Hyperloop pod: EV powertrain and engineering leadership
2017–2019
Engineering Team Lead (Mar–Jul 2018) · Propulsion Team Lead · Avishkar Hyperloop, IIT Madras
740 Vbattery pack
0.3 gfinal design point
~10%pod cost cut
- Stepped up to lead the entire engineering team for five months while the founders raised capital: recruitment, subsystem timelines toward the final design review, and a component review that cut pod cost by about 10%.
- Owned the powertrain against a fixed budget: motor, inverter and a 740 V 20s2p Li-Po pack, and designed the transmission in-house instead of buying a costlier vendor unit.
- Redesigned twice as constraints changed, ending on a lighter direct-drive BLDC system at a 0.3 g design point.
- Thermal simulations of motor and controller in vacuum, fault-tolerant limp-home kinematics, and a dynamometer test bed design.
Fusion 360AnsysBLDC / PMSMBattery pack sizingLeadership
Silicon wafer defect detection
Mar–Jul 2026
Research Intern · IEMN Laboratory, UPHF, Valenciennes, France
4 MHzexcitation bandwidth
3%hidden thickness error found
2 moahead of plan
- Built an end-to-end workflow: 3D Elmer FEM models, laser Doppler vibrometry up to 4 MHz across 72 points, passive ambient-noise methods adapted from seismology, and Python pipelines for beamforming and localisation.
- Traced a model–measurement mismatch to wafer thickness: the data alone moved the model from the 500 µm we were given to about 390 µm, later backed by a gauge reading.
- Designed and 3D-printed the wafer fixture, and finished all experiments in four months against a six-month plan.
Elmer FEMGmshLDVPythonRoot-cause analysis
Multiscale models for elastic waves
2021–present
PhD research · Computational Wave Mechanics Lab, IISc · Guide: Prof. S. Gopalakrishnan
50×faster
≤2%displacement error
- Coupled the atomistic Quasicontinuum method with the Spectral Finite Element Method: 50× faster than full Quasicontinuum at up to 2% displacement error.
- Calibrated Eringen's nonlocal length scale against Quasicontinuum for aluminium nanostructures, validated against published experiments.
- Now applying the framework to metal deposits on silicon wafers.
QuasicontinuumSpectral FEMFortranNumPy / Numba
Pricing models for rates trading
2020–2021
Quantitative Analyst · Quantitative Research, J.P. Morgan Services India
3trading regions served
1model change in production
- Modelled and valued rate–rate and rate–spread instruments, calibrated to market data, supporting desks in the UK, Germany and the US.
- Implemented a correlation-based model adaptation that went into production, working from requirements set by the desk head.
C++PythonCalibration