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"Big data is a term for data sets (https://en.wikipedia.org/wiki/Data_set) that are so large or complex that traditional data processing (https://en.wikipedia.org/wiki/Data_processing) applications are inadequate to deal with them. Challenges include analysis (https://en.wikipedia.org/wiki/Data_analysis), capture, data curation (https://en.wikipedia.org/wiki/Data_curation), search, sharing (https://en.wikipedia.org/wiki/Data_sharing), storage (https://en.wikipedia.org/wiki/Computer_data_storage), transfer (https://en.wikipedia.org/wiki/Data_transmission), visualization (https://en.wikipedia.org/wiki/Data_visualization), querying (https://en.wikipedia.org/wiki/Query_language), updating and information privacy (https://en.wikipedia.org/wiki/Information_privacy). The term "big data" often refers simply to the use of predictive analytics (https://en.wikipedia.org/wiki/Predictive_analytics), user behavior analytics (https://en.wikipedia.org/wiki/User_behavior_analytics), or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. (https://en.wikipedia.org/wiki/Big_data#cite_note-2) "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem." (https://en.wikipedia.org/wiki/Big_data#cite_note-3)
Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on". (https://en.wikipedia.org/wiki/Big_data#cite_note-Economist-4) Scientists, business executives, practitioners of medicine, advertising and governments (https://en.wikipedia.org/wiki/Government_database) alike regularly meet difficulties with large data-sets in areas including Internet search (https://en.wikipedia.org/wiki/Web_search_engine), finance, urban informatics (https://en.wikipedia.org/wiki/Urban_informatics), and business informatics (https://en.wikipedia.org/wiki/Business_informatics). Scientists encounter limitations in e-Science (https://en.wikipedia.org/wiki/E-Science) work, including meteorology (https://en.wikipedia.org/wiki/Meteorology), genomics (https://en.wikipedia.org/wiki/Genomics), (https://en.wikipedia.org/wiki/Big_data#cite_note-5) connectomics (https://en.wikipedia.org/wiki/Connectomics), complex physics simulations, biology and environmental research. (https://en.wikipedia.org/wiki/Big_data#cite_note-6)"
Our distinguished panel will discuss the latest innovations in big data.
Please come with questions and comments.
If you are big data startup and would like space on a demo table for the networking portion of the event, please send an email message to:
Put this in the subject header:
Th 4/6 Big Data Startup Demo Table
6:00 pm to 7:00 pm Check In, Food, Networking Reception
7:00 pm to 8:30 pm Panel Discussion, Q & A
8:30 pm to 9:00 pm More Networking
About the Moderator:
Eric Hanson is an attorney in the Corporate Practice Group at the Palo Alto law firm of Wilmer Hale. Eric's practice covers a broad range of general corporate and securities law. He has represented small startups, public companies and venture capital funds in both ongoing counseling and transactional matters.
Prior to his legal career, Eric worked as a membership coordinator for the Electronic Frontier Foundation and as a database programmer at the Breast Care & Cancer Research Center at the University of Washington.
About the Panelists:
Evangelos Simoudis is a recognized expert on big data strategies and corporate innovation. He is the author of The Big Data Opportunity In Our Driverless Future (https://goo.gl/Fdc4Le). Evangelos has been working in Silicon Valley for 25 years as a venture investor, entrepreneur, and corporate executive. He is the co-founder and Managing Director of Synapse Partners, a venture firm that invests in early-stage startups developing big data applications, and an advisor to global corporations on big data strategies and Startup-Driven Innovation. He has also served as Managing Director at Trident Capital, and Partner at Apax Partners. In 2012 and 2014 he was named top investor in online advertising. Prior to his venture and advisory career, Evangelos served as President and CEO of Customer Analytics, and as Vice President of Business Intelligence at IBM.
Evangelos serves on advisory boards for the Center for Information Science and Technology at Caltech, the International School of Business at Brandeis University, the Center for Urban Science and Progress at New York University, and the Autonomous Vehicle Task Force of SAFE. He earned a PhD in computer science from Brandeis University and a BS in electrical engineering from Caltech.
Prateek Joshi is an Artificial Intelligence researcher, a published author of sixbooks, and a TEDx speaker. He is the founder of Pluto AI, a venture-funded Silicon Valley startup building an analytics platform for water resource management powered by Deep Learning. His work in this field has led to patents, tech demos, and research papers at major IEEE conferences. He has been an invited speaker at technology and entrepreneurship conferences including TEDx, AT&T Foundry, Silicon Valley Deep Learning, and Open Silicon Valley.
His tech blog (www.prateekjoshi.com (http://www.prateekjoshi.com/)) has received 1.2M+ page views from 200+ countries and has 6,600+ followers. He frequently writes on topics such as Artificial Intelligence, Python programming, and abstract mathematics. He is an avid coder and has won many hackathon prizes, including at Facebook. He graduated from University of Southern California with a Masters degree specializing in Artificial Intelligence. He has previously worked at Nvidia and Microsoft Research. You can learn more about him on his personal website at:
Chase McMichael is a physicist and two time startup entrepreneur in mobile messaging, collaboration, video and big data. He is now the CEO and Co-Founder of InfiniGraph a video deep learning company. Chase has held positions at Hearst Corp, Chase Manhattan, Oracle and Sprint. He was awarded the Fast Tech 50 for his first Startup UNBOUND and won the Marketing Sherpa Viral Hall Of Fame award for a video contesting platform. Chase's focus is on machine learning and real time video analysis using deep learning for large digital and TV broadcasters.
Zong Ling, Ph. D., is currently a senior software engineer and scientist at the IBM Almaden Research Center in San Jose.
Dr. Ling has been working at the IBM Almaden Research Center for about 20 years, with a primary focus on performance evaluation of IBM data storage products. Dr. Ling engages in customer service globally through troubleshooting data storage issues, providing technical training classes, and publishing IBM whitepapers. Dr. Ling's current interests are in the areas of FinTech/Blockchain, Cognitive Business, Big Data Storage and Analytics, Cloud Computing Architecture, Service Science, Internet of Things, and Information Technology Service Management.
As an IBM University ambassador and evangelist of IBM corporate culture with many years of expertise in information technology engineering and services, Dr. Ling has delivered academic lectures at Stanford University, the University of California at Berkeley, and San Jose State University. He has also taught overseas and has hosted numerous seminars at top universities in China. In recognition of his contributions to the community, Dr. Ling has been a recipient of the United States President's Volunteer Service Award for the past 10 years. He holds a Ph.D. in Computer Engineering from the University of Hawaii at Manoa and a B.S. from the University of Science and Technology of China.
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