REDWOOD CITY, Calif. – May 25, 2022 – TigerGraph, provider of a leading graph analytics platform, today unveiled the winners of the Graph for All Million Dollar Challenge — awarding $1 million in cash to game-changing, graph-powered projects that analyze and address many of today’s biggest global social, economic, health, and climate-related concerns. The winning projects, announced at this week’s Graph + AI Summit, were hand-selected by the global judging committee from more than 1,500 registrations from 100+ countries. Mental Health Hero claimed the $250k Grand Prize for creating an application to help provide greater access and personalization to mental health treatment.
“From addressing mental health issues to supporting Ukrainian refugees to predicting how supply shocks will spread through the world economy, the submissions we received tackle real-world concerns and demonstrate innovative approaches to resolving them with graph technology,” said Dr. Yu Xu, founder and CEO of TigerGraph. “We wanted to create a challenge that produced new and innovative applications of graph technology and the global community did just that. The overwhelming focus on global issues in this challenge shows that regardless of geography, we all share many of the same concerns and challenges, and that graph technology can help address them.”
Graph For All Million Dollar Challenge Winners
After extensive review by the global judging committee, consisting of 32 experts from industry, academia, and TigerGraph, the following are the 15 award-winning projects.
Graph For All Million Dollar Challenge Grand Prize Winner
Grand Prize, $250,000: Mental Health Hero – Mental Health Hero is a graph-based approach to solving one of the largest public health epidemics today: the prevalence of untreated mental health issues such as anxiety and depression. According to the CDC, 400 million people globally are not receiving essential treatment for their mental health disorders . Additionally, only 40% of adults with mental illness are estimated to receive treatment for it .
Graph For All Million Dollar Challenge Top Awards
Most Impactful 1st place, $100,000: UAWelcome – The global refugee crisis reached a new level of awareness with the war in Ukraine. In response, UAWelcome created a platform that uses graph technology to connect individual refugees and their needs with a fast-growing community of volunteers and the limited and scattered resources. Their application is already in use connecting volunteers and scattered resources with Ukrainian refugees and helping refugees seek asylum in the U.S.
Most Innovative 1st place, $100,000: Universe Planner – A multiverse-metaverse planning app that allows users to solve complex problems by tapping into and leveraging social knowledge. It also socially connects users to others working on the same or similar mission, plan, or task.
Most Ambitious 1st place, $100,000: ShockNet – Allows users to adjust assumptions, investigate the predicted chains of shocks through the world economy, and identify ways to avoid economic crises by gaining visibility into how and why shocks spread. ShockNet includes an app that allows policymakers to visualize and adjust the model to better understand how to offset or avoid a future crisis.
Most Applicable 1st place, $100,000: BioDex – BioDex combines our natural curiosity with the motivation of gaming. By gamifying the experience of connecting to nature, players can snap images of nature, identify its species, and display its properties in real time while striving to identify as many species as possible and contributing biodiversity information to research.
Women Who Graph, $30,000: Diagnosx – After seeing first hand in the ER the dual struggles of patients not understanding their health conditions and doctors trying to draw pictures to help explain conditions, Bree Day knew there had to be a better way. Her idea to get 3D models to illustrate breadth and depth of a patient’s diagnosis into all patients’ hands is realized in Diagnosx. The application presents a 3D model of a patient’s diagnosis and medical history to better illustrate the findings and diagnosis, and decrease disparities in doctor/patient communication.
Most Popular, $20,000: Multimodality Cancer Graph – Many diseases are related to each other, and complications from a certain disease could cause another. Through the power of graphs and machine learning, this project aims to uncover new disease links and help researchers better prepare for future pandemics or emerging diseases.
- 2nd place, $50,000: Fact-Checker: Fighting Misinformation at Scale – A multi-platform, multi-lingual, real-time fact-checking system powered by machine learning and graph technology.
- 3rd place, $25,000: Project Athena – An automatic, generic knowledge graph framework that builds itself from textual unstructured data and uses natural language to query and apply data.
- 2nd place, $50,000: RepoLinks – A graph that shows the dense, complex interconnections between software developers, programming languages, and software projects, to better understand factors such as skill sets, productivity, and technology evolution within organizations.
- 3rd place, $25,000: Gemini – An eclectic news search engine that cuts through the noise and allows readers to dig deep into a specific topic or explore multiple facets of the news they are most interested in.
- 2nd place, $50,000: Finding Drug Interactions in Silico with Graph – Identifies drug interactions and potential side effects using graph machine learning during the pharmaceutical development process.
- 3rd place, $25,000: Candoor – A social networking site for people seeking to connect with others for candid conversations on anything from professional industry advice to tips for pursuing a hobby.
- 2nd place, $50,000: TigerGraph for United Nations (UN) Data – Makes UN data, the most robust dataset in the world, easily accessible to anyone by harnessing the power of graph technology.
- 3rd place, $25,000: BiasCheck – A cool new Google Chrome extension that fosters critical thinking by identifying bias/accuracy of all news sources. The technology also allows users to explore specific topics with differing viewpoints that challenge the status quo.
The Graph for All Million Dollar Challenge judging committee was comprised of the world’s brightest and most recognizable data scientists, professors, PhDs, distinguished engineers, and founders of global companies focusing on artificial intelligence (AI), analytics, knowledge graph, and other industry experts with deep knowledge of graph technology, graph use cases, and graph deployments. The judging committee included eight PhDs, three academics from top universities, an NSF Graduate Research Fellow, a marine geoscientist, and a 2x Kaggle Grand Master. TigerGraph engineers and product experts also joined the panel as employee judges.
“Wow! The creative use of graph and data in these solutions really shows how a graph approach with the right data can address so many global issues,” said Juan Sequeda, principal scientist, data.world and Graph for All Million Dollar Challenge judge. “What is truly exciting is that most of these projects can be expanded and applied in many different situations and use cases in the future. The projects serve as templates that can be adjusted, augmented, and adapted for other situations, helping make life better for even more people. Like the project created to help Ukrainian refugees, while it is excellent for refugee situations, that same application could be used to help people impacted by natural disasters throughout the world.”
TigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industry’s first and only distributed native graph database, TigerGraph’s proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis. The company is headquartered in Redwood City, California, USA. Start free with tigergraph.com/cloud.
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