Curriculum Vitae
Experience & Education
Building efficient machine learning systems across research labs and industry since 2020.
Experience
Jan 2025 — Present
Machine Learning Research Scientist
Zeiss, Munich, Germany
- Spearheading generative AI and computer vision solutions for real-time edge and cloud applications
- Optimizing and deploying foundation models (SAM, CLIP, ViT, DINO, DepthAnything, YOLO, DETR) and LLMs (Mistral, Phi, LLaMA, DeepSeek) for NPU/accelerator inference
- NPU-first quantization (PTQ/QAT, mixed precision), distillation, pruning, and kernel-level optimization on platforms such as Jetson, Hailo, Rockchip, Memryx, Sima, and Axelera
- Authoring project proposals and roadmaps; leading projects from concept to handover
- Publishing at academic conferences and filing IP on hardware-specific compression techniques
Jan 2025 — Present
Independent Researcher
INSAIT / ETH Zurich research ecosystem
- Independent research on efficient AI methodologies and optimization of complex model architectures
- Collaborating with ETH Zurich, Google, and the Swiss Center for Electronics and Microtechnology on EU-funded research projects
- First-author work on state-of-the-art image enhancement on the edge submitted to NeurIPS 2026
Jul 2024 — Dec 2024
Research Assistant
CARIAD (Volkswagen Group), Munich, Germany
- Developed instance and semantic segmentation algorithms for vehicle perception
- Achieved state-of-the-art performance on public dataset benchmarks
- Coordinated cross-functional teams to translate research into automotive applications
Mar 2023 — Jun 2024
Research Assistant
BMI Lab, ETH Zurich (Remote)
- Researched state-of-the-art compression techniques across tasks, including LLMs
- Published at NeurIPS 2024 on scalable Bayesian approaches to neural network sparsification (thesis grade: 1.0)
- Initiated a neural architecture search project for efficient model design
Oct 2023 — Mar 2024
Machine Learning Engineer (Part-Time)
BMW, Munich, Germany
- Designed and deployed optimized neural networks for resource-constrained environments
- Built a deployment framework around ONNX, TFLite, and Apache TVM
- Enhanced perception, sensor fusion, key localization, and child-presence-detection features
Mar 2023 — Aug 2023
Research Machine Learning Engineer (Part-Time)
Huawei Munich Research Center, Germany
- Developed reinforcement learning and LLM-based solutions for task assignment in robotic fleets
- Compressed and accelerated deep learning models for efficient edge inference and tracking
Sep 2022 — Feb 2023
Research Assistant
IVRL Lab, EPFL, Lausanne, Switzerland
- Improved saliency prediction networks through targeted image manipulation and augmentation
- Trained networks on generated datasets accounting for gaze-retargeting potential
Apr 2022 — Sep 2022
Research Intern — Machine Learning
Intel, Munich, Germany
- Researched sparsification and quantization strategies achieving high-sparsity regimes
- Delivered 4× memory reduction and up to 7× speedup on ResNets and ViTs
Nov 2020 — Feb 2023
Software Engineer (Part-Time) — Machine Learning
Infineon Technologies, Munich, Germany
- Built robust AI pipelines for microchip testing, leakage detection, and automated data analysis
- Designed efficient autoencoders for anomaly detection in hardware diagnostics
Apr 2021 — Aug 2021
Teaching Assistant
TUM, Chair of Algorithms and Complexity
- Conducted tutorials on algorithms and data structures
Nov 2020 — Jan 2021
Research Intern — Compilers / RISC-V
TUM, Chair of Electronic Design Automation
- Contributed to the ETISS Instruction Set Simulator
- Implemented an ELF loader and managed memory layout
Education
MSc in Robotics, Cognition, Intelligence
Technical University of Munich, Germany
Oct 2021 — Dec 2023 · Graduated with over 150 ECTS, emphasizing machine learning, computer vision, and autonomous systems
MSc Visiting Research Student
EPFL, Lausanne, Switzerland
Sep 2022 — Feb 2023 · Research on saliency prediction at the IVRL Lab; earned an additional 30 ECTS
BSc in Electrical Engineering & IT
Technical University of Munich, Germany
Oct 2018 — Sep 2021 · Thesis: Evaluation of the TVM LLVM backend for TinyML on RISC-V platforms
Academic Service
Scientific Reviewer
Jan 2025 — Present
- Reviewer for top-tier ML conferences (ICML, NeurIPS) and journals (JAIR)
- Areas: probabilistic inference, compression, efficient AI, computer vision, and LLMs
Skills
Programming
ML Frameworks & Tools
Deployment & Compilers
Expertise
Cloud & Data
Languages