Differences

This shows you the differences between two versions of the page.

--- aira:start [2025/11/25 18:02] – [Schedule Autumn 2025] mtm
+++ aira:start [2026/01/30 11:04] (current) – [Schedule Autumn 2025] mtm
@@ Line 21: / Line 21: @@
 ===== Schedule Autumn 2025 =====
+  * **[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:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQCelBjGaTY3T682gedK5w5RAXB_szxTRJTuLMg2EBRTWgg?e=V2bulY|View]]
+    * 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: [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAV7CU9Jhg1S49QuHoDFG0oAY94si6m4JRgvdvT6fWJdzI?e=RPaa1G|View]]
+    * 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//)
+    * Meeting link:[[https://teams.microsoft.com/meet/3589150835363?p=pX2Mdw519jnSEB0ANJ|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQBnXrZn0ZPxQI7Os_LtMfk3AS9IJnnSQahVtqwoJqFtf-g?e=gmADaw|View]]
+    * Presentation slides:  TDA
+  * **[PHD TRACK] 2026.01.08**: Sabri Manai, PhD Candidate @ Jagiellonian University, [[#section20260108|Counterfactual Guidance for Transparent Hyperparameter Tuning.]]
+    * Meeting link:[[https://teams.microsoft.com/meet/32849199521134?p=lDH0dJpC2Erut6yp2l|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQCT176aHoznSLelGvUYXiNdAX70dN5SXyp5H9b0Ddi8Ngw?e=j7Yrml|View]]
+    * Presentation slides:  {{:aira:slides-sabri-manai-2026-01-08.pdf|Download}}
+  * **[RESEARCH TRACK] 2025.12.18**: Maciej Zięba, Associate Professor @ Wrocław University of Technology, [[#section20251218|Normalizing Flows - fundamental concepts and applications in counterfactual explanations.]]
+    * Meeting link:[[https://teams.microsoft.com/meet/34011375285219?p=OD1aOgi4cwK5D4JUBN|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAF4oJfnkFIR7TVLeNj1ep-AauH7kaQFcmQx8AKa2HvFk0?e=lcCfRQ|View]]
+    * Presentation slides:  {{:aira:slides-maciej-zieba-2025-12-18.pdf|Download}}
+  * **[PHD TRACK] 2025.12.11**: Anna Sofia Lippolis, PhD Candidate @ University of Bologna, [[#section20251211|Enhancing Knowledge Engineering with LLMs.]]
+    * Meeting link: [[https://teams.microsoft.com/meet/35848296892369?p=0t3yTogmgGOsSwYeDO|MS Teams]]
+    * Recording: [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQDOFSfeEBkISrAKy1_qRsl3AVGI18eysApxCWWdZqbUjnM?e=vHo3Li|View]]
+    * Presentation slides: {{:aira:slides-anna-sofia-lippolis-2025-12-11.pdf|Download}}
+  * **[PHD TRACK] 2025.12.04**: Bartłomiej Małkus, PhD Candidate @ Jagiellonian University, [[#section20251204|Towards Explainable Meta-Models for Ensembles of Financial Alphas.]]
+    * Meeting link: [[https://teams.microsoft.com/meet/33172349128262?p=yBHWXyoke6oH4OVDl4|MS Teams]]
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAcdDsqtLGmTZeQB00YM3nJAWXUvYtNa_meXBFT91keV-0?e=zNMcS8|View]]
+    * Presentation slides:  {{:aira:slides-bartlomiej-malkus-2025-12-04.pdf|Download}}
   * **[RESEARCH TRACK] 2025.11.27**: Aleksander Mendyk, Professor PhD, DSc @  Jagiellonian University, [[#section20251120|AI/ML for pharmaceutical sciences – an industrial perspective.]]
     * Meeting link: [[https://teams.microsoft.com/meet/39537797907603?p=jjjJD0gjg5LcGl6eL9|MS Teams]]
-    * Recording:  TDA
+    * Recording:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQDqGs_UjUSkRIm82hi1-KgBAc4MLc-EjcVPaewZ6sYskI4?e=qTmdDd|View]]
-    * Presentation slides:  TDA
+    * Presentation slides:  {{:aira:slides-aleksander-mendyk-2025-11-27.pdf|Download}}
   * **[RESEARCH TRACK] 2025.11.13**: Tomáš Kliegr with the research team @ Prague University of Economics and Business, [[#section20251113|RAG research, LLMs as digital twins, Rule Learning in relational data - perspectives in AI Research .]]
     * Meeting link:[[https://teams.microsoft.com/meet/35466374465161?p=E80GGRrCPxyDKDYomv|MS Teams]]
     * Recording - Barbara Moreová:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQBAZ5wBtjiaTYjBlQDQACWHAQFaeBCECRYAmhZiYB1PI6c?e=G4VFdq|View]]
-    * Recording - Mateusz Ploskonka:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAC5l947emMQoLcwSSWuqhOATaOnpK3jqxWwR-U-EJ0ODs?e=p2R8tL|View]]
-    * Recording - Kateřina Hrudková:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQANTKVda1QPS45yKsybdKAYAZ1oSTeQo4b34J7sfF5pbWw?e=DVxlO5|View]]
     * Presentation slides - Barbara Moreová:  {{:aira:slides-barbara-moreova-2025-11-13.pdf|Download}}
+    * Recording - Mateusz Ploskonka:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAC5l947emMQoLcwSSWuqhOATaOnpK3jqxWwR-U-EJ0ODs?e=p2R8tL|View]]
     * Presentation slides - Mateusz Ploskonka:  {{:aira:slides-mateusz-ploskonka-2025-11-13.pdf|Download}}
+    * Recording - Kateřina Hrudková:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQANTKVda1QPS45yKsybdKAYAZ1oSTeQo4b34J7sfF5pbWw?e=DVxlO5|View]]
     * Presentation slides - Kateřina Hrudková:  {{:aira:slides-katerina-hrudkova-2025-11-13.pdf|Download}}
@@ Line 39: / Line 74: @@
     * Meeting link:[[https://teams.microsoft.com/meet/3127857308764?p=1vVlUBWtvXh3pJVm3z|MS Teams]]
     * Recording - Tomáš Kliegr:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQA6xvsR6r__Sb0uBw018DxdARL_jxuITdNrnlTomJNFcCI?e=SjdjzJ|View]]
-    * Recording - Lukáš Sýkora:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAD1MW0CrT7TbXn7305dHJUAWT51QewwEh9LPyrbfehOj8?e=KfQCx8|View]]
     * Presentation slides - Tomáš Kliegr:  {{:aira:slides-tomas-kliegr-2025-11-06.pdf|Download}}
+    * Recording - Lukáš Sýkora:  [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/IQAD1MW0CrT7TbXn7305dHJUAWT51QewwEh9LPyrbfehOj8?e=KfQCx8|View]]
     * Presentation slides - Lukáš Sýkora:  {{:aira:slides-lukas-sykora-2025-11-06.pdf|Download}}
@@ Line 185: / Line 220: @@
       * Meeting link: [[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1715342946914?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22c96e4eee-96f3-4b0f-88ef-fe65310f5f55%22%7d|MS Teams]]
       * Recording: [[https://ujchmura.sharepoint.com/:v:/t/Section_495645_1/EZe0bw0DZY5LtU3CCvns-6UBp432OE_5pD3_vs7zBOPhiA?nav=eyJyZWZlcnJhbEluZm8iOnsicmVmZXJyYWxBcHAiOiJTdHJlYW1XZWJBcHAiLCJyZWZlcnJhbFZpZXciOiJTaGFyZURpYWxvZy1MaW5rIiwicmVmZXJyYWxBcHBQbGF0Zm9ybSI6IldlYiIsInJlZmVycmFsTW9kZSI6InZpZXcifX0%3D&e=eU3MPT|View]] (if you are not UJ employee, ask Szymon Bobek for access)
-      * Presentation slides: {{ :aira:slides-mateusz-bulat-20240515.pdf |Download}}
+      * Presentation slides: {{ :aira:slides-mateusz-bulat-20240515x.pdf |Download}}
   * **[RESEARCH TRACK] 2024.05.09**: Jason J. Jung [[#20240509| Deep Learning for Anomaly Detection in Multivariate Time Series: Approaches, Applications, and Challenges ]]
     * Meeting link: [[https://teams.microsoft.com/l/meetup-join/19%3aJF1L0935A7eV6s8R9brG5MMYONrqy4XmxPSYLeRMCGM1%40thread.tacv2/1715082246704?context=%7b%22Tid%22%3a%22eb0e26eb-bfbe-47d2-9e90-ebd2426dbceb%22%2c%22Oid%22%3a%22c96e4eee-96f3-4b0f-88ef-fe65310f5f55%22%7d|MS Teams]]
@@ Line 487: / Line 522: @@
-==== 2025-11-27 ====
+==== 2026-01-29 ====
 <WRAP column 15%>
-{{ :aira:aleksander-mendyk-foto.png?200| }}
+{{ :aira:antonio-teruel-foto.jpeg?200| }}
 </WRAP>
 <WRAP column 75%>
-**Speaker**: Aleksander Mendyk, Professor @ Jagiellonian University
+**Speaker**: Antonio Guillen Teruel,  PhD Candidate @ University of Murcia
-**Title**: AI/ML for pharmaceutical sciences – an industrial perspective.
+**Title**: Calm-Data Generator: A Flexible Framework for Synthetic Dataset Creation Under Concept Drift.
 **Abstract**:
-Although reluctantly, pharmaceutical industry follows the footsteps of the other industries into the digital age. Among the digital innovations, data-driven approaches are more and more exploited in the various stages of drug discovery and development, including manufacturing as well. AI/ML is perceived as a disruptive technology capable of bringing safe innovation strategies and in the same time extending well known statistical process control and good practices for the benefit of development of safe and efficacious drugs. This movement towards AI/ML applications is stimulated both by industry itself and Regulatory Agencies like EMA and FDA. This talk will outline current areas and trends in the AI/ML applications for the pharmaceutical sciences, which are the backbone of the marketed medicinal products.
+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**:
-Prof. Aleksander Mendyk, PhD, DSc. is an expert in application of artificial&computational intelligence methods in pharmaceutical technology&biopharmacy, in vitro in vivo correlation (IVIVC) and bioequivalence, Author of over 100 publications. A pharmacist and programmer both in Open Source and commercial applications (R, Python, Java). Currently Head of the Department of Pharmaceutical Technology and Biopharmaceutics, Jagiellonian University-Medical College (JUMC), Kraków, Poland and Vice Dean for Science and Development at the Faculty of Pharmacy JUMC.
+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.
 </WRAP>
 <WRAP clear></WRAP>
-==== 2025-11-20 ====
+==== 2026-01-22 ====
 <WRAP column 15%>
 {{ :aira:zaidi-foto.png?200| }}
@@ Line 528: / Line 563: @@
 </WRAP>
 <WRAP clear></WRAP>
+==== 2026-01-15 ====
+<WRAP column 15%>
+{{ :aira:luis-miranda-foto.jpeg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Luiz do Valle Miranda,  PhD Candidate @ Jagiellonian University
+**Title**: Knowledge Graphs and Polyvocality in Cultural Heritage and Beyond.
+**Abstract**:
+Over the past decade, Knowledge Graphs (KGs) have emerged as one of the most promising technologies for organizing and exploring cultural heritage data. Within this domain, several international standards have been developed to enable interoperable modelling of library, archive, and museum resources, such as CIDOC-CRM and LRMoo. Alongside these standards, new conceptual and methodological trends—such as polyvocality representation—are reshaping how cultural narratives and multiple perspectives can be expressed, connected, and contextualized within KGs. In this talk, I will share insights from my experience developing and applying KGs in two cultural heritage–related projects: CHExRISH and LKG. I will also discuss ongoing and future work on polyvocality in and beyond cultural heritage domains.
+**Biogram**:
+Luiz do Valle Miranda is a Ph.D. candidate at the Jagiellonian University in Technical Computer Science since 2023. He graduated in BA in Cognitive Science at the John Paul II Catholic University of Lublin (2018), received the title of MA in Philosophy from the University of Antwerp (2020) and has a Ph.D. in Philosophy from the Charles University in Prague (2024).
+His research focuses on the development of knowledge-based systems, with particular emphasis on knowledge graphs. He is especially interested in the intersection of language model applications and explicitly represented knowledge, aiming to create intelligent technologies that promote human diversity and flourishing.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2026-01-08 ====
+<WRAP column 15%>
+{{ :pub:about_us:smi.jpeg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Sabri Manai,  PhD Candidate @ Jagiellonian University
+**Title**: Counterfactual Guidance for Transparent Hyperparameter Tuning.
+**Abstract**:
+This research explores how hyperparameter optimization can be made more transparent and interactive by incorporating human preferences into the search process. Instead of treating optimization as a black-box task, the approach uses counterfactual explanations to suggest alternative configurations under user-defined constraints. The method enables domain experts to better understand and guide model behavior, supporting more informed decision-making.
+**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>
+==== 2025-12-18 ====
+<WRAP column 15%>
+{{ :aira:maciej-zieba-foto.png?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Maciej Zięba, Associate Professor @ Wrocław University of Technology
+**Title**: Normalizing Flows - fundamental concepts and applications in counterfactual explanations.
+**Abstract**:
+During the talk, I will begin with a brief introduction to generative flow-based models. Then, I will present practical examples demonstrating how this class of models can be applied in real-world scenarios. I will introduce flows as probabilistic regression models, highlighting their versatility as plug-in components and their generative capabilities for point clouds. I will also discuss how we applied flow-based models to a few-shot regression problem. Finally, I will illustrate how normalizing flows can be used to address counterfactual explanation tasks.
+**Biogram**:
+Maciej Zięba is a research scientist at Tooploox and an Associate Professor at Wroclaw University of Science and Technology, where he received a Ph.D. degree in computer science and a master's degree in economics. He also obtained a master's degree in computer science at the Blekinge Institute of Technology in Sweden. In 2017, he was a visiting scholar at the University of Wollongong (Australia). His research is directed towards deep learning, especially generative models and representation learning. He was the co-author of a variable number of research papers published in influential journals and presented at the top ML conferences, including NeurIPS, AAAI, ICML, CVPR, and ICLR. He is also leading genwro.ai research group (https://genwro.ai.pwr.edu.pl/) at Wroclaw University of Science and Technology.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-12-11 ====
+<WRAP column 15%>
+{{ :aira:anna-lippolis-foto.png?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Anna Sofia Lippolis, PhD Candidate @ University of Bologna
+**Title**: Enhancing Knowledge Engineering with LLMs.
+**Abstract**:
+The development and spread of Large Language Models (LLMs) are having a growing impact on the world of the Semantic Web, profoundly transforming the field of Knowledge Engineering. This field, traditionally characterized by a high degree of manual work and collaboration between technical professionals and domain experts, faces various challenges related to scalability and the continuous evolution of knowledge. In this context, LLMs are emerging in several areas, from law to medicine, as tools that support researchers: from the automatic generation of ontologies to the assessment of the quality and semantic coverage of conceptual models, and even the exploration of analogical reasoning, through which it is possible to identify structural correspondences between different domains. This talk will present current research directions on collaboration between LLMs and researchers for knowledge modeling, within a critical overview of the opportunities offered by these tools for the future of the Semantic Web.
+**Biogram**:
+Anna Sofia Lippolis (she/her) is a PhD student at the University of Bologna, Italy, affiliated with the National Research Council’s Institute for Cognitive Sciences and Technologies (Rome, Italy). Her work investigates how semantic technologies intersect with Digital Humanities research and how AI can automate knowledge-engineering practices.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-12-04 ====
+<WRAP column 15%>
+{{ :aira:bartlmiej-malkus-foto.jpeg?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Bartłomiej Małkus,  PhD Candidate @ Jagiellonian University
+**Title**: Towards Explainable Meta-Models for Ensembles of Financial Alphas.
+**Abstract**:
+One branch of systematic trading research studies large libraries of formulaic alphas: small predictive models built from price and volume data. In practice, these alphas are combined into an ensemble whose composition changes with market conditions. From an ML perspective, this can be viewed as a meta-model that selects and weights weak experts based on their characteristics and the current environment.
+In this talk I will introduce this setting with minimal financial background (cross-sectional returns, information coefficient, long–short factor portfolios), and then reframe it in familiar ML terms. I will show how individual alphas can be treated as models with their own structural and behavioural features, and how this enables clustering them into "families" and reasoning about dynamic ensemble construction. Finally, I will sketch the idea of an explainable meta-model that maps alpha features and market descriptors to ensemble decisions, and highlight open methodological questions and possible research directions.
+**Biogram**:
+Bartłomiej Małkus is a PhD candidate at the Jagiellonian University in Technical Computer Science since 2021. He completed BSc and MSc studies in Computer Science at the AGH University of Science and Technology, and MSc studies in Financial Markets at the Cracow University of Economics. His field of interest are neurosymbolic approaches, prototypical networks, and financial applications of explainable ML. Commercially, he works in IBM on database and master data management solutions.
+</WRAP>
+<WRAP clear></WRAP>
+==== 2025-11-27 ====
+<WRAP column 15%>
+{{ :aira:aleksander-mendyk-foto.png?200| }}
+</WRAP>
+<WRAP column 75%>
+**Speaker**: Aleksander Mendyk, Professor @ Jagiellonian University
+**Title**: AI/ML for pharmaceutical sciences – an industrial perspective.
+**Abstract**:
+Although reluctantly, pharmaceutical industry follows the footsteps of the other industries into the digital age. Among the digital innovations, data-driven approaches are more and more exploited in the various stages of drug discovery and development, including manufacturing as well. AI/ML is perceived as a disruptive technology capable of bringing safe innovation strategies and in the same time extending well known statistical process control and good practices for the benefit of development of safe and efficacious drugs. This movement towards AI/ML applications is stimulated both by industry itself and Regulatory Agencies like EMA and FDA. This talk will outline current areas and trends in the AI/ML applications for the pharmaceutical sciences, which are the backbone of the marketed medicinal products.
+**Biogram**:
+Prof. Aleksander Mendyk, PhD, DSc. is an expert in application of artificial&computational intelligence methods in pharmaceutical technology&biopharmacy, in vitro in vivo correlation (IVIVC) and bioequivalence, Author of over 100 publications. A pharmacist and programmer both in Open Source and commercial applications (R, Python, Java). Currently Head of the Department of Pharmaceutical Technology and Biopharmaceutics, Jagiellonian University-Medical College (JUMC), Kraków, Poland and Vice Dean for Science and Development at the Faculty of Pharmacy JUMC.
+</WRAP>
+<WRAP clear></WRAP>
 ==== 2025-11-13 ====