GraphXD - Graphs Analysis Across Domains

BIDS GraphXD is a cross-domain initiative that promotes interdisciplinary collaboration and training for researchers, scientists, and theorists interested in using graphs and network analysis for applications in a variety of fields across STEAM including (but not limited to) anthropology, art, biology, computer science, economics, history, linguistics, mathematics, physics, and sociology.  

Graphs and networks are models of data – usually composed of nodes and vertices connected by edges – that can be used to analyze and to visualize different features and variables across a dataset, providing powerful at-a-glance summaries (or ‘signals’) of big and/or complex datasets. Network analysis allows each datapoint (or ‘node’) to contain an infinite number of features and variables for a given dataset. These features – such as strings, integers, boleans, and decimals, floats, doubles, etc. – can contain specialized data, and the graph database structure of a network allows for each datapoint/node to be connected to any other datapoint based on a measurable relation between them (‘edges’ or ‘links’).  

All interested researchers are welcome to learn more about graphs, networks and BIDS’ 2021 relaunch of the GraphXD initiative in this introductory article, view previous seminars and conferences on the GraphXD YouTube Channelsign up for the BIDS Mailing List to receive announcements about upcoming events and programs related to the BIDS XD initiatives, and sign up for the BIDS XD Community on Discord to get more involved in the new BIDS XD community online. All events and resources are open access to the broader community.

BIDS GraphXD 2021 — March 23, 2021 

GraphXD: Network analysis for data science applications across STEAM 
February 26, 2021  |  Adam Anderson  |  BIDS Blog: Data Science Insights

2018 GraphXD Workshop - March 27-29, 2018

GraphXD Seminar: Vector Representations of Graphs and the Maximum Cut Problem 
February 26, 2018  |  David P. Williamson, Cornell University

GraphXD Seminar: Data-Driven Methods for Learning Sparse Graphical Models 
November 30, 2017  |  Somayeh Sojoudi, UC Berkeley

GraphXD Seminar: Spectral Sparsification of Graphs 
October 19, 2017  |  Nikhil Srivastava, UC Berkeley

Graph Clustering Algorithms 
October 10, 2017  |  Jarrod Millman  |  BIDS Blog: Data Science Insights

GraphXD Seminar: Graph Clustering Algorithms 
September 28, 2017  |  Tselil Schramm, Simons Institute

BIDS Announces GraphXD (Graphs across Domains) 
September 25, 2017  |  Jarrod Millman  |  BIDS News

BIDS GraphXD (Graphs Across Domains)