3D implication logic: Preliminary results. - Gina C. Adam (FPT, 2011)

What motivates STEM teachers to attend professional development? A case study in Chilian high schools. - Gina C. Adam; Danielle Boyd Harlow; Vanessa N. Dominguez (FIE, 2014)

Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors. - Mirko Prezioso; Farnood Merrikh-Bayat; Brian Hoskins; Gina C. Adam; Konstantin K. Likharev; Dmitri B. Strukov (CoRR, 2014)

Three-Dimensional Stateful Material Implication Logic. - Gina C. Adam; Brian D. Hoskins; Mirko Prezioso; Dmitri B. Strukov (CoRR, 2015)

Highly-uniform multi-layer ReRAM crossbar circuits. - Gina C. Adam; Brian D. Hoskins; Mirko Prezioso; Farnood Merrikh-Bayat; Bhaswar Chakrabarti; Dmitri B. Strukov (ESSDERC, 2016)

Spiking neuromorphic networks with metal-oxide memristors. - Mirko Prezioso; Y. Zhong; D. Gavrilov; Farnood Merrikh-Bayat; Brian Hoskins; Gina C. Adam; Konstantin K. Likharev; Dmitri B. Strukov (ISCAS, 2016)

Highly-Secure Physically Unclonable Cryptographic Primitives Using Nonlinear Conductance and Analog State Tuning in Memristive Crossbar Arrays. - Hussein Nili; Gina C. Adam; Mirko Prezioso; Jeeson Kim; Farnood Merrikh-Bayat; Omid Kavehei; Dmitri B. Strukov (CoRR, 2016)

Utilizing I-V non-linearity and analog state variations in ReRAM-based security primitives. - Gina C. Adam; Hussein Nili; Jeeson Kim; Brian D. Hoskins; Omid Kavehei; Dmitri B. Strukov (ESSDERC, 2017)

Micro- and Macroscale Ideas of Current Among Upper-Division Electrical Engineering Students. - Gina C. Adam; Danielle Boyd Harlow; Susan M. Lord; Christian H. Kautz (IEEE Trans. Educ., 2017)

Streaming Batch Eigenupdates for Hardware Neuromorphic Networks. - Brian D. Hoskins; Matthew W. Daniels; Siyuan Huang 002; Advait Madhavan; Gina C. Adam; Nikolai Zhitenev; Jabez J. McClelland; Mark D. Stiles (CoRR, 2019)

Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract). - Siyuan Huang 002; Brian D. Hoskins; Matthew W. Daniels; Mark D. Stiles; Gina C. Adam (AAAI, 2020)

Batch Training for Neuromorphic Systems with Device Non-idealities. - Yutong Gao 003; Shang Wu; Gina C. Adam (ICONS, 2020)

Memory-efficient training with streaming dimensionality reduction. - Siyuan Huang 002; Brian D. Hoskins; Matthew W. Daniels; Mark D. Stiles; Gina C. Adam (CoRR, 2020)

A System for Validating Resistive Neural Network Prototypes. - Brian Hoskins; Wen Ma; Mitchell Fream; Osama Yousuf; Matthew W. Daniels; Jonathan Goodwill; Advait Madhavan; Hoang Tung; Mark Branstad; Muqing Liu; Rasmus Madsen; Jabez J. McClelland; et al. (ICONS, 2021)

Radiofrequency Switches Based on Emerging Resistive Memory Technologies - A Survey. - Nicolás Wainstein; Gina C. Adam; Eilam Yalon; Shahar Kvatinsky (Proc. IEEE, 2021)

Effect of OTS Selector Reliabilities on NVM Crossbar-based Neuromorphic Training. - Wen Ma; Tung Thanh Hoang; Brian Hoskins; Matthew W. Daniels; Jabez J. McClelland; Yutong Gao 003; Gina C. Adam; Martin Lueker-Boden (IRPS, 2022)

Hardware-Mappable Cellular Neural Networks for Distributed Wavefront Detection in Next-Generation Cardiac Implants. - Zhuolin Yang; Lei Zhang; Kedar Aras; Igor R. Efimov; Gina C. Adam (Adv. Intell. Syst., 2022)

RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture. - Jingdi Chen; Lei Zhang; Joseph Riem; Gina C. Adam; Nathaniel D. Bastian; Tian Lan 001 (DSC, 2023)

Neural Network Modeling Bias for Hafnia-based FeFETs. - Osama Yousuf; Imtiaz Hossen; Andreu Glasmann; Sina Najmaei; Gina C. Adam (NANOARCH, 2023)

Real-time Network Intrusion Detection via Decision Transformers. - Jingdi Chen; Hanhan Zhou; Yongsheng Mei; Gina C. Adam; Nathaniel D. Bastian; Tian Lan 001 (CoRR, 2023)

Device Modeling Bias in ReRAM-Based Neural Network Simulations. - Osama Yousuf; Imtiaz Hossen; Matthew W. Daniels; Martin Lueker-Boden; Andrew M. Dienstfrey; Gina C. Adam (IEEE J. Emerg. Sel. Topics Circuits Syst., 2023)

Low-Rank Gradient Descent for Memory-Efficient Training of Deep In-Memory Arrays. - Siyuan Huang 002; Brian D. Hoskins; Matthew W. Daniels; Mark D. Stiles; Gina C. Adam (ACM J. Emerg. Technol. Comput. Syst., 2023)

Co-Design of Decision Trees for Network Intrusion Detection at the Edge on Digital vs. Analog Hardware. - Joseph Riem; Lei Zhang; Jingdi Chen; Henry Mackay; Tian Lan 001; Nathaniel D. Bastian; Gina C. Adam (MILCOM, 2024)

RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space. - Jingdi Chen; Hanhan Zhou; Yongsheng Mei; Carlee Joe-Wong; Gina C. Adam; Nathaniel D. Bastian; Tian Lan 001 (NeurIPS, 2024)

Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural Network Performance. - Osama Yousuf; Brian Hoskins; Karthick Ramu; Mitchell Fream; William A. Borders; Advait Madhavan; Matthew W. Daniels; Andrew M. Dienstfrey; Jabez J. McClelland; Martin Lueker-Boden; Gina C. Adam (CoRR, 2024)

Biologically-Informed Excitatory and Inhibitory Balance for Robust Spiking Neural Network Training. - Joseph A. Kilgore; Jeffrey D. Kopsick; Giorgio A. Ascoli; Gina C. Adam (CoRR, 2024)

Multi-Memristor Based Distributed Decision Tree Circuit for Cybersecurity Applications. - Lei Zhang; Joseph Riem; Jingdi Chen; Henry Mackay; Tian Lan 001; Nathaniel D. Bastian; Gina C. Adam (IEEE Trans. Circuits Syst. I Regul. Pap., 2024)

Formation and retrieval of cell assemblies in a biologically realistic spiking neural network model of area CA3 in the mouse hippocampus. - Jeffrey D. Kopsick; Joseph A. Kilgore; Gina C. Adam; Giorgio A. Ascoli (J. Comput. Neurosci., 2024)

Optimizing Prompt Sequences using Monte Carlo Tree Search for LLM-Based Optimization. - Fei Xu Yu; Gina C. Adam; Nathaniel D. Bastian; Tian Lan 001 (CoRR, 2025)