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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>
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					<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>EZ 65: Control, PDEs and Machine Learning</title>
		<link>https://dcn.nat.fau.eu/ez65-control-pdes-and-ml/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 12 May 2026 03:13:09 +0000</pubDate>
				<category><![CDATA[EZuazua]]></category>
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					<description><![CDATA[Date: Mon.- Thu. June 08 &#8211; 11, 2026 Event: A conference in honour of Enrique Zuazua on the occasion of his 65th birthday Title: EZ 65: Control, PDEs and Machine Learning We are pleased to announce the conference &#8220;Control, PDEs and Machine Learning&#8221;, to be held at the University of Deusto in Bilbao from 8 [&#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>Mon, 11 May 2026 18:13:22 +0000</pubDate>
				<category><![CDATA[Akademy]]></category>
		<category><![CDATA[Akademy Enrique Zuazua]]></category>
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					<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) Registration form (on-site participation only): dcn.nat.fau.eu/registration-mlpdes26 Next Spring, our FAU MoD, Research Center for Mathematics of Data is hosting the [&#8230;]]]></description>
		
		
		
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		<title>International Congress of Pure and Applied Mathematics in the Modern Era</title>
		<link>https://dcn.nat.fau.eu/cerseu-fcm-unmsm-congress-april-2026/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 28 Apr 2026 15:39:13 +0000</pubDate>
				<category><![CDATA[EZuazua]]></category>
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					<description><![CDATA[Date: April 2, 2026 Event: Congreso Internacional de Matemática Pura y Aplicada en la Era Moderna: Avances, Retos y Aplicaciones en el Mundo Contemporáneo (International Congress of Pure and Applied Mathematics in the Modern Era) Organizer: CERSEU-FCM-UNMSM. National University of San Marcos (UNMSM) Lecture: Machine Learning, Control Theory and PDEs Speaker: Prof. Enrique Zuazua, FAU [&#8230;]]]></description>
		
		
		
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		<title>BNU &#8211; Control and Machine Learning: A Mathematical Journey</title>
		<link>https://dcn.nat.fau.eu/bnu-control-and-machine-learning-a-mathematical-journey/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 20 Mar 2026 13:56:53 +0000</pubDate>
				<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Events]]></category>
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					<description><![CDATA[Event: Beijing Normal University Mathematics Forum Date: Thu. March 19, 2026 Organizer: Beijing Normal University Lecture: Control and Machine Learning: A Mathematical Journey Speaker: Prof. Enrique Zuazua, FAU &#8211; Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) &#160; Enrique Zuazua Explores the Intersection of Control Theory and AI at Beijing Normal University On March 19, 2026, Prof. Enrique Zuazua presented [&#8230;]]]></description>
		
		
		
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		<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>
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		<category><![CDATA[EZuazua Events]]></category>
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					<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>Enrique Zuazua invited to deliver a Special Section Lecture at ICM 2026</title>
		<link>https://dcn.nat.fau.eu/icm2026-enrique-zuazua-lecture/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 20 Feb 2026 20:02:34 +0000</pubDate>
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					<description><![CDATA[Date: July 23 – 30, 2026 Event: ICM 2026. Philadelphia, Pennsylvania (USA) Lecture: Machine Learning and Control: Foundations, Advances, and Perspectives Speaker: Prof. Enrique Zuazua, FAU &#8211; Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Enrique Zuazua honored with a prestigious speaker invitation to deliver a Special Section Lecture on Control Theory at the International Congress of Mathematicians 2026 (ICM 2026) [&#8230;]]]></description>
		
		
		
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		<title>Trends in Mathematical Sciences II (2026)</title>
		<link>https://dcn.nat.fau.eu/trendsinmaths2026/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Thu, 05 Feb 2026 04:05:25 +0000</pubDate>
				<category><![CDATA[EZuazua]]></category>
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					<description><![CDATA[From February 5 &#8211; 7, 2026, the Instituto de Ciências Matemáticas e de Computação (ICMC) partnership with BAYLAT and the São Paulo Research Foundation (FAPESP) is pleased to announce the upcoming &#8220;Trends in Mathematical Sciences II&#8221; conference. This event will be held in São Carlos, Brazil. The Trends in Mathematical Sciences&#8217; primary objective is to establish [&#8230;]]]></description>
		
		
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		<title>Benasque XI Workshop-Summer School 2026: Partial differential equations, optimal design and numerics</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>
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					<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) Registration: https://benasque.org/2026pde/cgi-bin/appl.pl Deadline for applications: Wed. June 10, 2026 Next Summer, on August 23 &#8211; September 04, 2026 will be held the XI Partial Differential Equations, Optimization, Numerics, [&#8230;]]]></description>
		
		
		
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		<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[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
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					<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 Large Language Models (LLMs) are increasingly used in autonomous systems but face challenges in long-term reasoning, coordination, and scalability. This thesis introduces a hybrid, modular Multi-Agent [&#8230;]]]></description>
		
		
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