Adam Hulman, MSc, PhD
Associate Professor & Senior Data Scientist
adahul@rm.dk
+45 2370 7481
Research team
Research areas
- Clinical prediction
- Machine learning and its clinical applications
- Deep learning
- Synthetic data
- Longitudinal studies
- Latent class analysis
Research description
- My research focuses on how longitudinal multimodal data (tabular, time series, images) can be incorporated into clinical risk prediction models. To achieve this, we study state-of-the-art deep learning methods and, using transfer learning, repurpose them for clinical and epidemiological research.
- Supported by the NNF Data Science Emerging Investigator Programme (grant period: 2023-2028).