DATA-DRIVEN INNOVATION
 
DATA-DRIVEN INNOVATION
 
DATA-DRIVEN INNOVATION
 
DATA-DRIVEN INNOVATION
Sunday, March 13th, 2016  | 8:30pm IST | 11:00am EST | Free Interactive Web Seminar

Panelists:
Ashish Gupta | Senior Software Engineer Google NYC, Ph.D. Computer Science
Prukalpa Sankar | Founder SocialCops
Soroush Vosoughi | Postdoctoral Associate MIT Media Lab


Moderator:
Manish Agarwal | Quantitative Researcher Point 72 Asset Management, Ph.D. Information Theory


Data is a new source of inspiration. The Internet and mobile connectivity has enabled a plethora of data that offers unprecedented opportunities in many domains. Using automated analytical methods, it reveals patterns humans alone might never see and offers new approaches to age-old decision-making and problem-solving processes. From Data Science for X-ray Astronomy, which helps us unravel physical laws under the most extreme conditions known, to financial markets emanating massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans, data has unleashed endless innovation.

At no other time in history have humans felt so impressed and intimidated by what machines can do. With individuals, organisations and governments gradually realising how useful data can be, more interfaces and visualisation tools are bubbling up to make sense of them. Speakers of this groupinar, who are from diverse sectors like Academics, Bioinformatics, Non-profit, Finance and Internet, will discuss how they overcome data related challenges and how data is changing their industry.


Topics we hope to cover in this Groupinar:

  • How various industries are going through technological and organizational transformations to deal with new big data related challenges.
  • Areas where machines are already very active and those where machines are likely to make significant inroads in the next few years.
  • Big data industries such finance, social change, journalism and internet marketing.
  • Personal data industry which relies on second by second details on human behavior.
  • Behavioural data: what people really do, and how it differs from what they say.
  • Hybrid data: quantitative and qualitative.
  • Social Entrepreneurship: How to Get Started? What are Some Major Challenges?
  • Three different aspects of data industry: collection, analysis and business application.
  • Real-time, quantitative and geo-located data generated through crowd sourced sensors.
  • Alternative data sources like mobiles phones, website analytics, search engines, satellites and surveys.
  • Open source data. Free online resources and tools.
  • Finding patterns, machine learning and data science. New exciting algorithms like Deep learning.
  • Data visualization and new design challenges.
  • Finding applications of unstructured data like twitter, blogs, news and images.
  • Data science for improved public health.
  • Transforming industries like travel, transportation, shipping and logistics.
  • The role of data in shaping government policies, elections, public opinion, awareness and journalism.
  • Automation and dealing with the challenge from machines.
 
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