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--- aira:start [2026/06/01 19:43] – [Schedule Spring 2026] mtm
+++ aira:start [2026/06/21 08:05] (current) – [Schedule Spring 2026] mtm
@@ Line 22: / Line 22: @@
 ===== Schedule Spring 2026 =====
-  * **[PHD TRACK] 2026.05.28**: Soheila Molaei,  senior researcher @ University of Oxford, [[#section20260528|From Graphs to Graph Neural Networks: Foundations and Applications in Healthcare]]
+  * **[RESEARCH TRACK] 2026.06.18**: Elżbieta Sroka,  assistant professor @ Jagiellonian University, [[#section20260618|Exploring the use of artificial intelligence in digital cultural heritage research in european research centres.]]
+    * Meeting link: [[https://teams.microsoft.com/meet/355163613268564?p=EFfNrzZY2iaUuHn8OR|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQASrWSYnTz1RqHEehWmxIxvAXSok1ayAAu4-zQC2vwtQ08?e=zMyadc|View]]
+    * Presentation slides:  TDA
+  * **[PHD TRACK] 2026.06.11**: Sabri Manai,  PhD Candidate @ Jagiellonian University, [[#section20260611|Transparent and Adaptive AI for Human-Guided Decision Support.]]
+    * Meeting link: [[https://teams.microsoft.com/meet/351900951227620?p=Qqx0dV7zoNZpztQhB1|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQBfPoiQ1E7DRrskykUzslmoAWUM6quArL0DOTPXGfj8xQU?e=Eg6GHs|View]]
+    * Presentation slides:  {{:aira:slides-sabri-manai-2026-06-11.pdf|Download}}
+  * **[RESEARCH TRACK] 2026.05.28**: Soheila Molaei,  senior researcher @ University of Oxford, [[#section20260528|From Graphs to Graph Neural Networks: Foundations and Applications in Healthcare]]
     * Meeting link:[[https://teams.microsoft.com/meet/377493387003987?p=TVBcvsqGs42CdT7U9T|MS Teams]]
     * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQC8c4XxDZvTQ70h5GCoIrRwAYBNQyagBm3DaEdsBovDMNQ?e=8fwmHj|View]]
@@ Line 30: / Line 41: @@
     * Meeting link:[[https://teams.microsoft.com/meet/325587359264791?p=u7BhZIs7GL9MEk6U2J|MS Teams]]
     * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQCsLO1arlhfTrr7jI00i90eAQxEquR7e1UpPO6YKLrYbDI?e=g0rCPL|View]]
-    * Presentation slides:  TDA
+    * Presentation slides:  {{:aira:slides-jan-argasinski-2026-05-21.pdf|Download}}
   * **[RESEARCH TRACK] 2026.05.14**: Grzegorz Korcyl,  assistant professor @ Jagiellonian University, [[#section20260514|Innovative data processing methods on field programmable gate arrays (FPGAs)]]
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+==== 2026-06-18 ====
+<WRAP column 15%>
+{{ :aira:elzbieta-sroka-foto.jpg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Elżbieta Sroka,  assistant professor @ Jagiellonian University
+**Title**: Exploring the use of artificial intelligence in digital cultural heritage research in european research centres.
+**Abstract**:
+This presentation provides an overview of the current stage of research investigating the use of artificial intelligence (AI) in digital cultural heritage research within european research centres and cultural heritage institutions, conducted as part of the CHExRISH project. The study explores how AI is being adopted and applied in digital cultural heritage research, focusing on methods, tools, workflows, research infrastructures, and institutional practices. The study is based on fieldwork conducted in selected European countries and includes research visits, expert interviews, and observations. The fieldwork has so far covered research and cultural heritage institutions in eight European countries. The presentation outlines the research design, methodological approach, and data collection methods employed in the study, as well as the scope of the research and the types of institutions involved. It also provides an overview of the institutions visited to date. As the analysis of the empirical material is still ongoing, the presentation does not seek to offer final conclusions. Instead, it presents preliminary observations from the fieldwork, discusses emerging themes, and outlines the next stages of the research, including planned data analysis and future dissemination activities.
+**Biogram**:
+Elżbieta Sroka, PhD, certified UX designer, assistant professor at the Jagiellonian University in Krakow, Poland, Faculty of Physics, Astronomy and Applied Computer Science, at the Department of Human-Centred Artificial Intelligence and also Senior Specialist at Łukasiewicz Research Network – Institute of Artificial Intelligence and Cybersecurity 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>
+==== 2026-06-11 ====
+<WRAP column 15%>
+{{ :pub:about_us:smi.jpeg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Sabri Manai,  PhD Candidate @ Jagiellonian University
+**Title**: Transparent and Adaptive AI for Human-Guided Decision Support.
+**Abstract**:
+This talk presents Sabri's research into making AI systems more transparent, trustworthy, and useful for human decision-making. Across three lines of work, he develops explainable recommendations tailored to multiple stakeholders, grounds industrial anomaly detection in domain knowledge through knowledge graphs, and introduces counterfactual-guided hyperparameter optimisation with a conversational interface, showing that interactive explanation measurably outperforms static alternatives.
+Together these works reveal a common thread and a shared limitation: current explainable AI systems are built around one-shot outputs. They tell users why a decision was made, but offer no principled response when users push back. The second part of the talk examines this open problem: how AI systems should handle disagreement, adapt to feedback, and be evaluated not on perceived trust but on whether they genuinely improve human decisions.
+**Biogram**:
+Sabri Manai is a PhD candidate in Technical Computer Science at Jagiellonian University in Kraków, where his research focuses on explainable AI and pattern detection in multimodal data. His work investigates how human feedback and domain knowledge can improve the transparency and reliability of AI systems.
+He holds a Master’s degree in Software Systems Engineering from the Universitat Politècnica de València and a Bachelor’s degree in Computer Science from the South Mediterranean University in Tunis. Previously, he worked on AI-driven urban analytics within the Valencia Smart City project at Idrica and contributed to mobile development and cloud integration at Peaksource.
+</WRAP>
+<WRAP clear></WRAP>
 ==== 2026-05-28 ====