Masha Naslidnyk
📍 PhD student @ UCL. She/her.
Hi! I am a PhD student at the Foundational AI CDT at University College London, advised by FX Briol, Jeremias Knoblauch, and Carlo Ciliberto. Prior to starting my PhD, I was a Machine Learning Scientist at Amazon Research in Cambridge, where I worked on Alexa question answering (20152019), and then on Gaussian processes for supply chain emulation (20192021). I graduated from Part III in Pure Mathematics at the University of Cambridge in 2014.
My research interests lie broadly in the topics in Gaussian processes and kernel methods; at present, I am focussed on robust inference in conditional probability models.
I will happily respond to “Masha”, but if you’d like to pronounce my last name, it’s nahsleednyk, “y” as in “six”.
news
Sep 13, 2023  💬 Giving a talk at the Gaussian Process Summer School at the University of Manchester. 

Sep 1, 2023  💬 Visiting CISPA Helmholtz Center for Information Security under the Helmholtz Visiting Researcher Grant, SeptemberNovember 2023. 
May 8, 2023  💬 I am coorganising the Distancebased methods in Machine Learning workshop. 
Mar 29, 2023  💬 Our paper OptimallyWeighted Estimators of the Maximum Mean Discrepancy for LikelihoodFree Inference was accepted at ICML 2023. 
Jan 12, 2023  🎉 An upcoming paper, Robust Empirical Bayes for Gaussian Processes, won an ASA Section on Bayesian Statistical Science (SBSS) student paper award. It will be presented at JSM 2023. 
papers

EMNLPIJCNLPUsing Pairwise Occurrence Information to Improve Knowledge Graph Completion on LargeScale DatasetsIn Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLPIJCNLP) 2019