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Tapas Tripura is a researcher in computational mechanics and scientific machine learning. He received his B.Tech. in Civil Engineering from the NERIST and his M.Tech. in Structural Engineering from the IIT Guwahati. He is currently pursuing his Ph.D. in the Department of Applied Mechanics at IIT Delhi. At IIT Delhi, he is affiliated with the Center for Scientific Computing and Computational Mechanics, where his research lies at the intersection of physics, computation, and artificial intelligence. His current work focuses on data-driven discovery of physical systems, operator learning, scientific foundation modeling, and reinforcement learning for intelligent control of mechanical systems. Tapas has introduced the Wavelet Neural Operator (WNO) for operator learning, proposed a Lagrangian discovery framework for uncovering governing equations directly from data, and developed the scientific foundation model Neural Compositional Wavelet Operator (NCWNO). He is also a recipient of the prestigious Prime Minister’s Research Fellowship (PMRF), awarded by the Ministry of Education, Government of India.
Tapas Tripura is a researcher in computational mechanics and scientific machine learning. He received his B.Tech. in Civil Engineering from the NERIST and his M.Tech. in Structural Engineering from the IIT Guwahati. He is currently pursuing his Ph.D. in the Department of Applied Mechanics at IIT Delhi. At IIT Delhi, he is affiliated with the Center for Scientific Computing and Computational Mechanics, where his research lies at the intersection of physics, computation, and artificial intelligence. His current work focuses on data-driven discovery of physical systems, operator learning, scientific foundation modeling, and reinforcement learning for intelligent control of mechanical systems. Tapas has introduced the Wavelet Neural Operator (WNO) for operator learning, proposed a Lagrangian discovery framework for uncovering governing equations directly from data, and developed the scientific foundation model Neural Compositional Wavelet Operator (NCWNO). He is also a recipient of the prestigious Prime Minister’s Research Fellowship (PMRF), awarded by the Ministry of Education, Government of India.
Glimpses on my work at IIT Delhi as PMRF
Glimpses on my work at IIT Delhi as PMRF
🔗 Data-driven Physics Discovery of Dynamical systems
🔗 Data-driven Physics Discovery of Dynamical systems
Discovering interpretable Lagrangian of dynamical systems from data
Discovering interpretable Lagrangian of dynamical systems from data
MAntRA: A framework for model agnostic reliability analysis
MAntRA: A framework for model agnostic reliability analysis
🔗 Model Agnostic Predictive Control using Temporal Difference Reinforcement Learning
🔗 Model Agnostic Predictive Control using Temporal Difference Reinforcement Learning
Robust model agnostic predictive control algorithm for randomly excited dynamical systems
Robust model agnostic predictive control algorithm for randomly excited dynamical systems
🔗 Deep Neural Operator for Computational Mechanics
🔗 Deep Neural Operator for Computational Mechanics
Wavelet Neural Operator based elastography for tumors
Wavelet Neural Operator based elastography for tumors
Fault detection and isolation using probabilistic wavelet neural operator
Fault detection and isolation using probabilistic wavelet neural operator
🔗 Scientific Foundation Model
🔗 Scientific Foundation Model
Neural Combinatorial Wavelet Neural Operator for continual learning
Neural Combinatorial Wavelet Neural Operator for continual learning
🔗 Predictive Digital Twin
🔗 Predictive Digital Twin
🔗 Neural Architecture Search Algorithms
🔗 Neural Architecture Search Algorithms
Neural Combinatorial Wavelet Neural Operator for continual learning
Neural Combinatorial Wavelet Neural Operator for continual learning
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