About
I am a Master's student in Machine Learning at KTH in Stockholm with a background in applied AI, edge computing, and robotic perception. During the final year of my Computer Science Bachelor's, I researched at the Perceiving Systems Department in the Max Planck Institute for Intelligent Systems (MPI-IS), developing machine learning models for edge-based drone perception and realistic dynamic simulation environments.
Additionally, my experience spans building AI automation pipelines at the Tübingen AI Center, developing AI developer tools for VS Code, and optimizing large-scale software in the automotive industry.
Research Interests
- Edge AI and real-time inference
- Computer vision for robotics
- Autonomous systems perception
- Visual re-identification systems
- Sim-to-real transfer learning
Featured Research
Bachelor Thesis: Viewpoint Estimation for Animal Re-Identification on Edge Devices
Flight Robotics & Perception Group, Max Planck Institute for Intelligent Systems
Developed a lightweight, two-stage computer vision pipeline for edge platforms that extracts 2D pose data and utilizes a neural network to estimate the azimuth angle ($\phi$) of equids. This module mitigates perspective-based mismatches for animal re-identification from UAVs. The system achieved 86.7% accuracy running at 27 FPS on edge hardware, maintaining a 9 FPS full-system throughput within the RAPID pipeline.
- Research Output: Manuscript in preparation targeting submission to ICRA 2027.
- Code: GitHub Repository
Supervisors: Jun. Prof. Dr. Aamir Ahmad and András Zábó | Examiner: Prof. Andreas Geiger
Experience
Max Planck Institute for Intelligent Systems
Research Assistant - Robotic Simulation (GRADE), February 2026 - June 2026
Generated realistic, animated dynamic simulation environments to support advanced robotic simulation and perception tasks, enabling the extraction of high-quality synthetic data.
Tübingen AI Center
Research Assistant - Machine Learning Engineering, February 2026 - July 2026
Engineered AI and data orchestration pipelines using n8n to autonomously process new scientific publications. Partnered with the core software engineering team to build and deploy the production backend, fully automating the retrieval, management, and dynamic presentation of the AI Center's research portfolio.
University of Tübingen
Research Assistant - AI Developer Tools (Effekt), April 2025 - October 2025
Developed an AI assistant for the Effekt language's VS Code extension, integrated via MCP and powered by static compiler data for accurate, context-aware support. Implemented a Holes Panel that displays placeholder positions with in-scope bindings and expected types to feed structured input to the assistant.
University of Tübingen
Academic Tutor, October 2024 - March 2025
Education
KTH Royal Institute of Technology
M.Sc. Machine Learning, August 2026 - July 2028
University of Tübingen
B.Sc. Computer Science, October 2023 - June 2026
Grade: 1.2
Thesis: Viewpoint Estimation for Animal Re-Identification on Edge Devices
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