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. My research aims to answer real-world scientific questions by bridging ideas across machine learning, causality and design of experiments to develop models of cells that are general, and interpretable.

I’ve worked on many parts of the drug development and care pipeline. In 2024/25, I spent 6 months at Relation Therapeutics as a Machine Learning Research Intern working on models for target discovery in lab-in-the-loop. I developed adaptive clinical trial methodology at the MRC BSU, University of Cambridge. And I contributed to work on uncertainty quantification for COVID-19 forecasting at the S3RI collaborating with PHE and Dstl.

I obtained my master’s in Statistical Science at 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. (link)
• Kovačević et al. “Bayesian Model Averaging for Partial Ordering Continual Reassessment Methods” Biostatistics 26.1 (2025): kxaf035. (link)
• Kovačević et al. “Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments.” arXiv preprint arXiv:2407.06015 (2024). (link)