Location: Darmstadt

Simone Schaub-Meyer is an assistant professor and leads the research group Image and Video Analysis at the Technical University of Darmstadt. She is an ELLIS member and a member of the Hessian Center for Artificial Intelligence (hessian.AI). The focus of her research is on developing efficient, robust, and understandable methods and algorithms for image and video analysis. She received the renowned Emmy Noether Programme (ENP) grant from the German Research Foundation (DFG), supporting her research on Interpretable Neural Networks for Dense Image and Video Analysis. She obtained her doctoral degree from ETH Zurich, advised by Prof. Dr. Markus Gross and in collaboration with Disney Research Zurich. Her doctoral thesis was awarded the ETH Medal.

I am currently pursuing my Master’s degree in Informatik at TU Darmstadt. Additionally, I work as a research assistant at the Intelligent Autonomous Systems Lab at TU Darmstadt, with a focus on humanoid locomotion. My past research experience has mainly focused on reinforcement learning, including an internship at Porsche Motorsport. In addition to robot learning, my current research interests include robotics in complex and uncertain environments.

Marc Saghir is a master’s student in Artificial Intelligence and Machine Learning at TU Darmstadt, after concluding his bachelor in Cognitive Science. He currently works as a student research assistant (HiWi) at the Remote Sensing Institute of TU Darmstadt, contributing to ML projects like landslide detection or sustainability evaluation of cities. Prior to his graduate studies, he gained industry experience working as a Data Scientist and Machine Learning Engineer, where he developed machine learning solutions for real-world applications. His research interests lie broadly in computer science and machine learning, with a particular focus on transdisciplinary applications. He is especially interested in exploring how AI methods can be applied to fields such as environmental science, where data-driven approaches can support the analysis of complex environmental systems. Through his graduate studies and research work, he aims to deepen his machine learning knowledge and contribute to applications of AI for scientific challenges.

Leonie Schüßler is a master’s student in Artificial Intelligence and Machine Learning at TU Darmstadt and recently joined the ELIZA project. She holds a bachelor’s degree in Cognitive Science, which builds her interdisciplinary perspective on AI by bridging fields such as neuroscience, psychology, linguistics, and computer science. Her academic interests include computer vision and deep learning, and she is particularly interested in how these methods can be applied across various domains, including but not limited to medical imaging. Through her graduate studies, she aims to deepen her expertise and contribute to impactful AI research and solutions that address real-world challenges.

Sebastian is a master’s student in Artificial Intelligence and Machine Learning at TU Darmstadt and joined the Zuse School ELIZA in April 2025 as part of its master’s scholarship program, following the completion of his bachelor in Cognitive Science. His research focuses on computer vision, particularly object segmentation and representation learning, as well as combining the visual and linguistic domain in multi-modal models for complex tasks such as visual question answering. He is also fascinated by the intersection of AI systems and human cognition in context of the information processing theory, including the computational modelling of human eye movements to gain insight into human decision-making processes. He aims to consolidate his knowledge through his studies and intends to pursue a PhD to contribute meaningful research to contemporary challenges in computer vision.

I am a third year ELLIS Ph.D. at TU Darmstadt (UKP Lab), Germany and the University of Cambridge, UK. I am supervised by Prof. Iryna Gurevych and Prof. Anna Korhonen. My research interests lie at the intersection of NLP and ML. Specifically, I am interested in:
– Cross-lingual generalization (e.g., plasticity, early period of training, memorization vs generalization, spurious correlations etc.)
– Culturally aware and adapted NLP
– Multimodality
Previously, I studied at the University of Toronto, where I obtained both of my undergraduate and master’s degrees. My master’s research was under the supervision of Prof. Brendan Frey (PSI Lab, Toronto ML Group). I have been working in the industry for nearly a decade in the domain of NLP before I went back to school. I worked at Canadian start-ups like Meta (acquired by CZI), Wattpad (acquired by NAVER WEBTOON), and ElementAI.

I am Sebastian, a Master’s student in Artificial Intelligence and Machine Learning at TU Darmstadt and a scholarship holder at the Zuse School ELIZA. Alongside my studies, I work as a student assistant at Merck in Darmstadt, focusing on AI-related applications. I earned my Bachelor’s degree from Hochschule Darmstadt as part of a dual study program in cooperation with Deutsche Telekom, where I also worked as a software engineer before transitioning to Merck. My research interests lie in continuous machine learning and reinforcement learning. Currently, I’m involved in the JAXAtari Project at the AIML Lab, where I explore object-centric environments and JAX-based RL frameworks. One of my most impactful contributions so far is the paper OML-AD: Online Machine Learning for Anomaly Detection in Time Series Data, which was presented at OL2A 2025. The work proposes an adaptive approach to anomaly detection in streaming data scenarios.

Ananda is currently pursuing a Master’s degree in Artificial Intelligence and Machine Learning at TU Darmstadt, with a focus on Natural Language Processing, Machine Learning, and Large Language Models.

Prior to this, she worked for two years in the industry, gaining valuable experience. Her research interests lie at the intersection of computational linguistics and deep learning, with an emphasis on multilinguality and resource-scarce languages. She has worked on two notable projects that culminated in peer-reviewed publications, GlotEval, involving multilingual data processing and the evaluation of language models, and Commons Connect, a digital participatory tool to improve water security in rural India.

Through her drive towards academic and technical excellence and her passion for ethical AI in human development, she aims to explore inclusive and scalable NLP methods to foster a universally equitable, inclusive, and accessible world.

I am a Master’s student at TU Darmstadt, studying AIML in my 2nd semester. I have been working as a data and AI engineer at two companies, however, I always wanted to do research, so I lately started working as a research student assistant at UKP, in a project about AI-enhanced collaborative reading and writing. My research focus lies in LLMs, especially LLM agent systems and fine-tuning LLMs for coding assistance, AI for databases and multimodal AI. My first publication, “Integrating Symbolic Execution into the Fine-Tuning of Code-Generating LLMs, Marina Sakharova, Abhinav Anand, Mira Mezini”, is based on my Bachelor’s thesis and was recently published at NAACL SRW 2025. Besides this project, I have worked on various other projects involving developing and evaluating AI for database applications, data engineering for AI systems, or developing software for an autonomous driving car. I have been awarded with Female Student Travel Award by ELIZA, and Deutschlandstipendium.

I am working on enabling autonomous systems to efficiently reason on their environment and actions by combining the powers of probability theory with formal logic. To achieve continual reasoning under real-time constraints, exploiting properties of the agent’s perception and knowledge of its domain can help us to overcome the costs of probabilistic inference. Hence, my research focuses on creating reactive systems that are built on a foundation of probabilistic logic and message passing between individual models.