I am an AI researcher specializing in Spiking Neural Networks (SNNs) and biologically inspired artificial intelligence, with a Ph.D. in Aerospace Engineering from the Indian Institute of Science (IISc), Bangalore.

My research focuses on understanding and exploiting the spatio-temporal dynamics of spiking neural networks to develop computationally efficient and generalizable learning algorithms. I have worked on biologically plausible learning mechanisms, self-regulated learning, temporal spike-based decision making, interpretable SNN optimization, and decentralized learning for multi-agent problems. My work has explored how principles inspired by biological neural systems can be translated into practical algorithms for classification, task assignment, and autonomous decision making.

I have published my research in journals and conferences including IEEE Transactions on Aerospace and Electronic Systems, Engineering Applications of Artificial Intelligence, Unmanned Systems, IEEE World Congress on Computational Intelligence, and IEEE International Joint Conference on Neural Networks.

Currently, I work as an AI Engineer at Smart Bricks, where I develop AI systems for real-world applications in the PropTech domain. My broader research interest is in bridging biological intelligence and artificial intelligence by developing biologically plausible, energy-efficient, and generalizable neural algorithms for complex real-world problems.

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