The Spatial Data Science Conference (#SDSC19) is the first event to bring together Data Scientists and Developers who specialize in working with spatial data.
Founded in 2017, the conference brings together organizations who are pushing the boundaries of spatial data modelling - ranging from large enterprise, to cities and government, as well as thought leaders from academic institutions.
The agenda will be packed with keynotes, panels, technical workshops, and opportunities to network with experts in spatial data from across the globe.
Isaac Brodsky is a Senior Software Engineer at Uber, and is the lead for the H3 open source project. He has experience in big data and real time analytics.
Dunia is the Global Head of Real Estate Data and insights at WeWork. Her focus has been to build tools to optimize WeWork’s pre-opening scale and speed, as well as leading Market Intelligence.
Jack is on Airbnb's Homes Platform team, focusing on developing scalable products to onboard and manage hosts where short-term rental regulations apply.
Esteban Moro is associate professor at Universidad Carlos III de Madrid and currently, He is a visiting professor at MIT Media Lab.
Danil works on ML problems in Facebook Spatial Computing group. He holds PhD in Applied Math from Harvard and prior to Facebook worked on scalable computing at Microsoft and MathWorks.
Neera is a Senior Product Manager at Instacart, the North American grocery delivery and e-commerce company. As part of Instacart's Emerging Products team, Neera leads geographic and category expansions.
The day before the conference we'll be hosting a series of interactive workshops with experts from across the globe. Places are limited, and available to SDSC attendees only.
Towards Spatial Data Science
Remake US election with h3 and Kepler.gl
From Data Science to Spatial Data Science
Spatial Modelling in the Utilities Industry
Enabling Social Impact Organizations with Spatial Analysis Techniques
Exploring The Atlas of Inequality in US Cities
Geo Exploration with Elasticsearch and Kibana
Why the future of urban data might not be open…
From Growth Hacking to Growth Mapping
Geospatial Processing & Natural Experiments for Regulatory Affairs
Improving spatial models with new location data streams chaired by Javier Perez Trufero, Head of Data at CARTO.
Using complex datasets for infectious disease identification and intervention
Applications of geo-spatial analysis within fundamental investment research
Spatial Data Science for Social Good: Improving Haitian’s access to dignified sanitation through data
A series of Spatial Stories from leading Data Scientists.
The Vehicle Routing Problem: Optimizing School Bus Routes in Philadelphia through Spatial Analysis
Making Spatial Access Measurement Accessible
From Outsmarting Traffic to Eliminating it All Together
What is Data Strategy?
Data Mining the City: Agent Based Simulation for Spatial Behavior Prediction
Using Whitespace Analysis for PE Investment Decision Making
Satellite image analysis at scale
Location Intelligence and Optimization for the Enterprise
10:30 AM - 12:00 PM
This workshop will give an introduction to the R-spatial software ecosystem, its history and recent developments. It will discuss spatial
feature data, raster data, spatio-temporal data, movement data, show examples, and discuss future developments. It will also point to places for further reading, finding software packages, and asking questions.
Prior knowledge of R is useful, but not required.
2:00 PM - 4:00 PM
CARTO's Lead Data Scientist and CARTOframes creator, Andy Eschbacher, will host a workshop that introduces basic spatial data science workflows to show how to get more information out of geodata, including exploratory spatial data analysis, spatial lag and spatial error models, as well as dynamic visualization of model outputs in a map in a notebook.
370 Jay Street,
Alfred Lerner Hall,
New York, 10027.