Hybrid CMOS/memristor circuits. - Dmitri B. Strukov; Duncan R. Stewart; Julien Borghetti; Xuema Li; Matthew D. Pickett; Gilberto Medeiros-Ribeiro; Warren Robinett; Gregory S. Snider; John Paul Strachan; Wei Wu; Qiangfei Xia; J. Joshua Yang; et al. (ISCAS, 2010)

CMOS interface circuits for reading and writing memristor crossbar array. - Muhammad Shakeel Qureshi; Matthew D. Pickett; Feng Miao; John Paul Strachan (ISCAS, 2011)

Designing memristors: Physics, materials science and engineering. - Gilberto Medeiros-Ribeiro; J. Joshua Yang; Janice H. Nickel; Antonio Torrezan; John Paul Strachan; R. Stanley Williams (ISCAS, 2012)

Physics-based memristor models. - R. Stanley Williams; Matthew D. Pickett; John Paul Strachan (ISCAS, 2013)

Dot-product engine for neuromorphic computing: programming 1T1M crossbar to accelerate matrix-vector multiplication. - Miao Hu 002; John Paul Strachan; Zhiyong Li; Emmanuelle M. Grafals; Noraica Davila; Catherine Graves; Sity Lam; Ning Ge 001; Jianhua Joshua Yang; R. Stanley Williams (DAC, 2016)

Fading memory effects in a memristor for Cellular Nanoscale Network applications. - Alon Ascoli; Ronald Tetzlaff; Leon O. Chua; John Paul Strachan; R. Stanley Williams (DATE, 2016)

Accelerating Discrete Fourier Transforms with dot-product engine. - Miao Hu 002; John Paul Strachan (ICRC, 2016)

ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars. - Ali Shafiee; Anirban Nag; Naveen Muralimanohar; Rajeev Balasubramonian; John Paul Strachan; Miao Hu 002; R. Stanley Williams; Vivek Srikumar (ISCA, 2016)

Dot-product engine as computing memory to accelerate machine learning algorithms. - Miao Hu 002; John Paul Strachan; Zhiyong Li; R. Stanley Williams (ISQED, 2016)

History Erase Effect in a Non-Volatile Memristor. - Alon Ascoli; Ronald Tetzlaff; Leon O. Chua; John Paul Strachan; Richard Stanley Williams (IEEE Trans. Circuits Syst. I Regul. Pap., 2016)

Rescuing Memristor-based Neuromorphic Design with High Defects. - Chenchen Liu; Miao Hu 002; John Paul Strachan; Hai (Helen) Li (DAC, 2017)

Generalize or Die: Operating Systems Support for Memristor-Based Accelerators. - Pedro Bruel; Sai Rahul Chalamalasetti; Chris I. Dalton; Izzat El Hajj; Alfredo Goldman; Catherine Graves; Wen-Mei W. Hwu; Phil Laplante; Dejan S. Milojicic; Geoffrey Ndu; John Paul Strachan (ICRC, 2017)

Looking Ahead for Resistive Memory Technology: A broad perspective on ReRAM technology for future storage and computing. - Hai (Helen) Li; Yiran Chen 001; Chenchen Liu; John Paul Strachan; Noraica Davila (IEEE Consumer Electron. Mag., 2017)

Computing In-Memory, Revisited. - Dejan S. Milojicic; Kirk Bresniker; Gary Campbell; Paolo Faraboschi; John Paul Strachan; Stan Williams (ICDCS, 2018)

Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning. - Joao Ambrosi; Aayush Ankit; Rodrigo Antunes; Sai Rahul Chalamalasetti; Soumitra Chatterjee; Izzat El Hajj; Guilherme Fachini; Paolo Faraboschi; Martin Foltin; Sitao Huang; Wen-Mei Hwu; Gustavo Knuppe; et al. (ICRC, 2018)

Regular Expression Matching with Memristor TCAMs. - Catherine E. Graves; Wen Ma; Xia Sheng; Brent Buchanan; Le Zheng; Sity Lam; Xuema Li; Sai Rahul Chalamalasetti; Lennie Kiyama; Martin Foltin; Matthew P. Hardy; John Paul Strachan (ICRC, 2018)

Large Memristor Crossbars for Analog Computing. - Can Li; Yunning Li; Hao Jiang 017; Wenhao Song; Peng Lin; Zhongrui Wang; J. Joshua Yang; Qiangfei Xia; Miao Hu 002; Eric Montgomery; Jiaming Zhang; Noraica Dávila; et al. (ISCAS, 2018)

Regular Expression Matching with Memristor TCAMs for Network Security. - Catherine E. Graves; Wen Ma; Xia Sheng; Brent Buchanan; Le Zheng; Sity Lam; Xuema Li; Sai Rahul Chalamalasetti; Lennie Kiyama; Martin Foltin; John Paul Strachan; Matthew P. Hardy (NANOARCH, 2018)

Long short-term memory networks in memristor crossbars. - Can Li; Zhongrui Wang; Mingyi Rao; Daniel Belkin; Wenhao Song; Hao Jiang 017; Peng Yan; Yunning Li; Peng Lin; Miao Hu 002; Ning Ge 001; John Paul Strachan; et al. (CoRR, 2018)

Newton: Gravitating Towards the Physical Limits of Crossbar Acceleration. - Anirban Nag; Rajeev Balasubramonian; Vivek Srikumar; Ross Walker 001; Ali Shafiee; John Paul Strachan; Naveen Muralimanohar (IEEE Micro, 2018)

The Art and Science of Constructing a Memristor Model: Updated. - Suhas Kumar; Gary Gibson; Catherine E. Graves; Matthew D. Pickett; John Paul Strachan; R. Stanley Williams (Handbook of Memristor Networks, 2019)

PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. - Aayush Ankit; Izzat El Hajj; Sai Rahul Chalamalasetti; Geoffrey Ndu; Martin Foltin; R. Stanley Williams; Paolo Faraboschi; Wen-mei W. Hwu; John Paul Strachan; Kaushik Roy 001; Dejan S. Milojicic (ASPLOS, 2019)

Future Computing Systems (FCS) to Support "Understanding" Capability. - Raymond G. Beausoleil; Thomas Van Vaerenbergh; Kirk Bresniker; Catherine Graves; Kimberly Keeton; Suhas Kumar; Can Li; Dejan S. Milojicic; Sergey Serebryakov; John Paul Strachan (ICRC, 2019)

FPGA Demonstrator of a Programmable Ultra-Efficient Memristor-Based Machine Learning Inference Accelerator. - Martin Foltin; Glaucimar Aguiar; Rodrigo Antunes; Plínio Silveira; Gustavo Knuppe; Joao Ambrosi; Soumitra Chatterjee; Jitendra Onkar Kolhe; Sunil Lakshiminarashimha; Dejan S. Milojicic; John Paul Strachan; Craig Warner; et al. (ICRC, 2019)

Harnessing Intrinsic Noise in Memristor Hopfield Neural Networks for Combinatorial Optimization. - Fuxi Cai; Suhas Kumar; Thomas Van Vaerenbergh; Rui Liu 005; Can Li; Shimeng Yu; Qiangfei Xia; J. Joshua Yang; Raymond G. Beausoleil; Wei Lu 003; John Paul Strachan (CoRR, 2019)

Analog content addressable memories with memristors. - Can Li; Catherine E. Graves; Darrin Miller; John Paul Strachan (CoRR, 2019)

Thermodynamic Computing. - Tom Conte 001; Erik DeBenedictis; Natesh Ganesh; Todd Hylton; John Paul Strachan; R. Stanley Williams; Alexander A. Alemi; Lee Altenberg; Gavin E. Crooks; James P. Crutchfield; Lídia del Rio; Josh Deutsch; et al. (CoRR, 2019)

Long short-term memory networks in memristor crossbar arrays. - Can Li; Zhongrui Wang; Mingyi Rao; Daniel Belkin; Wenhao Song; Hao Jiang 017; Peng Yan; Yunning Li; Peng Lin; Miao Hu 002; Ning Ge 001; John Paul Strachan; et al. (Nat. Mach. Intell., 2019)

In situ training of feed-forward and recurrent convolutional memristor networks. - Zhongrui Wang; Can Li; Peng Lin; Mingyi Rao; Yongyang Nie; Wenhao Song; Qinru Qiu; Yunning Li; Peng Yan; John Paul Strachan; Ning Ge 001; Nathan McDonald; et al. (Nat. Mach. Intell., 2019)

Classical Adiabatic Annealing in Memristor Hopfield Neural Networks for Combinatorial Optimization. - Suhas Kumar; Thomas Van Vaerenbergh; John Paul Strachan (ICRC, 2020)

PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM. - Aayush Ankit; Izzat El Hajj; Sai Rahul Chalamalasetti; Sapan Agarwal; Matthew J. Marinella; Martin Foltin; John Paul Strachan; Dejan S. Milojicic; Wen-Mei Hwu; Kaushik Roy 001 (IEEE Trans. Computers, 2020)

Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. - Sitao Huang; Aayush Ankit; Plínio Silveira; Rodrigo Antunes; Sai Rahul Chalamalasetti; Izzat El Hajj; Dong Eun Kim; Glaucimar Aguiar; Pedro Bruel; Sergey Serebryakov; Cong Xu; Can Li; et al. (ASP-DAC, 2021)

Defect tolerant in-memory analog computing with CMOS-integrated nanoscale crossbars: Invited. - Mingrui Jiang; Ruibin Mao; John Paul Strachan; Can Li (ICECS, 2021)

Tree-based machine learning performed in-memory with memristive analog CAM. - Giacomo Pedretti; Catherine E. Graves; Can Li; Sergey Serebryakov; Xia Sheng; Martin Foltin; Ruibin Mao; John Paul Strachan (CoRR, 2021)

2021 Roadmap on Neuromorphic Computing and Engineering. - 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; et al. (CoRR, 2021)

Prospects for Analog Circuits in Deep Networks. - Shih-Chii Liu; John Paul Strachan; Arindam Basu (CoRR, 2021)

Integration of Physics-Derived Memristor Models with Machine Learning Frameworks. - Zhenming Yu; Stephan Menzel; John Paul Strachan; Emre Neftci (IEEECONF, 2022)

A general tree-based machine learning accelerator with memristive analog CAM. - Giacomo Pedretti; Sergey Serebryakov; John Paul Strachan; Catherine E. Graves (ISCAS, 2022)

Experimentally realized memristive memory augmented neural network. - Ruibin Mao; Bo Wen; Yahui Zhao; Arman Kazemi; Ann Franchesca Laguna; Michael T. Niemier; X. Sharon Hu; Xia Sheng; Catherine E. Graves; John Paul Strachan; Can Li (CoRR, 2022)

2022 roadmap on neuromorphic computing and engineering. - 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; et al. (Neuromorph. Comput. Eng., 2022)

State-Space Modeling and Tuning of Memristors for Neuromorphic Computing Applications. - Ming-Jay Yang; John Paul Strachan (ICONS, 2023)

Local Fading Memory Effects in a Tantalum Oxide ReRAM Cell from Hewlett Packard Labs. - Alon Ascoli; Nicolas Schmitt; Ioannis Messaris; Ahmet Samil Demirkol; Ronald Tetzlaff; John Paul Strachan; Leon O. Chua (MetroXRAINE, 2023)

Analog Feedback-Controlled Memristor Programming Circuit for Analog Content Addressable Memory. - Jiaao Yu; Paul-Philipp Manea; Sara Ameli; Mohammad Hizzani; Amro Eldebiky; John Paul Strachan (MetroXRAINE, 2023)

Non-idealities and Design Solutions for Analog Memristor-Based Content-Addressable Memories. - Paul-Philipp Manea; Chirag Sudarshan; Felix Cüppers; John Paul Strachan (NANOARCH, 2023)

High-Speed and Energy-Efficient Non-Volatile Silicon Photonic Memory Based on Heterogeneously Integrated Memresonator. - Bassem Tossoun; Di Liang; Stanley Cheung; Zhuoran Fang; Xia Sheng; John Paul Strachan; Raymond G. Beausoleil (CoRR, 2023)

Research Challenges for Energy-Efficient Computing in Automated Vehicles. - Robert P. Dick; Rob Aitken; Jace Mogill; John Paul Strachan; Kirk Bresniker; Wei Lu 003; Yorie Nakahira; Zhiyong Li; Matthew J. Marinella; William Severa; A. Alec Talin; Craig M. Vineyard; et al. (Computer, 2023)

The Ouroboros of Memristors: Neural Networks Facilitating Memristor Programming. - Zhenming Yu; Ming-Jay Yang; Jan Finkbeiner; Sebastian Siegel; John Paul Strachan; Emre Neftci (AICAS, 2024)

Gradient matching of higher order combinatorial optimization in quadratic Ising machines. - Dmitrii Dobrynin; Mauricio Tedeschi; Arne Heittmann; John Paul Strachan (ICRC, 2024)

Memristor-based hardware and algorithms for higher-order Hopfield optimization solver outperforming quadratic Ising machines. - Mohammad Hizzani; Arne Heittmann; George Higgins Hutchinson; Dmitrii Dobrynin; Thomas Van Vaerenbergh; Tinish Bhattacharya; Adrien Renaudineau; Dmitri B. Strukov; John Paul Strachan (ISCAS, 2024)

An Analytical Method to Induce a Multistable Periodic Response to Pulse Trains in a ReRAM Cell. - Alon Ascoli; Fernando Corinto; Marco Gilli; Ahmet Samil Demirkol; Nicolas Schmitt; Ioannis Messaris; Ronald Tetzlaff; John Paul Strachan; Leon O. Chua (MOCAST, 2024)

Computing High-Degree Polynomial Gradients in Memory. - Tinish Bhattacharya; George Higgins Hutchinson; Giacomo Pedretti; X. Sheng; Jim Ignowski; Thomas Van Vaerenbergh; Raymond G. Beausoleil; John Paul Strachan; Dmitri B. Strukov (CoRR, 2024)

Roadmap to Neuromorphic Computing with Emerging Technologies. - Adnan Mehonic; Daniele Ielmini; Kaushik Roy 001; Onur Mutlu; Shahar Kvatinsky; Teresa Serrano-Gotarredona; Bernabé Linares-Barranco; Sabina Spiga; Sergey Savelev; Alexander G. Balanov; Nitin Chawla; Giuseppe Desoli; et al. (CoRR, 2024)

Analog In-Memory Computing Attention Mechanism for Fast and Energy-Efficient Large Language Models. - Nathan Leroux; Paul-Philipp Manea; Chirag Sudarshan; Jan Finkbeiner; Sebastian Siegel; John Paul Strachan; Emre Neftci (CoRR, 2024)

Analog Softmax with Wide Input Current Range for In-Memory Computing. - Aradhana Dube; Paul Manea; Paolo Gibertini; Erika Covi; John Paul Strachan (ISCAS, 2025)

Impact of Variability Compensation on the Performance of an RRAM-based 3-SAT Solver. - Arne Heittmann; Mohammad Hizzani; John Paul Strachan (ISCAS, 2025)

Gain Cell-based Analog Content Addressable Memory for Dynamic Associative Tasks in AI. - Paul-Philipp Manea; Nathan Leroux; Emre Neftci; John Paul Strachan (ISCAS, 2025)

IMSSA: Deploying modern state-space models on memristive in-memory compute hardware. - Sebastian Siegel; Ming-Jay Yang; John Paul Strachan (ISCAS, 2025)

Not All Neurons Are Equal: Enhancing Hopfield Networks for Solving Quadratized Higher-Order Combinatorial Optimization. - Mohammad Hizzani; Arne Heittmann; John Paul Strachan (NewCAS, 2025)

Solving Boolean satisfiability problems with resistive content addressable memories. - Giacomo Pedretti; Fabian Böhm; Tinish Bhattacharya; Arne Heittmann; Xiangyi Zhang; Mohammad Hizzani; George Higgins Hutchinson; Dongseok Kwon; John Moon; Elisabetta Valiante; Ignacio Rozada; Catherine E. Graves; et al. (CoRR, 2025)

Hardware-Compatible Single-Shot Feasible-Space Heuristics for Solving the Quadratic Assignment Problem. - Haesol Im; Chan-Woo Yang; Moslem Noori; Dmitrii Dobrynin; Elisabetta Valiante; Giacomo Pedretti; Arne Heittmann; Thomas Van Vaerenbergh; Masoud Mohseni; John Paul Strachan; Dmitri B. Strukov; Raymond G. Beausoleil; et al. (CoRR, 2025)

Accelerating Hybrid XOR-CNF SAT Problems Natively with In-Memory Computing. - Haesol Im; Fabian Böhm; Giacomo Pedretti; Noriyuki Kushida; Moslem Noori; Elisabetta Valiante; Xiangyi Zhang; Chan-Woo Yang; Tinish Bhattacharya; Xia Sheng; Jim Ignowski; Arne Heittmann; et al. (CoRR, 2025)

Real-time raw signal genomic analysis using fully integrated memristor hardware. - Peiyi He; Shengbo Wang; Ruibin Mao; Sebastian Siegel; Giacomo Pedretti; Jim Ignowski; John Paul Strachan; Ruibang Luo; Can Li (CoRR, 2025)

QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models. - Sebastian Siegel; Ming-Jay Yang; Younes Bouhadjar; Maxime Fabre; Emre Neftci; John Paul Strachan (CoRR, 2025)

Nonlocal Monte Carlo via Reinforcement Learning. - Dmitrii Dobrynin; Masoud Mohseni; John Paul Strachan (CoRR, 2025)