Research

Context

I started in particle physics studying e+e− collisions with archived ALEPH data in connection to heavy ion physics, then moved to searches for new phenomena with the ATLAS experiment at the LHC. That work showed me where hadronic environments hit precision walls and what challenges we need to overcome for future searches. Many of those challenges trace back to how well we understand QCD, which brought me back to archived e+e− data from LEP with modern tools. That program is now the center of my research, and it connects naturally to the new technologies and future experiments needed to go further.

Searching for New Phenomena at the LHC

With the ATLAS experiment, I search for new physics in high-multiplicity hadronic final states. This includes R-parity violating SUSY and model-agnostic multijet resonance searches probing baryon number violation, and the first observation of tt̄ in PbPb collisions as a new probe of non-perturbative QCD. I also contributed to the commissioning of the ATLAS New Small Wheel muon trigger and detector system, which is critical for Run 3 and HL-LHC data taking.

Selected Contributions

  • Observation of tt̄ production in Pb+Pb collisions at √sNN = 5.02 TeV with the ATLAS detector. PRL Editor's Suggestion. 2411.10186
  • A model-agnostic search for multijet resonances in pp collisions at √s = 13.6 TeV with the ATLAS detector. In Internal Review, 2026.
  • A search for R-parity-violating supersymmetry in final states containing many jets in pp collisions at √s = 13 TeV with the ATLAS detector. JHEP. 2401.16333
  • The ATLAS Trigger System for LHC Run 3 and Trigger performance in 2022. JINST. 2401.06630
  • The ATLAS Experiment at the CERN LHC: A Description of the Detector Configuration for Run 3. JINST. 2305.16623
  • The New Small Wheel Electronics. JINST. 2303.12571

Precision QCD with e+e− Collision Data

Using archived data from the Large Electron-Positron Collider, I work on new measurements that were not possible when the data was first collected. The clean e+e− initial state lets us test high order perturbative predictions, non-perturbative phenomena, effective field theories, confinement mechanisms, and improve determinations of αS. These results help constrain theoretical models that limit are crucial for searches for new physics. This work is carried out in collaboration through the Electron-Positron Alliance.

Selected Contributions

  • Unbinned measurement of thrust in e+e− collisions at √s = 91.2 GeV with archived ALEPH data. 2510.22038
  • Energy Correlators from Partons to Hadrons: Unveiling the Dynamics of the Strong Interactions with Archival ALEPH Data. 2511.00149
  • Measurement of energy-energy correlators and thrust in e+e− collisions at 91.2 GeV with DELPHI open data. 2510.18762
  • Measurements of two-particle correlations in e+e− collisions at √s = 91 GeV with ALEPH archived data. PRL. 1906.00489
  • Jet energy spectrum and substructure in e+e− collisions at √s = 91 GeV with ALEPH archived data. JHEP. 2111.09914

New Technologies

I have broad interests in microelectronics and computational methods for particle physics. On the hardware side, I have worked on intelligent pixel detectors with on-chip AI/ML through the SmartPixel Collaboration at Fermilab, demonstrating in-pixel signal processing for radiation-hard ASICs. On the computational side, I develop ML methods for collider data analysis, including new approaches to combinatorial assignment problems and model-agnostic search strategies in multijet final states, and have explored agentic AI as a tool for accelerating experimental physics workflows.

Selected Contributions

  • In-pixel integration of signal processing and AI/ML based data filtering for particle tracking detectors. 2510.07485
  • Sensor co-design for smartpixels. 2510.06588
  • Intelligent pixel detectors: towards a radiation hard ASIC with on-chip machine learning in 28nm CMOS. PoS ICHEP2024. 2410.02945
  • Smart Pixels: In-pixel AI for on-sensor data filtering. IEEE NSS MIC RSTD 2024. 2406.14860
  • A data-driven and model-agnostic approach to solving combinatorial assignment problems in searches for new physics. PRD. 2309.05728
  • Solving Combinatorial Problems at Particle Colliders Using Machine Learning. PRD. 2201.02205
  • Agentic AI – Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data. 2603.05735

Future Experiments

I convene the FCC-ee Physics Group on QCD and photon-photon physics, working to define the precision program for the next generation of e+e− experiments. I aim to utilize the insights from my measurements of LEP data to make informed projections for the FCC-ee.