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2020 – today
- 2024
[j40]Arnab Neelim Mazumder
, Farshad Safavi, Maryam Rahnemoonfar, Tinoosh Mohsenin:
Reg-Tune: A Regression-Focused Fine-Tuning Approach for Profiling Low Energy Consumption and Latency. ACM Trans. Embed. Comput. Syst. 23(3): 44:1-44:28 (2024)- [j39]Hasib-Al Rashid, Utteja Kallakuri, Tinoosh Mohsenin:
TinyM2Net-V2: A Compact Low-power Software Hardware Architecture for Multimodal Deep Neural Networks. ACM Trans. Embed. Comput. Syst. 23(3): 47:1-47:23 (2024) - [c85]Bharat Prakash, Tim Oates, Tinoosh Mohsenin:
Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors. FLAIRS 2024 - [c84]Uttej Kallakuri, Edward Humes, Tinoosh Mohsenin:
Resource-Aware Saliency-Guided Differentiable Pruning for Deep Neural Networks. ACM Great Lakes Symposium on VLSI 2024: 694-699 - [i19]Hasib-Al Rashid, Argho Sarkar, Aryya Gangopadhyay, Maryam Rahnemoonfar, Tinoosh Mohsenin:
TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices. CoRR abs/2404.03574 (2024) - [i18]Hasib-Al Rashid, Tinoosh Mohsenin:
TinyM2Net-V3: Memory-Aware Compressed Multimodal Deep Neural Networks for Sustainable Edge Deployment. CoRR abs/2405.12353 (2024) - 2023
- [j38]Mozhgan Navardi, Edward Humes, Tejaswini Manjunath, Tinoosh Mohsenin:
MetaE2RL: Toward Meta-Reasoning for Energy-Efficient Multigoal Reinforcement Learning With Squeezed-Edge You Only Look Once. IEEE Micro 43(6): 29-39 (2023) - [j37]Arnab Neelim Mazumder, Tinoosh Mohsenin:
Reg-TuneV2: A Hardware-Aware and Multiobjective Regression-Based Fine-Tuning Approach for Deep Neural Networks on Embedded Platforms. IEEE Micro 43(6): 74-83 (2023) - [c83]Hasib-Al Rashid, Tinoosh Mohsenin:
HAC-POCD: Hardware-Aware Compressed Activity Monitoring and Fall Detector Edge POC Devices. BioCAS 2023: 1-5 - [c82]Arnab Neelim Mazumder, Niall Lyons, Ashutosh Pandey, Avik Santra, Tinoosh Mohsenin:
Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach. EUSIPCO 2023: 1-5 - [c81]Mozhgan Navardi, Tinoosh Mohsenin:
MLAE2: Metareasoning for Latency-Aware Energy-Efficient Autonomous Nano-Drones. ISCAS 2023: 1-5 - [i17]Tejaswini Manjunath, Mozhgan Navardi, Prakhar Dixit, Bharat Prakash, Tinoosh Mohsenin:
ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents. CoRR abs/2308.08737 (2023) - [i16]Bharat Prakash, Tim Oates, Tinoosh Mohsenin:
LLM Augmented Hierarchical Agents. CoRR abs/2311.05596 (2023) - [i15]Edward Humes, Mozhgan Navardi, Tinoosh Mohsenin:
Squeezed Edge YOLO: Onboard Object Detection on Edge Devices. CoRR abs/2312.11716 (2023) - 2022
- [j36]Aidin Shiri, Arnab Neelim Mazumder, Bharat Prakash, Houman Homayoun, Nicholas R. Waytowich, Tinoosh Mohsenin:
A Hardware Accelerator for Language-Guided Reinforcement Learning. IEEE Des. Test 39(3): 37-44 (2022) - [j35]Arnab Neelim Mazumder, Haoran Ren, Hasib-Al Rashid, Morteza Hosseini, Vandana Chandrareddy, Houman Homayoun, Tinoosh Mohsenin:
Automatic Detection of Respiratory Symptoms Using a Low-Power Multi-Input CNN Processor. IEEE Des. Test 39(3): 82-90 (2022) - [j34]Aidin Shiri, Mozhgan Navardi, Tejaswini Manjunath, Nicholas R. Waytowich, Tinoosh Mohsenin:
Efficient Language-Guided Reinforcement Learning for Resource-Constrained Autonomous Systems. IEEE Micro 42(6): 107-114 (2022) - [j33]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, Carlo Ricciardi, Shi-Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill, Scott T. Keene, Alberto Salleo, Julie Grollier, Danijela Markovic, Alice Mizrahi, Peng Yao, J. Joshua Yang, Giacomo Indiveri, John Paul Strachan, Suman Datta, Elisa Vianello, Alexandre Valentian, Johannes Feldmann, Xuan Li, Wolfram H. P. Pernice, Harish Bhaskaran, Steve B. Furber, Emre Neftci, Franz Scherr, Wolfgang Maass, Srikanth Ramaswamy, Jonathan Tapson, Priyadarshini Panda, Youngeun Kim, Gouhei Tanaka, Simon Thorpe, Chiara Bartolozzi, Thomas A. Cleland, Christoph Posch, Shih-Chii Liu, Gabriella Panuccio, Mufti Mahmud, Arnab Neelim Mazumder, Morteza Hosseini, Tinoosh Mohsenin, Elisa Donati, Silvia Tolu, Roberto Galeazzi, Martin Ejsing Christensen, Sune Holm, Daniele Ielmini, N. Pryds:
2022 roadmap on neuromorphic computing and engineering. Neuromorph. Comput. Eng. 2(2): 22501 (2022) - [j32]Aidin Shiri, Uttej Kallakuri, Hasib-Al Rashid, Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. ACM Trans. Design Autom. Electr. Syst. 27(5): 45:1-45:19 (2022) - [c80]Mozhgan Navardi, Aidin Shiri, Edward Humes, Nicholas R. Waytowich, Tinoosh Mohsenin:
An Optimization Framework for Efficient Vision-Based Autonomous Drone Navigation. AICAS 2022: 304-307 - [c79]Mozhgan Navardi, Edward Humes, Tinoosh Mohsenin:
E2EdgeAI: Energy-Efficient Edge Computing for Deployment of Vision-Based DNNs on Autonomous Tiny Drones. SEC 2022: 504-509 - [c78]Soheil Salehi, Tyler David Sheaves, Kevin Immanuel Gubbi, Sayed Arash Beheshti, Sai Manoj P. D., Setareh Rafatirad, Avesta Sasan, Tinoosh Mohsenin, Houman Homayoun:
Neuromorphic-Enabled Security for IoT. NEWCAS 2022: 153-157 - [i14]Arnab Neelim Mazumder, Tinoosh Mohsenin:
A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spotting. CoRR abs/2202.02361 (2022) - [i13]Hasib-Al Rashid, Pretom Roy Ovi, Aryya Gangopadhyay, Tinoosh Mohsenin:
TinyM2Net: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices. CoRR abs/2202.04303 (2022) - [i12]Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
Towards an Interpretable Hierarchical Agent Framework using Semantic Goals. CoRR abs/2210.08412 (2022) - 2021
- [j31]Tinoosh Mohsenin, Inna Partin-Vaisband, Houman Homayoun, Jae-Sun Seo, Xin Zhang:
Guest Editorial Cross-Layer Designs, Methodologies, and Systems to Enable Micro AI for On-Device Intelligence. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 527-531 (2021) - [j30]Arnab Neelim Mazumder, Jian Meng, Hasib-Al Rashid, Utteja Kallakuri, Xin Zhang, Jae-Sun Seo, Tinoosh Mohsenin:
A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 532-547 (2021) - [j29]Morteza Hosseini, Tinoosh Mohsenin:
QS-NAS: Optimally Quantized Scaled Architecture Search to Enable Efficient On-Device Micro-AI. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 597-610 (2021) - [j28]Morteza Hosseini, Tinoosh Mohsenin:
Binary Precision Neural Network Manycore Accelerator. ACM J. Emerg. Technol. Comput. Syst. 17(2): 19:1-19:27 (2021) - [j27]Mohit Khatwani, Hasib-Al Rashid, Hirenkumar Paneliya, Mark Horton, Nicholas R. Waytowich, W. David Hairston, Tinoosh Mohsenin:
A Flexible Multichannel EEG Artifact Identification Processor using Depthwise-Separable Convolutional Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 17(2): 23:1-23:21 (2021) - [j26]Nitheesh Kumar Manjunath, Aidin Shiri, Morteza Hosseini, Bharat Prakash, Nicholas R. Waytowich, Tinoosh Mohsenin:
An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning. IEEE Open J. Circuits Syst. 2: 182-195 (2021) - [j25]Hosein Mohammadi Makrani, Hossein Sayadi, Najmeh Nazari, Sai Manoj Pudukotai Dinakarrao, Avesta Sasan, Tinoosh Mohsenin, Setareh Rafatirad, Houman Homayoun:
Adaptive Performance Modeling of Data-intensive Workloads for Resource Provisioning in Virtualized Environment. ACM Trans. Model. Perform. Evaluation Comput. Syst. 5(4): 18:1-18:24 (2021) - [j24]Morteza Hosseini, Nitheesh Kumar Manjunath, Bharat Prakash, Arnab Neelim Mazumder, Vandana Chandrareddy, Houman Homayoun, Tinoosh Mohsenin:
Cyclic Sparsely Connected Architectures for Compact Deep Convolutional Neural Networks. IEEE Trans. Very Large Scale Integr. Syst. 29(10): 1757-1770 (2021) - [c77]Hasib-Al Rashid, Arnab Neelim Mazumder, Utteja Panchakshara Kallakuri Niyogi, Tinoosh Mohsenin:
CoughNet: A Flexible Low Power CNN-LSTM Processor for Cough Sound Detection. AICAS 2021: 1-4 - [c76]Aidin Shiri, Bharat Prakash, Arnab Neelim Mazumder, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. AICAS 2021: 1-4 - [c75]Han Wang, Soheil Salehi, Hossein Sayadi, Avesta Sasan, Tinoosh Mohsenin, Sai Manoj P. D., Setareh Rafatirad, Houman Homayoun:
Evaluation of Machine Learning-based Detection against Side-Channel Attacks on Autonomous Vehicle. AICAS 2021: 1-4 - [c74]Ali Mirzaeian, Jana Kosecka, Houman Homayoun, Tinoosh Mohsenin, Avesta Sasan:
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks. ISQED 2021: 319-324 - [i11]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, Carlo Ricciardi, Shi-Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill, Scott T. Keene, Alberto Salleo, Julie Grollier, Danijela Markovic, Alice Mizrahi, Peng Yao, J. Joshua Yang, Giacomo Indiveri, John Paul Strachan, Suman Datta, Elisa Vianello, Alexandre Valentian, Johannes Feldmann, Xuan Li, Wolfram H. P. Pernice, Harish Bhaskaran, Emre Neftci, Srikanth Ramaswamy, Jonathan Tapson, Franz Scherr, Wolfgang Maass, Priyadarshini Panda, Youngeun Kim, Gouhei Tanaka, Simon Thorpe, Chiara Bartolozzi, Thomas A. Cleland, Christoph Posch, Shih-Chii Liu, Arnab Neelim Mazumder, Morteza Hosseini, Tinoosh Mohsenin, Elisa Donati, Silvia Tolu, Roberto Galeazzi, Martin Ejsing Christensen, Sune Holm, Daniele Ielmini, N. Pryds:
2021 Roadmap on Neuromorphic Computing and Engineering. CoRR abs/2105.05956 (2021) - [i10]Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
Interactive Hierarchical Guidance using Language. CoRR abs/2110.04649 (2021) - [i9]Bharat Prakash, Nicholas R. Waytowich, Tinoosh Mohsenin, Tim Oates:
Automatic Goal Generation using Dynamical Distance Learning. CoRR abs/2111.04120 (2021) - 2020
- [c73]Bharat Prakash, Nicholas R. Waytowich, Ashwinkumar Ganesan, Tim Oates, Tinoosh Mohsenin:
Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. SafeAI@AAAI 2020: 153-161 - [c72]Han Wang, Hossein Sayadi, Tinoosh Mohsenin, Liang Zhao, Avesta Sasan, Setareh Rafatirad, Houman Homayoun:
Mitigating Cache-Based Side-Channel Attacks through Randomization: A Comprehensive System and Architecture Level Analysis. DATE 2020: 1414-1419 - [c71]Aidin Shiri, Arnab Neelim Mazumder, Bharat Prakash, Nitheesh Kumar Manjunath, Houman Homayoun, Avesta Sasan, Nicholas R. Waytowich, Tinoosh Mohsenin:
Energy-Efficient Hardware for Language Guided Reinforcement Learning. ACM Great Lakes Symposium on VLSI 2020: 131-136 - [c70]Hossein Sayadi, Yifeng Gao, Hosein Mohammadi Makrani, Tinoosh Mohsenin, Avesta Sasan, Setareh Rafatirad, Jessica Lin, Houman Homayoun:
StealthMiner: Specialized Time Series Machine Learning for Run-Time Stealthy Malware Detection based on Microarchitectural Features. ACM Great Lakes Symposium on VLSI 2020: 175-180 - [c69]Han Wang, Hossein Sayadi, Avesta Sasan, Setareh Rafatirad, Tinoosh Mohsenin, Houman Homayoun:
Comprehensive Evaluation of Machine Learning Countermeasures for Detecting Microarchitectural Side-Channel Attacks. ACM Great Lakes Symposium on VLSI 2020: 181-186 - [c68]Asmita Korde-Patel, Richard K. Barry, Tinoosh Mohsenin:
Compressive Sensing Based Data Acquisition Architecture for Transient Stellar Events in Crowded Star Fields. I2MTC 2020: 1-6 - [c67]Farnaz Behnia, Ali Mirzaeian, Mohammad Sabokrou, Sai Manoj P. D., Tinoosh Mohsenin, Khaled N. Khasawneh, Liang Zhao, Houman Homayoun, Avesta Sasan:
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks. ISQED 2020: 27-32 - [c66]Hasib-Al Rashid, Nitheesh Kumar Manjunath, Hirenkumar Paneliya, Morteza Hosseini, W. David Hairston, Tinoosh Mohsenin:
A Low-Power LSTM Processor for Multi-Channel Brain EEG Artifact Detection. ISQED 2020: 105-110 - [c65]Hirenkumar Paneliya, Morteza Hosseini, Avesta Sasan, Houman Homayoun, Tinoosh Mohsenin:
CSCMAC - Cyclic Sparsely Connected Neural Network Manycore Accelerator. ISQED 2020: 311-316 - [c64]Arnab Neelim Mazumder, Hasib-Al Rashid, Tinoosh Mohsenin:
An Energy-Efficient Low Power LSTM Processor for Human Activity Monitoring. SoCC 2020: 54-59 - [c63]Haoran Ren, Arnab Neelim Mazumder, Hasib-Al Rashid, Vandana Chandrareddy, Aidin Shiri, Nitheesh Kumar Manjunath, Tinoosh Mohsenin:
End-to-end Scalable and Low Power Multi-modal CNN for Respiratory-related Symptoms Detection. SoCC 2020: 102-107 - [e2]Tinoosh Mohsenin, Weisheng Zhao, Yiran Chen, Onur Mutlu:
GLSVLSI '20: Great Lakes Symposium on VLSI 2020, Virtual Event, China, September 7-9, 2020. ACM 2020, ISBN 978-1-4503-7944-1 [contents] - [i8]Farnaz Behnia, Ali Mirzaeian, Mohammad Sabokrou, Sai Manoj P. D., Tinoosh Mohsenin, Khaled N. Khasawneh, Liang Zhao, Houman Homayoun, Avesta Sasan:
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks. CoRR abs/2001.06099 (2020) - [i7]Ali Mirzaeian, Mohammad Sabokrou, Mohammad Khalooei, Jana Kosecka, Houman Homayoun, Tinoosh Mohsenin, Avesta Sasan:
Learning Diverse Latent Representations for Improving the Resilience to Adversarial Attacks. CoRR abs/2006.15127 (2020) - [i6]Ali Mirzaeian, Masoud PourReza, Mohammad Sabokrou, Ashkan Vakil, Tinoosh Mohsenin, Houman Homayoun, Avesta Sasan:
Cluster-Based Partitioning of Convolutional Neural Networks, A Solution for Computational Energy and Complexity Reduction. CoRR abs/2006.15799 (2020) - [i5]Morteza Hosseini, Haoran Ren, Hasib-Al Rashid, Arnab Neelim Mazumder, Bharat Prakash, Tinoosh Mohsenin:
Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information. CoRR abs/2011.13194 (2020)
2010 – 2019
- 2019
- [j23]Colin Shea, Tinoosh Mohsenin:
Heterogeneous Scheduling of Deep Neural Networks for Low-power Real-time Designs. ACM J. Emerg. Technol. Comput. Syst. 15(4): 36:1-36:31 (2019) - [j22]Maria Malik, Katayoun Neshatpour, Setareh Rafatirad, Rajiv V. Joshi, Tinoosh Mohsenin, Hassan Ghasemzadeh, Houman Homayoun:
Big vs little core for energy-efficient Hadoop computing. J. Parallel Distributed Comput. 129: 110-124 (2019) - [j21]Ali Jafari, Ashwinkumar Ganesan, Chetan Sai Kumar Thalisetty, Varun Sivasubramanian, Tim Oates, Tinoosh Mohsenin:
SensorNet: A Scalable and Low-Power Deep Convolutional Neural Network for Multimodal Data Classification. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(1): 274-287 (2019) - [c62]Hosein Mohammadi Makrani, Hossein Sayadi, Tinoosh Mohsenin, Setareh Rafatirad, Avesta Sasan, Houman Homayoun:
XPPE: cross-platform performance estimation of hardware accelerators using machine learning. ASP-DAC 2019: 727-732 - [c61]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, Nicholas R. Waytowich:
Learning Behaviors from a Single Video Demonstration Using Human Feedback. AAMAS 2019: 1970-1972 - [c60]Morteza Hosseini, Mark Horton, Hiren Paneliya, Uttej Kallakuri, Houman Homayoun, Tinoosh Mohsenin:
On the Complexity Reduction of Dense Layers from O(N2) to O(NlogN) with Cyclic Sparsely Connected Layers. DAC 2019: 203 - [c59]Hossein Sayadi, Hosein Mohammadi Makrani, Sai Manoj Pudukotai Dinakarrao, Tinoosh Mohsenin, Avesta Sasan, Setareh Rafatirad, Houman Homayoun:
2SMaRT: A Two-Stage Machine Learning-Based Approach for Run-Time Specialized Hardware-Assisted Malware Detection. DATE 2019: 728-733 - [c58]Bharat Prakash, Mohit Khatwani, Nicholas R. Waytowich, Tinoosh Mohsenin:
Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. FLAIRS 2019: 50-55 - [c57]Bharat Prakash, Mark Horton, Nicholas R. Waytowich, William David Hairston, Tim Oates, Tinoosh Mohsenin:
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. ACM Great Lakes Symposium on VLSI 2019: 507-512 - [c56]Maria Malik, Hassan Ghasemzadeh, Tinoosh Mohsenin, Rosario Cammarota, Liang Zhao, Avesta Sasan, Houman Homayoun, Setareh Rafatirad:
ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications. ICPP 2019: 7:1-7:11 - [c55]Morteza Hosseini, Hirenkumar Paneliya, Utteja Kallakuri, Mohit Khatwani, Tinoosh Mohsenin:
Minimizing Classification Energy of Binarized Neural Network Inference for Wearable Devices. ISQED 2019: 259-264 - [p1]Amey M. Kulkarni, Tinoosh Mohsenin:
SENSE: Sketching Framework for Big Data Acceleration on Low Power Embedded Cores. Security and Fault Tolerance in Internet of Things 2019: 201-214 - [e1]Houman Homayoun, Baris Taskin, Tinoosh Mohsenin, Weisheng Zhao:
Proceedings of the 2019 on Great Lakes Symposium on VLSI, GLSVLSI 2019, Tysons Corner, VA, USA, May 9-11, 2019. ACM 2019, ISBN 978-1-4503-6252-8 [contents] - [i4]Bharat Prakash, Mohit Khatwani, Nicholas R. Waytowich, Tinoosh Mohsenin:
Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. CoRR abs/1903.09328 (2019) - [i3]Bharat Prakash, Mark Horton, Nicholas R. Waytowich, William David Hairston, Tim Oates, Tinoosh Mohsenin:
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. CoRR abs/1903.10404 (2019) - [i2]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, Nicholas R. Waytowich:
Learning from Observations Using a Single Video Demonstration and Human Feedback. CoRR abs/1909.13392 (2019) - 2018
- [j20]Mohammad Hossein Hajkazemi, Mohammad Khavari Tavana, Tinoosh Mohsenin, Houman Homayoun:
Heterogeneous HMC+DDRx Memory Management for Performance-Temperature Tradeoffs. ACM J. Emerg. Technol. Comput. Syst. 14(1): 4:1-4:21 (2018) - [j19]Katayoun Neshatpour, Maria Malik, Avesta Sasan, Setareh Rafatirad, Tinoosh Mohsenin, Hassan Ghasemzadeh, Houman Homayoun:
Energy-efficient acceleration of MapReduce applications using FPGAs. J. Parallel Distributed Comput. 119: 1-17 (2018) - [j18]Ali Jafari, Nathanael Buswell, Maysam Ghovanloo, Tinoosh Mohsenin:
A Low-Power Wearable Stand-Alone Tongue Drive System for People With Severe Disabilities. IEEE Trans. Biomed. Circuits Syst. 12(1): 58-67 (2018) - [j17]Nasrin Attaran, Abhilash Puranik, Justin Brooks, Tinoosh Mohsenin:
Embedded Low-Power Processor for Personalized Stress Detection. IEEE Trans. Circuits Syst. II Express Briefs 65-II(12): 2032-2036 (2018) - [j16]Amey M. Kulkarni, Colin Shea, Tahmid Abtahi, Houman Homayoun, Tinoosh Mohsenin:
Low Overhead CS-Based Heterogeneous Framework for Big Data Acceleration. ACM Trans. Embed. Comput. Syst. 17(1): 25:1-25:25 (2018) - [j15]Adwaya Kulkarni, Adam Page, Nasrin Attaran, Ali Jafari, Maria Malik, Houman Homayoun, Tinoosh Mohsenin:
An Energy-Efficient Programmable Manycore Accelerator for Personalized Biomedical Applications. IEEE Trans. Very Large Scale Integr. Syst. 26(1): 96-109 (2018) - [j14]Tahmid Abtahi, Colin Shea, Amey M. Kulkarni, Tinoosh Mohsenin:
Accelerating Convolutional Neural Network With FFT on Embedded Hardware. IEEE Trans. Very Large Scale Integr. Syst. 26(9): 1737-1749 (2018) - [c54]Mohit Khatwani, Morteza Hosseini, Hirenkumar Paneliya, Tinoosh Mohsenin, W. David Hairston, Nicholas R. Waytowich:
Energy Efficient Convolutional Neural Networks for EEG Artifact Detection. BioCAS 2018: 1-4 - [c53]Colin Shea, Adam Page, Tinoosh Mohsenin:
SCALENet: A SCalable Low power AccELerator for Real-time Embedded Deep Neural Networks. ACM Great Lakes Symposium on VLSI 2018: 129-134 - [c52]Lahir Marni, Morteza Hosseini, Tinoosh Mohsenin:
MC3A: Markov Chain Monte Carlo ManyCore Accelerator. ACM Great Lakes Symposium on VLSI 2018: 165-170 - [c51]Ali Jafari, Morteza Hosseini, Adwaya Kulkarni, Chintan Patel, Tinoosh Mohsenin:
BiNMAC: Binarized neural Network Manycore ACcelerator. ACM Great Lakes Symposium on VLSI 2018: 443-446 - [c50]Avesta Sasan, Qi Zhu, Yanzhi Wang, Jae-sun Seo, Tinoosh Mohsenin:
Low Power and Trusted Machine Learning. ACM Great Lakes Symposium on VLSI 2018: 515 - [c49]Lahir Marni, Morteza Hosseini, Jennifer Hopp, Pedram Mohseni, Tinoosh Mohsenin:
A Real-Time Wearable FPGA-based Seizure Detection Processor Using MCMC. ISCAS 2018: 1-4 - [c48]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, W. David Hairston:
Denoising Time Series Data Using Asymmetric Generative Adversarial Networks. PAKDD (3) 2018: 285-296 - [c47]Ali Jafari, Morteza Hosseini, Houman Homayoun, Tinoosh Mohsenin:
A Scalable and Low Power DCNN for Multimodal Data Classification. ReConFig 2018: 1-6 - [c46]Morteza Hosseini, Rashidul Islam, Lahir Marni, Tinoosh Mohsenin:
MPT: Multiple Parallel Tempering for High-Throughput MCMC Samplers. SoCC 2018: 244-249 - 2017
- [j13]Adam Page, Ali Jafari, Colin Shea, Tinoosh Mohsenin:
SPARCNet: A Hardware Accelerator for Efficient Deployment of Sparse Convolutional Networks. ACM J. Emerg. Technol. Comput. Syst. 13(3): 31:1-31:32 (2017) - [j12]Amey M. Kulkarni, Tinoosh Mohsenin:
Low Overhead Architectures for OMP Compressive Sensing Reconstruction Algorithm. IEEE Trans. Circuits Syst. I Regul. Pap. 64-I(6): 1468-1480 (2017) - [c45]Ali Jafari, Maysam Ghovanloo, Tinoosh Mohsenin:
An embedded FPGA accelerator for a stand-alone dual-mode assistive device. BioCAS 2017: 1-4 - [c44]Maria Malik, Katayoun Neshatpour, Tinoosh Mohsenin, Avesta Sasan, Houman Homayoun:
Big vs little core for energy-efficient Hadoop computing. DATE 2017: 1480-1485 - [c43]Amey M. Kulkarni, Colin Shea, Houman Homayoun, Tinoosh Mohsenin:
LESS: Big data sketching and Encryption on low power platform. DATE 2017: 1631-1634 - [c42]Ali Jafari, Maysam Ghovanloo, Tinoosh Mohsenin:
A Real-Time Embedded FPGA Processor for a Stand-Alone Dual-Mode Assistive Device. FCCM 2017: 199 - [c41]Morteza Hosseini, Rashidul Islam, Amey M. Kulkarni, Tinoosh Mohsenin:
A Scalable FPGA-Based Accelerator for High-Throughput MCMC Algorithms. FCCM 2017: 201 - [c40]Tahmid Abtahi, Amey M. Kulkarni, Tinoosh Mohsenin:
Accelerating convolutional neural network with FFT on tiny cores. ISCAS 2017: 1-4 - [c39]Ali Jafari, Sunil Gandhi, Sri Harsha Konuru, W. David Hairston, Tim Oates, Tinoosh Mohsenin:
An EEG artifact identification embedded system using ICA and multi-instance learning. ISCAS 2017: 1-4 - [c38]Adwaya Kulkarni, Tahmid Abtahi, Colin Shea, Amey M. Kulkarni, Tinoosh Mohsenin:
PACENet: Energy efficient acceleration for convolutional network on embedded platform. ISCAS 2017: 1-4 - [i1]J. T. Turner, Adam Page, Tinoosh Mohsenin, Tim Oates:
Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection. CoRR abs/1708.08430 (2017) - 2016
- [j11]Amey M. Kulkarni, Youngok K. Pino, Matthew French, Tinoosh Mohsenin:
Real-Time Anomaly Detection Framework for Many-Core Router through Machine-Learning Techniques. ACM J. Emerg. Technol. Comput. Syst. 13(1): 10:1-10:22 (2016) - [c37]Asmita Korde-Patel, Richard K. Barry, Tinoosh Mohsenin:
Application of Compressive Sensing to Gravitational Microlensing Experiments. Astroinformatics 2016: 67-70 - [c36]Adam Page, Tinoosh Mohsenin:
FPGA-Based Reduction Techniques for Efficient Deep Neural Network Deployment. FCCM 2016: 200 - [c35]Amey M. Kulkarni, Ali Jafari, Colin Shea, Tinoosh Mohsenin:
CS-Based Secured Big Data Processing on FPGA. FCCM 2016: 201 - [c34]Amey M. Kulkarni, Tahmid Abtahi, Emily Smith, Tinoosh Mohsenin:
Low Energy Sketching Engines on Many-Core Platform for Big Data Acceleration. ACM Great Lakes Symposium on VLSI 2016: 57-62 - [c33]Adam Page, Nasrin Attaran, Colin Shea, Houman Homayoun, Tinoosh Mohsenin:
Low-Power Manycore Accelerator for Personalized Biomedical Applications. ACM Great Lakes Symposium on VLSI 2016: 63-68 - [c32]Amey M. Kulkarni, Youngok K. Pino, Tinoosh Mohsenin:
Adaptive real-time Trojan detection framework through machine learning. HOST 2016: 120-123 - [c31]Nasrin Attaran, Justin Brooks, Tinoosh Mohsenin:
A low-power multi-physiological monitoring processor for stress detection. IEEE SENSORS 2016: 1-3 - [c30]Adam Page, Colin Shea, Tinoosh Mohsenin:
Wearable seizure detection using convolutional neural networks with transfer learning. ISCAS 2016: 1086-1089 - [c29]Amey M. Kulkarni, Ali Jafari, Chris Sagedy, Tinoosh Mohsenin:
Sketching-based high-performance biomedical big data processing accelerator. ISCAS 2016: 1138-1141 - [c28]Amey M. Kulkarni, Youngok K. Pino, Tinoosh Mohsenin:
SVM-based real-time hardware Trojan detection for many-core platform. ISQED 2016: 362-367 - [c27]Maria Malik, Farnoud Farahmand, Paul Otto, Nima Akhlaghi, Tinoosh Mohsenin, Siddhartha Sikdar, Houman Homayoun:
Architecture Exploration for Energy-Efficient Embedded Vision Applications: From General Purpose Processor to Domain Specific Accelerator. ISVLSI 2016: 559-564 - 2015
- [j10]Adam Page, Chris Sagedy, Emily Smith, Nasrin Attaran, Tim Oates, Tinoosh Mohsenin:
A Flexible Multichannel EEG Feature Extractor and Classifier for Seizure Detection. IEEE Trans. Circuits Syst. II Express Briefs 62-II(2): 109-113 (2015) - [j9]Sina Viseh, Maysam Ghovanloo, Tinoosh Mohsenin:
Toward an Ultralow-Power Onboard Processor for Tongue Drive System. IEEE Trans. Circuits Syst. II Express Briefs 62-II(2): 174-178 (2015) - [c26]Ali Jafari, Nathanael Buswell, Adam Page, Tinoosh Mohsenin, Md. Nazmus Sahadat, Maysam Ghovanloo:
Live demonstration: Towards an ultra low power on-board processor for Tongue Drive System. BioCAS 2015: 1 - [c25]Ali Jafari, Adam Page, Chris Sagedy, Emily Smith, Tinoosh Mohsenin:
A low power seizure detection processor based on direct use of compressively-sensed data and employing a deterministic random matrix. BioCAS 2015: 1-4 - [c24]Adam Page, Amey M. Kulkarni, Tinoosh Mohsenin:
Utilizing deep neural nets for an embedded ECG-based biometric authentication system. BioCAS 2015: 1-4 - [c23]Adam Page, Siddharth Pramod, Tim Oates, Tinoosh Mohsenin:
An ultra low power feature extraction and classification system for wearable seizure detection. EMBC 2015: 7111-7114 - [c22]Amey M. Kulkarni, Tinoosh Mohsenin:
Accelerating compressive sensing reconstruction OMP algorithm with CPU, GPU, FPGA and domain specific many-core. ISCAS 2015: 970-973 - 2014
- [c21]J. T. Turner, Adam Page, Tinoosh Mohsenin, Tim Oates:
Deep Belief Networks Used on High Resolution Multichannel Electroencephalography Data for Seizure Detection. AAAI Spring Symposia 2014 - [c20]Adam Page, J. T. Turner, Tinoosh Mohsenin, Tim Oates:
Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods. FLAIRS 2014 - [c19]Adarsh Reddy Ashammagari, Hamid Mahmoodi, Tinoosh Mohsenin, Houman Homayoun:
Reconfigurable STT-NV LUT-based functional units to improve performance in general-purpose processors. ACM Great Lakes Symposium on VLSI 2014: 249-254 - [c18]Amey M. Kulkarni, Houman Homayoun, Tinoosh Mohsenin:
A parallel and reconfigurable architecture for efficient OMP compressive sensing reconstruction. ACM Great Lakes Symposium on VLSI 2014: 299-304 - [c17]Mohammad Khavari Tavana, Amey M. Kulkarni, Abbas Rahimi, Tinoosh Mohsenin, Houman Homayoun:
Energy-efficient mapping of biomedical applications on domain-specific accelerator under process variation. ISLPED 2014: 275-278 - [c16]Brice M. Cannon, Tanvir Mahmood, William Astar, Paul Boudra, Tinoosh Mohsenin, Gary M. Carter:
Polarization-insensitive phase-transmultiplexing of CSRZ-OOK and RZ-BPSK to RZ-QPSK via XPM in a PCF. OFC 2014: 1-3 - 2013
- [j8]Tinoosh Mohsenin, Houshmand Shirani-mehr, Bevan M. Baas:
LDPC Decoder with an Adaptive Wordwidth Datapath for Energy and BER Co-Optimization. VLSI Design 2013: 913018:1-913018:14 (2013) - [c15]Adam Page, Tinoosh Mohsenin:
An efficient & reconfigurable FPGA and ASIC implementation of a spectral Doppler ultrasound imaging system. ASAP 2013: 198-202 - [c14]Jérôme L. V. M. Stanislaus, Tinoosh Mohsenin:
Low-complexity FPGA implementation of compressive sensing reconstruction. ICNC 2013: 671-675 - [c13]Jordan Bisasky, Houman Homayoun, Farhang Yazdani, Tinoosh Mohsenin:
A 64-core platform for biomedical signal processing. ISQED 2013: 368-372 - 2012
- [c12]Jérôme L. V. M. Stanislaus, Tinoosh Mohsenin:
High performance compressive sensing reconstruction hardware with QRD process. ISCAS 2012: 29-32 - [c11]Jordan Bisasky, Darin Chandler, Tinoosh Mohsenin:
A many-core platform implemented for multi-channel seizure detection. ISCAS 2012: 564-567 - 2011
- [c10]Houshmand Shirani-mehr, Tinoosh Mohsenin, Bevan M. Baas:
A reduced routing network architecture for partial parallel LDPC decoders. ACSCC 2011: 2192-2196 - [c9]Tinoosh Mohsenin, Houshmand Shirani-mehr, Bevan M. Baas:
Low power LDPC decoder with efficient stopping scheme for undecodable blocks. ISCAS 2011: 1780-1783 - 2010
- [j7]Tinoosh Mohsenin, Dean Nguyen Truong, Bevan M. Baas:
A Low-Complexity Message-Passing Algorithm for Reduced Routing Congestion in LDPC Decoders. IEEE Trans. Circuits Syst. I Regul. Pap. 57-I(5): 1048-1061 (2010) - [j6]Tinoosh Mohsenin, Bevan M. Baas:
A Split-Decoding Message Passing Algorithm for Low Density Parity Check Decoders. J. Signal Process. Syst. 61(3): 329-345 (2010)
2000 – 2009
- 2009
- [j5]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, Paul Vincent Mejia, Bevan M. Baas:
A 167-Processor Computational Platform in 65 nm CMOS. IEEE J. Solid State Circuits 44(4): 1130-1144 (2009) - [c8]Tinoosh Mohsenin, Dean Truong, Bevan M. Baas:
An Improved Split-Row Threshold Decoding Algorithm for LDPC Codes. ICC 2009: 1-5 - [c7]Tinoosh Mohsenin, Dean Nguyen Truong, Bevan M. Baas:
Multi-Split-Row Threshold Decoding Implementations for LDPC Codes. ISCAS 2009: 2449-2452 - 2008
- [j4]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:
AsAP: An Asynchronous Array of Simple Processors. IEEE J. Solid State Circuits 43(3): 695-705 (2008) - [j3]Zhiyi Yu, Michael J. Meeuwsen, Ryan W. Apperson, Omar Sattari, Michael A. Lai, Jeremy W. Webb, Eric W. Work, Tinoosh Mohsenin, Bevan M. Baas:
Architecture and Evaluation of an Asynchronous Array of Simple Processors. J. Signal Process. Syst. 53(3): 243-259 (2008) - [c6]Tinoosh Mohsenin, Pascal Urard, Bevan M. Baas:
A thresholding algorithm for improved Split-Row decoding of LDPC codes. ACSCC 2008: 448-451 - 2007
- [j2]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:
AsAP: A Fine-Grained Many-Core Platform for DSP Applications. IEEE Micro 27(2): 34-45 (2007) - [j1]Ryan W. Apperson, Zhiyi Yu, Michael J. Meeuwsen, Tinoosh Mohsenin, Bevan M. Baas:
A Scalable Dual-Clock FIFO for Data Transfers Between Arbitrary and Haltable Clock Domains. IEEE Trans. Very Large Scale Integr. Syst. 15(10): 1125-1134 (2007) - [c5]Tinoosh Mohsenin, Bevan M. Baas:
High-Throughput LDPC Decoders Using A Multiple Split-Row Method. ICASSP (2) 2007: 13-16 - 2006
- [c4]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, Tinoosh Mohsenin:
Hardware and applications of AsAP: An asynchronous array of simple processors. Hot Chips Symposium 2006: 1-31 - [c3]Tinoosh Mohsenin, Bevan M. Baas:
Split-Row: A Reduced Complexity, High Throughput LDPC Decoder Architecture. ICCD 2006: 320-325 - [c2]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:
An asynchronous array of simple processors for dsp applications. ISSCC 2006: 1696-1705 - 2003
- [c1]Patrick Murphy, J. Patrick Frantz, Erik Welsh, Ricky Hardy, Tinoosh Mohsenin, Joseph R. Cavallaro:
VALID: Custom ASIC Verification and FPGA Education Platform. MSE 2003: 64-65
Coauthor Index
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