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bio

I completed my master's degree in electrical engineering at Aalto University, where I am majored in control, robotics, and autonomous systems, and minored in computer science. My master's thesis on learning computationally lightweight classifiers was advised and supervised by Prof. Dominik Baumann.

I was previously a graduate research assistant with the Sensor Informatics Group, working on implementing optimal control methods on a rotary inverted pendulum. The group is led by Prof. Simo Sarkka.

Before that, I was a junior research fellow with the Data, Control, and Autonomous Systems (DACAS) Lab, Indian Institute of Science, Bangalore, from 2021–2023, with Prof. Jishnu Keshavan. I graduated with a Bachelor of Engineering (B.Eng.) in mechanical engineering from Ramaiah Institute of Technology in 2021.

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publications

conferences

  1. S. Murali, C. R. Rojas, and D. Baumann, "Computationally lightweight classifiers with frequentist bounds on prediction errors," International Conference on Artificial Intelligence and Statistics, 2026 (accepted)

  2. S. Singhal, J. Keshavan, and S. Murali, "Constant optical flow divergence based robust adaptive control strategy for autonomous vertical landing of quadrotors", AIAA SCITECH 2023 Forum, doi:10.2514/6.2023-1150

journals

  1. J. Keshavan, S. Belgaonkar and S. Murali., "Adaptive Control of a Constrained First Order Sliding Mode for Visual Formation Convergence Applications," in IEEE Access, vol. 11, pp. 112263-112275, 2023, doi: 10.1109/ACCESS.2023.3323896

posters and talks

  1. "A Computationally Efficient Classifier with Frequentist Bounds on Prediction Errors," at the IEEE Finland Workshop on Emerging Trends in Automatic Control, September 26th 2025 (poster).
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contact

Office: Room 2554, Maarintie 8, Espoo 02150, Finland.

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Shreeram Murali

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I am a Ph.D. student at the Cyber-physical Systems Group at Aalto University, Finland, supervised by Prof. Dominik Baumann and Prof. Shankar Deka. I'm also affiliated with the Finnish Center of Artificial Intelligence.

Broadly, my research interests are at the intersection of machine learning, computational statistics, and autonomous control. More specifically, I'm interested in exploring ideas that make learning-based methods safer, computationally lightweight, and more robust for applications in robotics and healthcare. Outside of this, I'm into photography, filmmaking, film-watching, and noodling on my acoustic guitar.

link to CV

news

  • January 2026: Our paper "Computationally lightweight classfifiers with frequentist bounds on prediction errors" was accepted to AISTATS 2026. See you in Tangier, Morocco!

  • November 2025: I presented our poster on Nadaraya-Watson classifiers at the Nordic AI Meet, FCAI AI Day, and the IEEE Finland Workshop on Emerging Trends in Automatic Control.