Amritam Das ia a doctoral candidate in Control Systems (CS) group at the Department of Electrical Engineering. His research topic is 'Model-Based Control for Thermo-Fluidic Process' and his supervisor is prof. Siep Weiland. This project is in collaboration with Oc'e Technologies B.V., a Canon holding for manufacturing professional printers. His research interests include infinite dimensional system theory, control of distributed parameter systems, model approximation and reduction of distributed parameter systems, convex optimzation and optimal control. He is a regular visiting scholar in School of Enginnering for Matter, Transport and Energy (SEMTE) at Arizona State University where he collaborates with Dr. Matthew Peet on developing novel Sum of Squares (SOS) based framework for analysing and controling distributed parameter systems.
I am fascinated by the beautiful marriage between mathematics and engineering. Using their incredible interplay, I aim to develop technologies that are smarter, more reliable and energy-efficient.
Amritam Das was born on July 31st 1992 in West Bengal, India. He received his Bachelor of Technology degree in Mechatronics from SRM University, India in June 2014. His bachelor project was on ‘Design and Fabrication of Flapping Wing Ornithopter’. He was the recipient of gold medal from SRM University for being topper of his class 2010-2014. In September 2014, he started master’s degree in Systems & Control at Eindhoven University of Technology as a recipeint of prestigious ALSP Scholarship. During his study, he was also awarded with Océ Merit Scholarhsip for his personal and academic development. In August 2016, he received his MSc. degree in Systems & Control. His graduation thesis was titled ‘Vehicle Dynamics Simulation & Control’. Since September 2016, he is appointed as a PhD candidate in Control Systems (CS) group at the Department of Electrical Engineering.
Soft Sensing-Based In Situ Control of Thermofluidic Processes in DoD Inkjet PrintingIEEE Transactions on Control Systems Technology (2022)
A Closed-Form Solution to Estimate Spatially Varying Parameters in Heat and Mass TransportIEEE Control Systems Letters (2021)
A Closed-Form Solution to Estimate Spatially Varying Parameters in Heat and Mass Transport2021 American Control Conference, ACC 2021 (2021)
A Linear Least Squares Approach to Estimate Space-Dependent Parameters in Heat and Mass TransportBenelux Workshop on Systems and Control 2021 (2021)
A closed-form solution to estimate space-dependent parameters in heat and mass transportPhysics@Veldhoven 2021 (2021)
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