IRIS-HEP Fellow: Eric Moreno

Fellowship dates: Jun – Aug, 2021

Home Institution: MIT

Project: Anomaly Detection with Spiking Neural Networks

Spiking Neural Networks (SNNs) mimic organic systems like the human brain with asynchronous spikes, bridging the gap between artificial and biological intelligence and excelling at temporally-dependent data. The inherent strengths of these SNNs are extremely useful at the Large Hadron Collider (LHC) with their need for fast inference and accurate data-processing of petabytes of time-series events. This project involves the development of an anomaly detection algorithm based on SNNs and Autoencoders, which learn to identify outlier events in an unsupervised manner. This algorithm will complement LHC scientists in their search for beyond-standard-model physics, delivering a list of previously unidentified anomalous events.

More information: My project proposal

Mentors:

• Maurizio Pierini (CERN)

• Jean-Roch Vlimant (Caltech)

Presentations and Publications

• 27 Oct 2021 - "Anomaly Detection with Spiking Neural Networks", Eric Moreno, IRIS-HEP Topical Meetings Recording: Anomaly Detection with Spiking Neural Networks

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Current Status
June 2022 - Data Analyst at Supernal

Contact me:

• Send me an email
  
• Visit my GitHub Repo
  
• Visit my LinkedIn Profile