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Seminar on Internet Technologies (Winter 2023/2024): Difference between revisions
Seminar on Internet Technologies (Winter 2023/2024) (view source)
Revision as of 23:57, 31 October 2023
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| Explainable AI(XAI) / graph neural network (XGNN) | | Explainable AI(XAI) / graph neural network (XGNN) | ||
| In this topic, | | In this topic, student will study how AI models / GNNs are explained by SOTA papers. | ||
| Basic AI / GNN knowledge | |||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | |||
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| Yes | |||
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| Anomaly Detection in Graphs | |||
| In this topic, student will read papers to learn how to detect anomaly edge/graph/subgraph… with the help of GNN. | |||
| Basic AI / GNN knowledge | | Basic AI / GNN knowledge | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| Social Media Comments Network (Intern/Project/Thesis possible) | | Social Media Comments Network (Intern/Project/Thesis possible) | ||
| In this topic, | | In this topic, student will study methods to crawl the dataset from social networks(e.g. X, YouTube) and utilize social 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(Data crawling, cleaning, statistical data analysis, modeling and visualization), basic graph knowledge | | Python(Data crawling, cleaning, statistical data analysis, modeling and visualization), basic graph knowledge would be a plus | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | |||
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| Yes | |||
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| Influence of LLM robots in social networks (Intern/Project/Thesis possible) | |||
| In this topic, student will study methods to crawl the data of LLM robots from social networks(e.g. X, Facebook) and utilize NLP and SNA to evaluate the influence of LLM robots in a specific topic. | |||
| Python(Data crawling, cleaning, statistical data analysis, modeling and visualization), basic graph knowledge would be a plus | |||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| The life-circle of vanished scientific journals (Intern/Project/Thesis possible) | | The life-circle of vanished scientific journals (Intern/Project/Thesis possible) | ||
| In this topic, | | In this topic, student 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(Data Crawling, Cleaning, EDA, Modeling). Basic graph, XAI knowledge is a plus. | | Python(Data Crawling, Cleaning, EDA, Modeling). Basic graph, XAI knowledge is a plus. | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| Traffic prediction with GNN (Intern/Project/Thesis possible) | | Traffic prediction with GNN (Intern/Project/Thesis possible) | ||
| In this topic, | | In this topic, student will study how to use XGNN to predict traffic volumn. | ||
| Python(Modeling and Visualization). Graph and XAI knowledge. | | Python(Modeling and Visualization). Graph and XAI knowledge. | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| ML/DL based industrial equipment predictive maintenance (Intern/Project/Thesis possible) | | ML/DL based industrial equipment predictive maintenance (Intern/Project/Thesis possible) | ||
| In this topic, | | In this topic, student will study how to use cutting-edge machine learning models to predict when industrial equipment need to be maintained before crashing. | ||
| Python(Cleaning, EDA, Modeling and Visualization). XAI knowledge is a plus. | | Python(Cleaning, EDA, Modeling and Visualization). XAI knowledge is a plus. | ||
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | | [Zhengze Li, zhengze.li@cs.uni-goettingen.de] | ||
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| [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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