What we're about
Upcoming events (2)
Link visible for attendees
The PyData Global Online Conference is where users, contributors, and newcomers can share experiences to learn from one another and grow together. PyData provides a virtual forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization.
This three-day online event consists of talks, tutorials, and discussions to bring attendees the latest project features along with cutting-edge use cases.
The time span of the conference stretches beyond any single time zone, reflecting the global nature of our community. To accommodate our attendees, each session will be recorded and made available to attendees the following day. Following the Conference, all recordings will be posted to the PyData YouTube channel.
Tickets follow a pay-what-you-can model and can be found here: https://pydata.org/global2022/tickets/
Why Charge for an Online Conference?
Revenue from the event will go to PyData and NumFOCUS, a nonprofit organization that supports open source scientific computer programming. NumFOCUS currently sponsors 43 Open Source Projects, and organizes community-driven educational programs for users and developers of open source scientific tools.
While the 2022 PyData Global Conference has no costs for venue or catering, there are still costs associated with bringing the event online. We also need to continue paying fixed costs to keep NumFOCUS healthy, as well as continue supporting the open source community.
For this reason, we have chosen to sell tickets with a pay-what-you-can pricing model. We appreciate your support for us during this time so that we can keep supporting you in the future.
Speaker: Dr. Jacob Barhak
Abstract: The Reference Model for disease progression was initially a diabetes model. The model technology was transformed to model COVID-19 near the start of the epidemic.
The model performs simulation at the individual level while modeling entire populations using the MIcro-Simulation Tool (MIST), employing High Performance Computing (HPC), and using patented machine learning techniques to combine models.
The model is now composed of multiple models from multiple contributors that represent different phenomena: It includes infectiousness models, transmission models, human response/behavior models, mortality models, and observation models. Some of those models were calculated at different scales including cell scale, organ scale, individual scale, and population scale.
The Reference Model has therefore reached the achievement of being the first known multi-scale ensemble model for COVID-19. This project is ongoing and this presentation is constantly updated for each venue. The latest interactive presentation with results is accessible at https://jacob-barhak.github.io/COVID19_Ensemble_Latest.html
The above link contains details, interactive results, conflict-of-interest statement, and acknowledgments for multiple model contributors.
The Reference Model is widely published. For details see: https://simtk.org/projects/therefmodel/
Speaker Biography: Jacob Barhak is an independent Computational Disease Modeler focusing on machine comprehension of clinical data. The Reference Model for disease progression was self developed by Dr. Barhak. The Reference model is the most validated Diabetes model known worldwide and also the first COVID-19 multi-scale ensemble model. His efforts also include standardizing clinical data through ClinicalUnitMapping.com and he is the developer of the Micro Simulation Tool (MIST). Dr. Barhak has a diverse international background in engineering and computing science. He is active within the python community and organizes the Austin Evening of Python Coding meetup. For additional information, please visit https://sites.google.com/view/jacob-barhak/home