Fabrication and Performance of Hybrid ReRAM-CMOS Circuit Elements for Dynamic Neural Networks. - Maximilian Liehr; Jubin Hazra; Karsten Beckmann; Wilkie Olin-Ammentorp; Nathaniel C. Cady; Ryan Weiss; Sagarvarma Sayyaparaju; Garrett S. Rose; Joseph Van Nostrand (ICONS, 2019)

Optimization of Switching Metrics for CMOS Integrated HfO2 based RRAM Devices on 300 mm Wafer Platform. - Jubin Hazra; Maximilian Liehr; Karsten Beckmann; Minhaz Abedin; Sarah Rafiq; Nathaniel C. Cady (IMW, 2021)

Robust RRAM-based In-Memory Computing in Light of Model Stability. - Gokul Krishnan; Jingbo Sun; Jubin Hazra; Xiaocong Du; Maximilian Liehr; Zheng Li 020; Karsten Beckmann; Rajiv V. Joshi; Nathaniel C. Cady; Yu Cao 001 (IRPS, 2021)

In-memory Computation of Error-Correcting Codes Using a Reconfigurable HfOx ReRAM 1T1R Array. - Minhaz Abedin; Maximilian Liehr; Karsten Beckmann; Jubin Hazra; Sarah Rafiq; Nathaniel C. Cady (MWSCAS, 2021)

Investigation of ReRAM Variability on Flow-Based Edge Detection Computing Using HfO2-Based ReRAM Arrays. - Sarah Rafiq; Jubin Hazra; Maximilian Liehr; Karsten Beckmann; Minhaz Abedin; Jodh S. Pannu; Sumit Kumar Jha 001; Nathaniel C. Cady (IEEE Trans. Circuits Syst. I Regul. Pap., 2021)

A Compact Model for the Variable Switching Dynamics of HfO2 Memristors. - Manu Rathore; Ryan Weiss; Mst Shamim Ara Shawkat; Garrett S. Rose; Maximilian Liehr; Minhaz Abedin; Sarah Rafiq; Nathaniel C. Cady (MWSCAS, 2022)

Exploring Model Stability of Deep Neural Networks for Reliable RRAM-Based In-Memory Acceleration. - Gokul Krishnan; Li Yang 009; Jingbo Sun; Jubin Hazra; Xiaocong Du; Maximilian Liehr; Zheng Li 020; Karsten Beckmann; Rajiv V. Joshi; Nathaniel C. Cady; Deliang Fan; Yu Cao 001 (IEEE Trans. Computers, 2022)

Hybrid RRAM/SRAM in-Memory Computing for Robust DNN Acceleration. - Gokul Krishnan; Zhenyu Wang; Injune Yeo; Li Yang 009; Jian Meng; Maximilian Liehr; Rajiv V. Joshi; Nathaniel C. Cady; Deliang Fan; Jae-Sun Seo; Yu Cao 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

A 65nm RRAM Compute-in-Memory Macro for Genome Sequencing Alignment. - Fan Zhang 069; Wangxin He; Injune Yeo; Maximilian Liehr; Nathaniel C. Cady; Yu Cao 001; Jae-Sun Seo; Deliang Fan (ESSCIRC, 2023)

RFAM: RESET-Failure-Aware-Model for HfO2-based Memristor to Enhance the Reliability of Neuromorphic Design. - Hritom Das; Manu Rathore; Rocco Febbo; Maximilian Liehr; Nathaniel C. Cady; Garrett S. Rose (ACM Great Lakes Symposium on VLSI, 2023)

Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator. - Mehrdad Morsali; Sepehr Tabrizchi; Maximilian Liehr; Nathaniel C. Cady; Mohsen Imani; Arman Roohi; Shaahin Angizi (ICRC, 2023)

An Efficient and Accurate Memristive Memory for Array-Based Spiking Neural Networks. - Hritom Das; Rocco D. Febbo; Sree Nirmillo Biswash Tushar; Nishith N. Chakraborty; Maximilian Liehr; Nathaniel C. Cady; Garrett S. Rose (IEEE Trans. Circuits Syst. I Regul. Pap., 2023)

In-Memory Computation Using CMOS-Integrated Resistive RAM for Robotic Navigation. - Jeelka Solanki; Jacob Pelton; Rocco Febbo; Maximilian Liehr; Andrew DeCandia; Karsten Beckmann; Garrett S. Rose; Nathaniel C. Cady (ICONS, 2024)

A 65-nm RRAM Compute-in-Memory Macro for Genome Processing. - Fan Zhang 069; Amitesh Sridharan; Wangxin He; Injune Yeo; Maximilian Liehr; Wei Zhang 076; Nathaniel C. Cady; Yu Cao 001; Jae-Sun Seo; Deliang Fan (IEEE J. Solid State Circuits, 2024)