20
Jan
Pitchtalk Series • 20.01.2026 • DeepL Offices Munich
4:00 pm - 6:00 pm
MCML Pitchtalks With DeepL
Join Us for Networking and Insights
On January 20th, 4-6pm, MCML visits DeepL at their new Munich Offices for the next Edition of „MCML Pitchtalks with Industry“.
This time, we will have a lot to talk about Research Collaborations between MCML and DeepL, especially with a focus on NLP.
16
Jan
Certificate Course • 16.01.2026 • Online
Call for Applications: Data Science Professional Certificate Program @LMU 2026
Application Deadline: 16.01.2026
The Data Science Certificate Program at LMU Munich, offered in collaboration with MCML, is a graded, part-time academic training program. It is designed for working professionals, researchers, and executives who want to improve their skills in the field of data analytics, statistics, and machine learning. The program is offered twice a year. Apply …
14
Jan
Colloquium • 14.01.2026 • LMU Department of Statistics and via zoom
4:15 pm - 5:45 pm
Achieving Socio-Economic Parity Through the Lens of EU AI Act
Eirini Ntoutsi, UniBW München
This lecture addresses unfair treatment and discrimination as central ethical problems of AI systems and situates them within the context of the EU AI Act, which aims to promote innovation while simultaneously protecting fundamental rights. Although the Act calls for the use of existing fairness concepts, these often neglect socioeconomic status …
12
Jan
Workshop • 12.01.2026 • LMU IEC Space
9:00 am - 5:30 pm
Impact Business Model & Financial Foundations
Essentials Workshop
This Workshop introduces participants to the fundamentals of designing business models using the IEC Business Impact Canvas. They learn how to define the problem–solution fit, articulate a strong value proposition, and understand how value is created, delivered, and captured. Through real examples and hands-on exercises, participants explore key …
08
Jan
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AI Keynote Series • 08.01.2026 • Online via Zoom
5:00 pm - 6:30 pm
Causal Inference With Deep Generative Models
Murat Kocaoglu, Department of Computer Science, Johns Hopkins University
Causal knowledge is central to solving complex decision-making problems in many fields, from engineering and medicine to cyber-physical systems. Causal inference has also recently been identified as a key capability to remedy some of the issues modern machine learning systems suffer from, such as explainability and generalization. In this talk, we …
16
Dec
MCML Stammtisch • 16.12.2025 • Christmas Market at Münchner Freiheit
6:00 pm - 9:00 pm
MCML Stammtisch - December Edition
Join Us for an Evening of Connection and Conversation
We are pleased to invite you to the upcoming MCML Stammtisch, taking place on Tuesday, December 16th, at 6 pm, at the Weihnachtsmarkt am Chinesischen Turm, Englischer Garten 3, 80538 München. If you would like to join, please register here by December 9. We are looking forward to seeing you there and enjoying a festive evening together! If you have …
11
Dec
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Workshop • 11.12.2025 • Technische Universität München Arcisstr. 21 80333 München Raum 4905
3:00 pm - 8:00 pm
MCML Thinkathon: Future of Schools
Translating AI Research Into Teaching Practice
The MCML Thinkathon is dedicated to bridging the gap between cutting-edge research and Bavarian educational practice. Its goal is to translate current insights from AI research into concrete workshop kits for teachers.
10
Dec
Open Lab Day • 10.12.2025 • Boltzmannstraße 1, 85748 Garching
5:30 pm - 7:00 pm
Open Lab Day 2025
Linked Dimensions
At the Open Lab Day 2025 on December 10th at the Center for Virtual Reality and Visualization (V2C) of the Leibniz Rechenzentrum (LRZ), the focus is on the presentation of projects by LMU and TUM students under the motto “Linked Dimensions”. During an internship, the students gained experience in the development of interactive VR applications, such …
10
Dec
Colloquium • 10.12.2025 • LMU Department of Statistics, Room 144, Ludwigstraße 33, 80539 Munich
4:15 pm - 5:45 pm
Program Evaluation With Remotely Sensed Variables
Davide Viviano, Harvard University
Economists often use remote sensing variables (RSVs), such as satellite imagery, to estimate treatment effects in experiments when direct economic measurements are lacking. The usual method of training a predictor based on an observational sample and using its predictions as outcome measures is biased when RSVs themselves are influenced by economic …