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PhD
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
UCL
Doctor of Philosophy - PhD, Reinforcement Learning
April 1, 2018 – February 1, 2023
UCL
Master in science, Engineering
January 1, 2016 – January 1, 2017
UCL
Bachelor of Engineering - BE, Engineering
January 1, 2012 – January 1, 2015
Amazon Web Services (AWS)
Applied Scientist II
August 1, 2022 – Present
中国 上海市
Amazon Web Services (AWS)
Applied Scientist Intern
July 1, 2021 – October 1, 2021
中国 北京市
BBC
Research Intern
January 1, 2021 – June 1, 2021
London, England, United Kingdom
Advanced Digital Sciences Center (ADSC)
Summer Intern
June 1, 2016 – September 1, 2016
Singapore
Reinforcement Learning Algorithms Implementation
November 1, 2020 – Present
Implementing RL algorithms, based on Python, Pytorch, OpenAI Gym, including Q-Learning, Actor-Critic, DQN, A3C, PPO, DDPG, D4PG, TD3, SAC.
Cultural Fit Analysis
The candidate's background includes significant academic research (PhD) and industry experience at a major tech company (AWS), indicating a strong drive for innovation and practical application. The personal project on RL algorithm implementation demonstrates initiative and a deep interest in the field. The diversity of projects (gaming, LLM, vision-language models, recommendation systems) suggests adaptability and a broad technical curiosity. The alignment with the 'Applied Scientist II' role is very strong, indicating a good cultural fit for a research-driven, application-focused environment.
Soft Skills & Operational Fit
The candidate's experience at AWS and BBC suggests an ability to work in large, structured organizations. The project descriptions indicate a focus on practical application and deployment, which is crucial for an Applied Scientist role. However, without psychometric test results or interview data, specific soft skills like teamwork, stress handling, or communication clarity cannot be fully assessed.