A method for rapid screening of various low-k TDDB models. - Fen Chen; Carole Graas; Michael A. Shinosky; Chad Burke; Kai D. Feng; Craig Bocash; Ramachandran Muralidhar (IRPS, 2015)

A low maintenance particle pollution sensing system using the Minimum Airflow Particle Counter (MAPC). - Theodore G. van Kessel; Ramachandran Muralidhar; Josephine B. Chang; Jun-Song Wang; Michael A. Schappert; Hendrik F. Hamann (IEEE BigData, 2017)

Distributed wireless sensing for fugitive methane leak detection. - Levente J. Klein; Theodore G. van Kessel; Dhruv Nair; Ramachandran Muralidhar; Nigel Hinds; Hendrik F. Hamann; Norma E. Sosa (IEEE BigData, 2017)

Methane Leak Detection and Localization Using Wireless Sensor Networks for Remote Oil and Gas Operations. - Theodore G. van Kessel; Ramachandran Muralidhar; Levente J. Klein; Dhruv Nair; Nigel Hinds; Hendrik F. Hamann; Norma E. Sosa (IEEE SENSORS, 2018)

Field Deployment of a Portable Optical Spectrometer for Methane Fugitive Emissions Monitoring on Oil and Gas Well Pads. - Eric J. Zhang; Chu C. Teng; Theodore G. van Kessel; Levente J. Klein; Ramachandran Muralidhar; Gerard Wysocki; William M. J. Green (Sensors, 2019)

Satellite Guided Mobile Wireless Methane Detection for Oil and Gas Operations. - Theodore G. van Kessel; Levente J. Klein; Ramachandran Muralidhar; Eric J. Zhang; Hendrik F. Hamann (WF-IoT, 2020)

Source Localization and Bayesian leak magnitude inference of sparse wireless sensor data to detect fugitive methane leak. - Siddesh Nageswaran; Ramachandran Muralidhar; Theodore G. van Kessel; Levente J. Klein (IEEE Big Data, 2022)

AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing. - 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 (EDGE, 2023)

Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). - 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; et al. (IRPS, 2023)

Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). - 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; et al. (ISCAS, 2023)

A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh. - 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; et al. (IEEE Trans. Very Large Scale Integr. Syst., 2023)