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Assistant Professor at King's College London
https://www.yangyaodong.com Yaodong is a machine learning researcher with ten-year working experience in both academia and industry of finance/high-tech companies. Currently, he is an assistant professor at King's College London. His research is about reinforcement learning and multi-agent systems. He has maintained a track record of more than forty publications at top conferences/journals, along with the best system paper award at CoRL 2020 (first author) and the best blue-sky paper award at AAMAS 2021 (first author). Before KCL, he was a principal research scientist at Huawei UK where he headed the multi-agent system team in London, working on autonomous driving applications. Before Huawei, he was a senior research manager at AIG, working on AI applications in finance. He holds a Ph.D. degree from University College London, an M.Sc. degree from Imperial College London and a Bachelor degree from University of Science and Technology of China.
UCL
Ph.D., Computer Science & Machine Learning
January 1, 2016 – January 1, 2020
Imperial College London
M.Sc., Quant. Biology (Bio-statistics)
January 1, 2013 – January 1, 2014
University of Science and Technology of China
B.Eng., Electronic Engineering
January 1, 2009 – January 1, 2013
Shanghai Experimental School
High School
January 1, 2006 – January 1, 2009
King's College London
Assistant Professor
January 1, 2021 – January 1, 2022
Greater London, England, United Kingdom
Huawei Technologies Research & Development (UK) Ltd
Principal Research Scientist
May 1, 2019 – May 1, 2021
King’s Cross, London, UK
美亚保险
Senior Manager in Machine Learning
December 1, 2015 – April 1, 2019
Fenchurch Street, London, UK
LCG
Research Intern
October 1, 2014 – November 1, 2015
Devonshire Square, London, UK
Cultural Fit Analysis
The candidate has a strong academic and research background, with roles in both academia and R&D departments of large corporations. While the experience is heavily focused on advanced machine learning research and development, the target role is 'Data Analyst'. This suggests a potential mismatch in the day-to-day responsibilities and focus. The candidate's background is more aligned with a Research Scientist or Machine Learning Engineer role rather than a traditional Data Analyst role, which typically involves more data manipulation, visualization, and reporting, rather than deep model innovation and research. The diversity of projects is high in terms of technical complexity but less so in terms of typical data analyst tasks.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in research teams and significant contributions to business outcomes, suggesting strong problem-solving and impact-driven qualities. However, specific soft skills like collaboration, adaptability, or communication in a corporate data analyst setting are not explicitly detailed. The psychometric test score is not provided, so an assessment of work attitude, stress handling, and team collaboration cannot be made.