TUM Apply
TUM Apply streamlines doctoral candidate recruitment at TUM, providing a unified portal for posting positions, submitting applications, and managing evaluations.A modern application management portal for doctoral positions TUM Apply is a web-based platform designed to simplify and centralize the recruitment process for doctoral candidates at the Technical University of Munich. It replaces fragmented workflows with a single, unified portal where research groups can post open positions, prospective candidates can discover and apply for them, and committees can efficiently manage the evaluation process. A key goal of the project is to attract more women and diverse candidates for dissertation projects at TUM, fostering a more inclusive research environment.
Thesis Management
Thesis Management centralizes the entire thesis lifecycle, from topic discovery and application to writing, presentation, and grading, in a single platform for students, advisors, and supervisors.A centralized platform for managing the complete thesis lifecycle Thesis Management is a web-based system that streamlines the end-to-end thesis process at the Technical University of Munich. It brings together students, advisors, and supervisors on a single platform, replacing manual coordination with structured workflows for every stage, from topic discovery and application through writing, presentation, and final grading. The platform covers the key phases of the thesis lifecycle: students can browse available topics and submit applications with their proposals; advisors manage incoming applications and guide students through the writing process with integrated file management and feedback tools; supervisors oversee presentation scheduling and grading workflows. Role-based access ensures that each participant sees only the information and actions relevant to their responsibilities.
Iris
Iris integrates AI tutoring into Artemis, using LLMs to provide intelligent, context-aware guidance, feedback, and support.An AI-driven virtual tutor for computer science education Iris is an advanced AI-driven virtual tutor integrated into the open-source learning platform Artemis, designed to provide personalized and context-aware support to computer science students as they tackle programming exercises. Leveraging large language models (LLMs), Iris acts as a didactically calibrated tutor: instead of revealing complete solutions, it offers subtle hints and counter-questions to foster independent problem-solving and cognitive development. Additionally, Iris can access lecture content, enabling it to tap into course-specific knowledge for more tailored and relevant responses.
Athena
Athena enables efficient, scalable assessment in large courses by integrating with learning platforms to provide (semi-)automated feedback and grading for programming, modeling, and textual exercises using LLMs and traditional AI.Scalable, AI-powered feedback and assessment Athena is a research project focused on improving assessment and feedback processes in higher education, particularly in large-scale courses. By integrating with existing Learning Management Systems (LMS), Athena enables the (semi-)automated evaluation of student work, reducing manual grading effort while maintaining quality and consistency. The system supports a range of exercise types—including programming tasks, modeling exercises, and textual submissions—and generates formative and summative feedback using a combination of traditional AI techniques and modern large language models (LLMs), depending on the specific assessment approach employed. Its modular architecture allows for flexible integration of new feedback strategies and exercise formats, making it adaptable to evolving educational needs and extensible to additional domains in the future.
