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--- aira:start [2026/01/23 11:51] – [Schedule Autumn 2025] mzk
+++ aira:start [2026/01/30 11:04] (current) – [Schedule Autumn 2025] mtm
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   * **[PHD TRACK] 2026.01.29**: Antonio Guillen Teruel,  PhD Candidate @ University of Murcia, [[#section20260129|Calm-Data Generator: A Flexible Framework for Synthetic Dataset Creation Under Concept Drift.]]
     * Meeting link:[[https://teams.microsoft.com/meet/35628465517259?p=gMuL3AOryVNAxr51oK|MS Teams]]
-    * Recording:  TDA
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQCelBjGaTY3T682gedK5w5RAXB_szxTRJTuLMg2EBRTWgg?e=V2bulY|View]]
-    * Presentation slides:  TDA
+    * Presentation slides:  {{:aira:slides-antonio-guillen-teruel-2026-01-29.pdf|Download}}
   * **[PHD TRACK] 2026.01.22**: Syed Muhammad Hamza Zaidi, PhD Candidate @  Otto von Guericke University Magdeburg, [[#section20251120|Localizing the invisible: Graph Neural Networks for Biomedical Signals.]]
     * Meeting link:[[https://teams.microsoft.com/meet/36137568079081?p=YQbEHTAA1Iu2GHooUE|MS Teams]]
-    * Recording:  TDA
+    * Recording: [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAV7CU9Jhg1S49QuHoDFG0oAY94si6m4JRgvdvT6fWJdzI?e=RPaa1G|View]]
-    * Presentation slides:  TDA
+    * Presentation slides:  {{:aira:slides-syed-zaidi-2026-01-22.pdf|Download}}
   * **[RESEARCH TRACK] 2026.01.15**: Luiz do Valle Miranda,  Postdoc @ Jagiellonian University, [[#section20260115|Knowledge Graphs and Polyvocality in Cultural Heritage and Beyond.]] (//Project CHExRISH//)
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+==== 2026-01-29 ====
+<WRAP column 15%>
+{{ :aira:antonio-teruel-foto.jpeg?200| }}
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+**Speaker**: Antonio Guillen Teruel,  PhD Candidate @ University of Murcia
+**Title**: Calm-Data Generator: A Flexible Framework for Synthetic Dataset Creation Under Concept Drift.
+**Abstract**:
+Calm-Data Generator is designed to produce realistic synthetic datasets exhibiting different types of concept drift, enabling controlled evaluation of machine-learning models in dynamic environments. The framework implements multiple drift mechanisms, supports tabular data with customizable complexity, and provides a flexible API for defining data-generation functions, experimental scenarios, and temporal transitions. Its primary goal is to facilitate reproducible experimentation in concept drift research, allowing researchers to benchmark methods, analyze performance degradation, and study model robustness under shifting data distributions. This presentation will introduce the simulator’s architecture, its main modules, practical use cases, and the types of experiments it enables for applied research.
+**Biogram**:
+Antonio Guillén-Teruel (a.guillenteruel@um.es) is a PhD Student graduated in Mathematics from the University of Murcia in 2020. In 2021 he got a Masters degree in Big Data from the same university and started his Ph.D studies in Informatics. The following year he got a Masters degree in Advanced Mathematics at the University of Murcia. His research focuses on imbalanced problems in Machine Learning (ML), including both in regression and classification problems, as well as the study of concept drift in medical domains for imbalanced datasets.
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+<WRAP clear></WRAP>
 ==== 2026-01-22 ====