About

I am a Staff Data Scientist at Hive, a logistics and fulfillment startup, where I build intelligent agents and data solutions that power decision-making across the supply chain. My work focuses on applying machine learning and optimization to logistics, fulfillment, and delivery prediction. In parallel, I collaborate as a freelance data scientist with the Wild Dolphin Project, using machine learning to analyze and model dolphin communication as part of a long-term bioacoustics effort.

Previously, I was a Software Engineer (ML) at Meta working on audience building and targeting for online advertising, and a Data Scientist at Shopify helping create an email marketing and growth automation platform. My career began at Xing in Hamburg, where I worked on recommender systems and large-scale machine learning.

I hold a Ph.D. in Computer Science from the Georgia Institute of Technology, where I was a Graduate Research Assistant in the Contextual Computing Group under Thad Starner. Before Georgia Tech, I completed my Diploma Thesis (German equivalent to a Master’s) in the Intelligent Systems Research Group at the University of Bremen and briefly worked there as a researcher. Earlier, I developed Android and iOS software at the Neusta Software Development Group.

Current Interests

Machine learning for logistics, fulfillment, and delivery prediction
Online advertising, audience modeling, and personalization
Learning to rank & recommender systems
Deep learning & gesture recognition
Bioacoustic modeling of dolphin communication