Dr. Michael Fromm

Data Science Researcher based in Munich 🇩🇪

Email / Website / LinkedIn / GitHub / Twitter / G-Scholar

Research Interests

• Large Language Models / Conversational AI / Argument Mining / Multilingual LLMs
• Computer Vision / Remote Sensing

Work Experience

• Senior Research Scientist LLMs, Fraunhofer IAIS, (2023 - Present)
• Postdoc, LMU Munich (2022 - 2023)
• Innovation Lab Coordinator, LMU Munich (2020 - 2023)
• Research Scientist, LMU Munich, (2016 - 2023)
• Intern Software Development, Dassault Systemes (2015 - 2016)

Education LMU Munich

• PhD CS (2018 - 2022)
• MSc CS (2016 - 2018)
• BSc CS (2012 - 2016)

Teaching Experiences

• Introduction to Programming
• Argument Mining
• Big Data Management and Analytics
• Practical Machine Learning
• Seminar Machine Learning
• Deep Learning and Artificial Intelligence
• Artificial Intelligence for Games
• Machine Learning with limited labeled Data
• supervision of dozens of bachelor & master thesis

Projects from the Machine Learning Practical are also featured on the Innolab Website.

Current Research Projects

• TrustLLM: Democratize Trustworthy and Efficient Large Language Model Technology for Europe
• openGPT-X: Development of Large European Language Models

Former Research Projects

• ReMLAV: Relational Machine Learning for Argument Validation(ReMLAV)
• Munich Center for Machine Learning (MCML)

Selected Research Articles

Computer Vision

• Automated detection of conifer seedlings in drone imagery using convolutional neural networks
• Unsupervised anomaly detection for X-ray images
• XD-STOD: Cross-Domain Superresolution for Tiny Object Detection

Natural Language Processing

• Argument Mining Driven Analysis of Peer-Reviews
• TACAM: topic and context aware argument mining
• Diversity Aware Relevance Learning for Argument Search
• Active Learning for Argument Strength Estimation
• Cross-Domain Argument Quality Estimation

Skills

Python, Java, C++, Scala, NumPy, Huggingface, PyTorch, Scikit-learn, Optuna, MLflow, Pandas, SciPy, TensorFlow, Bash, ML for Production, Computer Vision, Natural-Language-Processing, AWS