Key Highlights
A snapshot of my current academic journey and research focus in artificial intelligence
University of Göttingen
Currently pursuing Ph.D. in Computer Science
Eschbach GmbH
Doctoral researcher in industrial AI applications
AI & NLP Focus
Deep Learning, Natural Language Processing, Data Mining
3+ Years Experience
Machine Learning, Academic research, and tutoring
About Me
I am a dedicated doctoral researcher passionate about advancing artificial intelligence technologies and their practical applications in industrial settings.
Research Interests
Deep Learning
Neural networks and advanced architectures
Natural Language Processing
Text analysis and language understanding
Data Mining
Knowledge discovery from large datasets
Data Visualization
Interactive and insightful data representation
Data Science
Statistical analysis and machine learning
Education
Ph.D. in Computer Science - Artificial Intelligence
University of Göttingen
Chair for Scientific Information Analytics, Prof. Bela Gipp. Focus: Natural Language Processing and its applications in industrial settings, in collaboration with Eschbach GmbH.
M.Sc. Computer Science - Artificial Intelligence
University of Freiburg
Thesis: Beyond WCSPH - Advancing SPH Simulations with Global Pressure Solvers and Boundary Handling Methods. Advisor: Prof. Dr. M. Teschner, Grade: 1.0.
B.Sc. Computer Science
University of Freiburg
Thesis: Solving Flatland with Multi-Agent Pathfinding (MAPF). Advisor: Prof. Dr. B. Nebel, Grade: 1.7.
Technical Skills
Programming Languages
Frameworks & Libraries
Tools & Technologies
Languages
Professional Experience
My journey through research, industry experience, and academic contributions in the field of artificial intelligence and computer science.
Doctoral Researcher, NLP and AI
Eschbach GmbH
Spearheading the creation and optimization of innovative NLP models to elevate industrial AI applications.
Key Responsibilities:
- •NLP Model Development: Creating and optimizing innovative NLP models for industrial AI applications
- •Algorithm Integration: Driving deployment of tailored NLP algorithms within the Shiftconnector platform
- •Enhancing communication and efficiency within industrial systems
- •Collaborating with AI team on cutting-edge research projects
Technologies Used:
Full Internship, Machine Learning Engineer
Eschbach GmbH
Enhanced SAS service through strategic refactoring, introduction of automated data analysis, machine learning capabilities, and advanced API/database technologies.
Academic Tutor, Graph Theory
University of Freiburg
Institute for Computer Networks and Telematics. Helped students understand and apply graph theory concepts.
Academic Tutor, Advanced Programming
University of Freiburg
Institute for Algorithms and Data Structures. Guide students in mastering advanced programming techniques (C++).
Academic Tutor, Databases and Information Systems
University of Freiburg
Institute for Databases and Information Systems. Teach database systems and related information management concepts.
Research & Projects
Exploring the frontiers of artificial intelligence through academic research, innovative projects, and practical applications in industrial settings.
Thesis Projects
Beyond WCSPH - Advancing SPH Simulations with Global Pressure Solvers and Boundary Handling Methods
Advanced research in Smoothed Particle Hydrodynamics (SPH) simulations, developing novel algorithms with global pressure solvers and boundary handling methods under Prof. Dr. M. Teschner.
Key Achievements:
- •Developed global pressure solvers for SPH simulations
- •Implemented advanced boundary handling methods
- •Improved computational efficiency and accuracy in fluid dynamics
- •Comprehensive analysis of WCSPH limitations and solutions
Technologies:
Solving Flatland with Multi-Agent Pathfinding (MAPF)
Implementation and optimization of multi-agent pathfinding algorithms for the Flatland railway optimization challenge under Prof. Dr. B. Nebel, focusing on conflict resolution and efficient path planning.
Key Achievements:
- •Implemented multiple MAPF algorithms for railway optimization
- •Developed conflict resolution strategies for multi-agent systems
- •Applied AI planning techniques to real-world railway scenarios
- •Created comprehensive algorithm evaluation framework
Technologies:
Current Research Areas
Natural Language Processing
Advanced NLP techniques for industrial applications
Focus Topics:
Industrial AI Applications
Practical implementation of AI in manufacturing and production
Focus Topics:
Deep Learning Architectures
Novel neural network designs for specific domain problems
Focus Topics:
Get In Touch
I'm always open to discussing research opportunities, collaborations, or just having a conversation about AI and technology. Feel free to reach out!