Angelie Kraft
Research Group Lead at Weizenbaum-Institut
Hamburg, Germany
Summary
👤
Senior🎓
Top SchoolAngelie Kraft is a Research Group Lead and multidisciplinary AI researcher based in Hamburg with nine years of experience spanning AI, psychology, and computer science. She combines academic rigor—pursuing a doctorate in computer science—with applied work on language models, knowledge graphs, and AI ethics across institutes like Weizenbaum and Universität Hamburg. Angelie co-founded Adalab and contributes to open-source ML tooling (notably extending image encoding and visual-story features in the popular deep-daze CLIP-based repo), reflecting a hands-on approach to generative art and reinforcement learning. Her background in psychology and cognitive science informs a rare focus on societal biases and representativeness in benchmarks, and she actively shapes community engagement through interviews and summer schools. Colleagues value her ability to bridge interdisciplinary teams, translate ethical concerns into technical inquiry, and iterate on practical ML implementations.
9 years of coding experience
4 years of employment as a software developer
Psychology and Philosophy, Psychology and Philosophy at National Taiwan UniversityJohns Hopkins UniversityBachelor of Science (BSc) Computer Science, Bachelor of Science (BSc) Computer Science at University of BremenBachelor of Science (BSc) Psychology, Bachelor of Science (BSc) Psychology at University of MannheimDr. rer. nat. Computer Science, Dr. rer. nat. Computer Science at University of Hamburg
German, English, Chinese, thailändisch, French
Github Skills (8)
transformers10
encode10
pytorch10
artificial-intelligence10
deep-learning10
clip10
encoding10
python9
Programming languages (5)
Github contributions (5)
lucidrains/deep-daze
Feb 2021 - Apr 2021
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun
Role in this project:
ML Engineer
ML EngineerContributions:4 reviews, 51 commits, 5 PRs in 1 month
Contributions summary:Angelie primarily focused on adding image encoding and custom encoding capabilities to the deep-daze project. They implemented methods for creating and setting CLIP encodings, including encoding images and averaging text and image embeddings. Furthermore, they introduced and refined the functionality for creating visual stories within the project, allowing for generating images for sliding windows of text. This included modifying and extending existing classes and methods related to the core deep-daze model.
pytorchcommand-line-tooltransformersrepresentationimplicit
NotNANtoN/AuViMi
Feb 2021 - Jul 2021
Contributions:159 commits, 149 pushes, 2 branches in 5 months
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