Research experience

From quantum materials to quantum control.

My research connects quantum materials, superconducting qubits, and RF control hardware, from cryogenic experiments to adaptive circuit architectures.

Northeastern University · September 2026–Present

Graduate Student Researcher · Ebrahimi Lab

Developing an adaptive RFIC-based control framework for superconducting transmon qubits to maintain high gate fidelity under control errors and device variations.

  • Modeling multi-level transmon dynamics in Python/QuTiP to quantify degradation of gate fidelity due to error mechanisms.
  • Simulating DRAG-shaped microwave pulses and closed-loop calibration schemes to correct qubit-control errors.
  • Evaluating RFIC and cryo-CMOS architectures for implementing quantum control algorithms in scalable cryogenic hardware.
Superconducting transmon qubitsRFIC & cryo-CMOSPython / QuTiPDRAG pulsesAdaptive calibration
Boston skyline beneath a blue sky and warm orange sunset
Boston at sunset — a new chapter in quantum control research at Northeastern.
Purdue University · 2024–2026

Quantum Spin Lab · Undergraduate researcher

Worked with Prof. Arnab Banerjee’s group on triangular lattice quantum materials. I grew and characterized single crystals, studied low temperature magnetic behavior with MPMS and PPMS measurements, and analyzed experimental data in Python. Our TlYbS₂ work is now available as a preprint, on which I am a co-author.

Flux crystal growthMagnetizationHeat capacityX-ray diffractionPython analysis
Piyush with research colleagues at a physics conference
With research colleagues at the APS Global Physics Summit 2026.
Purdue University · Summer 2024

Summer Undergraduate Research Fellow

Revisited the growth conditions for TlYbS₂ and helped obtain single crystals after earlier attempts had struggled. This experience showed me how much progress can come from carefully rechecking the literature and changing one part of a process at a time.

Experimental designMaterials synthesisSample preparation
Purdue University · 2023

Physics Data Mine · High energy physics

Used Python and Monte Carlo methods to study simulated top quark decay data and build selection routines for particle signatures. The work strengthened my data analysis and scientific programming skills.

PythonMonte Carlo simulationData selection
Feynman diagram: a top quark decays into a bottom quark and W boson, which decays into a charged lepton and neutrino
A representative leptonic top quark decay, illustrated for the high energy physics project.