research

I study ultrafast surface dynamics of quantum materials using Time- and Angle-Resolved Photoemission Spectroscopy (tr-ARPES) and Momentum Microscopy. These techniques use ultrashort laser pulses to drive materials out of equilibrium and probe the resulting changes in electronic structure on femtosecond timescales, revealing non-equilibrium phenomena inaccessible to static measurements.

Used Density Functional Theory (Quantum Espresso) on HPC systems to predict the atomic ordering, magnetic properties, and electronic structure of ternary Heusler alloys. Compared theoretical predictions against experimentally grown materials characterized by XRD and XRR. This work resulted in four peer-reviewed publications.

Developed a JupyterLab extension providing seamless integration between Zenodo (a CERN open-data repository) and analysis facilities, enabling researchers to access and share datasets directly from within a notebook environment. Presented results at the Astronomical Data Analysis Software and Systems (ADASS) conference.

Designed and constructed an optical setup generating terahertz radiation via photocurrent injection in semiconductors using a two-color excitation scheme. Analyzed the mobility and conductivity of MOCVD-grown monolayers using THz time-domain spectroscopy.

Worked with Dr. Sergei Gleyzer to evaluate the performance of convolutional neural networks for classifying raw jet data from the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider. Investigated data augmentation techniques to improve convergence of classification models.

Worked with Dr. Jianwei Sun on applying machine learning to accelerate Density Functional Theory calculations within the SCAN meta-GGA framework. Developed neural networks for property prediction and wrote automation scripts exploiting point-group symmetry to reduce redundancy in molecular input grids.