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Artificial Intelligence Seminar

Presented by USTC - Silicon Valley Alumni Association

Topic: Artificial Intelligence Seminar

1. Machine Learning for Medical image Analysis

2. Prospects for Investment in Artificial Intelligence

3. Artificial intelligence in Fog and Dust Computing

Speakers:

1. Qin Wenjian, Stanford University - University of Chinese Academy of Sciences co-training doctoral degree, the Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology Engineer, served as the Guangzhou Institute of Advanced Technology Institute of Science and Technology Deputy Director, Lenovo Research Institute practice researcher, National Standards Technical Committee. Participated in the creation of two medical device technology companies, presided over and participated in more than 10 scientific research projects, the cumulative funding of more than 2000 million, scientific research has repeatedly won the Entrepreneurship Competition awards.

2. Wang Chuan, Georgia Institute of Technology in 1994, received a master's degree in computer science, and has worked in Silicon Valley since. Experience across software design, real estate investment and financing, quantitative transactions. Currently focused on high-tech research on the secondary market investment. Over the past two years through its WeChat public number investguru published more than 100 original articles.

3. Ding Xianfeng, perception and cognitive expert. Huawei Sensor Laboratory Director and Chief Scientist, responsible for Huawei sensor import validation, context-aware algorithm development, software development and integration. Prior to working in Silicon Valley was in the sensor algorithm and artificial intelligence system development for 15 years, any STMicroelectronics Director of Engineering, Director Sensor Engineering Manager, the United States Semiconductor Engineering Director, Intel director, Chief Sensor System Architect.

Earlier Event: January 18
Reinforcement Learning
Later Event: January 25
Launch a new product @SVE Demo Night