Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany The “Chair for Dynamics, Control, Machine Learning, and Numerics – Alexander von Humboldt Professorship (FAU DCN-AvH)”, led by Prof. Enrique Zuazua, invites applications for a research assistant position. DEADLINE: January 7, 2026 Position Details • Duration: Initially limited to up to two (2) years, with the […]
Machine Learning
19 posts
Date: Mon.-Wed. June 22 – 24, 2026 Event: MLPDES26, Machine Learning and PDEs Workshop (2026) Host: FAU MoD, the Research Center for Mathematics of Data at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Event type: Hybrid (On-site / Online) Registration form: dcn.nat.fau.eu/registration-mlpdes26 Next Spring, our FAU MoD, Research Center for Mathematics of Data is […]
On November 19-25, 2025, our FAU MoD, Research Center for Mathematics of Data at FAU and the Digital Twin Lab under the CMAI, Center for Mathematics and Artificial Intelligence at GMU are organizing the “The Mathematics of Scientific Machine Learning and Digital Twins” workshop in Erice, Italy. The workshop is […]
*The recordings are available at: https://mod.fau.eu/mlpdes25/ On April 28 – 30, 2025, our FAU MoD, Research Center for Mathematics of Data is hosting the “Machine Learning and PDEs” workshop (MLPDES25) supported by the FAU DCN-AvH, Chair for Dynamics, Control, Machine Learning and Numerics, the AFOSR, Air Force Office of […]
Date: June 30 to July 4, 2025 Event: IEECI-IGSC 2025: International Graduate School on Control 2025 Module Control and Machine Learning (M18 DUBROVNIK) Speakers: • Prof. Enrique Zuazua. FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg • Prof. Martin Lazar. University of Dubrovnik Outline • Historical preliminaries • Control of linear finite-dimensional systems • The […]
On February 15, 2024 Prof. Enrique Zuazua will talk on Contrôle et apprentissage automatique an event organized by the Adria Business & Technology and the moroccan association Math & Maroc. Abstract. La motivation de contrôler les machines remonte à l’antiquité: des machines exécutent automatiquement le travail de l’homme afin que […]
On December 24, 2023 Prof. Enrique Zuazua will talk on “Control and Machine Learning” (S3-1) at the Symposium Controllability and Differential Equations of the 89th Annual Conference of Indian Mathematical Society an international meet organized annually by the IMS, Indian Mathematical Society, this year at BITS Pilani (India) on December […]
On November 24 – 29, 2024, Prof. Enrique Zuazua joint with Borjan Geshkovski (Cambridge) and Domènec Ruiz-Balet (London) are organizing the Oberwolfach Seminar: Control and Machine Learning (2448b) at the Mathematisches Forschungsinstitut Oberwolfach (Germany). This week-long seminar (2448b) will provide an overview of the recent developments and new horizons of […]
On May 29-30, 2024, Prof. Enrique Zuazua is giving a course on “Control and Machine Learning” at the ML&OC24 summer school “Machine Learning and Optimal Control” on May 27-31, 2024 at Gaeta (Italy). Abstract. In this course we shall present some recent results on the interplay between control and Machine […]
On November 23 – 27, our Head Prof. Enrique Zuazua is giving a historical introduction to Control and Machine Learning and then talking on control of finite dimensional systems and Supervised Learning by Control Methods at the Tutorial lecture series on “Advanced Topics Systems Control” organized (online) from November 23 […]
Next year, Prof. Enrique Zuazua (FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg) joint with Prof. Martin Lazar (University of Dubrovnik) will talk on “Control and Machine Learning” (M18 DUBROVNIK module) on July 1-5, 2024 at the IEECI-IGSC 2024: International Graduate School on Control 2024 organized by EECI – European Embedded Control Institute and IEEE […]
Course: Scalar Conservation Laws Lecturers: Enrique Zuazua, , Nicola De Nitti Period: 2022/2023 summer semester Date: April – July 2023 Location: FAU. Master’s Degree in Computational and Applied Mathematics ECTS: 10 This course at FAU StudON: –
Course: Transport Phenomena Lecturers: Enrique Zuazua, Nicola De Nitti Period: 2022/2023 winter semester Date: October 2022 – March 2023 Location: FAU. Master’s Degree in Computational and Applied Mathematics ECTS: 10 This course at FAU StudON: –
Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs) Introduction Accurate and fast predictions of numerical solutions are of significant interest in many areas of science and industry. On one hand, most theoretical methods used in the industry are the result of deriving differential equations that are […]
Course: Control, Machine Learning and Numerics (2022) Lecturers: Enrique Zuazua, Yongcun Song Period: 2021/2022 summer semester Date: April – July 2022 Location: FAU. Master’s Degree in Computational and Applied Mathematics ECTS: 10 This course at FAU StudON: –
Date: March 10, 2022 (4 weeks) Organized by: Institut Élie Cartan de Lorraine Cycle “Science and Society” Title: Contrôle et apprentissage automatique (Control and Machine Learning) Speaker: Prof. Dr. Enrique Zuazua Affiliation: Affiliation: FAU DCN-AvH, Chair for Dynamics Control and Numerics – Alexander von Humboldt Prof., Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Abstract. La […]
This year, our Head Prof. Enrique Zuazua (Friedrich-Alexander-Universität, Erlangen-Nürnberg) joint with Prof. Xiaoming Yuan (University of Hong Kong) will be talking (M20 – Hong Kong module) about “Machine Learning, Optimization and Control” on June 27th. – July 1st., 2022 at the IEECI-IGSC 2022: International Graduate School on Control 2022 organized […]
Course: Transport Phenomena Lecturers: Enrique Zuazua, Nicola De Nitti Period: 2021/2022 winter semester Date: October 2021 – March 2022 Location: FAU. Master’s Degree in Computational and Applied Mathematics ECTS: 10 This course at FAU StudON: –
Opening the black box of Deep Learning By Sergi Andreu Deep Learning is one of the three main paradigms of Machine Learning, and roughly consists on extracting patterns from data using neural networks. Its impact in modern technologies is huge. However, there is not a clear high-level description of what […]