Focus area: Foundations of ML: Natural Language Processing
Dr. Kuldeep Singh is the CEO and Co-founder of Eka Labs AI, a deeptech startup building hyper-specialized Small Language Models (SLMs) for domain-specific intelligence.
Previously, he served as Director of AI Technology at Cerence AI, where he led the development and scaling of Generative AI and LLM-powered products from 0→1, enabling millions of user interactions across leading automotive OEMs, including Volkswagen, Audi, Toyota, Geely, JLR, and Ford, as well as Tier-1 suppliers. He also contributed to the development of Cerence’s automotive-grade LLM (CaLLM) and its deployment into premium infotainment systems, shaping next-generation voice-driven mobility experiences.
Dr. Singh holds a Ph.D. from the University of Bonn as a Marie Curie Fellow under Prof. Dr. Sören Auer. He later led Conversational AI research at Fraunhofer IAIS, Sankt Augustin in collaboration with Prof. Dr. Jens Lehmann. He has authored 50+ publications in top AI venues such as ICLR, AAAI, ACL, and The Web Conference, and holds two U.S. patents. His research focuses on knowledge distillation and Reinforcement learning for SLMs and graph representation learning, and he actively contributes in program committee of leading AI conferences.
Hinrich Schuetze is Professor for Computational Linguistics and co-director of the Center for Information and Language Processing at the University of Munich (LMU Munich). He received his PhD from Stanford in 1995 for his early research on embeddings (ACL Test-of-Time Paper Award). He then worked on natural language processing and information retrieval technology at Xerox PARC, at several Silicon Valley startups and at Google 1995-2004 and 2008/9. Hinrich is a coauthor of Foundations of Statistical Natural Language Processing (with Chris Manning) and Introduction to Information Retrieval (with Chris Manning and Prabhakar Raghavan). He was awarded a European Research Council Advanced Grant in 2017. Hinrich served as president of the Association for Computational Linguistics in 2020. He is a fellow of ACL, ELLIS and HessianAI.
Letitia Parcalabescu has an academic background in Physics and Computer Science, and holds a PhD in Computational Linguistics. Her doctoral research focused on benchmarking and interpreting the internal processes and explanations of multimodal AI models. Currently, she is an AI researcher at Aleph Alpha Research, working on training interpretable reasoning models by design, as well as curating and synthesizing data for large-scale pre-training. She created the “AI Coffee Break with Letitia” YouTube channel where she breaks down complex AI concepts. Topics range from newest research results in natural language processing, computer vision, to the broader societal impact of AI.
Matthias W. Seeger received a Ph.D. from the School of Informatics, Edinburgh university, UK, in 2003 (advisor Christopher Williams). He was a research fellow with Michael Jordan and Peter Bartlett, University of California at Berkeley, from 2003, and with Bernhard Schoelkopf, Max Planck Institute for Intelligent Systems, Tuebingen, Germany, from 2005. He led a research group at the University of Saarbruecken, Germany, from 2008, and was assistant professor at the Ecole Polytechnique Federale de Lausanne from fall 2010. He joined Amazon as machine learning scientist in 2014. He received the ICML Test of Time Award in 2020.
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.
PhD student, AutoML Freiburg
Iryna Gurevych is Professor of Computer Science and Director of the Ubiquitous Knowledge Processing (UKP) Lab at the Technical University (TU) of Darmstadt. She is an ELLIS Fellow and Co-Director of the ELLIS NLP Program. She is widely known for her fundamental contributions to and innovative applications of natural language processing and machine learning. Iryna Gurevych’s work has received numerous prestigious awards, including the Milner Award of the Royal Society, an ERC Advanced Grant, and the first-ever Hessian LOEWE Distinguished Chair Award. She has taught both foundational and advanced courses in NLP, Information Management, Ethics in NLP, and Introduction to Scientific Work. She founded and served as the spokesperson for two research training groups in NLP and Computational Linguistics and has supervised more than 25 PhD students.
Prof. Dr. Marcus Rohrbach is a Full Professor (W3) at TU Darmstadt for Multimodal Reliable AI since 2023. He received his Ph.D. from Saarland University, working at the Max Planck Institute for Informatics with Prof. Dr. Bernt Schiele (2010-2014). During his postdoc at UC Berkeley with Prof. Dr. Trevor Darrell, USA, he pioneered multimodal deep learning. As a research scientist at FAIR (Fundamental AI Research, Meta, 2017-2023), he has scaled multimodal learning using multi-task and self-supervised methods and developed fundamental ideas for learning with rare and novel concepts, as well as continuous learning. In 2022, Dr. Rohrbach was awarded an Alexander von Humboldt Professorship for Artificial Intelligence for his outstanding scientific achievements, and in 2023, the LOEWE Spitzenprofessur.