S. Dahbi
Physics and Astronomy · Indiana University
Publications
776
Citations
23,893
Est. group size
—
Recurring co-author estimate
Active years
9
Publishing since 2018
S. Dahbi works in experimental and theoretical high-energy particle physics, including detector development for the ATLAS experiment at the Large Hadron Collider (LHC) and searches for new particles or resonances. A notable portion of the work also applies machine learning both to physics analyses (for example, spotting new particle signals) and to public-health data such as COVID-19 and mpox trends in South Africa.
Publication activity began around 2020 and has been irregular but ongoing, averaging roughly two to three papers per year with a peak in 2023.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Beam-test evaluation of pre-production Low Gain Avalanche Detectors for the ATLAS High Granularity Timing Detector
arXiv (Cornell University) · 2025
- Detecting the Presence of COVID-19 Vaccination Hesitancy From South African Twitter Data Using Machine Learning
IEEE Transactions on Computational Social Systems · 2025
- Thermal cycling reliability of hybrid pixel sensor modules for the ATLAS High Granularity Timing Detector
Journal of Instrumentation · 2025
- Evaluating automatic annotation of lexicon-based models for stance detection of M-pox tweets from May 1st to Sep 5th, 2022
PLOS Digital Health · 2024
- Detecting the Presence of COVID-19 Vaccination Hesitancy from South African Twitter Data Using Machine Learning
arXiv (Cornell University) · 2023
- COVID-19 South African Vaccine Hesitancy Models Show Boost in Performance Upon Fine-Tuning on M-pox Tweets
arXiv (Cornell University) · 2023
- Growing Excesses of New Scalars at the Electroweak Scale
arXiv (Cornell University) · 2023
- The use of Wasserstein Generative Adversarial Networks in searches for new resonances at the LHC.
Journal of Physics Conference Series · 2023
- Big data- and artificial intelligence-based hot-spot analysis of COVID-19: Gauteng, South Africa, as a case study
BMC Medical Informatics and Decision Making · 2023
- Consistency and interpretation of the LHC dijet excesses
Physical review. D/Physical review. D. · 2023
- Consistency and Interpretation of the LHC (Di-)Di-Jet Excesses
arXiv (Cornell University) · 2022
- An investigation of over-training within semi-supervised machine learning models in the search for heavy resonances at the LHC
arXiv (Cornell University) · 2021
- Big Data- and Artificial Intelligence-Based Hot-Spot Analysis of COVID-19: Gauteng, South Africa, as a case study
SSRN Electronic Journal · 2021
- Development of an Early Alert System for an Additional Wave of COVID-19 Cases using a Recurrent Neural Network with Long Short-Term Memory
SSRN Electronic Journal · 2021
- Machine learning approach for the search of resonances with topological features at the Large Hadron Collider
International Journal of Modern Physics A · 2021
- arXiv (Cornell University)×7
- medRxiv×2
- SSRN Electronic Journal×2
- Physical review. D/Physical review. D.×1
- BMC Medical Informatics and Decision Making×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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