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--- aira:start [2025/05/18 00:37] – [Schedule Spring 2025] mzk
+++ aira:start [2025/06/11 00:23] (current) – [Schedule Spring 2025] mzk
@@ Line 15: / Line 15: @@
 ===== Schedule Spring 2025 =====
+  * **[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:  TDA
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/EYgrsIJ986RNpBAtv_11xLcBcDlCsAbrXYbUbMoTEMuSww?e=3g2tJQ|View]]
-    * Presentation slides:  TDA
+    * 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 423: / Line 434: @@
 ===== Presentation details =====
+==== 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 ====