Meng Si

Meng Si has a wealth of work experience. From 2022 to present, they have been a Data Scientist - Analytics Team Lead and Data Scientist - Analytics at ZestyAI. From 2019 to present, they have been a Postdoctoral Fellow at the University of Toronto Scarborough, where they have carried out in-depth data analysis and visualization of long-term meteorological and air pollutant data using R, optimized the analysis method, and documented the optimization in Standard Operating Procedure. In 2019, they were an Instructor (Vancouver Summer Program) at The University of British Columbia, where they developed a curriculum on “Environmental Chemistry of the Atmosphere and Ocean” and taught the course to 13 international students. From 2012 to 2019, they were a Research Assistant at The University of British Columbia, where they directed the complete lifecycle of two field campaigns to collect air samples at remote locations in Canada, executed extensive data collection and analysis on the properties of aerosol particles in the atmosphere, and liaised with diverse stakeholders throughout research. In 2016, they were a Visiting Researcher at Karlsruhe Institute of Technology (KIT), where they initiated a collaboration through communication at a conference and partnered with researchers to execute a study regarding the ice-nucleating ability of soil particles.

Meng Si obtained a Bachelor's degree in Chemistry from Nankai University between 2008 and 2012. From 2012 to 2019, they earned a Doctor of Philosophy - PhD in Atmospheric Chemistry from The University of British Columbia. In 2021, they obtained a Diploma in Data Science from Concordia University. Additionally, they have obtained several certifications from DataCamp, Udemy, and Coursera, including a Data Scientist Professional Certificate and a Google Project Management Certificate.