[ABE-L] visita do Prof.=?ISO-8859-1?Q?_Michael_Jordan_=E0_?=UFRJ

[Dani Gamerman]

Caros colegas 

É com prazer que anunciamos a visita do Prof. Michael Jordan, 
da Universidade da California (Berkeley) à UFRJ. Essa visita 
está sendo conjuntamente organizada pelos Programa de PG em 
Estatística, Informática e Engenharia de Sistemas e Computação.

A visita será no dia 07 de agosto de 2018 e consistirá em
11-12 conferência no auditório do CT2
12-13 almoço
13-14 pequenas reuniões com alunos e docentes

Pedimos que os interessados em terem reunião com o Prof. Jordan
nos informem do seu interesse e procuraremos acomoda-los da melhor
forma possível.

Título e resumo da palestra seguem abaixo
On Computational Thinking, Inferential Thinking and Data Science

The rapid growth in the size and scope of datasets in science and
technology has created a need for novel foundational perspectives 
on data analysis that blend the inferential and computational sciences.  
That classical perspectives from these fields are not adequate to 
address emerging problems in Data Science is apparent from their 
sharply divergent nature at an elementary level---in computer science, 
the growth of the number of data points is a source of "complexity" 
that must be tamed via algorithms or hardware, whereas in statistics, 
the growth of the number of data points is a source of "simplicity" 
in that inferences are generally stronger and asymptotic results can 
be invoked.  On a formal level, the gap is made evident by the lack 
of a role for computational concepts such as "runtime" in core 
statistical theory and the lack of a role for statistical concepts 
such as "risk" in core computational theory.  I present several research
vignettes aimed at bridging computation and statistics, discussing 
the problem of inference under privacy and communication constraints,
the problem of the control of error rates in multiple decision-
making, and the notion of the "optimal way to optimize".


Um pequeno resumo do CV do Prof. Jordan segue abaixo.
Michael I. Jordan is the Pehong Chen Distinguished Professor in the
Department of Electrical Engineering and Computer Science and the
Department of Statistics at the University of California, Berkeley.
His research interests bridge the computational, statistical, cognitive
and biological sciences.  Prof. Jordan is a member of the National 
Academy of Sciences and a member of the National Academy of Engineering.
He has been named a Neyman Lecturer and a Medallion Lecturer by the
Institute of Mathematical Statistics.  He received the IJCAI Research
Excellence Award in 2016, the David E. Rumelhart Prize in 2015 and
the ACM/AAAI Allen Newell Award in 2009.

Esses dados já estão disponíveis na lista de palestras do Programa 
de PG em Estatística (www.dme.ufrj.br), na aba palestras do 2018/2.

Agradeço a colaboração dos Profs. Daniel Sadoc (Informática) e Daniel
Figueiredo (Engenharia de Sistemas e Computação) na organização.
Agradecemos a divulgação junto a possíveis interessados.

Saudações acadêmicas
Dani

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Dani Gamerman
Depto. de Métodos Estatísticos (DME)
Lab. de Sistemas Estocásticos (LSE)
Instituto de Matemática - UFRJ
http://www.dme.ufrj.br/dani
www.statpop.com.br
fb: StatPop, twitter: @blogStatPop
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