Sudeshna Sinha

Title: Sudeshna Sinha: Innovator in Physics Augmented Neural Networks

Introduction

Sudeshna Sinha is a prominent inventor based in Punjab, India. She has made significant contributions to the field of neural networks, particularly in the context of dynamical systems. Her innovative work focuses on the intersection of physics and artificial intelligence.

Latest Patents

Sudeshna Sinha holds a patent for "Physics augmented neural networks configured for operating in environments that mix order and chaos." This patent outlines methods, systems, and computer-readable media for utilizing an augmented neural network. The method includes utilizing a neural network pre-processor to convert generic coordinates associated with a dynamical system to canonical coordinates. It also involves concatenating a Hamiltonian neural network to the pre-processor to create a generalized Hamiltonian neural network. The trained generalized Hamiltonian neural network is then used to forecast nonlinear dynamics and quantify chaotic behavior, thereby discovering and mapping transitions between orderly and chaotic states.

Career Highlights

Sudeshna Sinha is affiliated with North Carolina State University, where she continues her research and development in neural networks. Her work has garnered attention for its innovative approach to understanding complex systems through the lens of physics and artificial intelligence.

Collaborations

She has collaborated with notable colleagues, including William Lawrence Ditto and John Florian Lindner, who share her passion for advancing the field of neural networks and dynamical systems.

Conclusion

Sudeshna Sinha's contributions to the field of physics augmented neural networks exemplify the innovative spirit of modern inventors. Her work not only enhances our understanding of complex systems but also paves the way for future advancements in artificial intelligence.