معرفی
Damian Machlanski is a Researcher at the University of Edinburgh's School of Engineering, working within the CHAI group (Causal AI Hub). He also holds a joint affiliation with the University of Essex as a Computer Science PhD candidate under the Department of Computer Science and Electronic Engineering (CSEE) and the Research Centre on Micro Social Change (MiSoC). His career includes roles as a Senior Research Officer at the Institute for Social and Economic Research (ISER) and prior experience as a Software Developer.
- Education
- BEng in Computer Science, West Pomeranian University of Technology
- MSc in Artificial Intelligence, University of Essex
- PhD (ongoing) in Computer Science, University of Essex
His research focuses on causal inference and machine learning, particularly addressing hyperparameter sensitivity and robustness in causal structure learning. Key subtopics include treatment effect estimation, observational data analysis, domain generalization, and generative tree models.
Damian's publications emphasize methodological rigor in causal discovery and algorithm evaluation. His work has been featured in venues like the Conference on Causal Learning and Reasoning and IEEE Access, with additional working papers on platforms such as arXiv.
He contributes to open-source tools like the CATE Benchmark and actively engages in scientific outreach through workshops like the IADS Summer School on Causality. His software engineering background enhances his research focus on reproducibility and performance engineering in machine learning systems.
