Theses and Projects: Difference between revisions

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* (P) Student project

=== * '''New!''' Task Offloading and Resource Allocation Optimization===

With the continuous advancement of the next-generation wireless communication technologies and the population of mobile devices, a variety of Internet of Things (IoT) applications are emerging and seeking efficient task execution paradigms. This topic presents efficient joint task offloading and auction-based resource allocation mechanisms in edge computing, which not only expand the computational capabilities of mobile devices but also enhance the Quality of Service of IoT applications by significantly reducing latency. We expect you have a background in edge computing, optimization algorithms, and programming skills.

Please contact Dongkuo Wu [dongkuo.wu@cs.uni-goettingen.de]

=== * '''New!''' Efficient Live Volumetric Video Streaming System===

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Please contact Yanlong Huang[yanlong.huang@cs.uni-goettingen.de]

=== * '''New!''' Using LLM for Sign Language Translation (B/M/P)===

Sign language is the primary means of communication for the deaf and hard-of-hearing community, yet most people do not understand it. This topic explores the integration of Large Language Models (LLMs) with computer vision to build an advanced sign language translation system - with special focus on overcoming the critical challenge of understanding long, continuous sign language videos. We welcome students passionate about Natural Language Processing (NLP) and Computer Vision (CV) to explore the cutting edge of sign language translation technology.

Please contact Wenfang Wu [wenfang.wu@cs.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.

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 expect you have a background in knowledge graph and programming skills in Python.

Please contact Wenfang Wu [wenfang.wu@cs.uni-goettingen.de]

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

=== * Privacy-preserved Video Analytics===

=== * '''[Closed]''' Privacy-preserved Video Analytics===

This project/thesis topic focuses on the protection of privacy in video analytics.

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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].

=== * AI for networking adaption ===

=== * '''[Closed]''' AI for networking adaption ===

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.

@@ Line 21: / Line 21: @@
 * (P) Student project
+===  * '''New!''' Task Offloading and Resource Allocation Optimization===
+With the continuous advancement of the next-generation wireless communication technologies and the population of mobile devices, a variety of Internet of Things (IoT) applications are emerging and seeking efficient task execution paradigms. This topic presents efficient joint task offloading and auction-based resource allocation mechanisms in edge computing, which not only expand the computational capabilities of mobile devices but also enhance the Quality of Service of IoT applications by significantly reducing latency. We expect you have a background in edge computing, optimization algorithms, and programming skills.
+Please contact Dongkuo Wu [dongkuo.wu@cs.uni-goettingen.de]
 ===  * '''New!''' Efficient Live Volumetric Video Streaming System===
@@ Line 33: / Line 38: @@
 Please contact Yanlong Huang[yanlong.huang@cs.uni-goettingen.de]
+===  * '''New!''' Using LLM for Sign Language Translation (B/M/P)===
+Sign language is the primary means of communication for the deaf and hard-of-hearing community, yet most people do not understand it. This topic explores the integration of Large Language Models (LLMs) with computer vision to build an advanced sign language translation system - with special focus on overcoming the critical challenge of understanding long, continuous sign language videos. We welcome students passionate about Natural Language Processing (NLP) and Computer Vision (CV) to explore the cutting edge of sign language translation technology.
+Please contact Wenfang Wu [wenfang.wu@cs.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.
+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 expect you have a background in knowledge graph and programming skills in Python.
 Please contact Wenfang Wu [wenfang.wu@cs.uni-goettingen.de]
@@ Line 114: / Line 125: @@
 Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]] (B/M/P)
-===   *  Privacy-preserved Video Analytics===
+===   * '''[Closed]''' Privacy-preserved Video Analytics===
 This project/thesis topic focuses on the protection of privacy in video analytics.
@@ Line 129: / Line 140: @@
 [1] Pecam: privacy-enhanced video streaming and analytics via securely-reversible transformation [https://dl.acm.org/doi/abs/10.1145/3447993.3448618].
-===  *  AI for networking adaption  ===
+===  * '''[Closed]''' AI for networking adaption  ===
 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.