NSF BRAID Workshop 2025

Accepted Posters

Superconducting optoelectronic hardware enables large-scale neuromorphic systems

Jeff Shainline — Great Sky (greatsky.ai)

Analysis of 2f and 4f Architectures for Free-Space Optical Matrix-Vector Multiplication

Dawson Lyles; Spencer LaVere Smith — UC Santa Barbara

Structural Plasticity as Active Inference: A Biologically-Inspired Architecture for Homeostatic Control

Brennen Hill — University of Wisconsin–Madison

TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks

Marco P. E. Apolinario; Kaushik Roy; Charlotte Frenkel — Purdue University / TU Delft

Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function

Erick Olivares Bravo; Fidel Santamaria — UT San Antonio

Neuromorphic Neuromodulation: A Low-Power Edge-Training Framework for the Future of Personalized and Closed-Loop Neurostimulation

Luis Fernando Herbozo Contreras; Leping Yu; Zhaojing Huang; Isabelle Aguilar; Armin Nikpour; Omid Kavehei — University of Sydney

Efficient ECG Classification via Event-Based Sampling and In-Memory Computing

Varun Raghuraman; Ryan Brinson; Xiaoyue Hu; Yan Fang — Kennesaw State University

Accelerated Sleep-time Replay for Long-range Hierarchical Temporal Learning

Jayanta Dey; Nicholas Soures; Dhireesha Kudithipudi — UT San Antonio

On the geometry of recurrent spiking networks

Josue Casco-Rodriguez — Rice University

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning

Boxun Xu; Yuxuan Yin; Vikram Iyer; Peng Li — UC Santa Barbara

Scope

We welcome posters across neuroscience, neuromorphic computing, including (but not limited to):

Computational & theoretical neuroscience: neural dynamics, plasticity, coding, circuit motifs
Algorithms & models: spiking neural networks, dynamical-systems approaches, brain-inspired learning rules
Hardware & devices: analog/mixed-signal neuromorphic circuits, in-memory compute, emerging devices (e.g., RRAM/PCM/FeFET) and CMOS baselines
Architectures & systems: accelerators, co-design across devices↔circuits↔algorithms, edge/embedded applications
Tools & evaluation: datasets, benchmarking, simulators, reproducibility practices

Submission

Abstract: ≤200 words (title, author list, affiliations).
How to submit: email strukov@ece.ucsb.edu
Content guidelines: Brief problem statement, key idea, methods/setup (short), results or expected outcomes; optional link to paper/code/data.

Review & selection

Submissions will be evaluated for relevance, clarity, and potential to stimulate discussion across neuroscience, algorithms, hardware, and systems.

The acceptance decisions will be communicated promptly following the completion of the review process

Contact

Questions: sbezugam@ucsb.edu

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Accepted Posters

Superconducting optoelectronic hardware enables large-scale neuromorphic systems

Jeff Shainline — Great Sky (greatsky.ai)

Analysis of 2f and 4f Architectures for Free-Space Optical Matrix-Vector Multiplication

Dawson Lyles; Spencer LaVere Smith — UC Santa Barbara

Structural Plasticity as Active Inference: A Biologically-Inspired Architecture for Homeostatic Control

Brennen Hill — University of Wisconsin–Madison

TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks

Marco P. E. Apolinario; Kaushik Roy; Charlotte Frenkel — Purdue University / TU Delft

Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function

Erick Olivares Bravo; Fidel Santamaria — UT San Antonio

Neuromorphic Neuromodulation: A Low-Power Edge-Training Framework for the Future of Personalized and Closed-Loop Neurostimulation

Luis Fernando Herbozo Contreras; Leping Yu; Zhaojing Huang; Isabelle Aguilar; Armin Nikpour; Omid Kavehei — University of Sydney

Efficient ECG Classification via Event-Based Sampling and In-Memory Computing