Laya Das

Postdoctoral Researcher at ETH Zürich

Led an industry-academia project with Swissgrid AG on deep learning for intelligent maintenance of transmission grid assets; Led projects with PNNL on graph foundation models and applications of LLMs in energy policy; Worked on physics-informed AI solutions for energy system optimisation, and generative AI models for design of climate resilient energy system.

Postdoctoral Research Scientist at Columbia University

Developed understanding of hidden representations of deep neural networks; Quantified and compared performance of computational optimization methods in adversarial environments; Developed symbolic-numeric machine learning algorithm for condition monitoring of wind turbines; Developed an uncertainty quantification framework for graph neural networks; Applied graph neural networks for critical node identification in power grids.

Scientific Assistant at IIT Gandhinagar

Led a research project on data-driven methods for industrial control system and state estimation performance assessment and monitoring; Worked with Amul as industrial partner.

Visiting Researcher at IIT Madras

Visiting researcher contributing to quantification frameworks and data mining algorithms for industrial systems; mentored AI and signal processing-focused projects; co-supervised AI-based condition monitoring of motors.