16–18 Jun 2025
Columbia University, Nevis Laboratories
America/New_York timezone

Session

Early Career Session: Anomaly Detection in HEP and Beyond

17 Jun 2025, 11:00
Nevis Science Center (Columbia University, Nevis Laboratories)

Nevis Science Center

Columbia University, Nevis Laboratories

Conveners

Early Career Session: Anomaly Detection in HEP and Beyond: Block 1

  • Kiley Kennedy

Early Career Session: Anomaly Detection in HEP and Beyond: Block 2

  • Andrew Loeliger (Princeton University (US))

Presentation materials

There are no materials yet.

  1. Chitrakshee Yede (Universität Hamburg)
    17/06/2025, 11:00
    Early Career Lightning Talk

    The search for physics beyond the Standard Model remains one of the primary focus in high-energy physics. Traditional searches at the LHC analyses, though comprehensive, have yet to yield signs of new physics. Anomaly detection has emerged as a powerful tool to widen the discovery horizon, offering a model-agnostic path as way to enhance the sensitivity of generic searches not targeting any...

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  2. Jack Cleeve
    17/06/2025, 11:15
    Early Career Lightning Talk

    We introduce an end-to-end, self-supervised neural workflow that learns the three-dimensional electric-field distortion in a Liquid Argon TPC directly from through-going cosmic muon tracks. The network uses geometric straightness and boundary conditions to generate its own target undistorted paths and iteratively refine them. In this talk, I will present the architecture of the model, detail...

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  3. Prasanth Shyamsundar (Fermi National Accelerator Laboratory)
    17/06/2025, 11:30
    Early Career Lightning Talk

    Recently a technique based on k-fold cross validation has become popular in anomaly detection in HEP, as a way to search for a wide class of anomalies in the data, without paying an associated penalty in sensitivity-depth. In this work, we point out that the breadth-depth tradeoff is an unavoidable aspect of anomaly detection, and cannot be overcome using the aforementioned k-fold cross...

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  4. Ranit Das (Rutgers University)
    17/06/2025, 11:45
    Plenary Talk - New Directions in AD

    Based on R-ANODE(https://arxiv.org/abs/2312.11629) and SIGMA(https://arxiv.org/abs/2410.20537).

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  5. Zixin Ding (University of Chicago)
    17/06/2025, 12:00
    Early Career Lightning Talk

    The Large Hadron Collider (LHC) produces collision data at the rate of 40 MHz, making it infeasible to store or analyze all events. Conventional trigger strategies at the experiments operating at the LHC typically rely on predefined physics signatures to decide which events to retain. However, possible manifestations of new physics may not conform to these established patterns and thus risk...

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  6. Radha Mastandrea (UC Berkeley)
    18/06/2025, 10:30
    Early Career Lightning Talk

    We present the first study of anti-isolated Upsilon decays to two muons (Υ → μ+μ−) in proton-proton collisions at the Large Hadron Collider. Using a machine learning (ML)-based anomaly detection strategy (CATHODE), we “rediscover” the Υ in 13 TeV CMS Open Data from 2016, despite overwhelming anti-isolated backgrounds. CATHODE can elevate the signal significance to 6.4σ (starting from 1.6σ...

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  7. Rikab Gambhir (Massachusetts Institute of Technology)
    18/06/2025, 10:45
    Early Career Lightning Talk

    Many Machine Learning (ML)-based Anomaly Detection (AD) methods are based on "extended bump hunt", where ML cuts are used to enhance the significance of signal in a bump. We show how, by taking advantage of the fact that ML methods (e.g. CATHODE with CWoLa) often involve learning the likelihood ratio of the signal and background hypotheses, events can be weighted rather than cut for improved...

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  8. Wonyong Chung (Princeton University)
    18/06/2025, 11:00
    Early Career Lightning Talk

    Physically-grounded anomaly detection requires reconstruction pipelines that preserve, rather than obscure, detector information. I introduce a two-stage strategy that inserts a synthetic, detector-aware representation (S) between the raw calorimeter readout (D) and low-dimensional truth (T). I demonstrate the concept in full simulation of a segmented dual-readout crystal ECAL for future...

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  9. Seokju Chung (Columbia University)
    18/06/2025, 11:15

    Real-time anomaly triggers based on autoencoders have been successfully demonstrated at the CMS experiment, including CICADA (operating on raw calorimeter data from ECAL and HCAL) and AXOL1TL (operating on trigger-level reconstructed objects such as electrons, taus, and jets). Motivated by the CICADA project, we explore the feasibility of applying similar techniques to raw wire data, which...

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  10. Tengfei Ma (Stony Brook University)
    18/06/2025, 11:30
    Early Career Lightning Talk

    This work introduces a new interpretable time series foundation model, and its application to anomaly prediction for sPHENIX - a recently commissioned detector at the RHIC facility at BNL. Our goal is to monitor the detector’s operational status, identify early warning signs, and predict potential anomalies. Despite diverse time series modeling techniques, existing models are black boxes and...

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  11. Adriano Cherchiglia (Universidade Estadual de Campinas)
    18/06/2025, 11:45
    Early Career Lightning Talk

    As neutrino experiments enter into the precision era, it is desirable to identify deviations from data in comparison to theory as well as provide possible models as explanation. Particularly useful is the description in terms of non-standard interactions (NSI), which can be related to neutral (NC-NSI) or charged (CC-NSI) currents. Previously, we have developed the code eft-neutrino that...

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  12. Elena Pinetti (Flatiron Institute/Simons Foundation)
    Early Career Lightning Talk

    Axions with a mass around 1 eV can decay into near-infrared photons. Utilising blank-sky observations from the James Webb Space Telescope, I search for a narrow emission line due to decaying dark matter and derive leading constraints on the axion-photon coupling in the eV-scale mass range.

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