I’m a final-year PhD student in Machine Learning for Biology at the University of Cambridge, and the MRC Biostatistics Unit under the supervision of Professor John Whittaker and Professor Sach Mukherjee. I work on machine learning methods for cell biology, bridging ideas across machine learning, causality and design of experiments, to develop models that are identifiable, general, and easy to interpret.

Previously, I spent 6 months at Relation Therapeutics as a Machine Learning Research Intern developing models for lab-in-the-loop. I’ve worked on adaptive clinical trial methodology at the MRC BSU and uncertainty quantification for COVID-19 forecasting at the S3RI in collaboration with PHE and Dstl. I hold an MSc in Statistical Science from the University of Oxford and a BSc in Mathematics with Computer Science from the University of Southampton.

Selected Publications

• Kovačević et al. “Inductive Biases for Disentangled Representation Learning with Correlated Treatment–Nuisance Factors.” NeurIPS 2025 Workshop on CauScien: Uncovering Causality in Science.
• Kovačević et al. “Bayesian model averaging for partial ordering continual reassessment methods.” Biostatistics 26.1 (2025): kxaf035.
• Kovačević et al. “Simulation-based benchmarking for causal structure learning in gene perturbation experiments.” arXiv preprint arXiv:2407.06015 (2024).