{"id":799,"date":"2018-07-25T12:09:57","date_gmt":"2018-07-25T12:09:57","guid":{"rendered":"http:\/\/www.iberamia.org\/iberamia\/iberamia2018\/?page_id=799"},"modified":"2018-10-17T16:09:48","modified_gmt":"2018-10-17T16:09:48","slug":"plenary-talks","status":"publish","type":"page","link":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/plenary-talks\/","title":{"rendered":"Plenary Talks"},"content":{"rendered":"

<\/a><\/p>\n

Iberamia 2018 Career Recognition Award<\/em><\/span> talk<\/strong><\/h3>\n

Ethics and Artificial Intelligence<\/strong><\/span><\/h3>\n

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 <\/p>\n

Prof. Juan Pav\u00f3n
\n<\/span><\/strong><\/p>\n

Grupo de investigaci\u00f3n en Aplicaciones Sociales e Interdisciplinares basadas en Agentes (GRASIA<\/a>)
\nComplutense University of Madrid\u00a0 (<\/span><\/em><\/span>12:15, Thursday, 15th Nov)<\/span><\/em><\/p>\n

\n

Current development of Artificial Intelligence shows systems with greater degree of autonomy and decision making capabilities. Also, their integration in all dimensions of our daily living raises ethical issues on their application and behavior. This talk will review how ethics has been considered in the design of intelligent systems, and will address questions such as: Can we control that these systems follow an ethical behavior? Can we program ethical values in intelligent systems? What would be the ethics of robots?<\/p>\n

Short Bio<\/strong>: Juan Pav\u00f3n holds a PhD degree in Computer Science from Universidad Polit\u00e9cnica Madrid (1988). From 1987 to 1997 he was working in R&D departments of Alcatel in Spain, France and Belgium, and in Bellcore (USA), especially in the development of component-based architectures for distributed systems, and their application to multimedia services on broadband networks and mobile systems. Currently he is Full Professor at Universidad Complutense Madrid, where he leads the GRASIA research group. His main areas of interest focus on the application of multi-agent systems technology in distributed control, service personalization, knowledge management, ambient assisted living, Systems of Systems engineering, complex systems simulation, and tools to support Responsable Research and Innovation (RRI).<\/p>\n

 <\/p>\n

Data-driven Analytics for Natural Resources<\/strong><\/h3>\n

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<\/a>
\nBianca Zadrozny, Ph.D.<\/strong><\/p>\n

Sr. Research Scientist
\nManager, Natural Resources Analytics
\nIBM Research – Brazil (<\/span><\/em><\/span>12:15, Wednesday, 14th Nov)<\/span><\/em><\/p>\n

\n

In this talk, I will give an overview of some of the most recent projects developed in the Natural Resources Analytics group at IBM Research Brazil. The group’s mission is to conduct research projects in data-driven analytics for decision making in the areas of oil&gas and mining, with a focus in developing new machine learning workflows to aid geoscientists in the discovery of natural resources. The topics I will cover in more detail include: seismic image segmentation using convolutional neural networks, prediction of well production from well logs and gold mineralization prediction using drill hole data.<\/p>\n

Short Bio<\/strong>: Bianca Zadrozny is a research manager at IBM Research Brazil, leading the Natural Resources Analytics group. The group’s mission is to conduct research projects in data-driven analytics for decision making in the areas of oil&gas and mining, with a great focus in developing new machine learning workflows to aid geoscientists in the discovery of natural resources. Bianca got her PhD in Computer Science from University of California, San Diego in 2003. After that, she has worked as a researcher at IBM T.J. Watson Research Center, New York and as a professor at Federal Fluminense University, Brasil. In 2011, she joined IBM Research Brazil. Bianca is an active researcher in the machine learning and data mining communities, having published more than 30 papers. She has served in the editorial board of the Journal of Machine Learning Research (JMLR) and the Data Mining and Knowledge Discovery (DMKD) journal and also in the program committees of conferences such as ICML, KDD, ECML, SDM e SBBD.<\/p>\n

 <\/p>\n

Aspectos Estad\u00edsticos y Computacionales del an\u00e1lisis de Big Data<\/strong><\/h3>\n

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<\/a>
\nDr. Edgar Acu\u00f1a Fern\u00e1ndez
\n<\/span><\/strong>Dpto. de Ciencias Matem\u00e1ticas y Programa Doctoral en Ciencias e Ingenier\u00eda de la Informaci\u00f3n y de la Computaci\u00f3n.
\nUniversidad de Puerto Rico en Mayaguez (<\/span><\/em><\/span><\/span>12:00, Thursday, 13th Nov)<\/span><\/em><\/p>\n

\n

Los mecanismos para la recolecci\u00f3n autom\u00e1tica de datos (por ejemplo, sensores) y el desarrollo de tecnolog\u00eda\u00a0 ha hecho posible que una gran volumen de datos (Big Data) pueda estar disponibles en bases de datos, almacenes de datos y otros repositorios de informaci\u00f3n. Hoy en d\u00eda, compa\u00f1\u00edas tales como Google, Twitter, Facebook, Amazon, Netflix, Linkedin, etc tienen\u00a0 la necesidad de convertir estos datos en conocimiento e informaci\u00f3n. En esta charla, revisaremos algunas herramientas estad\u00edsticas y computacionales para extraer conocimiento\u00a0 en conjuntos de datos masivos, esta es una de las principales tareas en el mundo de los grandes conjuntos de datos (Big data) Primero, daremos una breve introducci\u00f3n a miner\u00eda de datos y\u00a0 Big Data. Luego, explicaremos, el uso de Hadoop y Mapreduce, dos poderosas herramientas computacionales basadas en tecnolog\u00eda de Google para manipular Big Data . Asimismo, hablaremos de Spark (AMPlab-UC-Berkeley) y del uso de Python y R para hacer an\u00e1lisis de Datos Grandes.\u00a0 Finalmente,\u00a0 hablaremos uso acerca de varios servicios\u00a0 de\u00a0 Computaci\u00f3n en la Nube (Cloud Computing)\u00a0 para Big Data, tales como Google Cloud Platform, Amazon Web Services y Microsoft Azure<\/p>\n

Short Bio<\/strong>: El Dr. Edgar Acu\u00f1a\u00a0 es catedr\u00e1tico Principal\u00a0 del Departamento de Coencias Matem\u00e1ticas de\u00a0 la Universidad de Puerto Rico en Mayaguez. Su \u00e1rea de investigaci\u00f3n es en Aprendizaje Estad\u00edstico y Computacional para el Descubrimiento de Conocimiento en bases de datos.\u00a0 \u00a0En particular, \u00e9l est\u00e1 interesado en pre-procesamiento de datos y en ingenier\u00eda de datos. \u00a0Actualmente, \u00e9l est\u00e1 trabajando en miner\u00eda de datos masivos (Big Data) y en aplicaciones de an\u00e1lisis de datos funcionales a datos provenientes de distintas \u00e1reas cient\u00edficas y comerciales. \u00a0El ha supervisado a 25 estudiantes de maestr\u00eda en Estad\u00edstica y Computaci\u00f3n Cient\u00edfica y a 5 estudiantes doctorales en Ciencias e Ingenier\u00eda de la Informaci\u00f3n y Computaci\u00f3n. \u00a0En el 2009, Dr. Acu\u00f1a fue seleccionado como Fulbright Scholar para visitar universidades peruanas. El ha ofrecido conferencia en\u00a0 23 pa\u00edses alrededor del mundo.\u00a0 \u00a0El Dr. Acu\u00f1a\u00a0 ha sido el investigador principal de 4 proyectos patrocinados por la Oficina de Investigaci\u00f3n Naval, la Fundaci\u00f3n Nacional de las Ciencias y del Departamento de Defensa de los Estados Unidos. El Dr. Acu\u00f1a ha asistido por invitaci\u00f3n a institutos de veranos ofrecidos por el Centro de Supercomputadoras de San Diego(2015) y a Google(2017). Durante su carrera, el Dr. Acu\u00f1a ha recibido fondos de Intel y Hewlett Packard para adquirir\u00a0 equipo de computaci\u00f3n y para financiar a sus estudiantes graduados.<\/p>\n","protected":false},"excerpt":{"rendered":"

Iberamia 2018 Career Recognition Award talk Ethics and Artificial Intelligence   Prof. Juan Pav\u00f3n Grupo de investigaci\u00f3n en Aplicaciones Sociales e Interdisciplinares basadas en Agentes (GRASIA) Complutense University of Madrid\u00a0 (12:15, Thursday, 15th Nov) Current development of Artificial Intelligence shows systems with greater degree of autonomy and decision making capabilities. Also, their integration in all dimensions of our daily living raises ethical issues on their application and behavior. This talk… <\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-799","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/pages\/799","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/comments?post=799"}],"version-history":[{"count":0,"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/pages\/799\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.iberamia.org\/iberamia\/iberamia2018\/wp-json\/wp\/v2\/media?parent=799"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}