NET Wiki

Seminar on Internet Technologies (Winter 2024/2025): Difference between revisions

← Older edit
Stong (talk | contribs)
28 edits
No edit summary
Stong (talk | contribs)
28 edits
 
(20 intermediate revisions by 7 users not shown)
Line 4: Line 4:
{{CourseDetails
{{CourseDetails
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|module=M.Inf.1124
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu];[http://www.net.informatik.uni-goettingen.de/?q=people/tingting-yuan Tingting Yuan]
|ta =[http://www.net.informatik.uni-goettingen.de/?q=people/jiaquan-zhang MSc. Jiaquan Zhang];
|ta =[http://www.net.informatik.uni-goettingen.de/?q=people/jiaquan-zhang MSc. Jiaquan Zhang];
|'''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|'''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|ta = Tong Shen[shen.tong@cs.uni-goettingen.de]
|ta = Tong Shen[shen.tong@cs.uni-goettingen.de]
|time='''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|time='''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|univz=[https://studip-ecampus.uni-goettingen.de/dispatch.php/course/details/index/4f4ce922cd439f8a00f299fec776c727]
}}
}}


Line 31: Line 33:
*Actively and frequently participate in the project communication with the topic advisor
*Actively and frequently participate in the project communication with the topic advisor
**This accounts for 20% of your grade.
**This accounts for 20% of your grade.
* Present the selected topic (20 min. presentations + 10 min. Q&A).
* Present the selected topic '''offline''' (20 min. presentations + 10 min. Q&A).
** This accounts for 40% of your grade.
** This accounts for 40% of your grade.
* Write a report on the selected topic (6-8 pages) (LaTeX Template:[https://www.overleaf.com/latex/templates/template-sobraep-english/vnqtqpynnymb]).
* Write a report on the selected topic (6-8 pages) (LaTeX Template:[https://www.overleaf.com/latex/templates/template-sobraep-english/vnqtqpynnymb]).
Line 38: Line 40:


==Schedule==
==Schedule==
* '''TBD.01.2025''': Deadline for registration to attend the final presentation
* '''31.01.2025''': Deadline for registration to attend the final presentation
* '''TBD.01.2025''' : Final Presentations (Online, wait to decide)
* '''11.02.2025''' : Final Presentations (Offline)
* '''TBD.02.2025(23:59) ''': Deadline for submission of the report (should be sent to the topic adviser!).
* '''27.02.2025(23:59) ''': Deadline for submission of the report (should be sent to the topic adviser!).


== Topics ==
== Topics ==
Line 61: Line 63:
|-
|-
|-
|-
| How to do efficient offline training
| Remote Sensing Image Registration
| In this topic, you will study how to do efficient offline training for reinforcement learning
| In this topic, you will study and apply methods for the registration of multimodal remote sensing images with different resolution.
| Basic programming knowledge, Basic machine learning knowledge, need coding work
| [Tingting Yuan, tingting.yuan@cs.uni-goettingen.de]
|
| Yes
|-
|-
| Change Detection in Satellite Image Time Series
| In this topic, you will study methods to detect changes in land-use, vegetation, etc. in Satellite Image Time Series.
| Basic machine learning knowledge
| Basic machine learning knowledge
| [Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
| [Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
|
|
| No
| Yes
|-
|-
|-
|-
| Satellite Image Pixel Clustering for Change Estimation
| Disaster Monitoring
| In this topic, you will study pixel clustering methods for satellite images and apply their outputs for regression-based estimation of changes between different points in time.
| In this topic, you will study methods to monitor disaster scenarios (e.g. floodings) with aerial images.
| Basic machine learning knowledge
| Basic machine learning knowledge
| [Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
| [Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
Line 96: Line 90:
| In this topic, student will read papers to learn how to detect anomaly edge/graph/subgraph… with the help of GNN.
| 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]
|
| Yes
|-
|-
| The relationship between birds’ distribution and the health of the environment (Project possible)
| Birds are sensitive to environmental pressures and their populations can reflect changes in the health of the environment. By analyzing the change of the distribution of birds, perhaps we may evaluate the health of the environment.
| Basic Python knowledge, correlation analysis
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
|
|
Line 122: Line 108:
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
|
|
| Yes
| No
|-
|-
|-
|-
Line 136: Line 122:
| In this topic, student will study how to use XGNN to predict traffic volumn.
| 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]
|
| Yes
|-
|-
| ML/DL based industrial equipment predictive maintenance (Intern/Project/Thesis possible)
| 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.
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
|
| No
|-
|-
| AI for High-quality Image Restoration and Manipulation (Intern/Project/Thesis possible)
| Image restoration and manipulation are low-level vison problems aiming to either restore the degraded images for higher perceptual quality (such as better color, contrast brightness, etc.) or manipulate image styles content for better understanding or visual-appealing effects. Moreover, such problems also plays key role for many high-level computer vision tasks, including  image detection, recognition and (semantic) segmentation... In this topic, students need to follow the new trends and advances in the area of many sup-problem and explore new methods for completive or superior opportunity for academic and industrial applications.
| Python & CV knowledge.
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
|  
|  
Line 181: Line 151:
|-
|-
|-
|-
| Performance of real 5G communication
| Knowledge Graph Completion
| What are the key QoS requirements for future applications and scenarios? What are the shortcomings of today's 5G network? Where are the bottlenecks? How can performance be improved? In this topic, you will build an open-source 5G communication network from the core to the edge, test and analyze the real performance of 5G.
| What are the Knowledge Graph (KG) requirements for future applications and scenarios? What is the task of Knowledge Graph Completion? What is the correlation between KGs and NLP? How to use popular large language models (LLMs) to assist in the implementation of knowledge graph completion? In this topic, you will learn about KGs and learn to use LLMs to perform a KGC task.
| Network protocol stack & 5G architecture
| Knowledge Graph & NLP
| [Wanghong Yang, wanghong.yang@cs.uni-goettingen.de]
| [Tong Shen, shen.tong@cs.uni-goettingen.de]
|
| Yes
|-
|-
| Emotional Support Conversation Generation
| Does the large language model have emotions? Can it provide emotional support to users? In this topic, you will learn about techniques of large language models, such as prompt engineering and instruction fine-tuning, and use the above approaches to implement the emotional support conversation.
| Large Language Model & Emotional Support
| [Jing Li, jing.li@cs.uni-goettingen.de]
|
| Yes
|-
|-
| Intelligent Routing
| In this topic, you will learn how to configure an environment based on Software-Defined Networking, and then deploy reinforcement learning algorithms on it to achieve automated routing decision.
| Basic knowledge of reinforcement learning, fundamental computer network concepts, and coding work are required.
| [peichen.li@cs.uni-goettingen.de]
|
| Yes
|-
|-
| Rumor control and detection
| This topic focuses on how to analyze social networks, study information propagation models and design rumor control strategies. At the same time, you will consider automatically identifying and preventing the spread of false or misleading information in social networks to help reduce the spread of rumor information.
| Information Propagation  & GCN.
| [Fei Gao, fei.gao@cs.uni-goettingen.de]
|  
|  
| Yes
| Yes
|-
|-
|-
|-
| Low latency transmission mechanism for real-time interactive application
| Resource Optimization in Edge Computing
| There are so many mechanisms designed for providing low latency transmission from application layer adaptive algorithms to transport layer protocols, even from network assistance. However, the incoordination between the upper and lower layers may lead to "negative optimization". How is the transmission performance of the current protocol stack? Which combination performs best? Does the new technology really improve performance? In this topic, you will build a 5G communication simulation network from the core to the edge, test and analyze the latency performance of current mechanisms.
| This topic focuses on designing algorithms to better optimize various resources in edge computing, such as computing resources, storage resources, or network resources to realize a more efficient edge computing system.  
| Network Transmission Improvement & 5G architecture
| Task Scheduling  & Caching & Flow Scheduling.
| [Wanghong Yang, wanghong.yang@cs.uni-goettingen.de]
| [Chi Zhang, chi.zhang@cs.uni-goettingen.de]
|  
|  
| Yes
| Yes
Line 219: Line 213:


* Present your topic to the audience (in English).
* Present your topic to the audience (in English).
* The final presentation will be conducted offline.
* The final presentation will be conducted '''offline'''.
* 20 minutes of presentation followed by 10 minutes of discussion.
* 20 minutes of presentation followed by 10 minutes of discussion.


Retrieved from "https://wiki.net.informatik.uni-goettingen.de/wiki/Seminar_on_Internet_Technologies_(Winter_2024/2025)"