Tanjo AI, UCF Finalists in Pandemic Response Challenge

A winner will be announced on 26 February in the $500,000 Pandemic Response Challenge from among 48 finalists, including teams from Tanjo AI and two from the University of Central Florida. The teams are competing to develop artificial intelligence-driven models to prescribe actions for safely reopening society and limiting economic impact while minimizing COVID-19 transmissions.

The Challenge is from XPRIZE, which designs incentive competitions to solve humanity’s grand challenges, and sponsored by Cognizant, a leading technology and professional services company.

The finalist teams are from 17 countries, including 20 groups from the US and six each from Canada and China.

Chapel Hill, North Carolina-based Tanjo AI’s Community Confidence Covid-19 machine learning dashboard is designed to give business owners and community stakeholders real-time intelligence and predictive modeling on population health risk, consumer sentiment, and community resilience. Users can access this information in an easily understandable way that helps them view the risk to their organization or region, and they will even be able to simulate the impact of implementing evidence-based recommendations.

There has been a shift towards the wider digitisation of training. Find out more on this topic in  The Next Frontier of Interoperability.

“We are all working around the clock to help mitigate the negative impacts of Covid-19 through the smart application of artificial intelligence to ensure the health and safety of our communities,” said Richard Boyd, CEO, Tanjo AI. Boyd has helped create some of the most innovative game technology companies in the industry. Previously at Lockheed Martin he led a group of innovative engineers and designers known as Virtual World Labs.

The two UCF teams include faculty and graduate students from the departments of Statistics and Data Science and Computer Science.

Shunpu Zhang, chair and professor in UCF’s Department of Statistics and Data Science, who leads one team, said predictions based on hard numbers minimize guesswork and maximize impact. “That’s what big data analytics can solve. If you dig deeper through seemingly messy data, you can find some truths.” The value of the research lies in distinguishing association from causation, Wang says.

The second team, known as Pandemic Wave Predictor team, is led by computer science professor Lotzi Bölöni. The team’s computer model works by applying advanced machine learning to epidemiological models to learn their parameters, including when to recommend certain interventions for helping reduce the spread of Covid-19. “We believe that policy decisions should be made on an informed basis, not based on gut feeling,” Bölöni said. “(Our model) also takes into account the economic and human cost factors of the interventions, such as the closing of the schools, as well as cultural factors.”

“The finalists in the Pandemic Response Challenge have demonstrated incredible innovation in their efforts to help the world emerge from the Covid-19 pandemic,” said Brian Humphries, CEO of Cognizant. “Advancements these teams are making can have far-reaching implications – empowering policy-makers and business leaders globally with data-driven tools, informing countries’ decisions about their re-opening strategies, and proving the value of AI and collaboration in addressing future humanitarian crises.”

“This challenge has shown encouraging results that leverage artificial intelligence at the service of social impact,” said Amir Banifatemi, Chief Innovation and Growth Officer of XPRIZE. “We set out to maximize the power of collaboration, competition, and innovation to accelerate solutions that could be applied to Covid-19 and future pandemics.”