Dr Andrey Kravchenko
College Lecturer in Computer Science
Undergraduate teaching
Andrey teaches the following undergraduate Computer Science courses at the University of Oxford: Functional Programming, Imperative Programming, Discrete Maths, Continuous Maths, Linear Algebra, Probability, Introduction to Formal Proof, Design and Analysis of Algorithms, Algorithms and Data Structures, Models of Computation, Digital Systems, Databases, Compilers, Artificial Intelligence, Machine Learning, and Computational Game Theory.
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Research interests
Andrey’s DPhil qualification induced him to explore the intersection of machine learning and unstructured data extraction. He had a significant role in the DIADEM project, which produced state-of-the art research in the field of large-scale fully automated web data extraction. The technology underlying DIADEM was later commercialised as an Oxford University spin-off Wrapidity, which was acquired by Meltwater, one of the most predominant world-wide media intelligence companies. His current research focus is on exploring the broader connection between black-box machine learning models and knowledge-based systems, with a particular focus on knowledge graphs. Machine learning models do not involve human expertise and are often difficult, if not impossible, to explain. On the contrary, knowledge-based systems are easy to translate into an interpretable form but are based on human domain expertise and therefore require significant manual work to build. In particular, his research has been focused on multiagentic systems empowered by knowledge graphs and reasoning capabilities to both improve the accuracy and counteract possible hallucinations. He would like to work towards bridging the gap between these two different aspects of artificial intelligence in his research, and has a strong interest in scientific collaborations. If you have a project which may relate to his area of expertise, please contact him to discuss ideas of mutual interest and potential collaboration.
Andrey’s research has always had a strong focus on real-world applications, as well as potential business opportunities. He was actively involved with two Oxford University spin-offs focused on automated web data extraction and  large-scale knowledge graphs combined with reasoning, both based on research done here at Oxford. He has also founded an AI consultancy firm, Vitruvian Quality Lab, which develops a wide range of AI-based products with a particular focus on products that employ multiagentic systems grounded into knowledge graphs and reasoning.