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aira:start [2025/04/01 08:05] – [Schedule Spring 2025] mzk | aira:start [2025/04/17 08:34] (current) – [Schedule Spring 2025] mzk | ||
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===== Schedule Spring 2025 ===== | ===== Schedule Spring 2025 ===== | ||
- | * **[PHD TRACK] 2025.04.03**: Dmytro Polishchuk, PhD Candidate @ Jagiellonian University, [[#section20250403|Automated GitHub Repository Quality Evaluation: A Metrics-Based Approach.]] | + | * **[PHD TRACK] 2025.04.24**: Natalia Wojak-Strzelecka, PhD Candidate @ Jagiellonian University, [[#section20250424|Enhancing concept drift detection, explanation and adaptation to changes in industrial data streams.]] |
- | * Meeting link: [[https:// | + | * Meeting link: [[https:// |
* Recording: | * Recording: | ||
* Presentation slides: | * Presentation slides: | ||
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+ | * **[PHD TRACK] 2025.04.03**: | ||
+ | * Meeting link: [[https:// | ||
+ | * Recording: | ||
+ | * Presentation slides: | ||
* **[PHD TRACK] 2025.03.27**: | * **[PHD TRACK] 2025.03.27**: | ||
* Meeting link: [[|The talk will be held stationary in room C-2-10]] | * Meeting link: [[|The talk will be held stationary in room C-2-10]] | ||
- | * Recording: | + | * Recording: |
- | * Presentation slides: | + | * Presentation slides: |
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* **[PHD TRACK] 2025.03.13**: | * **[PHD TRACK] 2025.03.13**: | ||
* Meeting link: [[|offline mode]] | * Meeting link: [[|offline mode]] | ||
- | * Recording: | + | * Recording: |
- | * Presentation slides: | + | * Presentation slides: |
* **[RESEARCH TRACK] 2025.03.06**: | * **[RESEARCH TRACK] 2025.03.06**: | ||
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===== Presentation details ===== | ===== Presentation details ===== | ||
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+ | ==== 2025-04-24 ==== | ||
+ | <WRAP column 15%> | ||
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+ | </ | ||
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+ | **Speaker**: | ||
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+ | **Title**: Automated GitHub Repository Quality Evaluation: A Metrics-Based Approach. | ||
+ | |||
+ | **Abstract**: | ||
+ | In this seminar, we will explore three complementary approaches to handling evolving data in industrial environments. We'll discuss methods for detecting and adapting to domain shifts in data streams, distinguishing between real system failures and normal process changes, and using explainable AI to better understand and interpret concept drift. The presented work combines domain adaptation, drift detection, and XAI to improve the robustness and transparency of machine learning models in real-time settings like manufacturing and healthcare. | ||
+ | |||
+ | **Biogram**: | ||
+ | Natalia has received Bachelor' | ||
+ | </ | ||
+ | <WRAP clear></ | ||
+ | |||
+ | ==== 2025-04-03 ==== | ||
+ | <WRAP column 15%> | ||
+ | {{ : | ||
+ | </ | ||
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+ | <WRAP column 75%> | ||
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+ | **Speaker**: | ||
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+ | **Title**: Automated GitHub Repository Quality Evaluation: A Metrics-Based Approach. | ||
+ | |||
+ | **Abstract**: | ||
+ | This research aims to develop an automated system for evaluating the quality of GitHub repositories using a pre-established quality model. The system will assess repositories based on a variety of quality metrics, such as the commit history and its associated metadata (e.g., size, date, description), | ||
+ | |||
+ | **Biogram**: | ||
+ | Software engineer with a background in the telecom domain, specializing in network management systems and Software Defined Networking (SDN). Experienced in performance engineering, | ||
+ | </ | ||
+ | <WRAP clear></ | ||
==== 2025-03-27 ==== | ==== 2025-03-27 ==== |