Experience

Experience

Machine Learning Research Scientist

Carl Zeiss, Munich, Germany (01/2025 – Present)

  • Implementing robust ML solutions for sensitive use cases (surgical rooms, GPU components, FPGAs) with critical energy efficiency requirements.
  • Optimizing and deploying models on Edge devices.
  • Reducing computation costs (memory, bandwidth, network size, energy consumption).
  • Supervising interns and students.

Research Assistant

CARIAD (Volkswagen Group), Munich, Germany (07/2024 – 12/2024)

  • Developed visual perception techniques for unknown objects using instance segmentation, language-to-vision methods, and knowledge distillation.
  • Achieved state-of-the-art performance on COCO dataset.
  • Submitted findings to CVPR.

Research Assistant

ETH Zurich / Helmholtz AI / TUM, Remote (01/2024 – 06/2024)

  • Extended master’s thesis output to language modeling, LLMs, and vision transformers.
  • Published at NeurIPS 2024 and AABI.
  • Initiated a project on network architecture search.

Machine Learning Engineer (Part-Time)

BMW, Munich, Germany (10/2023 – 03/2024)

  • Optimized neural networks for deployment on edge devices.
  • Designed a framework for model optimization on resource-limited devices.

Research Machine Learning Engineer (Part-Time)

Huawei Munich Research Center, Munich, Germany (03/2023 – 08/2023)

  • Optimized task assignments and monitoring for fleets of robots using reinforcement learning and LLMs.
  • Specialized in compressing deep learning networks for edge devices.
  • Tools: PyTorch, TFLite, ROS, TensorRT, Jetson, SLAM

Master Thesis

ETH Zurich, Zurich, Switzerland (03/2023 – 12/2023)

  • Sparsified and compressed neural networks using Bayesian Occam’s razor.
  • Achieved a grade of 1.0 and published at NeurIPS 2024.

Visiting Researcher

EPFL, Lausanne, Switzerland (09/2022 – 02/2023)

  • Developed novel data augmentation methods for saliency prediction.
  • Achieved competitive performance on the MIT300 Validation set.

Software Engineer (Part-Time)

Infineon Technologies, Munich, Germany (11/2020 – 02/2023)

  • Conducted microchip testing and development.
  • Built an AI pipeline for leakage detection and developed an efficient autoencoder.

Research Project: Data Innovation Lab

Intel, Munich, Germany (04/2022 – 09/2022)

  • Researched and developed sparse and quantized neural networks.
  • Improved computational efficiency for edge device deployment.

Software Engineering Intern

Technical University of Munich, Chair of Electronic Design Automation (11/2020 – 01/2021)

  • Worked on an Instruction Set Simulator (ETISS).
  • Implemented an ELF loader and managed memory layout.

Education

MSc in Robotics, Cognition, Intelligence

Technical University of Munich, Germany (10/2021 – 12/2023)

  • Completed with over 150 ECTS out of 120.

BSc in Electrical Engineering and Information Technology

Technical University of Munich, Germany (10/2018 – 09/2021)

  • Thesis: Evaluating the viability of the TVM LLVM Backend for TinyML on RISC-V.

Skills

  • Programming Languages: Python, C++, C, R, Matlab, Perl, Java, VHDL, SQL
  • Frameworks & Tools: PyTorch, TensorFlow, CUDA, Docker, Kubernetes, FastAPI
  • Areas of Expertise: Efficient Learning, Computer Vision, NLP, Reinforcement Learning, Bayesian Inference