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Statistics and Data Science: Beyond Big, Missing or Corrupted DataJan. 19-20, 2019: Big Data, corrupted data, missing data – how to handle it all? HDSI in its role as a data science leader is co-sponsoring a two-day symposium — Statistics & Data Science Symposium: Beyond Big, Missing or Corrupted Data. The event will gather outstanding researchers pushing the frontiers of statistics as applied to the data. Speakers include leaders from Caltech, Facebook, Microsoft, Princeton and the U.S. Census Bureau. Focus will be on the impact of data-driven science on the field of statistics, addressing such key questions as:
Sponsored by the UC San Diego Department of Math and HDSI, registration remains open for the campus-based event Jan. 19-20. Learn more about special registration and reservation options.
The advent of new technologies has created great opportunities for data-driven discoveries spanning the worlds of science and industry and impacting both equally. In the past few years, data sources and availability have greatly changed. Examples include the abundance of data related to in some way to human behavior, policy implementations, interactions with a large number of computer devices and advertising materials, electronic records. Many datasets are now coming in a range of multimodal forms typically collected as streams of information; they now present highly unstructured patterns where a single phenomenon of interest is observed through multiple types of measurement devices, with each device possibly collecting only partial information of interest. Join our distinguished speakers and assembled experts to discuss issues like how can we disentangle and yet utilize all of the complex data in order to enrich statistical algorithms and models?
The event organizers are UC San Diego researchers Jelena Bradic and Dimitris Politis
Among the invited experts: From UC San Diego, Danna Zhang and Wenxin Zhou; Alekh Agarwal, Microsoft Research; Animashree Anandkumar, Caltech; Guang Cheng, Purdue University; Jianqing Fan, Princeton University; Sudeep Srivastava, Facebook; from UC Berkeley, Bin Yu, Peng Ding and Yian Ma; Yen-Chi Chen, University of Washington; from University of Chicago, Chao Gao and Veronika Rockova; Tucker Mcelroy, Census Bureau; Stanislav Minsker, University of Southern California; Annie Qu, University of Illinois, Urbana–Champaign; Aaditya Ramdas, Carnegie Mellon University; Zhao Ren, University of Pittsburgh; Srijan Sengupta, Virginia Tech; Stefan Wager, Stanford University; Anru Zhang, University of Wisconsin-Madison; Xianyang Zhang, Texas A&M University; Yinchu Zhu, University of Oregon; and Nan Zou, University of Toronto.