About us
Samsung AI Center in Warsaw is a place where a unique interdisciplinary AI community thrives, bringing together open and enthusiastic individuals who are conquering the world with their ideas and human-centered AI technology.
In our unit, we believe in human potential supported by AI, which is why we enhance it by developing artificial intelligence. AI that can be carried in your pocket, is safe and can be trusted. We aim to push the boundaries of knowledge, address user needs and creating further conveniences.
We focus on the dynamics of reasoning and expanding knowledge. We work on safety by developing "safety-by-design" and self-regulation concepts, ensuring easy understanding of AI models. We want to enable action planning and improve command comprehension through context-aware prediction.
Join us! Together, we can achieve more!

A graduate of the Warsaw University of Technology, twice a visiting professor at the MIT Department of Mathematics. He conducts research in the areas of numerical and randomized linear algebra and control theory. He develops algorithms for fast machine learning, data compression and reconstruction, and knowledge representation. Author of the theory of meta-factorization, which explains internal reactions between data structures and enables the construction of new matrix decomposition algorithms. He formulated the optimality conditions for energy-efficient control of processes on an infinite horizon and the optimality conditions for Nash equilibrium points in non-cooperative games induced by KKT conditions. A loving father and husband, dancer, and enthusiast of reading and writing.


Dr. Eng. Michał P. Karpowicz Head of Samsung AI Center Warsaw

A philosopher/cognitive scientist by education, and an NLP engineer by profession. A graduate of the University of Warsaw. In the past, he worked mainly in the area of adapting natural language processing tools to the specifics of the Polish language (dependency grammar, lexical analysis, question answering) and corpus linguistics. Recently, he has been focusing a lot on RAG systems and knowledge graphs. He values simplicity in explanations and good experimental design. In his free time, he tinkers with Linux, rides his bike, and listens to loud, noisy music.


Ryszard Tuora, AI Research Scientist

A graduate of the University of Glasgow and the University of Copenhagen, with an interdisciplinary education encompassing computer science, mathematics, and cognitive science. She conducts research on the safety and interpretability of artificial intelligence systems, developing technologies that enable more understandable and responsible use of AI. Her inspiration lies in understanding the workings of the human mind and intelligence – she believes that AI and cognitive science can inspire each other, creating new perspectives and opportunities in both fields. In her personal life, she is a proud resident of Warsaw, a lover of sports, good food, and travel.


Zuzanna Dubanowska, AI Research Engineer

A PhD student at the Warsaw University of Technology. She researches neural network-based models in terms of explainability and the ability to perceive spatial context. She has gained experience in the field of artificial intelligence at universities in Singapore, South Korea, Austria, and Switzerland. She enjoys popularizing science. A member of the expert committee of the Artificial Intelligence Olympiad. In her free time, she enjoys culinary improvisations.


Paulina Tomaszewska, Senior AI Research Scientist

A graduate of the Warsaw University of Technology with a PhD from the Polish Academy of Sciences. Postdoctoral researcher at the University of California, San Diego, and research fellow at the RIKEN Center for Brain Science in Japan. He conducts research in the areas of artificial intelligence, neural networks, and biomedical image analysis. He specializes in transfer learning techniques, neural representations, and computer vision. Author of numerous publications, recognized by Stanford University as one of the top 2% most influential scientists in the world. A fan of Asia, long-distance travel, and ambient music.


Michał Byra, AI Research Scientist
Areas we work in

Context & Coherence
Lab

How can we understand the context of images, sound, text, and the sensory input we receive from multiple sources? Understanding context is essential for prediction, planning, reasoning, reducing imagination, and preventing hallucinations. Without context, it is difficult to explain anything. We aim to teach AI models to comprehend context to assist them in making predictions, creating coherent and meaningful content, and taking logical actions accordingly.

Knowledge &
Reasoning

We aim to understand the process of continuous knowledge creation and supplementation, long-term memory retention, discovering relationships between observations, and building world models that drive imagination and reasoning. We want to comprehend and shape the dynamics of these processes, ensuring their stability and the speed of convergence. Ultimately, we seek to translate these discoveries into technologies that enable answering complex questions posed in natural language, supporting reflection, planning, and drawing conclusions.

Safety &
Alignment

We aim to understand the process of continuous knowledge creation and supplementation, long-term memory retention, discovering relationships between observations, and building world models that drive imagination and reasoning. We want to comprehend and shape the dynamics of these processes, ensuring their stability and the speed of convergence. Ultimately, we seek to translate these discoveries into technologies that enable answering complex questions posed in natural language, supporting reflection, planning, and drawing conclusions.
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