About
I am a final-year Computer Science student at the University of Tübingen, currently conducting my bachelor's thesis at the Max Planck Institute for Intelligent Systems (MPI-IS), Flight Robotics and Perception Group. My research focuses on computer vision for robotics and efficient machine learning systems for edge deployment.
Research Interests
- Edge AI and real-time inference
- Computer vision for robotics
- Autonomous systems perception
- Visual re-identification systems
- Sim-to-real transfer learning
Current Research
Bachelor Thesis: Viewpoint-Aware Animal Re-Identification
Flight Robotics & Perception Group, Max Planck Institute for Intelligent Systems
At the Flight Robotics and Perception group, I am developing a novel AI solution to enhance animal re-identification in the RAPID pipeline. My work focuses on integrating a 2D pose estimator and a specialized viewpoint estimation module to address perspective-based mismatches. The project emphasizes efficient edge deployment, ensuring high-accuracy orientation filtering and real-time inference speeds for drone-based hardware.
Supervisors: Prof. Andreas Geiger, Jun. Prof. Dr. Aamir Ahmad, PhD student András Zábó
Experience
Max Planck Institute for Intelligent Systems
Student Researcher - GRADE Project, February 2026 - Present
Building realistic dynamic simulation environments for robotics research, enabling high-quality synthetic data generation and advanced perception system validation.
Tübingen AI Center
Student Researcher, February 2026 - Present
Designing intelligent interfaces for scientific publication interaction, focusing on how AI systems can facilitate researcher understanding and engagement with research outputs.
University of Tübingen - Effekt Research Group
Student Research Assistant, April 2025 - October 2025
Developed an AI-assisted programming environment for the Effekt programming language. Created a VS Code extension integrating static compiler information with autonomous code generation agents, enabling context-aware intelligent code suggestions through a novel typed placeholder interface.
Marelli Automotive Lighting
Software Engineer (Working Student), March 2024 - October 2024
Optimized a large-scale engineering system, reducing critical load time from 60 seconds to 5 seconds through systematic performance analysis and architectural improvements. Focused on scalable system design and real-time software reliability for automotive applications.
Education
University of Tübingen
B.Sc. Computer Science, October 2023 - June 2026
Grade: 1.2
Thesis: Viewpoint-aware animal re-identification from drone images
Specialization: Artificial intelligence, programming language design, machine learning systems
Stockholm University
Exchange Semester - Computer Science, August 2025 - February 2026
Advanced courses in machine learning and AI systems:
- Data Science (Grade A)
- Embedded Machine Learning (Grade A)
- Explainable AI (Grade A)
- Quantum Computing (Grade A)
Awards & Recognition
- Deutschlandstipendium (Germany Scholarship), 2025-2027
- Amazon Future Engineer Program, 2025-2027
- Erasmus+ Exchange Scholarship
Contact
LinkedIn: https://www.linkedin.com/in/jakub-schwenkbeck
GitHub: github.com/JakubSchwenkbeck
Location: Tübingen, Germany