amey M. Kulkarni, Tinoosh Mohsenin |
| 2016 | FCCM | CS-Based Secured Big Data Processing on FPGA. | Amey M. Kulkarni, Ali Jafari, Colin Shea, Tinoosh Mohsenin |
| 2016 | FCCM | FPGA-Based Reduction Techniques for Efficient Deep Neural Network Deployment. | Adam Page, Tinoosh Mohsenin |
| 2016 | ISCAS | Sketching-based high-performance biomedical big data processing accelerator. | Amey M. Kulkarni, Ali Jafari, Chris Sagedy, Tinoosh Mohsenin |
| 2016 | ISCAS | Wearable seizure detection using convolutional neural networks with transfer learning. | Adam Page, Colin Shea, Tinoosh Mohsenin |
| 2015 | ISCAS | Accelerating compressive sensing reconstruction OMP algorithm with CPU, GPU, FPGA and domain specific many-core. | Amey M. Kulkarni, Tinoosh Mohsenin |
| 2014 | FlAIRS | Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods. | Adam Page, J. T. Turner, Tinoosh Mohsenin, Tim Oates |
| 2014 | ISLPED | 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 |
| 2012 | ISCAS | A many-core platform implemented for multi-channel seizure detection. | Jordan Bisasky, Darin Chandler, Tinoosh Mohsenin |
| 2012 | ISCAS | High performance compressive sensing reconstruction hardware with QRD process. | Jrme L. V. M. Stanislaus, Tinoosh Mohsenin |
| 2011 | ACSSC | A reduced routing network architecture for partial parallel LDPC decoders. | Houshmand Shirani-mehr, Tinoosh Mohsenin, Bevan M. Baas |
| 2011 | ISCAS | Low power LDPC decoder with efficient stopping scheme for undecodable blocks. | Tinoosh Mohsenin, Houshmand Shirani-mehr, Bevan M. Baas |
| 2009 | ISCAS | Multi-Split-Row Threshold Decoding Implementations for LDPC Codes. | Tinoosh Mohsenin, Dean Nguyen Truong, Bevan M. Baas |
| 2008 | ACSSC | A thresholding algorithm for improved Split-Row decoding of LDPC codes. | Tinoosh Mohsenin, Pascal Urard, Bevan M. Baas |
| 2007 | ICASSP | High-Throughput LDPC Decoders Using A Multiple Split-Row Method. | Tinoosh Mohsenin, Bevan M. Baas |
| 2006 | ICCD | Split-Row: A Reduced Complexity, High Throughput LDPC Decoder Architecture. | Tinoosh Mohsenin, Bevan M. Baas |