A Contact Tracing Project Supervised by Prof. Gary CHAN Achieved Remarkable Results in an Open Challenge on Bluetooth-based Proximity Detection
Led by Prof. Gary CHAN, completed together with his MPhil student Tianlang HE and undergraduate dual-degree student Maximilian PRINTZ, the project, Contact-Tracing-Project, topped in the Leaderboard among 14 international participating teams in the open Too-Close-for-Too-Long (TC4TL) Challenge. The challenge was organized by US National Institute of Standards and Technology (NIST) in collaboration with MIT PACT. It aimed to improve proximity detection based on Bluetooth Low Energy (BLE) for Covid-19 exposure notification.
After two months of competition, eventually four teams from USA, Argentina and Hong Kong met the deadline and were ranked. Using novel models on classification, machine learning and data mining, Prof. Chan's "Contact-Tracing-Project" team excelled in all 4 evaluation categories and the overall rank. The team shared their techniques and experience in a virtual conference held in late August 2020 with more than one hundred participants. For more information on the challenge, please refer to the official website and Leaderboard ranking.
They are currently integrating their winning approaches into a novel, automated and privacy-preserving IoT contact tracing system using smart wearables (watches, dongles, etc.) to combat against Covid-19. Congratulations to Prof. Chan, Tianlang and Maximilian, and all the best to develop the technology to protect our public health!