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Ajay Kumar Sampathirao

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Ajay Kumar Sampathirao

Technische Universität Berlin
Fachgebiet Regelungssysteme
Sekretariat EN11
Einsteinufer 17
D-10587 Berlin

Office: EN 240 (Elektrotechnik Neubau)
Phone: +49 (0)30 314-23573
Fax: +49 (0)30 314-21137
Email: Sampathirao@control.TU-berlin.de

Biography Hey, I'm Ajay and I am from India. I received my bachelors in electrical and electronics engineering from NIT Warangal, 2010. In 2012, I received my masters from IIT Delhi with specialisation in control and automation. I worked as a software engineer for a brief period in WESEE (Weapons and Electronics Systems Engineering) where I worked on numerical platforms estimation of actual signal from corrupt measurements. In 2013, I joined in the doctoral program in computer, decision systems unit in IMT, Lucca, Italy. My supervisors are Alberto Bemporad and Pantelis Sopasakis and discussed my thesis in December 2016.

Research My research focus on Model Predictive Control (MPC), parallel optimisation methods and GPUs. My PhD title is "Parallel methods of solving stochastic optimal control: control for drinking water networks". This work developed algorithms that can be suitably parallised to solve stochastic optimal control inn real-time. These algorithms are implemented on GPU hardware and employed for economic management of water networks.

Current work Currently, I am working on centralised and distributed energy management system (EMS) for isolated and interconnected microgrid. The objective of the EMS solutions is to maximise the infeed from the renewable sources and minimise the operation of the thermal and diesel generators.


Ajay Kumar Sampathirao, Grosso, Juan Manuel, Pantelis Sopasakis, Ocampo-Martinez, Carlos, Alberto Bemporad, Vicenc Puig. Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona Case Study. In 19th IFAC World Congress, Cape Town, South Africa, 2014.

Sampathirao, A.K., Sopasakis, P., Bemporad, A.. Decentralised hierarchical multi-rate control of large-scale drinking water networks. In 9th Int. Conf. Critical Information Infrastructures Security, volume 8985 of Lecture Notes in Computer Science (LNCS), Limassol, Cyprus, October 2014.

Sampathirao, A.K., Sopasakis, P., Bemporad, A., Patrinos, P.. Distributed solution of stochastic optimal control problems on GPUs. In 54 IEEE Conf. Decision and Control, Osaka, Japan, Dec 2015.

Sampathirao, A.K., Sopasakis, P., Bemporad, A., Patrinos, P.. Fast parallelizable scenario-based stochastic optimization. In 4th European Conference on Computational Optimization, Leuven, Belgium, September 2016.

A.K. Sampathirao, P. Sopasakis, A. Bemporad, P. Patrinos. GPU-accelerated stochastic predictive control of drinking water networks. Unpublished2016. publication in March 2017 IEEE CST.
A.K. Sampathirao, P. Sopasakis, A. Bemporad, P. Patrinos. Proximal Quasi-Newton Methods for Scenario-based Stochastic Optimal Control. Unpublished2016. Submitted to IFAC WC 2017.

In press

  • A.K. Sampathirao, P. Sopasakis, A. Bemporad and P. Patrinos, “An open-source GPU-accelerated software for uncertainty-aware management of urban water networks”


Ajay Kumar Sampathirao. Parallel methods for solving stochastic optimal control : control of drinking water networks. IMT, Dec 2016.

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