Experience

 
 
 
 
 
Schmidt AI Fellow
Caltech + Fermilab
September 2024 – Present Chicago, USA
  • High energy Higgs measurements
  • Real-time AI
  • Model-independent searches
 
 
 
 
 
Graduate Researcher in Particle Physics + AI
CMS Group / Duarte Lab, UC San Diego
September 2019 – June 2024 San Diego, USA
  • Developed new graph- and attention-based generative models for sparse and irregular data like that prevalent in particle physics
  • Lorentz-group equivariant graph neural network (GNN) autoencoders for compression and anomaly detection, machine learning for particle flow reconstruction, JetNet library for convenience and reproducibility in machine learning development in high energy physics
  • Developed and applyied GNN classifiers to set the most stringent constraints to date on double-Higgs production, allowing insight into the metastability of the universe
 
 
 
 
 
CERN Openlab Intern
Machine Learning for Particle Physics Group, CERN
June 2019 – August 2019 Geneva, Switzerland
  • Started our project on graph generative models for particle physics simulations, motivated primarily by the CMS experiment’s new High Granularity Calorimeter (HGCAL)
 
 
 
 
 
Experimental Quantum Information Science Researcher
Barreiro Lab, UC San Diego
June 2017 – June 2019 San Diego, USA
  • Designed and implemented a setup for a quantum gas microscope (QGM) to image with single-site resolution
  • Generated 2D dynamic, arbitrarily arranged, sub-micron optical tweezers, integrated with the QGM, via two methods, using: 1) a Digital Micromirror Device (i.e. holography), and 2) an acousto-optic deflector
  • Characterized a high (0.8) Numerical Aperture objective for the QGM using OSLO optical simulations and point-spread function image analysis in Python
  • Using an FPGA device, outputted RF waveforms that modulate laser beams with parabolic spatial intensity in order to produce a Bose-Einstein Condensate
  • Programmed FPGA and C electronic devices, and created and (3D) printed mechanical mounts and electronics circuits for experimental use
 
 
 
 
 
Neurophysics Researcher
Kleinfeld Lab, UC San Diego
September 2018 – June 2019 San Diego, USA
  • Used two-photon microscopy to measure pO2 in the mouse somatosensory cortex
  • Imaged the cortex to measure vasomotion relative to pO2
 
 
 
 
 
Software Intern
Focus Analytics
July 2016 – September 2016 Mumbai, India
  • Interned at a software startup which has since been bought by Moka
  • Developed and deployed a location prediction SparkJava server with Cassandra and Redis databases
  • Implemented ML k-means clustering and SVM linear classification algorithms on location data
  • Wrote NodeJS servers and pages for receiving users’ predicted locations and displaying the live data on maps
  • Designed Cassandra and MySQL databases storing user tracking data, and wrote server APIs for accessing/updating, along with web panels for easy viewing of the data (using said APIs)