Johannes Ismair and Daiana Geetan from MaibornWolff will give a talk in the elite program’s special lecture series. The title of the talk is “Web Accessibility 101” and it will take place in room 1055N at 4PM on 19th December 2024.

Abstract

Web Accessibility remains a largely overlooked aspect within projects. The journey to understanding it — navigating through ARIA, various user interfaces such as screen readers, and deciphering the official WCAG guidelines — can often feel daunting. However, drawing from my own experience, I’ve discovered that it’s possible to impart 80% of essential Web Accessibility knowledge swiftly and effectively. This talk aims to demystify the process, making Web Accessibility approachable and achievable for everyone.

Prof. Andreas Kipf from UTN will give a talk in the elite program’s special lecture series. The title of the talk is “What We Learned and What We Will Learn” and it will take place in room 1055N at 4PM on 7th November 2024.

Abstract

In this talk, I will provide an overview of my past, ongoing, and future ML for systems research, starting with my postdoc years at MIT, where I worked on benchmarking learned indexes, learning cardinality estimates, and developing SageDB, an instance-optimized Data Analytics System. I will also talk about my experience at Amazon, discussing my contributions to intelligent scaling in Amazon Redshift and Text2SQL translations. I will shine some light on the characteristics of cloud data warehouse workloads, and will emphasize the potential of (sub) query caching. Finally, I will talk about my ongoing and future research at UTN, where we work on simplifying data loading with LLMs, correlation-aware column compression, and optimizing queries by learning from query history.

Biography

Andreas Kipf is a professor of data systems at the University of Technology Nuremberg (UTN). Previously, he was an applied scientist at AWS and a postdoc researcher in the MIT Data Systems Group where he worked with Prof. Tim Kraska. His research explores applications of AI to build next-gen data systems that are efficient and easy to use. Andreas earned his PhD at TUM where he worked with Prof. Alfons Kemper and Prof. Thomas Neumann. During his PhD, he interned with Google in Mountain View & Zurich to work on query-driven materialization and lightweight secondary indexing. Andreas won the 2016 SIGMOD Best Demonstration Award and the 2017 SIGMOD Programming Contest.

Dr. Johannes Leupolz will give a talk in the elite program’s special lecture series. The title of the talk is “Qualitative and quantitative analysis of safety-critical systems with S#” and it will take place in room 1055N at 10AM on 4th July 2024.

Abstract

Safety-critical systems are expected to operate safely under regular circumstances as well as in many degraded situations. In the latter case, these systems have to cope with one or more components that are not working as specified, while at the same time they have to avoid (serious) economical or environmental damage, injuries, or even loss of lives. S# provides a modeling language specifically designed to express important safety-related concepts such as faults and the physical environment of a safety-critical system. For safety assessments, model simulations as well as formal safety analyses are supported.

Dr. Harald Störrle from QAware will give a talk in the elite program’s special lecture series. The title of the talk is “Wozu gibt es POs?” and it will take place in room 1055N at 4PM on 04 July 2024.

Abstract

In der Industrie werden heute vielfach “agile” Methoden der Softwareentwicklung angewandt. In der akademischen Ausbildung kommen solche Organisationsformen, notwendigerweise, höchstens am Rand vor. Ein besonders obskurer Aspekt dieser Vorgehensweisen ist die Rolle des Product Owners (PO). Gleichzeitig ist diese Rolle, nach meiner Erfahrung, entscheidend für den Erfolg eines Projektteams, und oft auch der entscheidende Faktor für den Erfolg eines Produktes insgesamt.

Ich berichte aus meiner langjährigen Praxis in der industriellen (und akademischen!) Herstellung von Software, insbesondere mit Scrum und SAFe, reflektiere über agile und andere Vorgehensweisen, ihre Stärken und Schwächen, und insbesondere die PO-Rolle: was macht man als PO, wie wird man PO, und was kommt danach?

Marc Zeller from Siemens will give a talk in the elite program’s special lecture series. The title of the talk is “Absicherung autonomer Systeme – Erfahrungen am Bespiel eines fahrerlosen Regionalzugs im Projekt safe.trAIn” and it will take place in room 1055N at 4PM on 16 May 2024.

Abstract

Dieser Vortrag präsentiert die bis dato gewonnen Erkenntnisse im öffentlich geförderten Projekt safe.trAIn (www.safetrain-projekt.de). In diesem arbeitet Konsortium aus 16 Partnern unter Beteiligung der Bahnindustrie, Technologiezuliefern, Forschungseinrichtungen sowie Normungs- und Prüforganisationen in einem gemeinschaftlichen Vorhaben, um die Möglichkeiten von KI mit den Sicherheitsbetrachtungen des Schienenverkehrs zu verbinden und eine Lösung am Beispiel des fahrerlosen Regionalzugs praktikabel umzusetzen. Im Rahmen des Vortrags wird das Projekt safe.trAIn eingeführt, die Architektur, inkl. der Quellen für Uncertainty, diskutiert und das im Projekt erarbeitete Konzept der Sicherheitsnachweisführung inkl. Validierungsplan vorgestellt.

The application period for the 2024 intake will start in March. The application deadline is 1 May 2024. The link to the application system will bei published on our Application page.

Der Elitestudiengang Software Engineering bietet im Januar und Februar Informationsveranstaltungen an den beteiligten Universitäten an:

• Universität Augsburg: 23.01.2024 ab 17:15 Uhr (Raum 3017N)
• Ludwig-Maximilians-Universität München: 5.2.2024 ab 17:00 Uhr
• Technische Universität München: 8.2.2024 ab 17:20 Uhr

Hierbei werden wir die Details des Studiengangs und des Bewerbungsverfahrens vorstellen und die Vorteile und Besonderheiten des Studiengangs darstellen.

Der Masterstudiengang Software Engineering bietet ein deutschlandweit einmaliges Ausbildungsprogramm und qualifiziert bestens für herausfordernde Tätigkeiten in Praxis und Wissenschaft.

Annika Madejska and Karola Klarl from Nitor will give a talk in the elite program’s special lecture series. The title of the talk is “Just because we can – it doesn’t mean we should” and it will take place as an online meeting at 4PM on 25 January 2024.

Abstract

Why we need to care about ethics in tech and how we can bring ethical thinking into the development process

With the recent big leaps in AI capabilities, it is becoming evident that a future that many thought were at least 20 years away – in fact is here.

This has raised voices of concern, and regulators are suddenly troubled about the safety of emerging technologies and their use.

But ethicists and ethical practitioners in the field of technology have been troubled about the intrusion of privacy, violations of copyright and manipulative applications for years.

This talk will open up this ethical can of worms that currently exists within tech, why we as employees or researchers in the field of computer science need to care about it – and what we can do to build a better foundation for future technology.

Biography

Annika Madejska is a Senior UX-designer at Nitor. She holds a Master of Science in Informatics with a specialization in Digital Design. She has also studied Behavioral Sciences and the Ethics of AI, and before she started working in the tech business she had a 16 year long career as a Visual Journalist at newspapers in Sweden and Finland. She has worked as a designer for companies within e-commerce, postal services and health tech. Her latest assignment was for a software company that provides deep-learning based image analysis AI models for microscopy images.

Karola Klarl is an Enterprise Coach / Agile Coach at Nitor. She studied in the Elite Program Software Engineering from 2014-2016 before working at Allianz and BMW in different agile roles. In 2023 she moved to Stockholm, Sweden and started working as Enterprise Coach / Agile Coach at Nitor.

Dr. Lucas Braun from Oracle Labs will give a talk in the elite program’s special lecture series. The title of the talk is “JavaScript and Databases: a Perfect Match” and it will take place as an online meeting at 3PM on 13 December 2023.

Abstract

Oracle 23c just released with in-database JavaScript application programming, powered by GraalVM. JavaScript boosts developer productivity because of its popularity and availability of open-source code.

But what does it take to make a JavaScript runtime (GraalVM) work (efficiently!) in a complex system like a database (Oracle) and scale to thousands of users?

This talk will not only answer this question, but also show JavaScript application development live in the database.

Join us in this talk, given by Dr. Lucas Braun who is working with the Oracle Labs team in Zurich, Switzerland. Oracle Zurich is where the major bits of Oracle Database Multilingual Engine (for JavaScript) and Property Graphs, MySQL Heatwave, Oracle Graph Studio, Oracle Cloud Autonomous Dependency Management and generative AI components, as well as many other flagship Oracle products are being developed. Besides the main part of the talk, you will also get a short glimpse into all of these topics as well as learn about Oracle Labs’ internship program.

Dr. Cornel Klein from Siemens will give a talk in the elite program’s special lecture series. The title of the talk is “safe.trAIn – Engineering and Assurance of a Driverless Regional Train” and it will take place in room 1055N at 4PM on 16 November 2023.

Abstract

With the introduction of highly automated train operation (Grade of Automation (GoA) 4 operation) a significant performance increase of railway systems can be achieved. This includes the enhancement of the transport capacity in existing tracks, energy savings by means of an optimized driving strategy, reduced mechanical wear and tear as well as increased passenger comfort by means of homogeneous driving, and increased flexibility for demand-oriented train services. Traditional automation technologies alone are not sufficient to enable the fully automated operation of trains. However, Artificial Intelligence (AI) and Machine Learning (ML) offers great potential to realize the mandatory novel functions to replace the tasks of a human train driver, such as obstacle detection on the tracks. The problem, which still remains unresolved, is to find a practical way to link AI/ML methodologies with the requirements and approval processes that are applied in the railway domain. The safe.trAIn project (2022 – 2024) aims to lay the foundation for safe use of AI/ML for the driverless operation of rail vehicles and to thus addresses this key technological challenge hindering the adoption of unmanned rail transport. Within the project, which is funded by the German government, there is a budget of €23 million available for this task.

The project goals are to perform integrated development of guidelines and methods for the safety assurance of artificial intelligent in highly automated train operation. Based on the requirements for the certification process in the railway domain, safe.trAIn creates a safety argumentation for an AI-based obstacle detection function of a driverless regional train. Therefore, the project investigates methods to prove trustworthiness of AI-based functions taking robustness, performance, uncertainty, transparency, and out-of-distribution aspects of the AI/ML model into account. These methods are integrated into a comprehensive and continuous testing and verification process for trains. Moreover, a GoA 4 train architecture incorporating safe, AI-based functions for automated train operation is defined and assessed in terms of safety. The feasibility of the guidelines and methods developed in safe.trAIn is evaluated with a real case study in which an exemplary safety case for a driverless regional train is created and assessed by auditors. Safe.trAIn builds on the results from the latest research and development activities (e.g., Shift2Rail, BerDiBa, ATO-Sense and ATO-Risk, and KI-Absicherung (“AI safeguarding”) and will continue the development of those activities in line with the new requirements.

The participating project partners are from the railway domain, academia, standardization bodies, and safety assessment bodies. The industrial partners will use the project’s outcomes to launch automation solutions in the market that enable highly automated and driverless operation of rail vehicles. In addition, relevant results from the safe.trAIn project will be integrated into standardization activities in the areas of safe and trustworthy AI and rail transportation.