Ross Cheung

Ross Cheung has a diverse background in data science and research. Their most recent position was as a Senior Scientist at Kairos Aerospace, starting in October 2021. Prior to that, they worked as a Data Scientist at AE Studio from September 2020 to September 2021, where they provided data science and machine learning solutions to clients. Their work included building models for natural language processing, computer vision, customer churn, and deep learning projects.

From December 2018 to September 2020, Ross worked as a Machine Learning Consultant at a LIDAR startup. Ross also served as a Data Science Fellow at Insight Data Science from January 2020 to August 2020. During this time, they gained experience in developing and implementing data science solutions.

Before transitioning into the data science field, Ross worked as an Air Quality Specialist at the South Coast Air Quality Management District from May 2017 to January 2020. Ross was responsible for analyzing data and developing a new cloud architecture to display real-time air quality data. Ross also created a system to track emissions from diesel ships using Python and API access.

Ross's research experience includes positions at the University of California, Los Angeles (UCLA) and UC Santa Barbara. At UCLA, they worked as a Researcher and Graduate Student Researcher from 2010 to 2017. Ross operated ground-based instruments, conducted computer modeling, and taught various classes as a Teaching Assistant. At UC Santa Barbara, they analyzed spectrometer measurements of natural methane seeps and developed retrieval algorithms.

Early in their career, Ross worked as a Researcher at the California Institute of Technology, Department of Geophysical and Planetary Sciences. Ross developed computer algorithms for the retrieval of OH column abundances from UV spectroscopy measurements, optimizing analysis routines and reducing uncertainties.

Overall, Ross Cheung has a strong background in data science, research, and atmospheric science. Ross has experience in developing and implementing data science solutions, conducting research, and analyzing environmental data.

Ross Cheung earned a Bachelor of Science (B.S.) degree in Mathematical and Computational Sciences from Stanford University in the years 2002 to 2006. Ross then pursued further education at UCLA, where they acquired a Master of Science (M.S.) degree in Atmospheric and Oceanic Sciences from 2008 to 2010. Ross continued their studies at UCLA and received a Doctor of Philosophy (PhD) degree in Atmospheric and Oceanic Sciences from 2010 to 2016.

In 2017, Ross attended The DevMasters and completed a Mastering Applied Data Science Bootcamp, focusing on Python and Machine Learning. Additionally, Ross has obtained various certifications, including a Deep Learning Specialization, Sequence Models, Convolutional Neural Networks, Structuring Machine Learning Projects, and Neural Networks and Deep Learning from Coursera. Ross also holds a Cheeky Scientist Associate certification from Cheeky Scientist.