Research

My research focuses on advancing the frontiers of spintronics and nanomagnetic devices through innovative fabrication techniques, machine learning approaches, and novel characterization methods. I work at the intersection of fundamental physics and practical applications, developing next-generation computing architectures.

Key Research Highlights

First ML-Designed Spin-Wave Lens

2022

Breakthrough in combining machine learning with experimental magnonics

Sub-micron Wavelength Manipulation

2023

Achieved unprecedented control over spin-wave propagation at nanoscale

Rowland Spectrometer for Spin Waves

2021

First demonstration of classical optical concepts in magnonic systems

Neuromorphic Computing Applications

2024

Developing brain-inspired computing architectures using spintronic devices

Techniques & Methods

Fabrication

Focused ion-beam writing, photolithography, e-beam lithography, and thin film deposition for creating nanoscale magnetic devices

Characterization

Brillouin light scattering spectroscopy, time-resolved optical microscopy, and electrical measurements for device analysis

Computation

Machine learning for inverse design, numerical simulations, and data analysis using Python and MATLAB

Open to Collaborations

I'm always interested in exploring new research directions and collaborative opportunities in spintronics, neuromorphic computing, and nanomagnetic devices.

Discuss Research Opportunities