Distinguished Seminar Series Sponsored by the Texas Quantum Institute (TQI) with Dr. Brad Aimone from Sandia National Laboratories
Sep
30
2026
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Brad Aimone
Sep
30
2026
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Brad Aimone
Description
Neuromorphic and quantum computing are largely orthogonal technologies and fields, yet they each promise a path to far more efficient computation than today’s conventional approaches. Today, both emerging technologies face fundamental theoretical and implementation challenges to reaching this promised impact, and in this talk, I will propose that neuromorphic and quantum computing’s respective strengths and challenges are more complementary than most people appreciate.
I will cover three areas of our research in scalable neuromorphic computing at Sandia. First, recognizing the importance of a strong formal theoretical framework to quantum computing’s successes, I will describe how considering the theoretical benefits of neuromorphic computing can help us understand both how to design more effective brain-inspired algorithms as well as give us a foothold in understanding how information may be encoded within the brain.
Next, I will describe our novel neuromorphic algorithm for iteratively solving large-scale sparse linear systems for finite elements (NeuroFEM), which not only shows near ideal parallel scaling but also may provide clues to intrinsically fault-tolerant and robust algorithm design.
Lastly, I will describe how probabilistic neural algorithms, inspired by the brain’s ubiquitous stochasticity, can be implemented on neuromorphic systems, and highlight how these probabilistic algorithms are fundamentally different than quantum computing’s approach to sampling complex distributions.
About the Speakers
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Brad Aimone
Sandia National Laboratories
Dr. Brad Aimone is a Distinguished Member of Technical Staff in the Center for Computing Research at Sandia National Laboratories, where he is a lead researcher in leveraging computational neuroscience ...
Dr. Brad Aimone is a Distinguished Member of Technical Staff in the Center for Computing Research at Sandia National Laboratories, where he is a lead researcher in leveraging computational neuroscience to advance artificial intelligence and in using neuromorphic computing platforms for future scientific computing applications. Brad leads several research efforts on designing neural algorithms for NeuroAI, scientific computing applications, and neuromorphic machine learning implementations.
Brad has published over 100 peer-reviewed journal and conference articles in venues such as Advanced Materials, Neuron, Nature Neuroscience, Nature Electronics, Communications of the ACM, and PNAS and he is one of the co-founders of the Neuro-Inspired Computational Elements, or NICE, conference. Brad led the team that was awarded the 2023 Misha Mahowald
Prize in Neuromorphic Engineering. Prior to joining the technical staff at Sandia in 2011, Dr. Aimone was a postdoctoral research associate at the Salk Institute for Biological Studies, with a Ph.D. in computational neuroscience from the University of California, San Diego and Bachelor’s and Master’s degrees in chemical engineering from Rice University.