Location: Darmstadt

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.

I am a Master’s student in Artificial Intelligence & Machine Learning at Technische Universität Darmstadt. My research interests focus on multimodal learning and computer vision. I am currently working on deepfake detection in facial videos and efficient video processing techniques for multimodal large language models. Previously, I worked as a Data Science Intern at DataSutram and as a Research Assistant at the CMATER Lab, Jadavpur University. My most recognized work, *“Supervision meets Self-supervision: A Deep Multitask Network for Colorectal Cancer Histopathological Analysis”*, with Soumitri Chattopadhyay and Dr. Pawan Kumar Singh, won Best Paper in the Deep Learning track at MISP’2022. I have also co-authored *“BeAts: Bengali Speech Acts Recognition using Multimodal Attention Fusion”*, accepted at INTERSPEECH 2023.

Contact: info@eliza.school

I am a Master’s student in Artificial Intelligence and Machine Learning at TU Darmstadt, with a Bachelor’s in Software Engineering from Yaşar University, where I graduated second in my department. I served as vice chairwoman of the IEEE Women in Engineering committee, organizing technical events and managing administrative tasks. My internships strengthened my skills in mobile and game development (Flutter, PHP, MySQL), energy optimization for solar-powered IoT devices, and NLP-based product classification (Java, Python, PostgreSQL). For my Bachelor’s thesis, I co-developed a method to classify English words into CEFR levels using linguistic features, data preprocessing, feature selection, and a tuned XGBoost model. During my Master’s, I contributed to a project evaluating the SPACE+MOC object extraction method on Atari games, improving classification with X-means. In another project, we tested the robustness of a visual grounding model (GLIP) on perturbed Flickr30k images, identifying effective attack strategies.