Neil Wang
About Neil Wang
Neil Wang is a Machine Learning Engineer at Booth AI, where he has worked since 2023. He earned a Master of Engineering in Engineering Science from the University of Oxford and has experience in various engineering roles, including product and backend engineering.
Work at Booth AI
Neil Wang has been employed at Booth AI as a Machine Learning Engineer since 2023. In this role, he focuses on enhancing image generation technologies. His responsibilities include developing and implementing machine learning models to improve the efficiency and effectiveness of the company's offerings. Neil's work contributes to the advancement of Booth AI's capabilities in the field of artificial intelligence.
Education and Expertise
Neil Wang studied at the University of Oxford, where he earned a Master of Engineering (MEng) in Engineering Science from 2016 to 2020. During his studies, he completed a first-class thesis on Computer Vision for human pose estimation and data visualization. His educational background provides him with a strong foundation in engineering principles and machine learning techniques.
Previous Experience in Engineering
Before joining Booth AI, Neil Wang worked at Mystic AI as a Product Engineer from 2022 to 2023 and as a Software Engineer from 2021 to 2022, both positions based in Bath, England. His experience includes product and backend engineering, with a focus on MLOps. This background has equipped him with skills in developing full stack web and iOS applications.
Internship Experience
Neil Wang has completed several internships that contributed to his professional development. He interned at the Bank of China in 2017 for one month in London, United Kingdom. Additionally, he worked as a Sales and Marketing Intern at WeWork in Shanghai City, China, in 2018 for one month. These experiences provided him with insights into different sectors and enhanced his skill set.
Academic Background
Prior to his studies at the University of Oxford, Neil Wang attended Christ College Brecon, where he studied Math, Further Math, Chemistry, and Physics. He achieved A levels in these subjects starting in 2015. This academic background laid the groundwork for his future studies in engineering and machine learning.