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--- aira:start [2025/05/30 08:07] – [Schedule Spring 2025] mtm
+++ 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]]
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 ===== 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 ====