Panagiotis Patrinos

Research

Optimization, Systems and Control

Current research team

Alexander Bodard, Robin Bruneel, Peter Coppens, Brecht Evens, Leander Hemelhof, Leander Hemelhof, Robin Kenis, Puya Latafat, Emanuel Laude, Konstantinos Oikonomidis, Pieter Pas, Teodor Rotaru, Mathijs Schuurmans, Renzi Wang, Jia Wang

Biography

Panagiotis (Panos) Patrinos is currently assistant professor at the Department of Electrical Engineering (ESAT) of KU Leuven, Belgium. During fall/winter 2014 he held a visiting assistant professor position in the department of electrical engineering at Stanford University. He received his Ph.D. in Control and Optimization, M.Sc. in Applied Mathematics and M.Eng., all from National Technical University of Athens (NTUA), in 2010, 2005 and 2003, respectively. During his studies at the NTUA he received numerous awards, scholarships and grants by the Technical Chamber of Greece, the National Scholarship Foundation, the Eugenides Foundation, the Thomaideio foundation and the General Secretariat of Research and Technology. After his PhD he held postdoctoral positions at the University of Trento and IMT School of Advanced Studies Lucca, Italy, where he became an assistant professor in 2012. He co-organized the Workshop on Embedded Optimization (EMBOPT 2014) and the European Conference on Computational Optimization (EUCCO 2016).  He has given invited talks at Stanford, Berkeley, UCLA, EPFL, KTH, Lund and Freiburg among other universities. He is the author of more than 40 papers in prestigious journals and conference proceedings.His current research interests are focused on optimization theory, in particular operator splitting techniques for convex and nonconvex optimization. Specifically, he is working on novel, efficient algorithms and software (ForBES: https://github.com/kul-forbes/ForBES) for large-scale, distributed and embedded real-time optimization with applications ranging from model predictive control of dynamical systems (robotics, automotive, aerospace) to high-dimensional statistics, machine learning and data mining. He is also interested in stochastic and risk-averse dynamic optimization with applications in the energy and power systems domain.

Active projects

• Learning to optimize nonconvex problems: provably and efficiently
• Van modelgebaseerd tot data-driven: signaalverwerking en regeltechniek voor niet-lineaire systemen
• Taming Nonconvexity in Structured Low-Rank Optimization
• Baekeland Mandaat Robin Bruneel - Stochastic energy forecasting and optimal risk-averse trading strategies on the energy market
• ELO-X - Embedded learning and optimisation for the next generation of smart industrial control systems
• FWO-Asp - Pieter Pas - Beyond optimization: an algorithmic framework for structured nonmonotone inclusions
• Global PhD - Global PhD Partnership
• SeLMA - Structured Low-Rank Matrix/Tensor Approximation: Numerical Optimization-Based Algorithms and Applications

Finished projects

• A unifying algorithmic framework for structured optimization
• Risk-averse Control and Dynamic Optimization Bridging the Gap Between Robust and Stochastic Control
• Newton-Type Operator Splitting Methods for Real-Time Optimization of Cyberphysical Systems
• Optimization frameworks for deep kernel machines
• Ford-KUL Alliance - Interaction-aware learning risk-averse MPC: ensuring safe interaction between automated vehicles and (vulnerable) road users
• Risk-Averse MPC - Real-time learning/Risk-Averse Model Predictive Control for Autonomous Vehicle Motion Control

Awards

• IJCTA Best Paper Award 2020

Publications

Contributions to books

1. Themelis A., Ahookhosh M., Patrinos P., "On the acceleration of forward-backward splitting via an inexact Newton method", in Chapter 15 of Splitting Algorithms, Modern Operator Theory, and Applications, (Luke R., Bauschke H., and Burachik R., eds.), Springer, 2019, pp. 363-412.


2. Latafat P., Patrinos P., "Primal-Dual Proximal Algorithms for Structured Convex Optimization: A Unifying Framework", in Chapter 5 of Large-Scale and Distributed Optimization, (Giselsson P., and Rantzer A., eds.), vol. 2227 of Lecture Notes in Mathematics , Springer International Publishing, 2018, pp. 97-120.

International Journal Papers

1. Laude E., Themelis A., Patrinos P., "Dualities for non-euclidean smoothness and strong convexity under the light of generalized conjugacy", SIAM journal on Optimization, vol. 33, no. 4, 2023, pp. 2721-2749.


2. Sampathirao A., Patrinos P., Bemporad A., Sopasakis P., "Massively parallelizable proximal algorithms for large-scale stochastic optimal control problems", Optimal Control Applications and Methods, 2023, pp. 1-19.


3. Ghaderi S., Ahookhosh M., Patrinos P., Skupin A., Moreau Y., "Smoothing unadjusted Langevin algoritms for nonsmooth composite potential functions", Applied Mathematics and Computation, vol. 464, 2024, 128377 p.


4. Bodard A., Pas P., Patrinos P., "PANTR: A proximal algorithm with trust-region updates for nonconvex constrained optimization", IEEE Control Systems Letters, vol. 7, Jun. 2023, pp. 2389-2394.


5. Khanh Hien L.T., Phan D.N., Gillis N., Ahookhosh M., Patrinos P., "Block Bregman Majorization Minimization with Extrapolation", SIAM Journal of Data Science, vol. 4, no. 1, 2022, pp. 1-25.


6. Schuurmans M., Patrinos P., "Distributionally Robust Optimization using Cost-Aware Ambiguity Sets", IEEE Control Systems Letters, vol. 7, Jun. 2023, pp. 1855 - 1860.


7. Hermans B., Themelis A., Patrinos P., "QPALM : a proximal augmented lagrangian method for nonconvex quadratic programs", Mathematical Programming Computation, vol. 14, Mar. 2022, pp. 497-541.


8. Latafat P., Patrinos P., "Primal-dual algorithms for multi-agent structured optimization over message-passing architectures with bounded communication delays", Optimization Methods and Software, vol. 37, no. 6, Feb. 2022, pp. 2052-2079.


9. Ahookhosh M., Hien L., Gillis N., Patrinos P., "Multi-block Bregman proximal alternating linearized minimization and its application to sparse orthogonal nonnegative matrix factorization", Computational Optimization and Applications, vol. 79, no. 3, 2021, pp. 681-715.


10. Schuurmans M., Katriniok A., Meissen C., Tseng H.E., Patrinos P., "Safe, Learning-Based MPC for Highway Driving under Lane-Change Uncertainty: A Distributionally Robust Approach", Artificial Intelligence, vol. 320, 2023, 103920 p.


11. Schuurmans M., Patrinos P., "A General Framework for Learning-Based Distributionally Robust MPC of Markov Jump Systems", IEEE Transactions on Automatic Control Special Issue on Learning for Control, vol. 68, no. 5, May 2023, pp. 2950-2965.


12. Hermans B., Pipeleers G., Patrinos P., "A penalty method for nonlinear programs with set exclusion constraints", Automatica, vol. 127, 2021, pp. 109-500.


13. Coppens P., Patrinos P., "Data-driven distributionally robust MPC for constrained stochastic systems", IEEE Control Systems Letters, vol. 6, Jun. 2021, pp. 1274-1279.


14. Latafat P., Themelis A., Ahookhosh M., Patrinos P., "Bregman Finito/MISO for nonconvex regularized finite sum minimization without Lipschitz gradient continuity", SIAM Journal on Optimization, vol. 32, no. 3, Jun. 2022, pp. 2230-2262.


15. Tonin F., Patrinos P., Suykens J. A.K., "Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints", Neural Networks, vol. 142, Oct. 2021, pp. 661-679.


16. Narayanan A. M., Patrinos P. and Bertrand A., "Optimal versus approximate channel selection methods for EEG decoding with application to topology-constrained neuro-sensor networks", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 29, Nov. 2020, pp. 92-102.


17. Themelis A., Stella L., Patrinos P., "Douglas-Rachford splitting and ADMM for nonconvex optimization: accelerated and Newton-type algorithms", Computational Optimization and Applications, vol. 82, no. 2, May 2022, pp. 395-440.


18. Wouters J., Patrinos P., Kloosterman F., Bertrand A., "Multi-pattern recognition through maximization of signal-to-peak-interference ratio with application to neural spike sorting", IEEE Transactions on Signal Processing, vol. 68, Nov. 2020, pp. 6240-6254.


19. Lekic A., Hermans B., Jovicic N., Patrinos P., "Microsecond Nonlinear Model Predictive Control for DC-DC Converters", International Journal of Circuit Theory and Applications, vol. 48, no. 3, 2020, pp. 406-419.


20. Sopasakis P., Herceg D., Bemporad A., Patrinos P., "Risk-averse model predictive control", Automatica, vol. 100, 2019, pp. 281-288.


21. Hans C.A., Sopasakis P., Raisch J., Reincke-Collon C., Patrinos P., "Risk-Averse Model Predictive Operation Control of Islanded Microgrids", IEEE Transactions on Control Systems Technology, vol. 28, no. 6, 2019, pp. 2136-2151.


22. Themelis A., Patrinos P., "SuperMann: A Superlinearly Convergent Algorithm for Finding Fixed Points of Nonexpansive Operators", IEEE Transactions of Automatic Control, vol. 64, no. 12, Dec. 2019, pp. 4875-4890.


23. Latafat P., Themelis A., Patrinos P., "Block-coordinate and incremental aggregated proximal gradient methods for nonsmooth nonconvex problems", Mathematical Programming, Jan. 2021, pp. 195-224.


24. Ahookhosh M., Hien L.T.K., Gillis N., Patrinos P., "A block inertial Bregman proximal algorithm for nonsmooth nonconvex problems with application to symmetric nonnegative matrix tri-factorization", Journal of Optimization Theory and Applications, vol. 190, 2021, pp. 234-258.


25. Stella L., Themelis A., Patrinos P., "Newton-Type Alternating Minimization Algorithm for Convex Optimization", IEEE Transactions on Automatic Control, vol. 64, no. 2, Feb. 2019, pp. 697-711.


26. Themelis A., Patrinos P., "Douglas-Rachford splitting and ADMM for nonconvex optimization: tight convergence results", SIAM Journal of Optimization, vol. 30, no. 1, Jan. 2020, pp. 149-181.


27. Ahookhosh M., Themelis A., Patrinos P., "A Bregman forward-backward linesearch algorithm for nonconvex composite optimization: superlinear convergence to nonisolated local minima", SIAM Journal on Optimization, vol. 31, no. 1, Feb. 2021, pp. 653-685.


28. de la Hucha Arce F., Patrinos P., Verhelst M., Bertrand A., "On the convexity of bit depth allocation for linear MMSE estimation in wireless sensor networks", IEEE Signal Processing Letters, vol. 27, Jan. 2020, pp. 291-295.


29. Murillo Y., Van den Bergh B., Beysens J., Bertrand A., Dehaene W., Patrinos P., Tuytelaars T., Vazquez Sabariego R., Verhelst M., Wambacq P., Pollin S., "Multidisciplinary Learning through Implementation of the DVB-S2 Standard", IEEE Communications Magazine, vol. 55, no. 5, May 2017, pp. 124-130.


30. Latafat P., Freris N. M., Patrinos P., "A New Randomized Block-Coordinate Primal-Dual Proximal Algorithm for Distributed Optimization", IEEE Transactions on Automatic Control, vol. 64, no. 10, Oct. 2019, pp. 4050-4065.


31. Verdyck J., Lanneer W., Tsiaflakis P., Coomans W., Patrinos P., Moonen M., "Optimal and Fast Dynamic Spectrum Management Algorithms for Multi-User Full-Duplex DSL networks", IEEE Access, vol. 7, Aug. 2019, pp. 106600-106616.


32. Sopasakis P., Sampathirao A., Bemporad A., Patrinos P., "Uncertainty-aware demand management of water distribution networks in deregulated energy markets", Environmental Modelling & Software, vol. 101, no. *, 2018, pp. 10-22.


33. Michaelides P.G., Vouldis T.E.G.A., Konstantakis K., Patrinos P., "A semi-parametric non-linear neural network filter : Theory and empirical evidence", Computational Economics, vol. 51, no. 3, Nov. 2018, pp. 637-675.


34. Themelis A., Stella L., Patrinos P., "Forward-backward envelope for the sum of two nonconvex functions : further properties and nonmonotone line-search algorithms", SIAM Journal on Optimization, vol. 28, no. 3, Aug. 2018, pp. 2274-2303.


35. Stella L., Themelis A., Patrinos P., "Forward-backward quasi-Newton methods for nonsmooth optimization problems", Computational Optimization and Applications, vol. 67, no. 3, Jul. 2017, pp. 443-487.


36. Latafat P., Patrinos P., "Asymmetric forward-backward-adjoint splitting for solving monotone inclusions involving three operators", Computational Optimization and Applications, vol. 68, no. 1, Sep. 2017, pp. 57-93.


37. Sampathirao A.K., Sopasakis P., Bemporad A., Patrinos P., "GPU-accelerated stochastic predictive control of drinking water networks", IEEE Control Systems Technology, vol. 26, no. 2, Mar. 2018, pp. 551-562.


38. Rubagotti M., Patrinos P., Guiggiani A., Bemporad A., "Real-time model predictive control based on dual gradient projection : Theory and fixed-point fpga implementation", International Journal of Robust and Nonlinear Control, vol. 26, no 15, 2016, pp. 3292-3310.

International Conference Papers

1. Behmandpoor P., Patrinos P., Moonen M., "Model-free decentralized training for deep learning based resource allocation in communication networks", in Proc. of the 31st European Signal Processing Conference (EUSIPCO), Helsinki, Zweden, Sep. 2023, pp. 1494-1498.


2. El Bourkhissi L., Necoara I., Patrinos P., "Linearized ADMM for nonsmooth nonconvex optimization with nonlinear equality constraints", in Proc. of the IEEE 62nd Annual Conference on Decision and Control (CDC), Marina Bay Sands, Singapore, Dec. 2023, pp. ?.


3. Coppens P., Patrinos P., "Ordered risk minimization : Learning more from less data", in Proc. of the IEEE 62nd Annual Conference on Decision and Control (CDC), Marina Bay Sands, Singapore, Dec. 2023.


4. Tonin F., Patrinos P., Suykens J.A.K., "Combining Primal and Dual Representations in Deep Restricted Kernel Machines Classifiers", in Proc. of the ECML PKDD 2023 - Workshop on Simplification, Compression, Efficiency and Frugality for Artificial intelligence, Torino, Italy, Sep. 2023, pp. 5.


5. Tonin F., Lambert A., Patrinos P., Suykens J.A.K., "Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms", in Proc. of the 40th International Conference on Machine Learning (ICML), Hawai, USA, Jul. 2023, 34379 p.


6. Kiessling D., Pas P., Astudillo A., Patrinos P., Swevers J., "Anderson Accelerated Feasible Sequential Linear Programming", in Proc. of the 22nd IFAC World Congress 2023, Yokohama, Japan, vol. 56-2, Jul. 2023, pp. 7436-7441.


7. Pethick T., Fercoq O., Latafat P., Patrinos P., Cevher V., "Solving stochastic weak Minty variational inequalities without increasing batch size", in Proc. of the International Conference on Learning Representations (ICLR), Kigali, Rwanda , May 2023.


8. Tonin F., Tao Q., Patrinos P., Suykens J.A.K., "Deep Kernel Principal Component Analysis for Multi-level Feature Learning"


9. Allamaa J.P., Patrinos P., Van der Auweraer H., Son T.D, "Safety Envelope for Orthogonal Collocation Methods in Embedded Optimal Control", in Proc. of the 2023 European Control Conference (ECC 2023), Bucharest, Romania, Jun. 2023, pp. 7.


10. Pas P., Themelis A., Patrinos P., "Gauss-Newton meets PANOC: A fast and globally convergent algorithm for nonlinear optimal control", in Proc. of the 22nd IFAC World Congress 2023, Yokohama, Japan, , vol. 56-2, Jul. 2023, pp. 4852-4857.


11. Bodard A., Moran R., Schuurmans M., Patrinos P., Sopasakis P., "SPOCK: A proximal method for multistage risk-averse optimal control problems", in Proc. of the 22nd IFAC World Congress 2023, Yokohama, Japan, vol. 56-2, Jul. 2023, pp. 1944-1951.


12. Hemelhof L., Markovsky I., Patrinos P., "Data-Driven Output Matching of Output-Generalized Bilinear and Linear Parameter-Varying systems", in Proc. of the 2023 European Control Conference (ECC), Bucharest, Romania, Jun. 2023, pp. 1-6.


13. Wang R., Schuurmans M., Patrinos P., "Interaction-aware Model Predictive Control for Autonomous Driving", in 2023 European Control Conference (ECC) (ECC), Bucharest, Romania , Jun. 2023, pp. 1 - 6.


14. Behmandpoor P., Patrinos P., Moonen M., "Federated Learning Based Resource Allocation for Wireless Communication Networks", in Proc. of the 30th European Signal Processing Conference (EUSIPCO), Belgrade, Serbia, Sep. 2022, pp. 1656-1660.


15. Simoes M., Themelis A., Patrinos P., "Lasry-Lions envelopes and nonconvex optimization : A homotopy approach", in Proc. of the 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, Aug. 2021, pp. 2089-2093.


16. Pethick T., Latafat P., Patrinos P., Fercoq O., Cevher V., "Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems", in Proc. of the International Conference on Learning Representations (ICLR), Virtual, Apr. 2022, 19 p.


17. Allamaa J.P., Patrinos P., Van der Auweraer H., Son T.D, "Sim2real for Autonomous Vehicle Control using Executable Digital Twin", in IFAC-PapersOnLine, 10th IFAC Symposium on Advances in Automotive Control AAC 2022, vol. 55, no. 24, Aug. 2022, pp. 385-391.


18. Pas P., Schuurmans M., Patrinos P., "Alpaqa: A matrix-free solver for nonlinear MPC and large-scale nonconvex optimization", in Proc. of the 2022 European Control Conference (ECC), London, Jul. 2022, pp. 417-422.


19. Evens B., Schuurmans M., Patrinos P., "Learning MPC for Interaction-Aware Autonomous Driving: A Game-Theoretic Approach", in Proc. of the European Control Conference (ECC 2022), London, UK, Jul. 2022, ? p.


20. Evens B., Latafat P., Themelis A., Suykens J., Patrinos P., "Neural Network Training as an Optimal Control Problem: An Augmented Lagrangian Approach", in Proc. of the 2021 60th IEEE Conferene on Decision and Control (CDC), Austin, USA, Dec. 2021, pp. 5136-5143.


21. Behmandpoor P., Patrinos P., Moonen M., "Learning-based resource allocation with dynamic data rate constaints", in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, Singapore, May 2022, pp. 4088-4092.


22. Schuurmans M., Patrinos P., "Data-driven distributionally robust control of partially observable jump linear systems", in Proc. of the IEEE Conference on Decision and Control (CDC), Cancun, Mexico, Dec. 2022, pp. 4332-4337.


23. Tonin F., Pandey A., Patrinos P., Suykens J. A.K., "Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machine", in Proc. of the 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, 2021, pp. 1-8.


24. Hien L., Gillis N., Patrinos P., "Inertial block mirror descent method for non-conves non-smooth optimization", in Proc. of the 37th International Conference on Machine Learning (ICML), Virtual, Virtual, 2020, pp. 5671-5681.


25. Schuurmans M., Katriniok A., Tseng H., Patrinos P., "Learning-based distributionally robust model predictive control for adaptive cruise control with stochastic driver models", in Proc. of the 21st IFAC World Congress, Virtual, Germany, Jul. 2020, pp. 15128-15133.


26. Themelis A., Hermans B., Patrinos P., "A new envelope function for nonsmooth DC optimization", in Proc. of the 59th IEEE Conference on Decision and Control (CDC), Virtual, Virtual, Dec. 2020, pp. 4697-4702.


27. Vervliet N., Themelis A., Patrinos P., De Lathauwer L., "A quadratically convergent proximal algorithm for nonnegative tensor decomposition", in 2020 28th European Signal Processing Conference (EUSIPCO) (EUSIPCO), Amsterdam, The Netherlands, Jan. 2021, pp. 1020-1024.


28. Schuurmans M., Patrinos P., "Learning-Based Distributionally Robust Model Predictive Control of Markovian Switching Systems with Guaranteed Stability and Recursive Feasibility", in Proc. of the 59th IEEE Conference on Decision and Control (CDC), Jeju Island, South Korea, Dec. 2020, pp. 4287-4292.


29. Coppens P., Patrinos P., "Sample Complexity of Data-Driven Stochastic LQR with Multiplicative Uncertainty", in Proc. of the 59th IEEE Conference on Decision and Control (CDC), Jeju, Korea (South) , Dec. 2020, pp. 6210-6215.


30. Coppens P., Schuurmans M., Patrinos P., "Data-driven distributionally robust LQR with multiplicative noise", in Proc. of the 2nd Conference on Learning for Dynamics and Control (L4DC), California, US, vol. 48, no. 3, Jun. 2020, pp. 521-530.


31. Sopasakis P., Fresk E., Patrinos P., "OpEn : Code Generation for Embedded Nonconvex Optimization", in Proc. of the 21st IFAC World Congress, Virtual, 2020, pp. 6548-6554.


32. Small E., Sopasakis E., Fresk E., Patrinos P., Nikolakopoulos G., "Aerial navigation in obstructed environments with embedded nonlinear model predictive control", in Proc. of the 2019 18th European Control Conference, Napoli, Italy, Jun. 2019, pp. 3556-3563.


33. Schuurmans M., Katriniok A., Tseng E., Patrinos P., "Learning-based risk-averse model predictive control for adaptive cruise control with stochastic driver models", in Proceedings of the 21st IFAC World Congress, Berlin, Germany, Jul. 2020, pp. 15337-15342.


34. Sopasakis P., Menounou K., Patrinos P., "SuperSCS : fast and accurate large-scale conic optimization", in Proc. of the 2019 18th European Control Conference (ECC), Napoli, Italy, Jun. 2019, pp. 1500-1505.


35. Hermans B., Themelis A., Patrinos P., "QPALM: A Newton-type Proximal Augmented Lagrangian Method for Quadratic Programs", in 2019 IEEE 58th Annual Conference on Decision and Control (CDC2019), Nice, France, Dec. 2019, pp. 4325-4330.


36. Hermans B., Pipeleers G., Patrinos P., "A Penalty Method Based Approach for Autonomous Navigation using Nonlinear Model Predictive Control", in Proc. of the 6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018), Madison, Wisconsin, Aug. 2018, pp. 234-240.


37. Coppens P., Hermans B., Vandersteen J., Pipeleers G., Patrinos P., "A New Heuristic Approach for Low-Thrust Spacecraft Trajectory Optimization", in Proc. of the 21st IFAC World Congress, Virtual, 2020, pp. 2.


38. Katriniok A., Sopasakis P., Schuurmans M., Patrinos P., "Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC", in 2019 IEEE Conference on Decision and Control (CDC), Nice, France, Dec. 2019, pp. 5272-5278.


39. Schuurmans M., Sopasakis P., Patrinos P., "Safe Learning-Based Control of Stochastic Jump Linear Systems: a Distributionally Robust Approach", in 2019 IEEE Conference on Decision and Control (CDC), Nice, France, Dec. 2019, pp. 6498-6503.


40. Latafat P., Patrinos P., "Multi-agent structured optimization over message-passing architectures with bounded communication delays", in Proc. of the 57th IEEE Conference on Decision and Control (CDC), Miami Beach, Florida, Dec. 2018, pp. 1688-1693.


41. Sopasakis P., Schuurmans M., Patrinos P., "Risk-averse risk-constrained optimal control", in Proc. of the 2019 18th European Control Conference (ECC), Naples, Italy, Jun. 2019, pp. 375-380.


42. Sathya A., Sopasakis P., Van Parys R., Themelis A., Pipeleers G., Patrinos P., "Embedded nonlinear model predictive control for obstacle avoidance using PANOC", in 2018 European Control Conference (ECC18), Limassol, Cyprus, Jun. 2018, pp. 1523-1528.


43. Latafat P., Bemporad A., Patrinos P., "Plug and Play Distributed Model Predictive Control with Dynamic Coupling: A Randomized Primal-dual Proximal Algorithm", in Proc. of the European Control Conference (ECC), Limassol, Cyprus, Jun. 2018, pp. 1160-1165.


44. Herceg D., Georgoulas G., Sopasakis P., Castano M., Patrinos P., Bemporad A., Niemi J., Nikolakopoulos G., "Data-driven modelling, learning and stochastic predictive control for the steel industry", in Proc. of the 25th Mediterranean Conference on Control and Automation (MED), Valletta, Malta, Jul. 2017, pp. 1361-1366.


45. Stella L., Themelis A., Sopasakis P., Patrinos P., "A Simple and Efficient Algorithm for Nonlinear Model Predictive Control", in 2017 IEEE 56th Annual Conference on Decision and Control (CDC2017), Melbourne, Australia, Dec. 2017, pp. 1939-1944.


46. Sopasakis P., Themelis A., Suykens J., Patrinos P., "A primal-dual line search method and applications in image processing", in 2017 25th European Signal Processing Conference (EUSIPCO), Kos, Greece, Aug. 2017, pp. 1065-1069.


47. Sampathirao A.K., Sopasakis P., Bemporad A., Patrinos P., "Proximal limited-memory quasi-newton methods for scenario-based stochastic optimal control", in Proc. of the 20th IFAC World Congress, Toulouse, France, Jul. 2017, pp. 11865-11870.


48. Herceg D., Ntouskas S., Sopasakis P., Dokoumetzidis A., Macheras P., Sarimveis H., Patrinos P., "Modeling and administration scheduling of fractional-order pharmacokinetic systems", in Proc. of the 20th IFAC World Congress, Toulouse, France, Jul. 2017, pp. 9742-9747.


49. Sopasakis P., Herceg D., Patrinos P., Bemporad A., "Stochastic economic model predictive control for markovian switching systems", in Proc. of the 20th IFAC World Congress, Toulouse, France, Jul. 2017, pp. 524-530.


50. Freris N., Patrinos P., "Distributed Computing over encrypted data", in Proc. of the 54th Annual Allerton Conference on Communication, Control , and Computing (Allerton Conference), Illinois, USA, Sep. 2016, pp. 1116-1122.


51. Guiggiani P., Patrinos P., Bemporad A., "Fixed-point implementation of a proximal Newton method for embedded model predictive control", in Proc. of the 19th IFAC World Congress, Cape Town, South Africa, Aug. 2014, pp. 2921-2926.


52. Latafat P., Stella L., Patrinos P., "New primal-dual proximal algorithms for distributed optimization", in Proc. of the 2016 IEEE 55th Conference on Decision and Control (CDC 2016), Las Vegas, USA, Dec. 2016, pp. 1959-1964.


53. Sopasakis P., Freris N., Patrinos P., "Accelerated reconstruction of a compressively sampled data stream", in Proc. of the 24th European Signal Processing Conference (EUSIPCO 2016), Budapest, Hungary, Aug. 2016, pp. 1078-1082.


54. Sampathirao A.K., Sopasakis P., Bemporad A., Patrinos P., "Distributed solution of stochastic optimal control problems on GPUs", in Proc. of the IEEE 54th Annual Conference on Decision and Control (CDC 2015), Osaka, Japan, Dec. 2015, pp. 7183-7188.


55. Themelis A., Villa S., Patrinos P., Bemporad A., "Stochastic gradient methods for stochastic model predictive control", in 2016 European Control Conference (ECC16), Aalborg, Denmark, Jun. 2016, pp. 154-159.

Internal Reports

1. Coppens P., Schuurmans M., Patrinos P., "Data-driven distributionally robust LQR with multiplicative noise", Internal Report 20-27, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2020. Abstractbook of the 39th Benelux Meeting on Systems and Control, Elspeet, Netherlands, Mar. 2020}.