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--- aira:start [2025/05/09 09:03] – [2025-05-08] mzk
+++ aira:start [2025/10/28 22:33] (current) – [2025-10-23] mzk
@@ Line 1: / Line 1: @@
 ====== Artificial Intelligence in Research and Applications Seminar (AIRA) ======
-GEIST is happy to announce, the launch of an open, online seminar on Artificial Intelligence in Research and Applications (AIRA).
+AIRA (the Artificial Intelligence Research and Applications) seminar (https://aira.geist.re) is an event organized by the GEIST group (https://www.geist.re) and the HCAI department (https://hcai.fais.uj.edu.pl) in the FAIS Faculty@JU in cooperation with the Mark Kac center (https://markkac.id.uj.edu.pl) and the JAHCAI lab (https://jahcai.id.uj.edu.pl).
-AIRA is a weekly event (with some breaks between semesters and holidays) devoted to recent results in AI research presented by invited guests from many AI-related fields as well as applications of AI methods and tools in areas of science, industry and business.
+AIRA was created in 2021 and has been regularly organized since then as an online/hybrid event.
+During this time we had almost 100 speakers (as of mid 2025) including researchers from many EU countries, PhD students from the Jagiellonian University, Poland, and Europe.
-**Please save your Thursdays between 3:15-4:45 PM Warsaw Time**
+The objective of AIRA is to create an open venue to discuss AI on an interdisciplinary level and from multiple perspectives. We invite AI talks from technical and exact sciences, but also welcome researchers from social sciences and humanities to share their views on AI development and its applications. Finally we are also open on practitioners from industry and business using AI in their companies.
-The program will be published at [[https://aira.geist.re]] in advance
+AIRA also formally exists as a PhD course in the Jagiellonian University in the Technical Computer Science program as one of the foundational seminars ([WFAIS.SDSP-IT001.01] and [WFAIS.SDSP-IT001.02]). The students are invited to presents their research plans, as well as to share the progress of their PhD projects. Furthemore, we welcome PhD students from other programs in the JU who are interested in AI. PhD students can participate actively presenting their work and perspectives; however, participation with no presentation is also possible, e.g. for persons who are not computer scientists.
-(a dedicated MS Teams group for announcements is available for those who are interested).
+**Please save your Thursdays between 3:15-4:45 PM Warsaw Time on MS teams.**
+The program will be published at the https://aira.geist.re webpage in advance (a dedicated MS Teams group for announcements is available for those who are interested).
 Scientific coordination: [[https://gjn.re|Grzegorz J. Nalepa]]
-Scientific secretaries [[https://szymon.bobek.re|Szymon Bobek]], [[https://www.geist.re/pub:about_us:mtm|Maciej Mozolewski]], [[https://www.geist.re/pub:about_us:mzk|Maciej Szelążek]]
+Scientific secretaries [[https://www.geist.re/pub:about_us:mzk|Maciej Szelążek]], [[https://www.geist.re/pub:about_us:mtm|Maciej Mozolewski]], [[https://szymon.bobek.re|Szymon Bobek]]
+Contact for enrollment of the JU PhD students [[https://fais.uj.edu.pl/wydzial/dziekanat|Mrs Ewa Lelek @ WFAIS]]
+===== Schedule Autumn 2025 =====
+  * **[RESEARCH TRACK] 2025.10.30**: Peter van Dam,  Associate Professor @ Jagiellonian University, [[#section20251030|Inverse problem in electrocardiography: modeling the ECG.]]
+    * Meeting link:[[https://teams.microsoft.com/meet/38693113399487?p=QVsurHuK9sLM4PH7ek|MS Teams]]
+    * Recording:  TDA
+    * Presentation slides:  TDA
+  * **[RESEARCH TRACK] 2025.10.23**: Marek Pędziwiatr,  PhD @ Jagiellonian University, [[#section20251023|Eye tracking as a bridge between psychology and computer science.]]
+    * Meeting link:[[https://teams.microsoft.com/meet/3686533128348?p=2ZQTEpXJiiJDSLC3jJ|MS Teams]]
+    * Recording:  TDA
+    * Presentation slides:  TDA
+  * **[PHD TRACK] 2025.10.16**: Karol Dobiczek,  PhD Candidate @ Jagiellonian University, [[#section20251016|Applying Counterfactual Explanations in Evolving Scenarios and Expert Domains.]]
+    * Meeting link:[[https://teams.microsoft.com/meet/3634985739900?p=D3AqLZM4yWIU1nXOWh|MS Teams]]
+    * Recording:  TDA
+    * Presentation slides:  TDA
+  * **2025.10.09**: Grzegorz J. Nalepa, AIRAmaster @ Jagiellonian University, //Introduction to AIRA to the new PhD students//
 ===== Schedule Spring 2025 =====
+  * **[RESEARCH TRACK] 2025.06.26**: Artur Miroszewski,  PhD @ Jagiellonian University, [[#section20250626|Exploring Quantum Machine Learning through Earth Observation Case Studies.]]
+    * Meeting link:[[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1750076384548?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22a39bd3b1-7b43-47ab-b5ec-29d9ab0ccbb2%22%7d|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/Eb-PxGrj_L9Hka7sdu3TMY4BI2qKDq_5Bvl5hfUPyUwnNA?e=IFBlWx|View]]
+    * Presentation slides:  {{:aira:slides-artur-miroszewski-2025-06-26.pdf|Download}}
+  * **[RESEARCH TRACK] 2025.06.05**: Elżbieta Sroka,  PhD @ Łukasiewicz Research Network - EMAG Institute of Innovative Technologies, [[#section20250605| Interaction Design in Consideration of User Research and UX Specialist Perspectives.]]
+    * Meeting link:[[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1748969648131?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22a39bd3b1-7b43-47ab-b5ec-29d9ab0ccbb2%22%7d|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/EXXr2Bww-WlGtD4kSo63kioBnlcBhajhN7zEXY22ok6huw?e=zPIl1S|View]]
+    * Presentation slides:  {{:aira:slides-elżbieta-sroka-2025-06-05.pdf|Download}}
+  * **[PHD TRACK] 2025.05.29**: Bogdan Gulowaty, PhD @ Wrocław University of Science and Technology, [[#section20250529|Building transparent classification models.]]
+    * Meeting link:[[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1748506829263?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22a39bd3b1-7b43-47ab-b5ec-29d9ab0ccbb2%22%7d|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/EZxjf0UnTCtChkK4Lk39qcIBDU9df_PNwuCe9D_2MpFn_w?e=GtoV3X|View]]
+    * Presentation slides:  {{:aira:slides-bogdan-gulowaty-2025-05-29.pdf|Download}}
+  * **[PHD TRACK] 2025.05.22**: Jacek Karolczak,  PhD Candidate @ Poznań University of Technology, [[#section20250522|Explainable AI: Moving from numbers to meaningful insights via prototype-based explanations.]]
+    * Meeting link:[[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1747385677830?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22a39bd3b1-7b43-47ab-b5ec-29d9ab0ccbb2%22%7d|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/EYgrsIJ986RNpBAtv_11xLcBcDlCsAbrXYbUbMoTEMuSww?e=3g2tJQ|View]]
+    * Presentation slides:  {{:aira:slides-jacek karolczak-2025-05-22.pdf|Download}}
   * **[PHD TRACK] 2025.05.15**: Anastasiya Pechko,  PhD Candidate @ Jagiellonian University, [[#section20250515|Adaptive Modular Housing Design for Crisis Situations.]]
     * Meeting link:[[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1746780764971?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22a39bd3b1-7b43-47ab-b5ec-29d9ab0ccbb2%22%7d|MS Teams]]
-    * Recording:  TDA
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/EbyiCvceYJdEnCVPvfgVlNsBVB5BDIsbHRpDRgc8_19rMA?e=wktReu|View]]
-    * Presentation slides:  TDA
+    * Presentation slides:  {{:aira:slides-anastasiya-pechko-2025-05-15.pdf|Download}}
   * **[RESEARCH TRACK] 2025.05.08**: Gianluca Guglielmo,  PhD @ Tilburg University, [[#section20250508|From Video Games to Real-life ”Games”: The Emergence of Real-life Expertise in (Serious) Video Games.]]
@@ Line 418: / Line 464: @@
 ===== Presentation details =====
+==== 2025-10-30 ====
+<WRAP column 15%>
+{{ :aira:peter-vanDam-foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Peter van Dam,  Associate Professor @ Jagiellonian University
+**Title**: Inverse problem in electrocardiography: modeling the ECG.
+**Abstract**:
+The electrocardiogram (ECG) measured on the body surface shows beat-by-beat the electrical functioning of the heart. This ECG consists of a number of electrical time signals that are caused by the currents produced by the myocardial cells. These ECG signals require clinical interpretation, which in the In current clinical practice is close to an art. Modeling the ECG, i.e. have a model of the heart that simulates the electrical processes of the myocardium and calculates the ECG signals on the body surface, can help to understand these waveforms in a cause -effect relationship. This is the major subject of my current and past research, which I will introduce during this talk.
+**Biogram**:
+Dr hab. Peter van Dam is a scientist and lecturer specializing in cardiac modeling, electrocardiographic diagnostics, and the development of innovative educational and clinical tools based on heart signal analysis and 3D imaging. In 2025, he obtained his postdoctoral degree (habilitation) in medical sciences at the Jagiellonian University Medical College, presenting a scientific achievement entitled “Localization of PVC (Premature Ventricular Contraction): Evaluation and Validation of Inverse ECG Modeling.” He is also a laureate of the prestigious NCN OPUS grant, focused on inverse modeling of repolarization heterogeneity to assess arrhythmogenic risk.
+His academic path began with studies in electronic engineering at MBO-College Gouda (1981–1985) and Hogeschool Utrecht (1985–1990). He also studied philosophy (Rijksuniversiteit Utrecht, 1991–1992) and physics (Universität Oldenburg, 1992–1993). Between 1997–2004, he earned a master’s degree in biology and physics at the Open University in Heerlen, where his thesis involved developing a simulation of the P-wave in ECG and IEGM (2004). In 2010, he defended his PhD at Radboud University Nijmegen under the supervision of Prof. Adriaan van Oosterom, presenting the dissertation “The shortest path to cardiac activation.”
+Peter van Dam’s professional experience spans both academia and the medical industry. He began his career in 1997 as a senior scientist at Vitatron/Medtronic. Since 2009, he has been affiliated with Peacs BV (Chief Scientific Officer). In 2020, he became CEO of ECG-Excellence, focusing on developing innovative diagnostic and educational tools based on heart signal analysis and 3D modeling.
+In academia, he has worked at Radboud University (2011–2017, validating ECGI methods in an animal model), at UCLA (2013–2016, developing arrhythmia mapping methods), and currently conducts research and teaching at UMC Utrecht, UT Twente, and Hochschule Luzern Technik & Architektur. Since 2023, he has also collaborated with the Jagiellonian University Medical College, Center for Digital Medicine and Robotics, where he serves as Visiting Professor at the Department of Radiology. Since 2024, he has also been a specialist at the Laboratory of Functional and Virtual Medical 3D Imaging (3D-FM) at the University Hospital in Kraków.
+His research focuses on: inverse ECG modeling and arrhythmia source localization; the use of 3D imaging and simulation in cardiology; developing modern educational tools for students and physicians; integrating engineering and clinical expertise in the diagnosis of cardiac rhythm disorders.
+Dr hab. Peter van Dam sees great potential in interdisciplinary collaboration between universities and university hospitals worldwide. His goal is to create and implement groundbreaking 3D ECG technologies that not only enable more precise diagnostics but also open new possibilities for more effective treatment of cardiac arrhythmias. By combining clinical and engineering perspectives, he strives to set new standards in modern cardiology.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-10-23 ====
+<WRAP column 15%>
+{{ :aira:marek-pedziwiatr-foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Marek Pędziwiatr,  PhD @ Jagiellonian University
+**Title**: Eye tracking as a bridge between psychology and computer science.
+**Abstract**:
+We move our eyes around three times per second. While we are rarely aware of these movements, they play a crucial role in shaping how we see the world: they determine what visual input reaches the brain and is processed by it (e.g., memorized). Understanding the process of (involuntarily) deciding where to look is one of the key problems in modern experimental psychology, and it has substantial practical significance for domains such as automated content-aware image cropping. Studies aimed at solving this problem typically rely on recording eye movements of individuals viewing visual materials (e.g. images) and relating these recordings to the outputs of image-processing algorithms that attempt to predict which image regions would attract human gaze. In my talk, I will provide an overview of this field and use examples from my work to showcase the potential of combining methods from experimental psychology and computer science.
+**Biogram**:
+Marek Pędziwiatr is a vision scientist interested in how we make sense of what we see. In particular, he studies human eye movements during picture viewing. He completed a PhD in psychology at Cardiff University (UK). Afterwards, Marek worked as a postdoctoral researcher at Queen Mary University of London. Then, he returned to Krakow, where, before moving to the UK, he obtained undergraduate degrees in Control Engineering and Robotics (BSc and MSc) and Cognitive Science (BSc), and joined the Centre for Brain Research at Jagiellonian University.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-10-16 ====
+<WRAP column 15%>
+{{ :aira:karol-dobiczek-foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Karol Dobiczek,  PhD Candidate @ Jagiellonian University
+**Title**: Applying Counterfactual Explanations in Evolving Scenarios and Expert Domains.
+**Abstract**:
+Counterfactual explanations (CE) are one of the building blocks of many explainable machine learning methods, however their application and effects when applied to realistic scenarios are often missing. This seminar presents two works on counterfactual explanations that address some of these scenarios. First work explores the effects of applying CEs in an evolving domain and model, the second investigates whether existing methods for natural language CEs can handle being applied to expert domains. Other current and future directions in applying CEs and other XAI methods will be discussed.
+**Biogram**:
+Karol Dobiczek is a PhD candidate in the team led by professor Grzegorz J. Nalepa at the Jagiellonian University in Kraków. He received his Master's degree from the Delft University of Technology in 2024 and his Bachelor's thesis from the same university in 2022. His work focuses on explainable and interpretable machine learning, mostly on the use of counterfactual explanations. Karol is currently a Software Engineer at Qualtrics and a Research Software Engineer at the MI2 team at the Warsaw University of Technology.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-06-26 ====
+<WRAP column 15%>
+{{ :aira:artur-miroszewski-foto.jpeg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Artur Miroszewski,  PhD @ Jagiellonian University
+**Title**: Exploring Quantum Machine Learning through Earth Observation Case Studies.
+**Abstract**:
+The analysis of satellite images has attracted significant research interest due to its numerous applications and unparalleled scalability in Earth Observation (EO). Although artificial intelligence algorithms for EO emerge at a steady pace, the community still needs to address many practical challenges that are concerned with such highly dimensional and unprecedentedly large volumes of image data. Quantum Machine Learning (QML) is a promising research avenue here. Despite the growing interest and funding in the field, current results remain inconclusive, shifting focus toward understanding the strengths and limitations of QML rather than solely expanding applications of such methods. This seminar addresses a critical gap by consolidating advancements in QML, with a special focus put on quantum kernel methods - which already proved their value in EO - to evaluate their role in advancing state-of-the-art EO solutions and exploring the potential quantum advantage via identifying their benefits and shortcomings in an unbiased and thorough way.
+**Biogram**:
+Artur Miroszewski received the Ph.D. degree in theoretical physics from the National Centre for Nuclear Research, Otwock, Poland, in 2021. He is a Postdoctoral Researcher with the Jagiellonian University, Kraków, Poland.
+He is involved in European Space Agency projects exploring the potential of quantum machine learning for satellite data analysis and serves as a quantum computing lecturer at the IEEE GRSS HDCRS summer schools. He is a co-chair of the QUEST IEEE GRSS Technical Committee.
+His main research interest include the study and applications of quantum kernel methods.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-06-05 ====
+<WRAP column 15%>
+{{ :aira:elzbieta-sroka-foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**:  Elżbieta Sroka,  PhD @ Łukasiewicz Research Network - EMAG Institute of Innovative Technologies
+**Title**: Interaction Design in Consideration of User Research and UX Specialist Perspectives: Artificial intelligence in UX Design, users experience in digital library and the needs of digital humanities researchers, reception of signed avatars by Deaf users.
+**Abstract**:
+The presentation presents the results of research in the field of Human-Computer Interaction (HCI), with a special focus on the needs of different user groups and the application of artificial intelligence (AI) tools in both the design and research processes. The areas discussed include: the use of AI in UX design and designers' perspectives; the experiences of digital library users, especially in the context of orientation in the field, navigation, and information retrieval; the needs of digital collection researchers and their expectations regarding AI-supported solutions; and the accessibility of research tools for Deaf people and the reception of sign avatars communicating in Polish Sign Language (PJM) in the Deaf community.
+**Biogram**:
+Elżbieta Sroka, PhD, certified UX designer, Senior Specialist at the Łukasiewicz Research Network – Institute of Innovative Technologies EMAG in Katowice, Poland.
+She obtained her doctoral degree in 2018 from the University of Silesia in Katowice, based on a dissertation focused on the digitization of social life documents in Polish digital libraries.
+Her research interests include research users information behavior, user experience (UX) design, and digital humanities, as well as applications of artificial intelligence—particularly in the context of human–AI interaction, the impact of AI on UX, and the use of AI in the study of digital collections. She also conducts research in the areas of digital accessibility, information management and information retrieval.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-05-29 ====
+<WRAP column 15%>
+{{ :aira:Bogdan_Gulowaty_foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Bogdan Gulowaty,  PhD @ Wrocław University of Science and Technology
+**Title**: Building transparent classification models.
+**Abstract**:
+As AI and ML technologies advance and become deeply integrated into daily life, the need for transparent and interpretable models grows increasingly urgent. AI systems must be understandable, trustworthy, and ethical, especially in critical healthcare, finance, and legal sectors. The rise of XAI seeks to address these challenges by providing explanations of model decisions, making AI systems more transparent. However, much of the progress in XAI has focused on deep neural networks, leaving other complex models like ensemble methods needing to be explored more regarding their interpretability.
+The thesis aims to fill that gap by developing novel methods to improve the transparency and interpretability of ensemble classifiers while ensuring these models maintain competitive predictive performance and build inherently transparent models. The central hypothesis of the thesis is that it is possible to construct such transparent or explainable models that perform as well as black-box models in a wide range of classification tasks. The work focuses on three primary methods designed to either explain or replace complex models with transparent alternatives: NOTE, optimal-centroids and quad-split algorithms.
+**Biogram**:
+Finished his PhD at Wroclaw University of Technology in 2025. Full time Software Engineer. Enthusiast of mountaineering, various sports activities and motorcycling. Born in Bolesławiec, currently lives in Wrocław.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-05-22 ====
+<WRAP column 15%>
+{{ :aira:Jacek_Karolczak_foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Jacek Karolczak,  PhD Candidate @ Poznań University of Technology
+**Title**: Explainable AI: Moving from numbers to meaningful insights via prototype-based explanations.
+**Abstract**:
+The increasing complexity of machine learning models has heightened the demand for their explainability. Most existing work in explainable artificial intelligence (xAI) focuses on techniques like pixel attribution or feature importance, especially Shapley values. However, these types of explanations are often criticized for being hard to interpret—not just for laypersons, but even for machine learning experts. In contrast, the XAI 2.0 manifesto advocates for concept-based explanations, such as prototypes - representative instances. This talk will introduce the problem and survey existing approaches, with a focus on recent developments in prototype-based explainability. It will also present the author’s own work on prototype-based concept drift detection, which maintains intrinsic interpretability. Finally, open challenges and directions for future work in prototype-based explainability will be discussed.
+**Biogram**:
+Jacek Karolczak is a PhD student at Poznan University of Technology, where he also earned BSc and MSc in Artificial Intelligence. His research focuses on improving the interpretability of machine learning models, particularly in dynamic environments where data continuously evolves. He believes the world of explainable AI (xAI) is shifting beyond feature-importance explanations, embracing high-level concept-based interpretations that better align with the language and reasoning of end users.
+</WRAP>
+<WRAP clear></WRAP>
 ==== 2025-05-15 ====