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ORCIDRamachandran Muralidhar
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2020 – today
- 2023
[j2]Shubham Jain
, Hsinyu Tsai, Ching-Tzu Chen, Ramachandran Muralidhar, Irem Boybat, Martin M. Frank, Stanislaw Wozniak, Milos Stanisavljevic, Praneet Adusumilli, Pritish Narayanan, Kohji Hosokawa, Masatoshi Ishii, Arvind Kumar, Vijay Narayanan, Geoffrey W. Burr:
A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh. IEEE Trans. Very Large Scale Integr. Syst. 31(1): 114-127 (2023)- [c9]Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte J. Rasch, Manuel Le Gallo, Hsinyu Tsai, Ramachandran Muralidhar, Smaïl Niar, Hamza Ouarnoughi, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui:
AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing. EDGE 2023: 233-244 - [c8]Martin M. Frank, Ning Li, Malte J. Rasch, Shubham Jain, Ching-Tzu Chen, Ramachandran Muralidhar, Jin-Ping Han, Vijay Narayanan, Timothy Philip, Kevin Brew, Andrew Simon, Iqbal Saraf, Nicole Saulnier, Irem Boybat, Stanislaw Wozniak, Abu Sebastian, Pritish Narayanan, Charles Mackin, An Chen, Hsinyu Tsai, Geoffrey W. Burr:
Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). IRPS 2023: 1-10 - [c7]Hsinyu Tsai, Pritish Narayanan, Shubham Jain, Stefano Ambrogio, Kohji Hosokawa, Masatoshi Ishii, Charles Mackin, Ching-Tzu Chen, Atsuya Okazaki, Akiyo Nomura, Irem Boybat, Ramachandran Muralidhar, Martin M. Frank, Takeo Yasuda, Alexander M. Friz, Yasuteru Kohda, An Chen, Andrea Fasoli, Malte J. Rasch, Stanislaw Wozniak, Jose Luquin, Vijay Narayanan, Geoffrey W. Burr:
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). ISCAS 2023: 1-5 - [i1]Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte J. Rasch, Manuel Le Gallo, Hsinyu Tsai, Ramachandran Muralidhar, Smaïl Niar, Hamza Ouarnoughi, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui:
AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing. CoRR abs/2305.10459 (2023) - 2022
- [c6]Siddesh Nageswaran, Ramachandran Muralidhar, Theodore G. van Kessel, Levente J. Klein:
Source Localization and Bayesian leak magnitude inference of sparse wireless sensor data to detect fugitive methane leak. IEEE Big Data 2022: 4868-4875 - 2020
- [c5]Theodore G. van Kessel, Levente J. Klein, Ramachandran Muralidhar, Eric J. Zhang, Hendrik F. Hamann:
Satellite Guided Mobile Wireless Methane Detection for Oil and Gas Operations. WF-IoT 2020: 1-4
2010 – 2019
- 2019
- [j1]Eric J. Zhang, Chu C. Teng, Theodore G. van Kessel, Levente J. Klein, Ramachandran Muralidhar, Gerard Wysocki, William M. J. Green:
Field Deployment of a Portable Optical Spectrometer for Methane Fugitive Emissions Monitoring on Oil and Gas Well Pads. Sensors 19(12): 2707 (2019) - 2018
- [c4]Theodore G. van Kessel, Ramachandran Muralidhar, Levente J. Klein, Dhruv Nair, Nigel Hinds, Hendrik F. Hamann, Norma E. Sosa:
Methane Leak Detection and Localization Using Wireless Sensor Networks for Remote Oil and Gas Operations. IEEE SENSORS 2018: 1-4 - 2017
- [c3]Theodore G. van Kessel, Ramachandran Muralidhar, Josephine B. Chang, Jun-Song Wang, Michael A. Schappert, Hendrik F. Hamann:
A low maintenance particle pollution sensing system using the Minimum Airflow Particle Counter (MAPC). IEEE BigData 2017: 4577-4582 - [c2]Levente J. Klein, Theodore G. van Kessel, Dhruv Nair, Ramachandran Muralidhar, Nigel Hinds, Hendrik F. Hamann, Norma E. Sosa:
Distributed wireless sensing for fugitive methane leak detection. IEEE BigData 2017: 4583-4591 - 2015
- [c1]Fen Chen, Carole Graas, Michael A. Shinosky, Chad Burke, Kai D. Feng, Craig Bocash, Ramachandran Muralidhar:
A method for rapid screening of various low-k TDDB models. IRPS 2015: 3
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