Recognized among the world’s top 2% scientists by Stanford University and Elsevier in 2024 and 2025; Ph.D. student Sidharth S. Menon published his first paper 'Anant-Net: Breaking the curse of dimensionality with scalable and interpretable neural surrogate for high-dimensional PDEs' in Computer Methods in Applied Mechanics and Engineering; A new preprint on BubbleONet was released; Another preprint on Scientific Foundation Models was also released.
Research Experience
Leading the Param-Intelligence (π) Lab at the Department of Aerospace Engineering, WPI.
Background
Research interests encompass scientific machine learning, physics & data-driven methods, trustworthy machine learning (ML) algorithms for scientific computations, and parallel algorithms. Particularly interested in tackling different problems in computational physics including inverse problems, high-dimensional problems, Fractional and Non-local PDEs, Stochastic PDEs, etc.