Vid Kocijan

Vid Kocijan has held a variety of roles in the field of Machine Learning and Natural Language Processing. In 2022, they began working as a Machine Learning Engineer at Kumo.AI. Prior to this, they were a Quantum Natural Language Processing Engineer at Cambridge Quantum from 2021. In 2020, they were a Visiting Researcher at New York University, where they worked on analysis of transfer learning in natural language processing and investigated the potential of using influence functions for the prediction of training sample relevancy. In 2018, they were the Undergraduate Innovation of the Year Winner at Oxford Foundry, where they developed an AI-powered solution to try and find the safest way home. This idea was also awarded as the best in the UK by the European Space Agency as part of the ActInSpace event. In 2017, they were the Co-Chair of the Scientific Committee at Central European Olympiad in Informatics, where they were responsible for the preparation of the content and of evaluation procedure for the international competition. Finally, in 2016, they were a Visiting Researcher at Stanford University, where they developed an efficient implementation and improvements to the Node2vec algorithm for network analysis. Vid'simplementation is now a core feature of SNAP library for network analysis.

Vid Kocijan attained a Bachelor's degree in Mathematics and Computer Science from the University of Ljubljana between 2014 and 2017. Vid then went on to pursue a Master of Science - MS in Computer Science at the University of Oxford between 2017 and 2018. Vid Kocijan is currently in the process of completing their Doctor of Philosophy - PhD in Computer Science at the University of Oxford, which they began in 2018.