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Javier Mauricio Duarte (Univ. of California San Diego (US))16/08/2025, 08:45
Throughout different scientific disciplines, there is a need for machine learning models that leverage domain knowledge through inductive bias and data representations to maximize their potential. In addition, efficient machine learning implementations optimized for inference in hardware are critical for low-latency, high-throughput, or limited-resource scientific applications. In this...
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Pan Li16/08/2025, 10:00
This talk will provide an overview of HAC’s achievements over the past year and briefly introduce some ongoing projects.
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Kate Scholberg16/08/2025, 10:15
I'll give an overview with highlights of A3D3 MMA activities.
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Eli Shlizerman16/08/2025, 10:30
Update/overview presentation on NeuroAI and Neuroscience developments and achievements in the past year.
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Melissa Quinnan (Univ. of California San Diego (US))16/08/2025, 10:45
We present an overview of current and planned High Energy Physics research activities in A3D3, driven by real-time machine learning. We report the first deployment of ML-based anomaly detection at the Level-1 trigger in both CMS and ATLAS, realized through the AXOL1TL (“Anomaly eXtraction L1 Trigger Lightweight”) and GELATO (“Generic Event-Level Anomalous Trigger Option”) algorithms,...
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Andy Meza16/08/2025, 11:15
When deployed in edge applications, neural networks (NNs) undergo numerous changes to ensure they adhere to strict power, performance, and size constraints while simultaneously being robust to faults. In prior work, NN robustness is evaluated using a bit-level ranking based on how sensitive an edge NN is to a fault in a given parameter bit. Unfortunately, the fault injection campaigns used to...
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Argyro Sasli16/08/2025, 11:30
Modern time-domain surveys like the Zwicky Transient Facility (ZTF) and the Legacy Survey of Space and Time (LSST) generate hundreds of thousands to millions of alerts, demanding automatic, unified classification of transients and variable stars for efficient follow-up. We present AppleCiDEr, a novel framework that integrates four key data modalities (photometry, image cutouts, metadata, and...
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Dr Hao Fang16/08/2025, 11:45
Intracortical brain-computer interfaces (iBCIs) aim to decode behavior from neural population activity, enabling individuals with motor impairments to restore motor functions and communication abilities. A central challenge in the long-term deployment of iBCIs is the nonstationarity of neural recordings, where instability of electrode recordings alters the composition and tuning of the...
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Jason Weitz (University of California, San Diego)16/08/2025, 12:00
Machine learning is a critical tool for analysis and decision making across a wide range of scientific domains, from particle physics to materials science. However, the deployment of neural networks in resource constrained environments, such as the Level-1 Trigger and edge devices, remains a significant challenge. This often requires specialized expertise in both neural architecture design and...
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Sagar Addepalli (SLAC National Accelerator Laboratory (US))16/08/2025, 15:20
The absence of beyond-Standard-Model physics discoveries at the LHC suggests that new physics may evade conventional trigger strategies. The existing ATLAS triggers are required to control data collection rates with high energy thresholds and target signal topologies specific to only certain models. Unsupervised machine learning enables the use of anomaly detection, presenting a unique...
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Sonata Simonaitis-boyd (University of California San Diego)16/08/2025, 15:35
To advance the search for 0𝜈𝛽𝛽 decay, the LEGEND-1000 experiment will require scaling-up from its predecessor, LEGEND-200, the cryostat in particular containing a copper reentrant tube (RT) in order to create separate volumes containing underground versus atmospheric argon. As the thinnest part of the RT will only be ~3 mm thick, small-scale pressure and strain testing is underway to confirm...
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Gregory Jun16/08/2025, 15:50
High-level synthesis (HLS) has greatly improved the accessibility of FPGAs by enabling a faster transition from algorithmic descriptions to efficient hardware implementations. Advances in automated design space exploration (DSE) and MLIR-based compiler flows, such as ScaleHLS, have further enhanced the ability to transform high-level algorithms into optimized hardware designs. Recent research...
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Haoyang Li (Univ. of California San Diego (US))16/08/2025, 16:05
The Higgs boson's self-coupling has a significant impact on the production rate of multiple Higgs bosons. Measuring the self-coupling at the CERN LHC is crucial because any deviations from our expectations could potentially lead to new discoveries of physics beyond the standard model of particle physics. Most events are fully hadronic, meaning every Higgs boson decays to a bottom...
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Ethan Colbert (Purdue University (US))16/08/2025, 16:45
As deep learning methods and particularly Large Language Models have shown huge promise in a variety of applications, we apply a model inspired by BERT (Bidirectional Encoder Representations from Transformers), developed by Google and utilizing the multi-headed attention mechanism, to a high energy physics problem. We focus on the process of top quark-antiquark decay reconstruction and...
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Josh Peterson16/08/2025, 16:45
Atmospheric muon neutrinos and antineutrinos passing through the Earth experience matter effect induced oscillations, due to the interior structure of the Earth, which only affect neutrinos or antineutrinos depending on the true neutrino mass ordering (NMO). By leveraging the fact that more neutrinos are expected to be detected than antineutrinos in IceCube DeepCore, the detector can be used...
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Kyungseop Yoon (Massachusetts Institute of Technology)16/08/2025, 16:45
Fast and accurate parameter estimation of gravitational wave (GW) signals is crucial in multi-messenger astrophysics. These signals are the first to arrive, requiring prompt analysis of the merger properties. However, extracting these parameters from observed binary mergers from GW detectors remains a computational bottleneck. Current approaches, such as Markov-Chain Monte Carlo (MCMC) methods...
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16/08/2025, 16:45
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Hao Fang16/08/2025, 16:45
Intracortical brain-computer interfaces (iBCIs) aim to decode behavior from neural population activity, enabling individuals with motor impairments to restore motor functions and communication abilities. A central challenge in the long-term deployment of iBCIs is the nonstationarity of neural recordings, where instability of electrode recordings alters the composition and tuning of the...
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Joshua Queen16/08/2025, 16:45
Observation of neutrinos from the next galactic core collapse supernova will provide insights on numerous questions in physics. There are a variety of middle- to large-scale neutrino detectors currently online that will be sensitive to these neutrinos, but a better observation can be made with more detectors and varied detection channels. The COHERENT collaboration operates a variety of low...
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Pan Li
This talk will provide an overview of HAC’s achievements over the past year and briefly introduce some ongoing projects.
Go to contribution page -
Melissa Quinnan (Univ. of California San Diego (US))
We present an overview of current and planned High Energy Physics research activities in A3D3, driven by real-time machine learning. We report the first deployment of ML-based anomaly detection at the Level-1 trigger in both CMS and ATLAS, realized through the AXOL1TL (“Anomaly eXtraction L1 Trigger Lightweight”) and GELATO (“Generic Event-Level Anomalous Trigger Option”) algorithms,...
Go to contribution page -
Javier Mauricio Duarte (Univ. of California San Diego (US))
Throughout different scientific disciplines, there is a need for machine learning models that leverage domain knowledge through inductive bias and data representations to maximize their potential. In addition, efficient machine learning implementations optimized for inference in hardware are critical for low-latency, high-throughput, or limited-resource scientific applications. In this...
Go to contribution page -
Kate Scholberg
I'll give an overview with highlights of A3D3 MMA activities.
Go to contribution page -
Eli Shlizerman
Update/overview presentation on NeuroAI and Neuroscience developments and achievements in the past year.
Go to contribution page
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