Experience & Education

Technical strengths across research and industry.

Experience

Jan 2025 — Present

Machine Learning Research Scientist

Carl Zeiss, Munich, Germany

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

Jul 2024 — Dec 2024

Research Assistant

CARIAD (Volkswagen Group), Munich, Germany

  • Developed visual perception techniques for unknown objects using instance segmentation
  • Achieved state-of-the-art performance on COCO dataset
  • Submitted findings to CVPR

Jan 2024 — Jun 2024

Research Assistant

ETH Zurich / Helmholtz AI / TUM

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

Oct 2023 — Mar 2024

Machine Learning Engineer (Part-Time)

BMW, Munich, Germany

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

Mar 2023 — Aug 2023

Research ML Engineer (Part-Time)

Huawei Munich Research Center, Munich, Germany

  • Optimized task assignments for fleets of robots using RL and LLMs
  • Compressed deep learning networks for edge devices

Mar 2023 — Dec 2023

Master Thesis

ETH Zurich, Switzerland

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

Sep 2022 — Feb 2023

Visiting Researcher

EPFL, Lausanne, Switzerland

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

Nov 2020 — Feb 2023

Software Engineer (Part-Time)

Infineon Technologies, Munich, Germany

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

Apr 2022 — Sep 2022

Research Project: Data Innovation Lab

Intel, Munich, Germany

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

Nov 2020 — Jan 2021

Software Engineering Intern

TUM, Chair of Electronic Design Automation

  • 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

Oct 2021 — Dec 2023 · Completed with over 150 ECTS out of 120

BSc in Electrical Engineering & IT

Technical University of Munich, Germany

Oct 2018 — Sep 2021 · Thesis: TVM LLVM Backend viability for TinyML on RISC-V

Skills

Languages

Python C++ C R Matlab Java VHDL SQL

Frameworks

PyTorch TensorFlow CUDA Docker K8s FastAPI

Expertise

Efficient Learning CV NLP RL Bayesian ML

Deployment

TensorRT ONNX TFLite Apache TVM Jetson