Betreute Abschlussarbeiten

  • Issue Specific Audio Event detection using Deep Learning (Master, October 2019)
  • Videobasiertes Situationsbewusstseinssystem mit Datenschutz (Master, July 2020)
  • Entwurf und Implementierung eines auf Schwingungssignalen basierenden Kontextwahrnehmungssystems (Master, November 2020)
  • Kontextbewusstes Internet der Dinge Plattformdesign und Implementierung (Bachelor, November 2020)
  • Schätzung der binären Laufrichtung und der Anzahl der gehenden Personen mithilfe von maschinellem Lernen (Bachelor, November 2020)
  • Design und Implementierung eines KI-orientierten 3D Smart Home Simulators (Bachelor, März 2021)
  • AI-basierter Streaming-Massenmessungsansatz Entwurf und Implementierung von Schlüsselalgorithmen (Master, TBD)
  • DeepWolf: Data set construction toward artificial intelligence-based identity recognition of werewolf (Bachelor, TBD)
  • DeepWolf: Artificial intelligence-based identity recognition in the Game of Werewolf (Semantic Analysis Direction) (Master, TBD)
  • DeepWolf: Artificial intelligence-based identity recognition in the Game of Werewolf (Intonation, Sentiment Analysis Direction) (Master, TBD)

Topics for Theses

In our research, we are concerned with the AI-based context recognition and context based machine reasoning.

Many different types of sensors provide a wealth of data. This provides the feasibility for the machine to recognize this environment. Traditional situational awareness methods are often based on the setting of rules. It is not easy to perceive more abstract or obscure information. With the efficient implementation of neural network back-propagation algorithms on GPUs, artificial intelligence technology based on deep neural networks has been pushed to the hot spot of the times. Our project uses deep neural networks to learn multi-mode sensor signal data so that the machine can perceive the complex situation in the area where the sensor is located thus offer humans more intelligent supporting services.

With the help of sensors, a digital world can be established that corresponds to the real world. That is the digital twins. In the digital world, computer hardware, computing algorithms, and artificial intelligence methods can be used. Thus, some kind of approach based on this data makes it possible to reason about the real-world situation and requirements. So as to provide better services for mankind in the real-world. Based on the above methods, practical applications such as judicial forensics and smart homes become feasible to benefit humanity.

If you are interested in any of these problems, write me a mail and we can think of a topic that fits into my research area and your skills/interests.

Open Topics

Research Interests

  • Machine Learning, Deep Learning, Reinforcement Learning and Machine Learning based Application
  • Context-aware Computing
  • AI-based Context Recognition
  • Cyber-Physical AI Systems
  • Pervasive Computing and Internet of Things

Selected Projects

  • Research project “Privacy Mechanisms”, funded by Evonik

Academic Services

Journal Reviewer

  • IEEE Access


2021 (1)

  • Hussain, Shabir and Yu, Yang and Ayoub, Muhammad and Khan, Akmal and Rehman, Rukhshanda and Wahid, Junaid Abdul and Hou, Weiyan
    IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19
    In: Applied Sciences

2020 (2)

  • Yu, Yang and Waltereit, Marian and Matkovic, Viktor and Hou, Weiyan and Weis, Torben
    Deep Learning-based Vibration Signal Personnel Positioning System
    In: IEEE Access
  • Yu, Yang and Weis, Torben
    A Privacy-Protecting Indoor Emergency Monitoring System based on Floor Vibration
    In: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers

2013 (1)

  • Yu, Yang
    Temperature-controlled water saving valve
    In: Patent {CN}202812427U

2012 (2)

  • Yu, Yang
    Large powder material storage
    In: Patent {CN}202509831U
  • 于洋(Yu, Yang)
    In: 中国新通信




WiSe 20/21

SoSe 2020

WiSe 19/20

WiSe 18/19

Yang Yu

Wissenschaftlicher Mitarbeiter



  • Gebäude BC, Raum 317
  • Bismarckstr. 90 47057 Duisburg, Deutschland

Consultation hour

Nach Vereinbarung


seit 06/2018

Doktorand, Wissenschaftlicher Mitarbeiter, Fachgebiet Verteilte Systeme, Universität Duisburg-Essen


Master of Science in Eingebettet Systeme Ingenieurwesen, Universität Duisburg-Essen

10/2015 - 06/2018

Studium der Eingebettet Systeme Ingenieurwesen, Universität Duisburg-Essen

09/2014 - 09/2015

Laborassistent, Zhengzhou Universität

06/2013 - 09/2015

Chief Information Officer, Assistent des Präsidenten, Anyang Cenluxuriant Silo Co., Ltd.


Bachelor of Engineering in Kommunikation Ingenieurwesen, Zhengzhou Universität

07/2009 - 06/2013

Studium der Kommunikation Ingenieurwesen, Zhengzhou Universität