Manish Yadav

Dr. Manish Yadav is a Postdoctoral Researcher at the Chair of Cyber-Physical Systems in Mechanical Engineering at Technische Universität Berlin, working on the DFG priority program SPP 2353. He earned his B.Sc. and M.Sc. in Physics from IISER Mohali (2013–2018), focusing on nonlinear dynamics, and his Ph.D. (2023) at the Max Planck Institute of Neurobiology of Behavior under Dr. Aneta Koseska, developing transient-based biochemical information processing models.

• Education: B.Sc./M.Sc. in Physics (IISER Mohali), Ph.D. (Max Planck Institute)

His research bridges nonlinear dynamics and machine learning, particularly through reservoir computing for fast, green AI applications in structural dynamics. He explores network science, transient dynamics, and computational capacity optimization, with a focus on compact network architectures and denoising nonlinear systems.

In collaboration with Prof. Merten Stender, Dr. Yadav leads projects on dynamics-informed design assistants, contributing to emerging paradigms in reservoir computing through submitted and in-review works in journals like Chaos and Physical Review E. Current efforts include developing minimal-data frameworks and performance-dependent network evolution models.

Research areas include:

• Reservoir computing for complex dynamics
• Network topology optimization
• Transient-based computation
• Green machine learning
• Interdisciplinary applications of chaos theory
• Data-driven structural modeling