Fruitful scientific interaction between relAI, MDSI and SAP

On January 20, 2026, researchers from relAI, MDSI and our industry partner SAP gathered for a pitchtalk session at the SAP Labs Munich Campus in Garching. In an interactive setup, participants from the three organizations exchanged research insights and explored ideas for future collaborations.

The afternoon opened with short welcome words from representatives of SAP (Dr. Tobias Müller), MDSI (Sylvia Kortüm) and relAI (Dr. Mónica Campillos). The following pitchtalks covered a wide range of topics relevant to AI and Data Science, spanning methodological approaches to practical research resources.

Pitchtalk Session

The talks introduced methodologies and applications across various research fields, from uncertainty modeling to personalized medicine and research data infrastructure.

Max Beier, a relAI PhD student, discussed the advantage of using linear-operator methods in dynamical systems. By focusing on linear operators, his approach supports optimal control, scalable optimization algorithms, and reliable forecasting across time scales ranging from milliseconds to days. He showed that this methodology allows efficient learning of system behavior, modeling of trajectory distributions, and generation of coherent sequences, addressing current limitations in decision‑making models for complex dynamical environments.

Parastoo Pashmchi, an industrial PhD student at SAP, introduced an efficient algorithm to handle missing data, a common challenge in AI projects. She presented an ML‑based imputation method that preserves the original data distribution by sampling from the conditional distribution of nearest neighbors, overcoming the limitations of common techniques like kNNImputer. By enabling uncertainty quantification and multiple imputations, her approach improves the reliability of predictive models such as SAP’s green energy forecasting use case, where missing solar production data can significantly undermine model accuracy.

Mario Picciani, an MDSI PhD student,  highlighted recent developments and applications of ProteomicsDB, a proteomics resource established in 2012 through a collaboration between MDSI Core Member Prof. Bernhard Küster and SAP. ProteomicsDB is a powerful multi‑omics, multi‑organism platform that enables real‑time exploration of proteomic, transcriptomic, and drug‑interaction data across the tree of life, supporting research from basic biology to large‑scale initiatives. With expanding capabilities for analyzing drug mechanisms, predicting cell responses, and supporting precision oncology, the SAP HANA–powered resource could become a central tool for biomarker discovery, systems biology, and personalized medicine.

Sebastian Gallenmüller, an MDSI PhD student, presented SLICES-DE, a digital research infrastructure for computing and communication, embedded within a European collaborative network. As a national digital research infrastructure for ICT, SLICES‑DE offers remote‑accessible testbeds, reproducible workflows, and long‑term data management to support research in areas such as 6G, AI, cybersecurity, and cloud‑edge systems. Built as a community‑driven, flexible, and scalable platform, it enables shared experiments, training, and industry collaboration, providing both academia and companies with a versatile environment that can even be booked for individual lectures or large‑scale projects.

Networking over pretzels and lemonade

An informal networking session after the pitchtalks gave speakers and participants from relAI, MDSI, and SAP the opportunity to connect, exchange impressions, discuss research interests, and explore potential collaborations.

We thank our industry partner SAP for hosting this event and sharing insights into ongoing research projects – we look forward to future editions!

👉 Photo Gallery

We are excited to announce that the call for applications to the PhD program 2026 of our Konrad Zuse School of Excellence in Reliable AI (relAI) is now open!

The novel, innovative PhD relAI program offers a cross-sectional training for successful education in AI including scientific knowledge, professional development courses and industrial exposure, providing a coherent, yet flexible and personalised training.

Funded applicants will receive a full salary for three years, including social benefits (TV-L E13 of the German public sector). They may receive additional support through travel grants for conference attendance, research stays, or home travel. Doctoral students are hosted by a relAI Fellow who helps them to define their research project. Depending on the affiliation of this hosting fellow, they enrol at TUM or LMU.

We highly encourage you to apply if you have: 

  • an excellent master’s degree (or equivalent) in computer science, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines;
  • a genuine interest to work on a topic of reliable AI covering aspects such as safety, security, privacy and responsibility in one relAI’s research areas Mathematical & Algorithmic foundations, Algorithmic Decision-Making, Medicine & Healthcare, Robotics & Interacting Systems, or Learning and Education;
  • certified proficiency in English.

📆 Application Deadline: January 13th, 2026

🔗 Apply now: www.zuseschoolrelai.de/application

Please help us in spreading the word, especially to excellent international candidates.

When we try to help the most vulnerable, and we have limited resources to deploy, should we invest them in building better prediction models, or is it sometimes more effective to simply expand access and help more people, even if the targeting isn´t absolutely perfect?

If you’d like to learn more about it, check out the 👉 podcast!

In this episode of Executive Code, PhD student Unai Fischer Abaigar discusses his paper The Value of Prediction in Identifying the Worst-Off. He explains how governments utilize AI to allocate limited resources—and when it is more effective to enhance predictive models versus simply expanding access to public programs. Using real data from Germany’s employment offices, Unai’s research challenges the assumption that better prediction always means better outcomes in public decision-making.

On October 23, 2025, relAI, the Munich Data Science Institute (MDSI), the Munich Center for Machine Learning (MCML), and the AI Hub@LMU organized the Munich Career Fair AI & Data Science 2025 at TranslaTUM.

The event brought together eleven industry partners and over 150 students across various educational stages, from bachelor’s to doctoral levels. Each partner presented an overview about their activities in AI and data science, highlighting associated career opportunities. Additionally, students had ample time and space for networking and personal interactions at the industry stands in the foyer of TranslaTUM.

We extend our heartfelt thanks to all participants, especially the industry partners, for showcasing potential career paths in AI and Data Science and contributing to the success of the fair. We look forward to seeing all of you at the next edition.

🎉 Congratulations!

We are excited to announce that a team consisting of relAI PhD students Shuo Chen, Bailan He, and Jingpei Wu, along with relAI Fellow Volker Tresp and members of the Torr Vision Group from the University of Oxford and TU Berlin, received the Honorable Mention Award at OpenAI Red-Teaming Challenge on Kaggle.  They ranked among the top 20 teams (Top 3%) out of 5,911 participants and over 600 teams.

The Red Teaming Challenge, initiated by OpenAI, tasked participants with probing its newly released open-weight model, gpt-oss-20b. The objective was to identify previously undetected vulnerabilities and harmful behaviors, such as lying, deceptive alignment, and reward-hacking exploits.

Would you like to learn more about the awarded work?

The write-up of the hackathon and the accompanying paper, “Bag of Tricks for Subverting Reasoning-Based Safety Guardrails,” detail the findings of the study, revealing systemic vulnerabilities in recent reasoning-based safety guardrails like Deliberative Alignment.

👉 Check them out: https://chenxshuo.github.io/bag-of-tricks/

🎉 Congratulations!

We are proud to share that relAI PhD student Yusuf Sale has been honored with one of the IJAR Young Researcher Awards. The prestigious prize, funded by the International Journal of Approximate Reasoning (IJAR), recognizes students who demonstrate excellence in research at an early stage of their scientific careers.  

Yusuf received the award at ISIPTA 25, the 14th International Symposium on Imprecise Probabilities: Theories and Applications, organized by ISIPTA, the leading international forum for theories and applications of imprecise probabilities.   

🎉 Congratulations!

We are thrilled to announce that the paper The Value of Prediction in Identifying the Worst-Off co-authored by relAI PhD student Unai Fischer Abaigar, relAI Fellow Christoph Kern, and Juan Carlos Perdomo, from Harvard University, has been selected for an Outstanding Paper Award at ICML 2025, one of the top-tier conferences in the field of machine learning and artificial intelligence.     

This is an exceptional outcome, considering that only six papers have received this recognition out of more than 12000 submitted this year.

relAI has been instrumental in fostering the collaboration that led to this significant outcome by funding Unai Fisher Abaigar's research stay at Harvard University. Visits to international centres are one of the components of the relAI PhD curriculum, designed to support collaborations with international researchers and gain international research experience on the topic of the reliability of artificial intelligence (AI).  

The paper tackles aspects of the Algorithmic Decision-Making relAI research area and the relAI central theme Responsibility, exploring how predictive models, particularly those using machine learning, can be used in government programs to identify and support the most vulnerable individuals.

On the latest TV episode of “Neuland” by BR - Bayerischer Rundfunk, relAI PhD student Sarah Ball shares her insights about fundamental issues surrounding a central theme of relAI: “responsibility in AI systems.” She addresses topics such as when AI might reinforce discrimination and how to ensure that AI systems align with human values.

Here is a short clip from the conversation and the link to the full video: https://www.ardmediathek.de/video/Y3JpZDovL2JyLmRlL2Jyb2FkY2FzdC9GMjAyNVdPMDA5MzQ2QTA

Last week, our industry partner QuantCo generously hosted over 30 relAI students at its offices in Munich. The visit provided a valuable platform for our students and QuantCo colleagues to connect, fostering a friendly environment for discussions on potential future collaborations.

We extend our sincere gratitude to QuantCo for their warm welcome and for facilitating such a beneficial exchange!