Going Small: Using the Insect Brain as a Model System for Edge Processing Applications. - Angel Yanguas-Gil (ACM Great Lakes Symposium on VLSI, 2018)

Polymers Selection for Harsh Environments to Be Processed Using Additive Manufacturing Techniques. - Alvaro Rodríguez-Prieto; Ana María Camacho; Ana M. Aragon; Miguel Angel Sebastián; Angel Yanguas-Gil (IEEE Access, 2018)

Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning. - Sandeep Madireddy; Angel Yanguas-Gil; Prasanna Balaprakash (ICONS, 2019)

Task-Based Neuromodulation Architecture for Lifelong Learning. - Anurag Reddy Daram; Dhireesha Kudithipudi; Angel Yanguas-Gil (ISQED, 2019)

Coarse scale representation of spiking neural networks: backpropagation through spikes and application to neuromorphic hardware. - Angel Yanguas-Gil (ICONS, 2020)

Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning. - Sandeep Madireddy; Angel Yanguas-Gil; Prasanna Balaprakash (CoRR, 2020)

Atomic Layer Deposition Optimization Using Convolutional Neural Networks. - Julian Cagnazzo; Osama Sam Abuomar; Angel Yanguas-Gil; Jeffrey W. Elam (CSCI, 2021)

Fast, Smart Neuromorphic Sensors Based on Heterogeneous Networks and Mixed Encodings. - Angel Yanguas-Gil (CoRR, 2021)

AutoML for neuromorphic computing and application-driven co-design: asynchronous, massively parallel optimization of spiking architectures. - Angel Yanguas-Gil; Sandeep Madireddy (ICRC, 2022)

Machine learning and atomic layer deposition: predicting saturation times from reactor growth profiles using artificial neural networks. - Angel Yanguas-Gil; Jeffrey W. Elam (CoRR, 2022)

General policy mapping: online continual reinforcement learning inspired on the insect brain. - Angel Yanguas-Gil; Sandeep Madireddy (CoRR, 2022)

Biological underpinnings for lifelong learning machines. - Dhireesha Kudithipudi; Mario Aguilar-Simon; Jonathan Babb; Maxim Bazhenov; Douglas Blackiston; Josh C. Bongard; Andrew P. Brna; Suraj Chakravarthi Raja; Nick Cheney; Jeff Clune; Anurag Reddy Daram; Stefano Fusi; et al. (Nat. Mach. Intell., 2022)

Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures. - Sandeep Madireddy; Angel Yanguas-Gil; Prasanna Balaprakash (CoLLAs, 2023)

Memristor-Spikelearn: A Spiking Neural Network Simulator for Studying Synaptic Plasticity under Realistic Device and Circuit Behaviors. - Yuming Liu; Angel Yanguas-Gil; Sandeep Madireddy; Yanjing Li (DATE, 2023)

Design Principles for Lifelong Learning AI Accelerators. - Dhireesha Kudithipudi; Anurag Reddy Daram; Abdullah M. Zyarah; Fatima Tuz Zohora; James B. Aimone; Angel Yanguas-Gil; Nicholas Soures; Emre Neftci; Matthew Mattina; Vincenzo Lomonaco; Clare D. Thiem; Benjamin R. Epstein (CoRR, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)

Benchmarking large language models for materials synthesis: the case of atomic layer deposition. - Angel Yanguas-Gil; Matthew T. Dearing; Jeffrey W. Elam; Jessica C. Jones; Sungjoon Kim; Adnan Mohammad; Chi Thang Nguyen; Bratin Sengupta (CoRR, 2024)

EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants. - Franck Cappello; Sandeep Madireddy; Robert Underwood; Neil Getty; Nicholas Lee-Ping Chia; Nesar Ramachandra; Josh Nguyen; Murat Keçeli; Tanwi Mallick; Zilinghan Li; Marieme Ngom; Chenhui Zhang; et al. (CoRR, 2025)

Surrogate models to optimize plasma assisted atomic layer deposition in high aspect ratio features. - Angel Yanguas-Gil; Jeffrey W. Elam (CoRR, 2025)