Peter Wang has been developing commercial scientific computing and visualization software for over 15 years. He has extensive experience in software design and development across a broad range of areas, including 3D graphics, geophysics, large data simulation and visualization, financial risk modeling, and medical imaging. As a creator of the PyData community and conferences, he devotes time and energy to growing the Python data science community and advocating and teaching Python at conferences around the world. Peter holds a BA in Physics from Cornell University.
Holden is a transgender Canadian open source developer with a focus on Apache Spark, Airflow, Kubeflow, and related “big data” tools. She is the co-author of Learning Spark, High Performance Spark, and Kubeflow for Machine Learning. She is a committer and PMC on Apache Spark. She was tricked into the world of big data while trying to improve search and recommendation systems and has long since forgotten her original goal.
Travis is a well-known leader in the Python Data community having authored or led the creation of industry cornerstones such as NumPy, SciPy, Numba, Conda, XND, NumFOCUS, and PyData. Prior to Quansight, he founded Anaconda and established the industry-standard platform for data science and machine learning.
Chelle is a passionate advocate for open science, open source software, and inclusivity. She co-chaired the National Academies’ Report on Open Source Software Policy Options for NASA Earth and Space Sciences, and in addition to being a full time oceanographer, also leads NASA ESDS Program’s development of open source and open science best practices for NASA researchers. As a physical oceanographer focused on remote sensing, she has worked for over 25 years on retrievals of ocean temperature from space and using that data to understand how the ocean impacts our lives. She is the lead scientist on a proposed new NASA satellite, Butterfly. Her more recent research focuses on using cloud computing for interdisciplinary science, air-sea interaction research, and geophysical algorithm development. She has served on scientific committees, notably as co-chair of a standing committee for the National Academy of Sciences and has presented to a federal house committee on NASA’s implementation of scientific community priorities.
Joe Schmid is Chief Technology Officer at SymphonyRM, a provider of machine learning powered products that help healthcare organizations proactively engage patients. Prior to his current role, Joe lead platform engineering at Victrio (acquired by Verint), a provider of machine learning-based fraud detection systems with card issuers, banks, and merchant acquirers. Joe has served in a number of other engineering roles at technology companies in the areas of data analytics, fraud detection, speech recognition, and mobile computing.
Grant is a data scientist at Walmart Global Tech, product developer, and expert number cruncher with a decade of experience in solving problems with data. Most of Grant’s work is centered around building artificially intelligent applications driven by machine learning models deployed in cloud-based micro-services architectures.
Jie is a Machine Learning Engineer at SymphonyRM. In the past two years, she has helped the team successfully build scalable machine learning and data pipelines. These Dask powered ML workflows has enabled the team to deliver the products efficiently and reliably. She graduated from Heinz College at Carnegie Mellon with a Master degree in Information Systems Management in 2019.