Benedikt Blumenstiel
AI for Climate Impact, IBM Research | Based in Zurich
About me
Hello! I'm Benedikt — an open-minded individual passionate about machine learning, innovation, sustainability. During my studies, I focused on computer vision, natural language processing, and time series forecasting. Now at IBM Research, I contribute to the Team AI for Climate Impact and delve into MLOps. Eager to connect and share experiences in the intersection of machine learning research and sustainability.
Looking forward to connect with you!
Selected projects
MESS Benchmark
Holistic benchmarks allow a robust quantitative comparison of model architectures. However, such evaluation practice covering a wide range of real-world applications is lacking for multi-modal (i.e., text-to-image) zero-shot semantic segmentation tasks. Thus, our motivation to compose the Multi-domain Evaluation of Semantic Segmentation (MESS) benchmark, which consists of 22 datasets for varying application domains. More details can be found on our website.
CLAIMED Component Compiler (C3)
The CLAIMED framework enables rapid development and deployment of processing steps, e.g. for data preprocessing in deep learning. Using the CLAIMED Component Compiler (C3), components can be easily built from a Python script or notebook and deployed on KubeFlow, Kubernetes, or locally via CLI. Notably, C3 eliminates the need for Docker or Kubernetes expertise, making it accessible to any data scientist to deploy code on clusters. Check out the Getting Started page for more information.
Résumé
Work Experience
Research Scientist, AI for Climate Impact, IBM Research
02/2023 - present
- Research on geospatial foundation models for multi-spatial and multi-modal satellite data
- Developing the data pipeline for a geospatial ML platform and foundation model pre-training
Intern, AI for Climate Impact, IBM Research
08/2023 - 02/2023
- Deploying and applying MLOps tools and pipelines
- Developing the CLAIMED Component Compiler (C3) for the CLAIMED project
- Experiments with remote sensing image retrieval using geospatial foundation models
Junior Researcher, Applied AI in Services Lab, KIT
05/2020 - 04/2022
- Research about human-AI collaboration and machine learning, with a focus on few-shot learning
- Developed AI applications for a AI project in the AEC industry
- Worked with multiple computer vision models and deployed them on high performance clusters
Design Thinking project, KIT & HUK Coburg
10/2019 - 06/2020
- Used design thinking to develop user-centered innovations and prototypes for retirement saving
Intern, R&D Strategy, AUDI AG
07/2017 - 02/2018
- Supported the project manager in defining a new technology-focused R&D strategy
- Worked in the project management office of an R&D transformation project
Education
M.Sc. Information Systems, Karlsruhe Institute of Technology
10/2019 - 04/2023
- Focus on machine learning and service innovation
Exchange, Norwegian University of Science and Technology
01/2021 - 06/2021
- Courses in computer vision, natural language processing and statistics
B.Sc. Industrial Engineering, Karlsruhe Institute of Technology
10/2015 - 09/2019
- Focus on digital services and business strategy