Kids today! Engineers tomorrow? - John Cohn (ISSCC, 2009)

Preface: Technologies for a Smarter Planet. - Joanne L. Martin; Hugh Varilly; John Cohn; Glenn R. Wightwick (IBM J. Res. Dev., 2010)

An integrated zigbee transmitter and DC-DC converter on 0.18μm HV RF CMOS technology. - Chaojiang Li; Dawn Wang; Myra Boenke; Ted Letavic; John Cohn (ASICON, 2013)

SCALE: Safe community awareness and ale rting leveraging the internet of things. - Kyle E. Benson; Charles Fracchia; Guoxi Wang; Qiuxi Zhu; Serene Almomen; John Cohn; Luke D'arcy; Daniel Hoffman; Matthew Makai; Julien Stamatakis; Nalini Venkatasubramanian (IEEE Commun. Mag., 2015)

The Future of IoT. - Joern Ploennigs; John Cohn; Andy J. Stanford-Clark (IEEE Internet Things Mag., 2018)

MCUNet: Tiny Deep Learning on IoT Devices. - Ji Lin 002; Wei-Ming Chen; Yujun Lin 001; John Cohn; Chuang Gan 001; Song Han 003 (NeurIPS, 2020)

SonicPACT: An Ultrasonic Ranging Method for the Private Automated Contact Tracing (PACT) Protocol. - John Meklenburg; Michael A. Specter; Michael Wentz; Hari Balakrishnan; Anantha P. Chandrakasan; John Cohn; Gary Hatke; Louise Ivers; Ronald L. Rivest; Gerald Jay Sussman; Daniel J. Weitzner (CoRR, 2020)

Deep Analysis of CNN-Based Spatio-Temporal Representations for Action Recognition. - Chun-Fu (Richard) Chen; Rameswar Panda; Kandan Ramakrishnan; Rogério Feris; John Cohn; Aude Oliva; Quanfu Fan (CVPR, 2021)

CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection. - Quanfu Fan; Yilai Li; Yuguang Yao; John Cohn; Sijia Liu 001; Seychelle M. Vos; Michael A. Cianfrocco (CoRR, 2022)

Quantifying worker interactions and characterizing worker performance through ubiquitous IoT. - Wen Dong 001; Edmund Do; Byung Suk Lee 001; John Cohn (Pervasive Mob. Comput., 2022)

A Secure Digital In-Memory Compute (IMC) Macro with Protections for Side-Channel and Bus Probing Attacks. - Maitreyi Ashok; Saurav Maji; Xin Zhang 025; John Cohn; Anantha P. Chandrakasan (CICC, 2024)

CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection. - Quanfu Fan; Yilai Li; Yuguang Yao; John Cohn; Sijia Liu 001; Ziping Xu; Seychelle M. Vos; Michael A. Cianfrocco (WACV, 2024)

Efficient Circuit Performance Prediction Using Machine Learning: From Schematic to Layout and Silicon Measurement with Minimal Data Input. - Dimple Vijay Kochar; Maitreyi Ashok; John Cohn; Anantha P. Chandrakasan; Xin Zhang 025 (ISCAS, 2025)

A 14-nm Energy-Efficient and Reconfigurable Analog Current-Domain In-Memory Compute SRAM Accelerator. - Aya G. Amer; Maitreyi Ashok; Xin Zhang 025; John Cohn; Anantha P. Chandrakasan (VLSID, 2025)

Digital In-Memory Compute for Machine Learning Applications With Input and Model Security. - Maitreyi Ashok; Saurav Maji; Xin Zhang 025; John Cohn; Anantha P. Chandrakasan (IEEE J. Solid State Circuits, 2025)