Dr. rer. nat. Javad Ghofrani

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

If you are looking for a Master's thesis, Bachelor's thesis, or research internship in the fields of Cyber-physical 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 (more information here)
2. Master/Bachelor: Adaptive Control Strategy in Robot Swarms 
3. Master: Human-Swarm Interaction using Reinforcement learning: (More information here)

Internships:

1. Precise Object Measurement with Mobile Robots for Quality Control
2. development of simulation tools for swarm robotics

Projects

1. literature study on swarm robotics tools 

Useful literature for scientific work:

1. Guidelines for Conducting Software Engineering Research

2. Benchmarking Basics

3. Machine learning Tutorials

Teaching

I am responsible of follwoing courses at University of Luebeck:

• Seminar Bio-inspired Robotics "Cyber Physical Systems"
• Bachelor-Seminar Informatik "Einführung in die disruptiven Technologien für Industrie 4.0"
• Wireless Sensor Networks
• Evolutionary Robotics
• Collective Robotics
• Organic Computing
• Parallel Computer Systems
• Real Time Systems

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