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	<title>EZuazua Akademy &#8211; FAU DCN-AvH</title>
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	<description>Chair for Dynamics, Control, Machine Learning and Numerics -Alexander von Humboldt Professorship</description>
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	<title>EZuazua Akademy &#8211; FAU DCN-AvH</title>
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		<title>PhD Thesis defense by Z. Wang</title>
		<link>https://dcn.nat.fau.eu/phd-thesis-defense-by-z-wang/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Wed, 14 Oct 2026 10:32:16 +0000</pubDate>
				<category><![CDATA[2026-resources]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
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		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=33766</guid>

					<description><![CDATA[This year our team member Ziqi Wang will present his PhD Thesis on: &#8220;Federated Learning under Heterogeneity: Efficiency, Fairness, and Safety&#8221; Advisor: • Prof. Enrique Zuazua, FAU &#8211; Friedrich Alexander-Universität Erlangen-Nürnberg (Germany) Abstract. Machine learning has become central to modern science and technology, and its performance depends heavily on diverse training datasets. However, such data [&#8230;]]]></description>
		
		
		
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		<title>PhD Thesis defense by A. Alcalde</title>
		<link>https://dcn.nat.fau.eu/phd-thesis-defense-by-a-alcalde/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 17:30:16 +0000</pubDate>
				<category><![CDATA[2026-resources]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=33747</guid>

					<description><![CDATA[Next Monday November 30, 2026 our team member Albert Alcalde will present his PhD Thesis on: &#8220;A Dynamical Perspective on Transformers, with Applications to Data-Driven Modeling&#8221; Advisors: • Prof. Giovanni Fantuzzi, FAU &#8211; Friedrich Alexander-Universität Erlangen-Nürnberg (Germany) • Prof. Enrique Zuazua, FAU &#8211; Friedrich Alexander-Universität Erlangen-Nürnberg (Germany) Abstract. Transformers form a central class of architectures [&#8230;]]]></description>
		
		
		
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		<title>PhD Thesis defense by A. Alvarez-Lopez</title>
		<link>https://dcn.nat.fau.eu/phd-thesis-defense-by-a-alvarez-lopez/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 29 Jun 2026 17:33:28 +0000</pubDate>
				<category><![CDATA[2026-resources]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=33046</guid>

					<description><![CDATA[Next Wednesday July 1, 2026 our team member Antonio Álvarez-López will present his PhD Thesis on: &#8220;Deep Learning with Controlled Flows: Expressivity, Generalization and Generation&#8221; Advisors: • Prof. Enrique Zuazua, FAU &#8211; Friedrich Alexander-Universität Erlangen-Nürnberg (Germany) • Prof. Rafael Orive, Autonomous University of Madrid (UAM) Abstract. This thesis studies deep learning from the perspective of [&#8230;]]]></description>
		
		
		
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		<title>MLPDES26, Machine Learning and PDEs Workshop (2026)</title>
		<link>https://dcn.nat.fau.eu/mlpdes26/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 16 Jun 2026 11:13:22 +0000</pubDate>
				<category><![CDATA[Akademy]]></category>
		<category><![CDATA[Akademy Enrique Zuazua]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[EZuazua Events]]></category>
		<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32265</guid>

					<description><![CDATA[Date: Mon.-Wed. June 22 &#8211; 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) #MLPDES26 Book of Abstracts *Recordings available at: https://mod.fau.eu/mlpdes26/ This Spring, our FAU MoD, Research Center for Mathematics of Data is [&#8230;]]]></description>
		
		
		
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		<title>Synthetic profile generation for energy system planning using Artificial Intelligence</title>
		<link>https://dcn.nat.fau.eu/synthetic-profile-generation-for-energy-system-planning-using-artificial-intelligence/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 01 Jun 2026 19:58:04 +0000</pubDate>
				<category><![CDATA[2023-resources]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32933</guid>

					<description><![CDATA[Master Thesis: &#8220;Synthetic profile generation for energy system planning using Artificial Intelligence&#8221; Author: Aniruddha Maiti Supervisors: Prof. Enrique Zuazua, Zhengping Ji Date: June, 2026 Rapid urbanization and population growth have led to a significant increase in energy consumption, especially in densely populated metropolitan areas. Simultaneously, the European Union and Germany have set ambitious goals to [&#8230;]]]></description>
		
		
		
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		<title>Robust Creep Control Algorithm with motion shaping and tracking for passenger vehicles</title>
		<link>https://dcn.nat.fau.eu/robust-creep-control-algorithm-with-motion-shaping-and-tracking-for-passenger-vehicles/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 01 Jun 2026 03:13:51 +0000</pubDate>
				<category><![CDATA[2023-resources]]></category>
		<category><![CDATA[Akademy]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32990</guid>

					<description><![CDATA[Master Thesis: &#8220;Robust Creep Control Algorithm with motion shaping and tracking for passenger vehicles&#8221; Author: Dante Amor Supervisors: Prof. Enrique Zuazua, Zhengping Ji Date: May, 2026 This thesis aims to provide a new architecture that provides torque commands to control the vehicle, not only reaching a target velocity, but by shaping the full trajectory of [&#8230;]]]></description>
		
		
		
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		<item>
		<title>Course: Introduction to Control and Machine Learning</title>
		<link>https://dcn.nat.fau.eu/course-introduction-to-control-and-machine-learning/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 10 Mar 2026 22:55:33 +0000</pubDate>
				<category><![CDATA[Akademy]]></category>
		<category><![CDATA[Akademy Enrique Zuazua]]></category>
		<category><![CDATA[Akademy Martin Hernandez]]></category>
		<category><![CDATA[Akademy Yongcun Song]]></category>
		<category><![CDATA[Akademy Zhenping Ji]]></category>
		<category><![CDATA[Akademy Ziqi Wang]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[EZuazua Events]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32471</guid>

					<description><![CDATA[Introduction to Control and Machine Learning Master Course – FAU, Friedrich-Alexander-Universität Erlangen–Nürnberg This course explores the deep connections between control theory, dynamical systems, and modern machine learning, highlighting how mathematical tools developed for the analysis of differential equations can help understand and design modern AI systems. Course Overview The course introduces the mathematical foundations of [&#8230;]]]></description>
		
		
		
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		<title>Benasque XI Workshop-Summer School 2026</title>
		<link>https://dcn.nat.fau.eu/benasque-xi-2026/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 13 Jan 2026 12:13:55 +0000</pubDate>
				<category><![CDATA[Akademy]]></category>
		<category><![CDATA[Akademy Enrique Zuazua]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[EZuazua Events]]></category>
		<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32129</guid>

					<description><![CDATA[Event: Benasque XI Workshop-Summer School 2026: XI Partial Differential Equations, Optimization, Numerics, and Machine Learning Date: Sun.-Fri. August 23 &#8211; September 04, 2026 Event type: On-site (Benasque) The Benasque XI Workshop on Partial Differential Equations, Optimization, Numerics, and Machine Learning has come to an end after two intense and rewarding weeks. The event brought together [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Development of a Modular Multi-Agent System Architecture for Enhanced Flexibility and Scalability</title>
		<link>https://dcn.nat.fau.eu/development-of-a-modular-multi-agent-system-architecture-for-enhanced-flexibility-and-scalability/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Sun, 30 Nov 2025 22:13:06 +0000</pubDate>
				<category><![CDATA[2023-resources]]></category>
		<category><![CDATA[Akademy]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32203</guid>

					<description><![CDATA[Master Thesis: &#8220;Development of a Modular Multi-Agent System Architecture for Enhanced Flexibility and Scalability&#8221; Author: Greshma Shaji Supervisors: Ziqi Wang, Prof. Enrique Zuazua, Prof. Frauke Liers Date: November, 2025 See all details at master thesis: &#8220;Development of a Modular Multi-Agent System Architecture for Enhanced Flexibility and Scalability&#8221;, by Greshma Shaji (November, 2025) Large Language Models [&#8230;]]]></description>
		
		
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			</item>
		<item>
		<title>A workshop in Speinshart: Scientific center for AI and SuperTech</title>
		<link>https://dcn.nat.fau.eu/speinshart-workshop-nov2025/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 28 Nov 2025 11:19:24 +0000</pubDate>
				<category><![CDATA[Akademy]]></category>
		<category><![CDATA[Akademy Enrique Zuazua]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[EZuazua Events]]></category>
		<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=32147</guid>

					<description><![CDATA[Event: A workshop in Speinshart: Scientific center for AI and SuperTech Date: Tue.-Sun. November 11 &#8211; 16, 2025 Event type: On-site From November 11 – 16, 2025, Kloster Speinshart hosted a workshop bringing together researchers, students, and industry professionals to explore the intersections of mathematics, control theory, machine learning, and industrial innovation. The serene monastery [&#8230;]]]></description>
		
		
		
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