Assistant Professor of Spatio-Temporal Control Systems

PhD Thesis

Amritam Das, A digital twin for controlling thermo-fluidic processes, Eindhoven University of Technology. PhD Dissertations, ISBN: 978-90-386-5140-8 [pdf]

Book Chapters

  1. Miguel Aguiar, Amritam Das, and Karl H. Johansson, Learning flows of control systems, 36th Conference on Neural Information Processing Systems (DLDE Workshop), 2022.
  2. Miguel Aguiar, Amritam Das, and Karl H Johansson, Learning flow functions from data with applications to nonlinear oscillators, IFAC-PapersOnLine, 56(2):4088–4093, 2023.
  3. Miguel Aguiar, Amritam Das, and Karl H Johansson, Universal approximation of flows of control systems by recurrent neural networks, 2023 62nd IEEE Conference on Decision and Control (CDC), pages 2320–2327. IEEE, 2023.
  4. Miguel Aguiar, Amritam Das, and Karl H Johansson, Learning flow functions of spiking systems, 6th Annual Learning for Dynamics & Control Conference, pages 591–602. PMLR, 2024.
  5. Andrew Alleyne, Frank Allgöwer, Aaron D Ames, Saurabh Amin, James Anderson, Anuradha M Annaswamy, Panos J Antsaklis, Neda Bagheri, Hamsa Balakrishnan, Bassam Bamieh, et al., Control for societal-scale challenges: Road map 2030, 2023.
  6. Thomas Chaffey, Amritam Das, and Rodolphe Sepulchre, Splitting algorithms and circuit analysis, arXiv preprint arXiv:2208.04765, 2022. [arXiv:2208.04765]
  7. Amritam Das, A digital twin for controlling thermo-fluidic processes, PhD thesis, Technische Universiteit Eindhoven, 2020.
  8. Amritam Das, Thomas Chaffey, and Rodolphe Sepulchre, Oscillations in mixed-feedback systems, 2022.
  9. Amritam Das and Jan Heiland, Low-order linear parameter varying approximations for nonlinear controller design for flows, 2024 European Control Conference (ECC), pages 2065–2070. IEEE, 2024.
  10. Amritam Das, Yanin Kasemsinsup, and Siep Weiland, Optimal trajectory tracking control for automated guided vehicles, IFAC-PapersOnLine, 50(1):303–308, 2017.
  11. Amritam Das, Ramachandra R Kolluri, and Iven Mareels, Data industry, The Impact of Automatic Control Research on Industrial Innovation: Enabling a Sustainable Future, pages 13–41, 2024.
  12. Amritam Das, Martijn Princen, Mahnaz Shokrpour, Amol Khalate, and Siep Weiland, Soft sensing based in situ control of thermo-fluidic processes in dod inkjet printing, IEEE Transactions on Control Systems Technology, 2020.
  13. Amritam Das, Sachin Shivakumar, Matthew Peet, and Siep Weiland, Robust analysis of uncertain ode-pde systems using pi multipliers, pies and lpis, 2020 59th IEEE Conference on Decision and Control (CDC), pages 634–639. IEEE, 2020.
  14. Amritam Das, Sachin Shivakumar, Siep Weiland, and Matthew Peet, Representation and stability analysis of pde-ode coupled systems, arXiv preprint arXiv:1812.07186, 2018. [arXiv:1812.07186]
  15. Amritam Das, Sachin Shivakumar, Siep Weiland, and Matthew M Peet, h∞-optimal estimation for linear coupled pde systems, 2019 IEEE 58th Conference on Decision and Control (CDC), pages 262–267. IEEE, 2019.
  16. Amritam Das and Siep Weiland, Modelgebaseerd regelen van thermische effecten in inkjetprinters, 2019.
  17. Amritam Das, Siep Weiland, and Laura Iapichino, Model approximation of thermo-fluidic diffusion processes in spatially interconnected structures, 2018 European Control Conference (ECC), pages 2653–2658. IEEE, 2018.
  18. Amritam Das, Siep Weiland, and Matthijs Van Berkel, Frequency domain estimation of spatially varying parameters in heat and mass transport, 2019 American Control Conference (ACC), pages 600–605. IEEE, 2019.
  19. Valerio Gori, Will Hendrix, Amritam Das, and Zhiyong Sun, Effect of weight distribution and active safety systems on electric vehicle performance, Sensors, 24(11):3557, 2024.
  20. Tuan Dat Hoang, Amritam Das, Sjirk Koekebakker, and Siep Weiland, Sensorless field-oriented estimation of hybrid stepper motors in high-performance paper handling, 2019 IEEE Conference on Control Technology and Applications (CCTA), pages 252–257. IEEE, 2019.
  21. Pramod P Khargonekar, Tariq Samad, Saurabh Amin, Aranya Chakrabortty, Fabrizio Dabbene, Amritam Das, Masayuki Fujita, Mario Garcia-Sanz, Dennice F Gayme, Marija Ilić, et al., Climate change mitigation, adaptation, and resilience: Challenges and opportunities for the control systems community, IEEE Control Systems Magazine, 44(3):33–51, 2024.
  22. Julius PJ Krebbekx, Roland Tóth, and Amritam Das, Scaled relative graph analysis of lur’e systems and the generalized circle criterion, arXiv preprint arXiv:2411.18318, 2024. [arXiv:2411.18318]
  23. Julius PJ Krebbekx, Roland Tóth, and Amritam Das, Nonlinear bandwidth and bode diagrams based on scaled relative graphs, arXiv preprint arXiv:2504.01585, 2025. [arXiv:2504.01585]
  24. TJ Meijer, A Das, and S Weiland, Moving-boundary port-hamiltonian systems, arXiv preprint arXiv:2501.14930, 2025. [arXiv:2501.14930]
  25. Muhammad Umar B Niazi, John Cao, Xudong Sun, Amritam Das, and Karl Henrik Johansson, Learning-based design of luenberger observers for autonomous nonlinear systems, 2023 American Control Conference (ACC), pages 3048–3055. IEEE, 2023.
  26. E Javier Olucha, Patrick JW Koelewijn, Amritam Das, and Roland Tóth, Automated linear parameter-varying modeling of nonlinear systems: A global embedding approach, arXiv preprint arXiv:2502.13082, 2025. [arXiv:2502.13082]
  27. E Javier Olucha, Rajiv Singh, Amritam Das, and Roland Tóth, On-the-fly surrogation for complex nonlinear dynamics, arXiv preprint arXiv:2504.00276, 2025. [arXiv:2504.00276]
  28. E Javier Olucha, Bogoljub Terzin, Amritam Das, and Roland Tóth, On the reduction of linear parameter-varying state-space models, arXiv preprint arXiv:2404.01871, 2024. [arXiv:2404.01871]
  29. M Peet, S Shivakumar, A Das, and S Weiland, Discussion paper: A new mathematical framework for representation and analysis of coupled pdes, 3rd IFAC Workshop on Control of Systems Governed by Partial Differential Equations CPDE 2019: Oaxaca, Mexico, 20–24 May 2019, volume 9, pages 132–137. 2019.
  30. Jake Rap and Amritam Das, On-traffic: An operator learning framework for online traffic flow estimation and uncertainty quantification from lagrangian sensors, arXiv preprint arXiv:2503.14053, 2025. [arXiv:2503.14053]
  31. Daniel Selvaratnam, Amritam Das, and Henrik Sandberg, Electrical fault localisation over a distributed parameter transmission line, 2023 62nd IEEE Conference on Decision and Control (CDC), pages 7088–7093. IEEE, 2023.
  32. Daniel Selvaratnam, Alessio Moreschini, Amritam Das, Thomas Parisini, and Henrik Sandberg, Fault localisation in infinite-dimensional linear electrical networks, arXiv preprint arXiv:2504.04910, 2025. [arXiv:2504.04910]
  33. Daniel Selvaratnam, Alessio Moreschini, Amritam Das, Thomas Parisini, and Henrik Sandberg, Frequency-domain bounds for the multiconductor telegrapher’s equation, arXiv preprint arXiv:2504.01599, 2025. [arXiv:2504.01599]
  34. Sachin Shivakumar, Amritam Das, Declan Jagt, and Matthew Peet, Pietools 2021a, 2021.
  35. Sachin Shivakumar, Amritam Das, and Matthew Peet, Dual representations and h∞-optimal control of partial differential equations, arXiv preprint arXiv:2208.13104, 2022. [arXiv:2208.13104]
  36. Sachin Shivakumar, Amritam Das, and Matthew Peet, h∞-optimal control of coupled ode-pde systems using pie framework and lpis, arXiv preprint arXiv:2208.13104, 2022. [arXiv:2208.13104]
  37. Sachin Shivakumar, Amritam Das, and Matthew M Peet, Pietools: A matlab toolbox for manipulation and optimization of partial integral operators, 2020 American Control Conference (ACC), pages 2667–2672. IEEE, 2020.
  38. Sachin Shivakumar, Amritam Das, and Matthew M Peet, Representation of linear pdes with spatial integral terms as partial integral equations, 2023 American Control Conference (ACC), pages 1788–1793. IEEE, 2023.
  39. Sachin Shivakumar, Amritam Das, Siep Weiland, and Matthew Peet, Extension of the partial integral equation representation to gpde input-output systems, IEEE Transactions on Automatic Control, 2024.
  40. Sachin Shivakumar, Amritam Das, Siep Weiland, and Matthew M Peet, A generalized lmi formulation for input-output analysis of linear systems of odes coupled with pdes, 2019 IEEE 58th conference on decision and control (CDC), pages 280–285. IEEE, 2019.
  41. Sachin Shivakumar, Amritam Das, Siep Weiland, and Matthew M Peet, Duality and h∞-optimal control of coupled ode-pde systems, 2020 59th IEEE Conference on Decision and Control (CDC), pages 5689–5696. IEEE, 2020.
  42. Sachin Shivakumar, Declan Jagt, Danilo Braghini, Amritam Das, and Matthew Peet, Pietools 2024: User manual, arXiv preprint arXiv:2101.02050, 2025. [arXiv:2101.02050]
  43. Sachin Shivakumar and M Peet, h∞-optimal control of coupled ode-pde systems using the pie framework and lpis, Technical report, arXiv preprint arXiv:2208.13104, 2022. [arXiv:2208.13104]
  44. Ricky JR van Kampen, Amritam Das, Siep Weiland, and Matthijs van Berkel, A closed-form solution to estimate spatially varying parameters in heat and mass transport, IEEE Control Systems Letters, 5(5):1681–1686, 2020.
  45. Ricky JR van Kampen, Amritam Das, Siep Weiland, and Matthijs van Berkel, A closed-form solution to estimate space-dependent parameters in heat and mass transport, Physics@ Veldhoven 2021, 2021.
  46. RJR van Kampen, Amritam Das, Siep Weiland, and Matthijs van Berkel, Complex gaussian process regression for estimating spatially varying coefficients in thermal transport, 39th Benelux Meeting on Systems and Control 2020, 2020.