London, England, United Kingdom
Quantitative researcher with a background in machine learning and optimisation. -Host of the 2nd Jane Street Kaggle competition -Winner of the 1st Jane Street Market Prediction competition -Kaggle Grandmaster with rich practical machine learning experiences -PhD with a demonstrated academic track record in optimisation and machine learning research -Proficient in Optimisation, Time-Series, Resource Allocation, Machine Learning and Deep Learning and Python
Alpha research for global equities trading
Machine learning-based alpha research for Chinese equities trading
I participate in Kaggle competitions during my spare time out of daily research for practising machine learning skills including regression/classification for tabular data, computer vision, NLP, etc. This is also to stay engaged and keep learning fantastic data science skills. My profile link: https://www.kaggle.com/gogo827jz * 1st in Jane Street Market Prediction: Winner | Gold Medal (1/4245) * Public 2nd in Mechanisms of Action (MoA) Prediction: Published 7 gold-medal notebooks and 30 gold-medal discussion topics * 15th in Santa 2020 - The Candy Cane Contest: Silver Medal (15/788) * 41th in CommonLit Readability Prize: Silver Medal (41/3682) * 63th in Understanding Clouds from Satellite Images: Silver Medal (63/1556, Top 5%) * 96th in Instant Gratification: Bronze Medal (96/1832, Top 6%) * 182th in Predicting Molecular Properties: Bronze Medal (182/2749, Top 7%) * 293th in 2019 Data Science Bowl: Bronze Medal (293/3497, Top 9%)
Exploiting the potential of machine learning algorithms on machine-to-machine (M2M) communications on the Internet of Silicon Retinas (IoSiRe) networks (government-sponsored project).
Teaching Assistant of: Electronics Application Project and Engineering Lab I Electronics Application Project and Engineering Lab II