Wistan Chou

Wistan Chou is a machine learning engineer at Lev. Wistan previously worked as a senior software engineer at Salesforce from September 2019 to September 2021, where they conducted quantitative research focused on using machine learning to analyze alternative data. Wistan also created a genetic algorithm-based pipeline to find specific and optimal stock portfolios based on time series data. In addition, they used LDA and other unsupervised NLP algorithms for topic modeling and embedding stocks based on unstructured data. Wistan also built a real-time social media sentiment analyzer to estimate the live sentiment of products during product releases.

Before joining Salesforce, Chou interned at the company from June 2018 to August 2018. During their internship, they worked on machine learning models in the Search Ranking team within Salesforce Search Relevance. Wistan also created a query-independent global search re-ranking model using sparse MRU affinity features that scaled Salesforce’s personalized search from 10 to 500 organizations. In addition, they leveraged NLP to build query-specific models based on named entities. Wistan also worked on feature linearization using rc-splines and discovering significant first-order feature interactions. Furthermore, they worked on using adversarial learning for cross-organization regularization for search re-ranking.

Wistan Chou graduated from Swarthmore College with a Bachelor's Degree in Mathematics and Computer Science. Wistan then became a Visiting Student at the University of Oxford in the field of Computer Science and Mathematics. Finally, they attended International School of Beijing, where they completed the IB Bilingual Diploma.