I am a Postdoctoral Research Scientist at UCLouvain, Belgium, working at the convergence of condensed matter physics, functional nanomaterials, and artificial intelligence. My current work deploys generative AI — VAEs, Diffusion Models, and multimodal networks — for the inverse design of quantum and functional materials, resulting in the MEIDNet framework published in npj Computational Materials (2026).
My roots span both materials synthesis and physics theory. During my Ph.D. at INST-IISER Mohali, I engineered piezoelectric PVDF nanocomposites, lead-free perovskite hybrids (Cs₃Bi₂I₉), and triboelectric polymer laminates — then fused deep learning directly onto these physical systems to create self-powered sensors capable of recognising voice (Small, 70 citations), tracking cardiovascular health (Adv. Mater. Technol., 32 citations), and classifying movement disorder (Adv. Mater. Technol., 34 citations).
As a Raman-Charpak Fellow at IMS, University of Bordeaux, I extended this materials-AI loop to thin-film polymer acoustics: voiceprint biometrics from a programmable PVDF interface (Adv. Mater. Technol., Journal Cover, 24 citations), an e-skin respirometer built on flexoelectric nanofibre physics (Adv. Sensor Res.), and an emotion sensor exploiting multimodal piezoresistive response (Adv. Intell. Syst.). My Quantum ML work shows entanglement-enhanced kernels outperforming classical SVMs on structured materials datasets (APL Quantum, 2025).
I serve on the Editorial Advisory Board of APL Machine Learning, as Guest Editor for Nanotechnology (IOP), and as Student Ambassador of APS — bridging the materials, physics, and AI communities from the inside.
