Working with the FAIRmat consortium to foster data infrastructure and analytics in the field of materials science

Explored and implemented modern ML architectures to learn complex material microstructural transformations. As an outcome, these ML-based surrogate models infer stress distributions in microstructures just as robustly as numerical solvers, only orders of magnitude faster.

As part of the AI/ML team at Ericsson Eurolab, contributed to its ML-based anomaly detection system for log data and helped explore the use case for data-driven resource allocation in telecom services.

Worked with Dr. Vincent Demers's group to design and verify numerical simulations for Powder Injection Molding of metallic powders. Our work on the impact of rheological models on such simulations was published in Powder Metallurgy - https://doi.org/10.1080/00325899.2020.1852492.

Worked with Prof. Dr. Dhiraj Mahajan's group on the synthesis of intrinsic self-healing Polymers. My work was to verify the replicability of the synthesis of such polymers and improve their texture. Synthesized the polymer using multi-step reactions and characterized the results using NMR and Mass Spectroscopy techniques.