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2017 NECINA AI Conference

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发表于 2017-11-30 07:00:32 | 显示全部楼层 |阅读模式
活动类型:
讲座
活动时间:
2017-12-2 10:00 AM 至 2017-12-2 05:00 PM 商定
活动地点:
Cambridge Innovation Center (1 Broadway, Cambridge, MA) Room: Havana (5th floor)
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本帖最后由 zeng217 于 2017-11-30 07:01 AM 编辑

Overview:
In the sphere of business, Artificial Intelligence is poised have a transformational impact, and the effects will be magnified in the coming decades. As manufacturing, retailing, transportation, finance, healthcare, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning, AI has catalyzed waves of innovations and new opportunities. The bottleneck now is in management, implementation, and business imagination.

This conference will focus on the practical implications and the potential barrier to adoption of AI technologies in two vertical industries: healthcare and finance. We believe that the interdisciplinary discussion will evolve insightful and innovative ideas.

Registration: [url=]http://42frztdj.eventdove.com/[/url]

Time: 10: 00 am ~ 5:00 pm 12/2/2017 Saturday
Location: Cambridge Innovation Center (1 Broadway, Cambridge, MA) Room: Havana (5th floor)
Host: NECINA
Co-host: Liaoyuan, CIC
Partners: Po Dan Boston, Harvard Medical School CSSA

Who should come:
As an audience:
•    Understand the pain point of the industry for the entrepreneurs
•    Make a clearer career plan for young professionals and new graduates
•    Get ideas of choosing research and industry areas for PhDs and post-doctors
As a speaker & guest:
•    Help and contribute to the growth Boston AI community
•    Connect with other speakers & VIP guests to discover opportunities for career development
•    Get a communication channel with guests & audiences to find talents, partners

Agenda:
  • 9:30 am ~ 10:00 am Registration & Breakfast
  • 10:00 am ~ 11:00 am keynote 1: Coach Wei, Topic— Migrant Mentality: Learning, Career and Entrepreneurship (45 min talk + 15 min Q&A)
  • 11: 00 am ~ 12: 00 pm keynote 2:  Royal Wang, Topic: Deep Reinforcement Learning and Its Practical Applications (45 min talk + 15 min Q&A)
  • 12:00 pm ~ 1:00 pm Lunch Break
  • 1:00 pm ~ 2:00 pm Panel 1: HR Panel — Amazon, Facebook, Pham/Life Science HR Director (10 min individual talk + 30 min Q&A)
  • 2:00 pm ~ 3:20 pm panel 2: AI in Healthcare;
    • Panelist: Dr. Jason [email protected] MD Anderson Cancer Center/Novartis
    • Tenghui Chen @ Sanofi (20 min individual talk + 20 min Q&A)
  • 3:30 pm ~ 5:00 pm panel 3:AI in Finance
    • Panelist: David Xiao, CEO and Founder at Katapal, Inc
    • Yunpeng Zhang, Sr. Quantitative Analyst, VP at State Street
    • Victor Cao, COO at AuthRight (20 min individual talk + 20 min Q&A)
  • 5:00 pm Wrap-up
Keynote Speakers

Coach Wei | Executive Chairman at Yottaa
Mr. Wei is the founder of Yottaa, which provides a cloud-based automation platform that enables businesses to optimize, secure and manage end user experience in real time to drive business impact for their online and mobile applications. He also serves as the Chairman of Nexaweb Technologies, a Boston based company he founded in 2000 that pioneered Rich Internet Applications and enterprise web 2.0. He raised over $20M in venture capital for Nexaweb, built a global team, grew the revenue from zero to multi-million dollars and achieved over 7,000 global deployments of the Nexaweb Platform. Mr. Wei is an accomplished writer and speaker, he has published numerous articles on topics including: AJAX, J2EE and .NET, RIA development, XML, signal/image processing, composite materials and ultrasonic imaging.

Royal Wang | Sunny Crown, Founder
Royal and his friends at Sunny Crown concentrate on applying the knowledge of Machine Learning and Human-Computer Interaction to specific scenes. Their products, Personalized Intelligent Tutor (PI Tutor) for example, could learn from user behavior and provide personalized learning experience. Based on Deep Learning, PI Tutor understands the character and need of each user, therefore, improves learning efficiency and effectiveness.

Parking & Direction:  
By Car: Free parking at MIT Tang Center(E-51) parking Lot or street meter parking
By Subway: Kendall Square T station (Red line)

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