Dr. rer. nat. Javad Ghofrani

Photo of Javad  Ghofrani

Interim Professorship in Service Robotics

Ratzeburger Allee 160
23562 Lübeck
Building 64, Room 120 (2nd Floor)

Phone:+49 451 3101 6322
Fax:+49 451 3101 6304



Head of Intelligent Systems Lab 

Research Interests

  • Swarm Intelligence and Collective Robotics
  • Distributed Intelligent Systems
  • Software and System Architectures
  • Software Product Line Engineering and Software Variability Management,
  • Microservices and SOA

Bachelor and Master Thesis Offers

If you are looking for a Master's thesis, Bachelor's thesis, or research internship in the fields of Cyberphysical Systems, Software Architectures, Industrie 4.0, and utilization of Machine Learning in these domains feel free to contact me. Following topics are available: 

  1. Master/Bachelor: Human-in-the-loop Collection Decision Making (Weitere Informationen: here
  2. Master/Bachelor: Applications of Intelligent Sensors in Smart Cities(weitere Informationen: here)
  3. Master/Bachelor: Adaptive Control Strategy in Robot Swarms 
  4. Master: Anwendung von Reinforcement Learning für die Entwicklung eines Assistenzsystems für die Interaktion zwischen Mensch und Schwarm. (weitere Informationen: here)
  5. Master/Bachelor: Anwendung des 3D-Drucks in der industriellen Automatisierungstechnik (weitere Informationen: here)
  6. Bachelor: Analysis of swarm robotics tools (contact javad.ghofrani(at) for details)


Useful literature for scientific work:

1. Guidelines for Conducting Software Engineering Research

2. Benchmarking Basics

3. Machine learning Tutorials


I am responsible of follwoing courses at University of Luebeck:


Writing Scientific Work

Please note that your scientific work (e.g., master thesis) should cover following parts

  1. Introduction (which explains the problem that you are aiming and why it is important to solve that specific problem)
  2. Related work ( you should do some literature research and analysis of similar work done by others to show that you work is interesting for some scientific or industrial communities)
  3. Propose your solution as an abstract model without implementations
  4. Describe your implementation of the solution
  5. Design of evaluation and experiments for showing that your solution is working
  6. Show the results and discuss their details, and eventually compare your results with the results from part 2 (Related Work)
  7. Conclusion