BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//WordPress - MECv7.33.0//EN
X-ORIGINAL-URL:https://dcn.nat.fau.eu/
X-WR-CALNAME:
X-WR-CALDESC:FAU DCN-AvH. Chair for Dynamics, Control, Machine Learning and Numerics -Alexander von Humboldt Professorship
X-WR-TIMEZONE:Europe/Berlin
BEGIN:VTIMEZONE
TZID:Europe/Berlin
X-LIC-LOCATION:Europe/Berlin
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T030000
RRULE:FREQ=YEARLY;BYMONTH=03;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=4SU
END:STANDARD
END:VTIMEZONE
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-PUBLISHED-TTL:PT1H
X-MS-OLK-FORCEINSPECTOROPEN:TRUE
BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-66b0cd925d80e64555a2babbb2ccddc2@dcn.nat.fau.eu
DTSTART;TZID=Europe/Berlin:20250721T090000
DTEND;TZID=Europe/Berlin:20250723T110000
DTSTAMP:20250624T133841Z
CREATED:20250624
LAST-MODIFIED:20250720
PRIORITY:5
SEQUENCE:10
TRANSP:OPAQUE
SUMMARY:JLU Short course: PDEs Meet Machine Learning: Integrating Numerics, Control, and Machine Learning by E. Zuazua
DESCRIPTION:Event: JLU Short-course\nDate: Mon.-Tue. July 21-23, 2025 \nTitle: PDEs Meet Machine Learning: Integrating Numerics, Control, and Machine Learning\nSpeaker: Prof. Enrique Zuazua. FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)\nWatch a short on YouTube\nAbstract.  Partial Differential Equations (PDEs) form the cornerstone of mathematical modeling in mechanics and the natural sciences, driving advances in analysis, numerical methods, and applied mathematics. Today, the rise of Machine Learning (ML) and Artificial Intelligence (AI) presents transformative opportunities and challenges for classical PDE methodologies. Can ML enhance PDE techniques without sacrificing mathematical rigor? Can we develop hybrid computational frameworks that leverage data-driven approaches while maintaining the reliability of traditional methods?\nThis course explores these questions through an interdisciplinary lens, bridging PDE theory, control, and ML. We examine the intrinsic connections between representation, optimization, and control theory—rooted in cybernetics (from Ampère to Wiener) and historically motivated by the quest to design intelligent machines. Interestingly, the goals of control theory align closely with those of modern AI, emphasizing mathematics’ unifying power in modeling and innovation.\nWe discuss recent work addressing two key challenges: Why does ML generalize so effectively? and How can data-driven insights be rigorously integrated into classical applied mathematics, particularly for PDEs and numerical methods? This exploration is shaping a new paradigm of PDE+D(ata), to forge the next generation of computational tools.\nWHEN\nFrom Mon.-Tue. July 21 – 23, 2025 at 09:00H – 11:00H (local time)\nWHERE\nOn-site / Online\n[On-site] JLU\nZhengxin building, 209 (2th Floor)\nJilin University, No. 2699, Qianjin Street, Changchun City, Jilin Province\n[Online] Zoom: ID: 904 645 6677 |  Password: 2025\nWatch a short on YouTube\n
URL:https://dcn.nat.fau.eu/events/jlu-course-pdes-meet-ml-ezuazua-july2025/
ORGANIZER;CN=JLU, Jilin University:MAILTO:
CATEGORIES:EZuazua,Seminar/Talk,Workshop
ATTACH;FMTTYPE=image/png:https://dcn.nat.fau.eu/wp-content/uploads/JLUcourse_EZuazua_21-23jul2025.png
END:VEVENT
END:VCALENDAR