prof. Agnieszka Janiuk
- Graduate of the Faculty of Physics of the University of Warsaw (1998). Doctorate in astronomy at the Astronomical Center of the Polish Academy of Sciences in Warsaw (2003). She has held several research internships, including at the Scuola Internazionale Superiore di Studi Avanzati in Trieste, the Harvard Smithsonian Center for Astrophysics in the USA, the Max Planck Institute fuer Astronomy and Astrophysics in Munich, the Inter University Center for Astronomy and Astrophysics in Pune, India, and a postdoctoral contract at the Department of Physics at the University of Nevada, Las Vegas, USA. She received her habilitation in astronomy at CAMK PAN in Warsaw (2011), and the title of Professor of Science and Life Sciences (2021).
Since 2010, she has been working at the Center for Theoretical Physics of the Polish Academy of Sciences. From 2011 to 2015, she served as Deputy Director. Since 2011, she has been leading the astrophysics research group. She works on the astrophysics of accretion disks, the structure of active galactic nuclei, as well as the origin of gamma-ray flares and nucleosynthesis of heavy elements in the kilonova phenomenon, and modeling the collapse of massive stars and electromagnetic signals from gravitational wave sources. She has led grants from the National Science Center, and the Ministry of Science and Higher Education. She is a member of the Polish and European Astronomical Societies, and the International Astronomical Union: Commission B1 (Computational Astrophysics) and Division D (High Energy Astrophysics). Since 2015, she has been a member of the Committee on Astronomy of the Polish Academy of Sciences.
Relativistic MHD simulations of merging and collapsing stars
Compact binary mergers and the collapse of massive stars can produce intense transients observable across high-energy wavelengths. Events such as gamma-ray bursts and kilonova emissions are often accompanied by gravitational wave detections, making them crucial sources for multi-messenger astrophysics. To explore these phenomena theoretically, state-of-the-art approaches like numerical relativity and GR magnetohydrodynamic simulations are used. In this talk, I will review the current progress in simulations of mergers and collapsars, and present recent findings from my team, achieved using Polish PL-Grid and European High-Performance Computing facilities.
dr Paweł Gora
- Scientist, IT specialist, philanthropist, and entrepreneur working mainly on applications of AI and quantum computing, especially in transportation and medicine. A graduate of the Faculty of Mathematics, Informatics and Mechanics of the University of Warsaw (M.Sc. in Mathematics, M.Sc. in Computer Science, and Ph.D. in Computer Science), he was later a Postdoctoral Researcher at Sano. He is the Founder and CEO of Fundacja Quantum AI, Chairperson of the Board of QWorld, and Coordinator of one of its local QCousins, QPoland. He also cooperates with several startups serving as a technical and business advisor. In the past, he worked as a software engineering intern or research intern at Microsoft, Google, CERN, and IBM Research, and was a member of the Council for Digitalization.
Introduction to Quantum Computing - Optimizing Logistics case study
In this talk, I will give an introduction to the quantum computing domain, explaining the basic concepts and algorithms, how it is different from the traditional way of computing, and what are the biggest challenges in this field. I will also explain the difference between circuit-based models and the quantum annealing approach. Finally, I will present a use case demonstrating how quantum computing could be applied to solve routing problems in logistics.
Remigiusz Kinas
- artificial intelligence specialist. Involved in research and development projects in the field of AI - computer vision, generative artificial intelligence (LLM/vLLM model development). He is actively involved in the SpeakLeash community - the initiative to create the Polish Bielik language model (LLM), where he supports the team in model finetuning, quantization, and benchmarking. He holds the title of double Grand Master of Kaggle on the largest AI community platform.
Bielik: The Road to the Polish Large Language Model
The presentation [in Polish] will detail the history of the Bielik models, starting from the beginning of the collaboration between SpeakLeash and ACC Cyfronet AGH to the publication of various versions of the model, such as Bielik v0.1 and Bielik v2.0. Another important part of the presentation will be a discussion of the stages of LLM model preparation, such as model and approach selection, tokenization, baseline training, instructional finetuning, and optimization. Methods for improving data quality will also be presented, including deduplication, cleaning, and anonymization, which are key to obtaining high-quality results. Finally, Bielik use cases will be presented. Among them will be answers to questions about how the model can be tailored to meet specific needs, and how its flexibility and low cost of use make it an attractive choice for a variety of applications.
