Category: News

Workshop: Big Data Causal Discovery

The Increasing Diversity in Interdisciplinary Big Data to Knowledge (IDI-BD2K) Program at the University of Puerto Rico is pleased to announce a workshop on Big Data causal discovery.

Wednesday Feb 17, 2016

A.   Introduction. Presentations from the Center for Causal Discovery of the University of Pittsburgh and from the UPR IDI-BD2K participant faculty. Dr. Gregory Cooper and Dr. Richard Scheines from the University of Pittsburgh and several faculty members from UPR (and other participating institutions) will briefly present their ongoing projects.  These presentations are aimed at introducing students and faculty to Big Data Projects in Causal Discovery as applied to biomedical problems and at establishing collaborations between the BD2K participants and U. Pittsburgh

Wed 17 Feb, 2016
8:30 – 11:00 am

NCN A-211
Natural Sciences
Rio Piedras Campus
University of Puerto Rico

B. STUDENT RECRUITMENT for Big Data Summer Research Experiences. Drs Joseph Ayoob and David Boone will be presenting information on opportunities for training of students in Big Data, particularly in summer programs for undergraduate students at the University of Pittsburgh.

Wed Feb 17, 2016
11:30 am – 12:30 pm

NCN-A-211
Natural Sciences
Rio Piedras Campus
University of Puerto Rico

C.  HANDS ON WORKSHOP

Causal Discovery from Biomedical Data
Dr. Richard Scheines
University of Pittsburgh

Limited to 30 participants.  Those interested must register by writing to: jegarcia@hpcf.upr.edu

Wed February 17,  2016
1:00-3:00 pm

Julio Garcia Diaz building, room 123
Rio Piedras Campus
University of Puerto Rico

Seminar: Bugs, Parasites and Cities: the complex ecology of Chagas disease in Southern Peru.

The Increasing Diversity in Interdisciplinary Big Data to Knowledge (IDI-BD2K) Program at the University of Puerto Rico is pleased to announce a seminar:

Bugs, Parasites and Cities: the complex ecology of Chagas disease in Southern Peru

Dr. Michael Levy
Assistant Professor
Biostatistics and Epidemiology
University of Pennsylvania

Tuesday, February 9, 2016

Noon

Julio Garcia Diaz building, room 123
Rio Piedras Campus
University of Puerto Rico

Seminar: Graphlet kernels for vertex classification

Graphlet kernels for vertex classification

Where:   College of Natural Sciences, Department of Computer Science
When:    Monday, November 23, 2015
Hour:      2:30 pm
Room:    C-356

Graph kernels for supervised learning and inference on graphs have been around for more than a decade. However, the problem of designing robust kernel functions that can effectively compare graph neighborhoods in a variety of practical scenarios (e.g. the presence of incomplete and/or noisy data, auxiliary information) remains much less explored. Here, I will present my methods for vertex classification in large, sparse, and labeled graphs. Then, I will present an application of these methods to predicting protein function as well as molecular mechanisms of disease.

José Lugo-Martinez is a PhD candidate in Computer Science at Indiana University. The focus of his doctoral research has been the development of graph-based classification algorithms in the supervised and semi‐supervised scenarios, as well as statistical inference from large, noisy, biased, and high‐dimensional data. In particular, he develops computational approaches towards understanding protein function and how disruption of protein function leads to disease. Mr. Lugo-Martinez received dual B.S. degrees in Computer Science and Mathematics at the University of Puerto Rico-Rio Piedras, and M.S. degree in Computer Science at the University of California-San Diego. His research interest include machine learning, data mining and structural bioinformatics.

Department of Computer Science

graphlet

Reunion informativa

Estimado estudiante,

Hoy como nunca antes la investigación  biomédica está generando cantidades masivas de datos, cuyo análisis e interpretación tiene el potencial de producir dramáticos avances en nuestro conocimiento sobre la salud humana y sobre nuestra calidad de vida. El análisis de estos conjuntos masivos de datos (“Big Data”) require técnicas que combinan conocimientos en Biología, Química, Estadística, Ciencias  de Cómputo y otras áreas.

Existe la posibilidad de que NIH apruebe una propuesta enviada por un grupo de profesores de la Facultad de Ciencias Naturales de la UPR-Rio Piedras para preparar estudiantes de diferentes concentraciones en investigación biomédica usando grandes cantidades de datos (“Big Data to Knowledge”- BD2K) Estos estudiantes tomarían una secuencia de cursos dependiendo de su concentración de origen, y también cursos enfocados en el manejo y análisis de  “Biomedical Big Data”. Los mejores estudiantes de este grupo realizarán internados en laboratorios nacionales financiados por NIH.

Si eres estudiante de la Facultad de Ciencias Naturales y te interesa este reto:

te invitamos a una reunión informativa los días 10 y 12 de agosto de 2015 al medio dia en el anfiteatro A-211.

En esta reunion esperamos poder formar dos grupos de estudiantes.  El primero con estudiantes comenzando su 2do, 3er o 4to año que estén avanzados en sus estudios y que puedan incorporarse al programa como un grupo piloto.  El segundo, estudiantes de 1er a 3er año que puedan ir tomando los cursos necesarios para incorporarse al Programa el año entrante.

Ciencia de Cómputos
Matemáticas
Biologia