I supervise MSc thesis projects at the AI Laboratory for Molecular Engineering (AIME), Chalmers University of Technology, mostly around machine learning for targeted protein degradation. Several of these projects have grown into published work — the students are co-authors, not acknowledgees.
If you are a Chalmers or GU student looking for a thesis project in AI for drug discovery, get in touch. Open topics usually sit somewhere between generative chemistry, property prediction, and the very unglamorous but very necessary business of building good datasets.
Tingting Mo and Jia Xin Zhu — a systematic framework for PROTAC synthesizability assessment, combining PROTAC-Splitter decomposition with AiZynthFinder-based retrosynthesis scoring.
Alexander Persson and Felix Erngård — generative design of complete PROTACs using language models with reinforcement learning, optimised against several objectives at once.
Ranxuan Zhang — learning to split a PROTAC into its E3 ligand, linker and warhead, and using that decomposition to improve degradation activity prediction.
Teaching assistant and course contributor at Chalmers University of Technology.
| Year | Course |
|---|---|
| 2025–2026 | DAT341 Applied Machine Learning |
| 2025–2026 | AI for Molecules |
| 2025–2026 | DAT565 Introduction to Data Science and AI |
| 2024–2025 | DAT341 Applied Machine Learning |
| 2024–2025 | DAT410 Design of AI Systems |
| 2024–2025 | DIT862 Statistical Methods for Data Science |
| 2024–2025 | DAT565 Introduction to Data Science and AI |
| 2019–2020 | DAT093 Introduction to Electronic System Design |
| 2018–2019 | DAT093 Introduction to Electronic System Design |
| 2017–2018 | EDA332 Datorsystemteknik |
| 2017–2018 | EDA322 Digital Konstruktion |
| 2017–2018 | DAT093 Introduction to Electronic System Design |
| 2016–2017 | EDA322 Digital Konstruktion |
Student projects at AIME have been supported by the Chalmers Gender Initiative for Excellence (Genie) and the Wallenberg AI, Autonomous Systems and Software Program (WASP), funded by the Knut and Alice Wallenberg Foundation, with compute provided by Chalmers e-Commons and the National Academic Infrastructure for Supercomputing in Sweden (NAISS).