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Seminar on Internet Technologies (Summer 2023): Difference between revisions
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Seminar on Internet Technologies (Summer 2023) (view source)
Revision as of 13:28, 8 March 2023
, 8 March 2023→Topics
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| | | Explainable AI(XAI) / graph neural network (XGNN) | ||
| In this topic, | | In this topic, students study how AI models / GNNs are explained with SOTA papers. | ||
| Basic | | Basic AI / GNN knowledge | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| | | Yes | ||
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| | | Social Media Comments Network (Intern/Project/Thesis possible) | ||
| In this topic you will study methods to crawl the dataset from | | In this topic, you will study methods to crawl the dataset from social networks(e.g. YouTube) and utilize social science network analysis in any topic you are interested in (science/education/language…) to find out the network structure and compare the difference among different topics. | ||
| | | Python skills (Data crawling, cleaning, statistical data analysis, modeling and visualization), basic graph knowledge | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| | | Yes | ||
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| The life-circle of vanished scientific journals (Intern/Project/Thesis possible) | |||
| In this topic, students will mine the information of vanished/(ongoing)/top journals, try to find out the difference features(manually/ML-based method) between journals facing different destinies. | |||
| Python skills (Data Crawling, Cleaning, EDA, Modeling). Basic graph, XAI knowledge is a plus. | |||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | |||
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| Yes | |||
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| Traffic prediction with GNN (Intern/Project/Thesis possible) | |||
| In this topic, students will study how to use XGNN to predict traffic volumn. | |||
| Strong Python skills (Modeling and Visualization). Graph and XAI knowledge. | |||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | |||
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| Yes | |||
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| ML/DL based industrial equipment predictive maintenance (Intern/Project/Thesis possible) | |||
| In this topic, students will study how to use cutting-edge machine learning models to predict when industrial equipment need to be maintained before crashing. | |||
| Strong Python skills (Cleaning, EDA, Modeling and Visualization). XAI knowledge is a plus. | |||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | |||
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| Yes | |||
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| Open topics | |||
| Open topics in Data Science & Applied Statistics, especially XAI | |||
| Depends | |||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | |||
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| Yes | |||
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