November 2024 - informatik-vortraege

Einladung Informatik Oberseminar Lubna Ali
by Bombelka, Angelika 28 Feb '25

28 Feb '25

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Dienstag, 30. Januar 2024, 14.00 Uhr Ort: 9222, E3, Ahornstr. 55 und hybrid via Zoom (https://rwth.zoom-x.de/j/64937773189?pwd=eGttNUMzSElnQUVkc3FrYzBqK2F4UT09) Referent: Lubna Ali M.Sc. RWTH Lehr- und Forschungsgebiet Informatik 9 (Lerntechnologien) Thema: convOERter: A Technical Assistance Tool to Support Semi-Automatic Conversion of Images in Educational Materials as OER Abstract: Open Educational Resources (OER) are seen as an important element in the process of digitizing higher education teaching and as essential building blocks for openness in education. They can be defined as teaching, learning, and research materials that have been made openly available, shareable, and modifiable. OER include different types of resources such as full courses, textbooks, videos, presentations, tests, and images, which are usually published under the open Creative Commons licences. OER can play an important role in improving education by facilitating access to high quality digital educational materials. Accordingly, there is a steady increase among higher education institutions to participate in the so-called "open movement" in general and in utilizing OER in particular. Nevertheless, there are many challenges that still face the deployment of OER in the educational context. One of the main challenges is the production of new OER materials and converting already existing materials into OER, which could be viable by qualifying educators through training courses and/or supporting them with specific tools. There are many platforms and tools that support the creation of new OER content. However, to our knowledge, there are no tools that perform fully- or semi-automatic conversion of already existing educational materials. This identified gap was the basis for the design and implementation of the OER conversion tool (convOERter). The tool supports the user by semi-automatically converting educational materials containing images into OER-compliant materials. The main functionality of the tool is based on reading a file, extracting all images as well as all possible metadata, and substituting the extracted images with OER elements in a semi-automated way. The retrieved OER images are referenced and licenced properly according to the known TASLL rule. Finally, the entire file is automatically licenced under Creative Commons excluding specific elements from the entire licence such as logos. In order to evaluate the effectiveness of the tool in promoting the use of OER, a comprehensive user study was conducted with educators and OER enthusiastic at different universities. The study was accomplished by offering a series of OER evaluation workshops to compare the conversion efficiency of the tool with manual conversion. The results show that using the conversion tool improves the conversion process in terms of speed, license quality, and total efficiency. These results highlight that the tool can be a valuable addition to the community, especially for users less experienced with OER. As a future work, it is intended to further develop the tool and improve its functionality. Additionally, a long-term study can be conducted to assess the impact of the tool in facilitating and enhancing the production of OER on a larger scale. Es laden ein: die Dozentinnen und Dozenten der Informatik

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Einladung: Informatik-Oberseminar Alexander
by DSME-Office 29 Nov '24

29 Nov '24

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Dienstag, 3. Dezember 2024, 12.00 Uhr Ort: Technologiezentrum Aachen, Seminarraum Halle F1 Referent: Alexander von Rohr M.Sc. Institut für Data Science im Maschinenbau (DSME) Thema: Probabilistic Optimization for the Control of Dynamical Systems Abstract: Controlling dynamical systems is a key aspect of automation technology. However, designing resource-efficient controllers for each system is challenging and costly. Machine learning can help automate this process, but learning-based control requires data-efficient and robust methods. We frame learning-based control as a probabilistic optimization problem, proposing novel methods for decision-making under uncertainty and learning-based control algorithms with formal guarantees. First, we address controller tuning using Bayesian optimization to efficiently improve candidate controllers, validated on synthetic problems, simulations, and hardware experiments. Second, we propose three probabilistically robust control methods for uncertain, data-driven models, addressing probabilistic stability, aleatoric uncertainty, and event-triggered learning for time-varying dynamics. Es laden ein: die Dozentinnen und Dozenten der Informatik

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Einladung: Informatik-Oberseminar Herr Mohamed Behery
by Maaßen, Leany 22 Nov '24

22 Nov '24

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Donnerstag, 05.12.2024, 13:30-14:30 Der öffentliche Vortrag findet hybrid statt: Raum: Raum 5053.2 (B-IT-Hörsaal)/Informatikzentrum, Ahornstraße 55 Zoom: https://rwth.zoom-x.de/j/64360669610 Referent: Herr Mohamed Behery, M. Sc. LuFG Informatik 5 (KBSG) Thema: Digital Shadows for Industrial Robotic Agents in the World Wide Lab Abstract: The digital transformation of production has become imperative to increase efficiency, adaptability, and innovation required to face the rapidly changing market requirements, supply chain disruptions, and global competition. In addition to initiatives such as Industry 4.0 and the Industrial Internet of Things (IIoT), the Internet of Production (IoP) aims to establish a world-wide network of research and industrial partners through the World Wide Lab (WWL). Such a network requires standardized communication protocols, which need to remain flexible to accommodate the different standards, use cases, and contexts. To this end, the WWL uses Digital Shadows (DSs) to represent the different entities: parts, products, machines, processes, and companies. DSs are context and purpose-specific representations of entities in the WWL, which enables them to replace the omnipresent Digital Twins by representing different aspects of the denoted entities. The thesis offers a road map for achieving the WWL as an application on top of the IoP. The thesis focuses on industrial robotics processes, which involve teleoperated robots or human-robot collaborative assembly and are not fully integrated in the WWL as they lack a standard DS for task representation. To bridge this gap, the thesis proposes using Behavior Trees (BTs), which offer a flexible, modular, and composable task representation for industrial robotics processes. BTs emerged in the video game industry and were adopted by the roboticists but do not yet fulfil all the requirements to be a standard DS. The presented work offers a plan to fulfill these requirements. The thesis introduces a framework for extracting and creating DSs for robot teleoperation tasks in industrial processes. It starts by collecting data to extract discrete actions. After that, it learns a library of BTs that represent the commonly executed behaviors. This allows a user to compose more complex behaviors using the learned BTs. The different modules of the framework are evaluated qualitatively and quantitatively. The thesis also proposes and demonstrates three BT extensions increasing BT flexibility to accommodate more use cases. They allow a BT to handle highly dynamic production environments, where it interacts with heterogeneous agents such as humans or robots with different capabilities or knowledge. The dissertation concludes with a discussion that evaluates the applicability of the proposed framework and extensions to different industrial scenarios giving recommendations for future work. Es laden ein: die Dozentinnen und Dozenten der Informatik _______________________________ Leany Maaßen RWTH Aachen University Lehrstuhl Informatik 5, LuFG Informatik 5 Prof. Dr. Stefan Decker, Prof. Dr. Matthias Jarke, Prof. Gerhard Lakemeyer Ph.D., JunProf. Dr. Sandra Geisler Ahornstrasse 55 D-52074 Aachen Tel: 0241-80-21509 Fax: 0241-80-22321 E-Mail: maassen(a)dbis.rwth-aachen.de

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Einladung Informatik-Oberseminar Dr. Till Hofmann, 27. November 2024,
by Stephanie Jansen 21 Nov '24

21 Nov '24

********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * *********************************************************************** Zeit: Mittwoch, 27. November 2024, 13:00 Uhr Ort: Raum 9222, E3, Informatikzentrum Referent: Dr. Till Hofmann; Lehrstuhl Informatik 6 Thema: Uncertainty in Robotics Abstract: Robotic systems must navigate a world full of unpredictability, facing challenges from dynamic environments, noisy sensors, and imperfect actuators. A robot’s environment is constantly changing, influenced by interactions with other robots and humans. Sensors, with their inherent limitations and noise, provide only an imperfect view of the world. Finally, actuators—susceptible to noise, wear, and mechanical failure—introduce further uncertainty, complicating the robot’s ability to execute precise actions. In this lecture, I will discuss how these challenges can be addressed through probabilistic robotics, where uncertainty is explicitly represented using probability distributions to describe the robot's estimated state of the world. I will first explore how fundamental robotics tasks—such as localization, mapping, and control—are inherently uncertain and demonstrate the benefits of probabilistic methods. In the second part, I will introduce Bayes filters, a general algorithm for belief computation that serves as the theoretical foundation for many robotics algorithms. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Stephanie Jansen Faculty of Mathematics, Computer Science and Natural Sciences Chair of Computer Science 6 ML - Machine Learning and Reasoning RWTH Aachen University Theaterstraße 35-39 D-52062 Aachen Tel: +49 241 80-21601 sek(a)ml.rwth-aachen.de www.hltpr.rwth-aachen.de

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Einladung: Informatik-Kolloquium Nitesh Goyal (Google)
by Martin Henze 20 Nov '24

20 Nov '24

+********************************************************************** * * * Einladung * * * * Informatik-Kolloquium * * * +********************************************************************** Zeit: Mittwoch, 27. November 2024, 10.30 Uhr Ort: AH V, Ahornstr. 55 Referent: Nitesh Goyal, PhD Google, New York Thema: Leveraging AI Responsibly in Sensemaking for Successful Human-AI Workflows Abstract: My research vision is to enable expert and non-experts to successfully make sense of complex world problems. As a Human-Computer Interaction researcher, I iteratively focus on studying how sensemaking is performed to identify challenges in collaborative data analytics, design tools using computational techniques that overcome these challenges and evaluate my designs using human participants to inform subsequent designs. In particular, I have focussed on three domains: criminal justice, ML Development and Online Harassment. Solving crimes correctly is a critical and life-altering problem where intelligence analysts are constantly struggling against their biases. ML engineering and development requires constantly struggling with fairness and equity issues related to datasets and algorithmic outcomes. Managing online harassment requires emotional and physical labor by targets of harassment while making sense of who is harassing them and why? There are many similarities across these 3 domains and despite, recurring themes of how AI should be designed responsibly to support these use cases/users, we have barely started to scratch the surface. In this talk, I introduce the notion of Sensemaking Translucence into biases, fairness and equity related challenges. I then provide examples of how AI can support Sensemaking Translucence. My work finally makes the case that it is important to design from a human centered perspective by leveraging AI to support these Human AI Collaboration workflows. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Prof. Dr. Martin Henze Security and Privacy in Industrial Cooperation (SPICe) RWTH Aachen University Im Süsterfeld 9 52072 Aachen, Germany henze(a)spice.rwth-aachen.de https://www.spice.rwth-aachen.de/

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Einladung Informatik-Oberseminar Tim Seppelt
by Tim Seppelt 07 Nov '24

07 Nov '24

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 29. November 2024, 11.00 Uhr Ort: Raum 9222, Gebäude E3, Informatik-Zentrum Referent: Tim Seppelt, MASt Lehrstuhl Informatik 7 Thema: Homomorphism Indistinguishability Abstract: Two graphs/G/ and/H/ are homomorphism indistinguishable over a class of graphs 𝓕 if, for all graphs/F/ ∊ 𝓕, the number of homomorphisms from/F/ to/G/ is equal to the number of homomorphisms from/F/ to/H/. In 1967, Lovász showed that two graphs are isomorphic if, and only if, they are homomorphism indistinguishable over the class of all graphs. Subsequently, many graph isomorphism relaxations such as quantum isomorphism, spectral, and logical equivalences have been characterised as homomorphism indistinguishability relations over certain graph classes. Thereby, homomorphism indistinguishability connects seemingly disparate fields such as quantum information, finite model theory, and machine learning. This thesis explores three themes: We first review the plenitude of *characterisations* of graph isomorphism relaxations as a homomorphism indistinguishability relation. Focusing on integer programming relaxations for graph isomorphism, we prove that the feasibility of each level of the Sherali–Adams and Lasserre hierarchies is characterised as homomorphism indistinguishability relations. These results, which are derived using (bi)labelled graphs and homomorphism tensors, shed light on the distinguishing power of these hierarchies. In particular, we determine the precise number of Sherali–Adams levels necessary such that their feasibility guarantees the feasibility of a given Lasserre level. Abstracting from the wealth of homomorphism indistinguishability characterisations, we embark on a more principled study of homomorphism indistinguishability investigating the distinguishing power and the complexity of homomorphism indistinguishability relations over minor-closed graph class. The homomorphism distinguishing*closure* cl(𝓕) of a graph class 𝓕 is the central notion for studying the distinguishing power of homomorphism indistinguishability relations. It is defined as the maximal graph class whose homomorphism indistinguishability relation coincides with the one of 𝓕. Roberson conjectured that every minor-closed union-closed graph class 𝓕 is homomorphism distinguishing closed, i.e. cl(𝓕) = 𝓕. We confirm Roberson's conjecture, which is generally wide open, for further graphs classes and prove unconditionally that if 𝓕 is minor-closed then so is cl(𝓕). Lastly, we investigate the*complexity* of deciding whether two graphs are homomorphism indistinguishable over a fixed graph class. For infinite graph classes, this problem is a priori not even decidable. In stark contrast to this, we show that, over every minor-closed graph class of bounded treewidth, homomorphism indistinguishability can be decided in randomised polynomial time. Es laden ein: die Dozentinnen und Dozenten der Informatik

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