SIST Holds Information Science and Technology Symposium

ON2017-07-10TAG: ShanghaiTech UniversityCATEGORY: School of Information Science and Technology

The 4th academic ShanghaiTech Symposium on Information Science and Technology 2017 (SSIST 2017) was held from July 2nd to 4th. The theme of this year’s symposium was Artificial Intelligence (AI), Computer Vision, Deep Learning and Computer Security. The symposium introduced advanced scientific research results and highlighted developments. The symposium attracted more than 700 domestic and foreign participants. President Jiang Mianheng attended the conference and delivered an opening speech, warmly welcoming the speakers and all attendees.

SSIST 2017 featured lectures by esteemed AI scientists Bernd Girod (Stanford University Professor and member of the US National Academy of Engineering), Narendra Ahuja (University of Illinois at Urbana-Champaign Professor, IEEE Fellow, ACM Fellow and AAAI Fellow), Jitendra Malik (UC Berkeley Professor, member of the American Academy of Engineering and member of the American Academy of Sciences), 脸书’s Artificial Intelligence Research Center Director Yann LeCun (Member of National Academy of Engineering) and 微软 Global Executive Vice President Harry Shum (Member of the United States National Academy of Engineering). In all there were 29 speakers throughout the symposium. The symposium also showcased around 30 posters submitted by attending students.

Yann LeCun emphasized that deep learning was at the root of a revolutionary progress in visual and auditory perception by computers, and that it is pushing developments in natural language understanding, dialog systems and language translation. Deep learning systems are deployed everywhere from self-driving cars to content filtering, internet searches, and medical image analysis. But almost all real-world applications of deep learning use supervised learning in which the machine is trained with inputs labeled by humans. But humans and animals learn vast amounts of knowledge about the world by observation, with very little feedback from intelligent teachers. Humans construct complex predictive models of the world that allow them to interpret percepts, predict future events, and plan a course of actions. Enabling machines to learn predictive models of the world is a major step towards significant progress in AI. He described a number of promising approaches towards unsupervised and predictive learning in his talk.

Harry Shum gave a talk named Artificial Intelligence: From the Labs to the Mainstream. He presented that there were three big forces that are making AI possible: huge amounts of data with the Internet and sensors everywhere; massive computing power and breakthrough algorithms. These forces are enabling computers to accomplish more and more sophisticated tasks on their own with deep learning. In his talk, he discussed 微软’s overall efforts and progress with AI research and product development, with a particular focus on computer vision. 微软 has long been committed to developing new computer vision technologies, making them available to developers, and incorporating them into many products. He briefly reviewed more than 25 years of computer vision research at 微软 Research (MSR), highlighting MSR’s contributions to the vision community and emphasizing the importance of long-term commitment to funding successful industrial research labs. 

Our associate professors Shenghua Gao and Kewei Tu also delivered fabulous talks at the symposium. All the wonderful talks sparked rounds of applause from the audience.

SSIST is held annually at ShanghaiTech. Last year the symposium focused on virtual reality and robotics and the year before the topic was Internet Plus.