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See a [https://wiki.net.informatik.uni-goettingen.de/w/images/5/5a/NETGroup_Poster-Jan2021.pdf poster] for a general overview, an [http://www.net.informatik.uni-goettingen.de/?q=research anchor] to our research activities, a list of [https://wiki.net.informatik.uni-goettingen.de/w/images/a/a3/Social_Computing_publications.pdf social computing related] or networking-related publications, and the  
See a [https://wiki.net.informatik.uni-goettingen.de/w/images/5/5a/NETGroup_Poster-Jan2021.pdf poster] for a general overview, an [http://www.net.informatik.uni-goettingen.de/?q=research anchor] to our research activities, a list of [https://wiki.net.informatik.uni-goettingen.de/w/images/a/a3/Social_Computing_publications.pdf social computing related] or networking-related publications, and the  
[http://www.net.informatik.uni-goettingen.de/?q=news/annual-report-2020-best-wishes-2021 annual report(s)] for our recent activities.
[http://www.net.informatik.uni-goettingen.de/?q=news/annual-report-2020-best-wishes-2021 annual report(s)] for our recent activities.
== Joint PhD Program with University of Sydney ==
From September 2024 on there will be the possibility to start a joint PhD with the University of Sydney (Australia). PhD students will stay in both Göttingen and Sydney for at least one year and can achieve two PhD degrees.
For more information, please contact Prof. Xiaoming Fu [fu@cs.uni-goettingen.de].
In November/December 2023, Fabian visited research groups in Melbourne and Sydney. Impressions of his visit can be seen here: [[Media:australia.pdf | pdf]]


== Open Theses and Student Project Topics ==
== Open Theses and Student Project Topics ==
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===  * '''New!''' 3D natural hazard simulator  ===
===  * '''New!''' Efficient Live Volumetric Video Streaming System===
 
The exponential growth of digital data and multimedia content necessitates robust and efficient systems to handle the streaming of high-resolution, three-dimensional volumetric videos. These videos offer a more immersive and realistic experience, making them increasingly used in various sectors such as virtual reality, augmented reality, and entertainment. The challenge here lies in creating a system that can handle the high-bandwidth and computation-intensive demands of live volumetric video streaming while ensuring the delivery of a seamless and high-quality user experience. This project conceptualizes the development and optimization of efficient algorithms and systems to handle volumetric video streams, mitigating bandwidth cost and latency issues. We expect you to have a background in video streaming technologies, computer vision, and programming skills.
 
Please contact Yanlong Huang[yanlong.huang@cs.uni-goettingen.de]
 
===  * '''New!''' Edge-Cloud Orchestration for LiDAR-based Traffic Analysis===
 
The imminent era of smart cities and autonomous vehicles paves the way for the deployment and operation of advanced monitoring and processing systems. Among these, LiDAR technology stands out for its ability to provide high-resolution, three-dimensional traffic data, becoming an essential component for efficient traffic analysis and management. However, the computation-intensive and latency-sensitive nature of LiDAR data processing poses significant challenges and dictates the need for efficient orchestration between edge and cloud computing resources. Edge-Cloud Orchestration offers an innovative solution to this problem by bridging the gap between these two technologies, enabling the low-latency processing of complex LiDAR data. It would be good if you have a background in point cloud processing/cloud computing, K8s, and programming skills.
 
Please contact Yanlong Huang[yanlong.huang@cs.uni-goettingen.de]
 
===  * '''New!''' Blockchain-based Spectrum and Computation Resources Sharing in Mobile Networks===
 
The sixth-generation (6G) system is widely envisioned as a global network consisting of pervasive devices that interact with each other. Besides exchanging information, these peer entities also share heterogeneous and distributed network resources. Blockchain is a promising technology to secure resource sharing in a peer-to-peer way. We need students for this topic. We expect you have a background in computer network and programming skills in Python.
 
Please contact Jin Xie [jin.xie@stud.uni-goettingen.de]
 
===  * '''New!''' Using LLM for Sentiment Knowledge Graph Construction (B/M/P)===
 
Constructing a sentiment knowledge graph using Large Language Models (LLMs) like ChatGPT involves leveraging the model's capabilities to understand and analyze textual data, extract entities and relationships, perform sentiment analysis, and organize the information into a graph structure.  We need students for this topic. We expect you have a background in knowledge graph and programming skills in Python.
 
Please contact Wenfang Wu [wenfang.wu@cs.uni-goettingen.de]
 
===  * '''New!''' Using LLM for Knowledge Graph Completion (B/M/P)===
 
Large language models (LLMs), such as ChatGPT and GPT-4 (OpenAI, 2023), have extensive internal knowledge repositories from their vast pretraining corpora, which can be used as an extra knowledge base to alleviate information scarcity for the long-tail entities in Knowledge Graphs. However, there is no effective workflow design for LLM on KGC tasks. How to leverage the LLM to perform reasoning on the KG Completion (KGC) task is a noteworthy and significant topic. We need students for this topic. We expect you to have a background in knowledge graph and LLMs, you'd better have a programming skill in Python.
 
Please contact Tong Shen [shen.tong@cs.uni-goettingen.de]
 
===  * '''New!''' Tree Growth Detection using Satellite Images and Computer Vision Methods (B/M/P) ===
 
A tree planting project in Madagascar was initiated several years ago. The outcomes of this project shall now be evaluated by analyzing satellite images of the study area with Computer Vision methods. In a first step, very high resolution (VHR) satellite images from 2023 with a resolution of 0.5m will be used to identify trees with object detection / semantic segmentation. In the next step a lower resolution (5m) satellite image time series starting in 2015 will be used for change detection to identify, in which locations the project was  (un)successful.
 
Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]
 
===  * '''New!''' Image-to-Image Translation of Different Nightlight Image Types (B/M/P) ===
 
Nightlight intensities have been proven to be a good indicator for socio-economic status. However, for long-term temporal analyses their use can be challenging, as different satellites for sensing nightlight intensities operated at different times (DMSP OLS 1992-2014 and VIIRS 2012-2023). Both types differ not only in resolution, but there is also a big discrepancy in the optical appearance and value ranges. To obtain consistent nightlight images for temporal analysis, Image-to-Image Translation methods shall be used in this project/thesis for the conversion between both types. Finally the performance of the translated and original nightlight images for a regression on socio-economic indicators shall be evaluated.
 
Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]
 
===  [Occupied] Satellite Image Indices and Machine Learning for Socio-economic Estimation (B/M/P) ===
 
There are several indices, which can be derived from satellite images. For example the Normalized Difference Vegetation Index (NDVI) indicates the presence and condition of vegetation, while the Normalized Difference Built-up Index (NDBI) indicates the presence of built-up areas such as buildings or roads. The distributions of these and other indices may have different explanatory power to estimate the socio-economic status of locations. Therefore in this project/thesis the regression performance of machine learning models - using statistics of these indices as features - to estimate socio-economic indicators shall be evaluated for the individual and also combined indices. Optionally, Convolutional Neural Networks (CNNs) can be applied additionally, which take the derived index images as input.
 
Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]
 
===  * 3D natural hazard simulator  ===


The aim of the project is to simulate representative natural hazards for hazard response, such as flooding and forest fire. A natural hazard response simulator will be implemented for both visualization and performance validation. For example, we can visualize the flooding of 2021 in Germany, and then validate the performance of drone deployment in hazard sensing and emergency communication. Here, we introduce some related works in virtual 3D scene which may help you to understand this project, e.g., Agents Toolkit (ML-Agents) [1], DisasterSim [2] and Airsim [3].
The aim of the project is to simulate representative natural hazards for hazard response, such as flooding and forest fire. A natural hazard response simulator will be implemented for both visualization and performance validation. For example, we can visualize the flooding of 2021 in Germany, and then validate the performance of drone deployment in hazard sensing and emergency communication. Here, we introduce some related works in virtual 3D scene which may help you to understand this project, e.g., Agents Toolkit (ML-Agents) [1], DisasterSim [2] and Airsim [3].
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Please contact  Prof. Xiaoming Fu [fu@cs.uni-goettingen.de](B/M/P)
Please contact  Prof. Xiaoming Fu [fu@cs.uni-goettingen.de](B/M/P)


===  * '''New!''' UAV trajectory planning for disaster monitoring  ===
===  * '''[Occupied]''' OCR (Optical Character Recognition) and Annotation Transfer ===
Satellite images will be used for segments hazard regions and level of danger; next, combining image/video analytics/geo-information to find out interest of points (e.g., buildings); last, planning multiple UAVs' trajectory for monitoring detail informations.


Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de], Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P)\\
The aim of the project is to develop a tool/software that can convert a printed paper with annotations and text into electronic versions with text highlighting and annotations. The successful candidate will be responsible for developing this tool/software that can perform the following tasks:


1. Text Alignment: Develop algorithms to align the text in the electronic version with the original printed paper.


2. Annotation Recognition: Develop software that can recognize annotation areas in the printed paper and transfer them to the electronic version.


3. Transfer Annotations: Transfer annotations and highlighting from the paper-based article to the electronic version.


===  * '''New!''' OCR (Optical Character Recognition) and Annotation Transfer ===
[1] https://medium.com/analytics-vidhya/opencv-perspective-transformation-9edffefb2143


The aim of the project is to develop a tool/software that can convert a printed paper with annotations and text into electronic versions with text highlighting and annotations. The successful candidate will be responsible for developing this tool/software that can perform the following tasks:
[2] https://developer.adobe.com/analytics-apis/docs/2.0/guides/endpoints/annotations/


1. Text Alignment: Develop algorithms to align the text in the electronic version with the original printed paper.
[3] https://developer.adobe.com/document-services/apis/pdf-services/
 
2. Annotation Recognition: Develop software that can recognize annotation areas in the paper-based article and transfer them to the electronic version.
 
3. Transfer Annotations: Transfer annotations and highlighting from the paper-based article to the electronic version.


[1] https://developer.adobe.com/document-services/apis/pdf-services/
[4] https://www.cameralyze.co/blog/how-can-i-detect-lines-in-images-or-pdfs


Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]] (B/M/P)
Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]] (B/M/P)


===  [Occupied] Privacy-preserved Video Analytics===
===  * Privacy-preserved Video Analytics===
This project/thesis topic focuses on the protection of privacy in videos analytics.
This project/thesis topic focuses on the protection of privacy in video analytics.


The project involves three key tasks:
The project involves three key tasks:


1) Implementation of a system utilizing YOLO and CycleGANs/DataGen for video analysis and processing. Code for this is already available for use.
1) Implementation of a system utilizing YOLO and CycleGANs/DataGen for video analysis and processing. The code for this is already available for use.


2) Development of a privacy protection mechanism by adjusting the level of blur applied to the video, taking into account a trade-off between inference accuracy (e.g. detection by YOLO) and the level of privacy protection.
2) Development of a privacy protection mechanism by adjusting the level of blur applied to the video, taking into account a trade-off between inference accuracy (e.g., detection by YOLO) and the level of privacy protection.


3) Optimization of the blur level for Pan-tilt-zoom cameras, to ensure that the system is effective at capturing key visual information while still preserving privacy.
3) Optimize the blur level for Pan-tilt-zoom cameras to ensure that the system effectively captures key visual information while still preserving privacy.


Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de] (B/M/P)
Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de] (B/M/P)
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[1] Pecam: privacy-enhanced video streaming and analytics via securely-reversible transformation [https://dl.acm.org/doi/abs/10.1145/3447993.3448618].
[1] Pecam: privacy-enhanced video streaming and analytics via securely-reversible transformation [https://dl.acm.org/doi/abs/10.1145/3447993.3448618].


===  * '''New!''' AI for networking adaption  ===
===  * AI for networking adaption  ===
In this project/theses topic, you will explore how to make AI meets networking requirements (e.g., fluctuating network states).  
In this project/theses topic, you will explore how to make AI meets networking requirements (e.g., fluctuating network states).  
You will (1) deploy and test Genet[1]; (2)extend the Genet environment to multi-client environment (e.g., ABR); (3) deploy multi-agent algorithms on Genet and valid the performance.
You will (1) deploy and test Genet[1]; (2)extend the Genet environment to multi-client environment (e.g., ABR); (3) deploy multi-agent algorithms on Genet and valid the performance.
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Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de], Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P)
Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de], Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P)
=== * [Occupied] Convolutional neural networks and transfer learning for change estimation with satellite images ===
Satellite images are a popular input to estimate wealth measures (e.g. income or consumption) on the spatial scale, so to determine which locations are richer or poorer than others within a certain time interval. However, the use of these images for estimation of the changes in these measures over time for given locations is investigated only insufficiently. This project/thesis topic intends to address this problem by applying Convolutional Neural Networks (CNNs) with Transfer Learning on a small data set of images from villages in Thailand and Vietnam. Among other things, this topic contains experimental comparisons of different approaches and CNNs in both Regression and Classification.
Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de](B/M/P)


=== * [Occupied] AI for Games  ===  
=== * [Occupied] AI for Games  ===  
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=== New video/image encoding for DNN applications ===
=== [Closed] Super resolution technique for efficient video delivery ===


* '''New!''' Video/image encoding is important for image/video storage/delivery on Internet. It reduces file size by eliminating spatial-temporal redundancy. Along with the development of Deep Neural Network in the computer vision(CV) community, video/image encoding for DNN applications is becoming more and more crucial. This project attempts to compare the difference between video/image encoding for QoE and DNN applications; and explore the design space in the video/image encoding for DNN applications. We expect you have Digital Image Process and Computer Vision background, as well as programming skills like Python and C/C++.
Super-resolution (SR) is one of the fundamental tasks in Computer vision. Video delivery on Internet or in WAN is important for various applications, eg., video analytics and video viewing. This project attempts to explore the potential of SR for video delivery. We expect you have Data Science and Computer Vision background, as well as programming skills like Python.


Please contact Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P)
Please contact Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P)
=== Super resolution technique for efficient video delivery ===
* '''New!''' Super-resolution (SR) is one of the fundamental tasks in Computer vision. Video delivery on Internet or in WAN is important for various applications, eg., video analytics and video viewing. This project attempts to explore the potential of SR for video delivery. We expect you have Data Science and Computer Vision background, as well as programming skills like Python.
Please contact Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P)


=== [closed]  Assessing city livability with big data ===
=== [closed]  Assessing city livability with big data ===
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Please contact  Dr.Tingting Yuan [tingting.yuan@cs.uni-goettingen.de ] and Weijun Wang [weijun.wang@informatik.uni-goettingen.de](B/M/P)
Please contact  Dr.Tingting Yuan [tingting.yuan@cs.uni-goettingen.de ] and Weijun Wang [weijun.wang@informatik.uni-goettingen.de](B/M/P)
-->


== Ongoing Topics ==
== Ongoing Topics ==
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|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Description'''
|{{Hl2}} |'''Student'''
|{{Hl2}} |'''Student'''
 
|-
| OCR (Optical Character Recognition) and Annotation Transfer (Bachelor Project+Thesis)
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan]
|
|
| Assigned to Jiaying
|-
| AI for Games (Bachelor Project+Thesis)
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan]
|
|
| Completed by Jason
|-
| Neural video analytics(Master Thesis)
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan]
|
|
| Completed by Mai
|-
| Submodel Federated learning (Bachelor Project + Thesis)
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan]
|
|
| Completed by Zilin
|-
|-
|Bio-Data analysis (Student project)
|Bio-Data analysis (Student project)
Hyanlon
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