Self-motivated PhD candidate with a particular interest in the application of computational technologies to natural sciences. Independent, hard-working, and fast-learning team player equipped with essential skills for researching and problem solving. My PhD project aims to apply machine learning techniques to the design of multimetallic nanoparticles as catalysts.


  • How does cross-conjugation influence thiol additions to enones? A computational study of thiol trapping by the naturally occurring divinyl ketones zerumbone and α-santonin
  • Data-driven causal inference of process-structure relationships in nanocatalysis
  • Optimization-Free Inverse Design of High-Dimensional Nanoparticle Electrocatalysts Using Multi-target Machine Learning
  • Causal Paths Allowing Simultaneous Control of Multiple Nanoparticle Properties Using Multi‐Target Bayesian Inference

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