Research

My Research

As an experimental particle physicist, I do my research to understand the world of Physics at the most fundamental level in terms of the particles, which are the building blocks of our universe. I conduct various searches for New Physics using the data collected by the ATLAS detector at CERN and I also do measurements of physics processes, hardware studies, and algorithm developments for our ATLAS experiment. I also pursue some phenomenological studies based on personal interest.

Completed Searches / Physics Projects at ATLAS

1. Search for New Physics using Event-based Anomaly Detection

• Paper: PhysRevLett.132.081801
  We searched for new physics in the form of anomalous events using a novel anomaly detection technique based on unsupervised machine learning. This was the first event-based anomaly detection search of ATLAS/CERN, and showed significant improvement in sensitivity across 9 different BSM channels.

2. Enhancing Di-Higgs Boson search sensitivities with ML

• Paper: arXiv:2504.12418
  Developed machine learning techniques to enhance sensitivity for di-Higgs boson searches, using both anomaly detection and supervised classifiers in multiple final states.

3. ADFilter: Web Tool for Anomaly Detection

• Paper: arXiv:2409.03065
  Co-developed the ADFilter web tool to reinterpret BSM models using anomaly detection with trained autoencoders from ATLAS data.

4. WIPUNet: Pileup-Resistant Image Denoising

• Paper: arXiv:2509.05662
  Developed WIPUNet, a physics-inspired neural network for image denoising. The network embeds pileup-mitigation principles to increase robustness against noise. Applications are underway in jet images and calorimeter data.

5. Search for Vector Boson Resonances (W′ → tb)

• Paper: JHEP12(2023)073
  Searched for left- and right-handed W′ bosons via their decay into top and bottom quarks, in both hadronic and leptonic channels. Mass limits up to 4.6 TeV were established.

6. Multi-body Invariant Mass Searches

• Paper: JHEP07(2023)202
  Searches for new physics in 3-body and 4-body invariant masses in isolated lepton events, using √s = 13 TeV pp collisions in ATLAS data.

7. Phenomenological Studies on Multi-body Invariants

• Papers:
  • Universe 2021, 7(9), 333, arXiv:2209.13128, arXiv:2210.02591
    These model-independent proposals contributed to Snowmass 2021 topical reports on BSM physics and collider theory.

8. Charged Higgs Search (dijet + lepton channel)

• Paper: JHEP 06 (2020) 151
  Searched for singly charged Higgs bosons through the dijet + lepton channel. The analysis also probed Z′, dark matter, and various BSM scenarios.

9. W′ Search in All-Hadronic Decay

• Paper: ATLAS-CONF-2021-043
  Used full Run 2 ATLAS data to search for W′ → tb in all-hadronic channels. Results are presented as exclusion limits on mass vs coupling.

10. b-Jet Identification Algorithm: Direct Tag

Developed a new mistag calibration method named Direct Tag with advisor Prof. Alexander Khanov during PhD, improving performance of b-jet identification in heavy flavor enriched samples.

Ongoing Physics Projects at ATLAS

1. Next-Generation Anomaly Detection Search

Currently developing a new ATLAS search using enhanced anomaly detection algorithms with broader final-state coverage.

2. Vertex, Track, and Jet Pileup Separation for HL-LHC

Working with the SLAC National Lab group to develop novel tools for vertex selection, track reconstruction, and jet-pileup mitigation for High-Luminosity LHC and other future collider experiments.

3. Quantum Machine Learning at LHC

Exploring quantum computing platforms for solving high-dimensional ML problems in LHC analyses using quantum circuit-based machine learning models.

Machine Learning Studies for LHC Physics

• Active since 2017 in developing ML applications for object classification, event recognition, and unsupervised anomaly detection using ATLAS detector data.
• Engaged in applying Quantum Machine Learning techniques for potential performance gains in high-energy physics analyses.

Detector Upgrade Studies for HL-LHC

• As ANL-ATLAS Graduate Fellow 2017 and resident associate at Argonne National Lab, contributed to the ITk Pixel R&D project using Fermilab Test Beam Facility.
• Results included in:
  • FERMILAB-TM-2734-DI
  • FERMILAB-TM-2702-DI
• Delivered public presentations based on test beam analysis outcomes.

Other Work (ALICE & Master’s Thesis)

• ALICE Intern at CERN (2015): Worked in accelerator physics, developed outreach tools for diverse audiences, and created a CERN TWiki page on accelerator awareness.
• Master’s Thesis in India: Studied 3-flavor neutrino oscillations in matter and vacuum. Analyzed future prospects of 23 neutrino experiments globally.