collaborators

6 papers

cs.CV2026

Spiking Neural Networks for Energy-Efficient Object Detection in Forward-Looking Sonar Imagery

Gwenevere Frank, Gert Cauwenberghs

Autonomous underwater vehicles (AUVs) are increasingly important tools in industries ranging from research, to energy, to defense. AUVs are power-constrained platforms operating in…

cs.AR2026

HiAER-Spike Software-Hardware Reconfigurable Platform for Event-Driven Neuromorphic Computing at Scale

Gwenevere Frank, Gopabandhu Hota, Keli Wang +12

In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 milli…

cs.AI2026

NeuroAI and Beyond

Jean-Marc Fellous, Gert Cauwenberghs, Cornelia Fermüller +2

Neuroscience and Artificial Intelligence (AI) have made significant progress in the past few years but have only been loosely inter-connected. Based on a workshop held in August 20…

cs.AR2025

Clo-HDnn: A 4.66 TFLOPS/W and 3.78 TOPS/W Continual On-Device Learning Accelerator with Energy-efficient Hyperdimensional Computing via Progressive Search

Chang Eun Song, Weihong Xu, Keming Fan +10

Clo-HDnn is an on-device learning (ODL) accelerator designed for emerging continual learning (CL) tasks. Clo-HDnn integrates hyperdimensional computing (HDC) along with low-cost Kr…

eess.SP2025

Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA

Gwenevere Frank, Seyed Yahya Shirazi, Jason Palmer +3

Independent Component Analysis (ICA) is an important step in EEG processing for a wide-ranging set of applications. However, ICA requires well-designed studies and data collection…

cs.NE2025

HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing

Gwenevere Frank, Gopabandhu Hota, Keli Wang +8

In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 milli…