Tim Luka Horstmann

Research Assistant (Machine Learning and Natural Language Processing)

BSc (RheinMain University of Applied Sciences), MPhil (University of Cambridge), MSc (Institut Polytechnique de Paris)

My research interests lie in applied machine learning and natural language processing, with a focus on designing reliable end-to-end AI systems for real-world use. Beyond traditional methods, I work primarily with language-model-based approaches, including reasoning over text and structured data, agentic AI systems, and controllable generative models such as text-to-speech. Across these areas, my work emphasises robustness, explainability and system-level design, translating modern ML methods into scalable, deployable tools for industry, academia and society.

Tim Luka Horstmann.

My details

Contact details

t.horstmann@jbs.cam.ac.uk

horstmann.tech

Academic area

Operations and Technology Management

Professional experience

Tim Luka Horstmann has applied machine learning and data science across research and industry settings. At the Hi! PARIS Research Center, in collaboration with École Polytechnique, he built end-to-end AI systems spanning language and speech, including controllable text-to-speech and agentic AI tooling. He previously worked at Amazon as a Business Intelligence Intern, where he developed analytics pipelines and dashboards to support large-scale operational decision-making, and at McKinsey & Company, where he delivered quantitative analyses and risk assessments for senior leadership. Earlier, he held software engineering and data science roles at Continental AG as part of a dual-study programme, working on automation and data-driven systems deployed in production environments.

Previous appointments

Prior to joining Cambridge Judge Business School, Tim Luka Horstmann conducted research at the Hi! PARIS Research Center in collaboration with École Polytechnique, focusing on applied machine learning systems that use language-model-based methods and controllable generative modelling for speech. He previously carried out NLP research during his MPhil in Advanced Computer Science at the University of Cambridge, including work on extracting, structuring and matching financial regulatory information.

Publications

Selected publications

  • Horstmann, T.L., Geisenberger, B., Alam, M. (2026) “T-REX: Table – Refute or Entail eXplainer.” In: Dutra, I. et al (eds.) Machine learning and knowledge discovery in databases. Applied Data Science Track and Demo Track. ECML PKDD 2025. Lecture Notes in Computer Science, vol.16022. Cham: Springer. (DOI: 10.1007/978-3-032-06129-4_33)
  • Ould Ouali, N., Sani, A.H., Bueno, R., Dauvet, J., Horstmann, T.L. and Moulines, E. (2025) “Improving French synthetic speech quality via SSML Prosody Control.” In: Proceedings of the International Conference on Natural Language and Speech Processing (8th): ICNLSP-2025, Southern Denmark University, Odense, Denmark. Association for Computational Linguistics, pp.302-314

Awards and honours

  • Winner, {Tech: Europe} Hackathon Paris, 2025
  • Alumni Association Prize for Graduate Excellence, Lucy Cavendish College, University of Cambridge, 2024
  • ContiBestenEhrung, Continental AG, 2022
Top