IASC News November 2021

IASC-LARS: Forthcoming Joint Virtual Event

Title: The 6th Latin American Conference on Statistical Computing (LACSC 2022) with the 16th Brazilian Meeting of Bayesian Statistics (EBEB 2022) (virtual meeting).
Summary: The 6th Latin American Conference on Statistical Computing (LACSC 2022) will be held in São Carlos-Brazil, from March 16 to March 18, 2022. It is jointly organized with the 16th Brazilian Meeting of Bayesian Statistics (EBEB 2022).

The 6th Latin American Conference on Statistical Computing (LACSC 2022) will be held in São Carlos city, São Paulo state, Brazil, from March 16 to March 18, 2022. Only virtual format. LACSC 2022 is jointly organized by the Department of Applied Mathematics and Statistics, University of São Paulo, and the Latin American Regional Section of the International Association for Statistical Computing (IASC-LARS). In this edition, LACSC will be held jointly with the 16th Brazilian Meeting of Bayesian Statistics (EBEB 2022) which is organized by the Brazilian Chapter of the International Society for Bayesian Analysis (ISBA).

The meeting of both communities (LACSC and EBEB) is expressed in the variety of our confirmed Keynote Speakers, take a look!

  • Andrew Gelman (Columbia University),
  • Cathy W. S. Chen (Feng Chia University),
  • Jorge Luis Bazán (University of São Paulo),
  • Marina Silva Paez (Federal University of Rio de Janeiro),
  • Mark Steel (University of Warwick),
  • Pedro Ramos (Pontifical Catholic University of Chile),
  • Sônia Petrone (Universita’ Bocconi),
  • Vinicius Mayrink (Federal University of Minas Gerais),
  • Xiaojing Wang (University of Connecticut),
  • Yanina Bellini Saibene (National Institute of Agricultural Technology of Argentina).

A little about our communities:
The Latin American Regional Section (LARS) of the International Association for Statistical Computing (IASC) was established by the IASC General Assembly during the 22nd International Conference on Computational Statistics, held in Oviedo, Spain, August 23-26, 2016. Annually the IASC-LARS organizes The Latin American Conference on Computational Statistics (LACSC). In 2022, scheduled to take place online, March 16-18, in São Carlos, SP, Brazil, this will be the sixth edition of the LACSC. The 1st Latin American Conference on Statistical Computing – July 22-24, 2016, was held in Gramado RS, Brazil. The 2nd Latin American Conference on Statistical Computing – March 9-11, 2017, was held in Valparaiso, Chile. The 3rd Latin American Conference on Statistical Computing – February 27 to March 2, 2018, was held in San José, Costa Rica, the 4th Latin American Conference on Statistical Computing – May 28-31, 2019, was held in Guayaquil, Ecuador, and the V Latin American Conference on Statistical Computing – April 19-21, 2021, was held in Mexico City, Mexico (turned into Online meeting because of the SARS-Cov-2 global pandemic).

EBEB has been held every two years since 1991, initially organized by groups of Brazilian researchers interested in the dissemination and growth of research in Bayesian Statistics in the country. The previous 14 editions of EBEB were held in the states of Sao Paulo, Rio de Janeiro, and Minas Gerais. In 2000, the organization of the EBEB became the responsibility of the board of ISBRA, the Brazilian Society of Bayesian Statistics, and the Brazilian Section of the International Society for Bayesian Analysis (ISBA). In 2002, ISBRA organized its first event, the 6th EBEB, in conjunction with the First Latin American Bayesian Statistics Congress (I COBAL), which was born out of the need to know what was being developed in Bayesian Statistics throughout Latin America and integrate research groups from Latin American countries. Since then, EBEB has gained greater projection and both national and international recognition, as attested by the participation of renowned professors and leading researchers in all subsequent editions of EBEB. In addition, the latest editions have attracted researchers from various countries, especially South America, who have considered EBEB as a good forum to disseminate the results of their research in their countries, giving this important Brazilian event a more international character. National recognition is noted by the number of participants, around 150, and the variety of places of origin. The participation of students, especially graduate students, has also been significant.

Early Announcement:
The 6th Latin American Conference on Statistical Computing (LACSC 2022) with the 16th Brazilian Meeting of Bayesian Statistics (EBEB 2022) calls for submissions. The call of papers and all the information is available at https://eventos.galoa.com.br/ebeb-lacsc-2022/page/1381-home

 

 

IASC-LARS School on Computational Statistics and Data Science and the EBEB School for 2022

Title: IASC-LARS announces double School for 2022.
Summary: The Fourth IASC-LARS School on Computational Statistics and Data Science “Deep neural networks: Fundamentals, computational, mathematical aspects and advances”; and the EBEB School “Bayesian Survival Analysis with BUGS”

Forthcoming Events: IASC-LARS announces double School for 2022!

The Fourth IASC-LARS School on Computational Statistics and Data Science “Deep neural networks: Fundamentals, computational, mathematical aspects and advances”; and the EBEB School “Bayesian Survival Analysis with BUGS”

Both Schools will be offered in online format, from March 14 to March 15 of 2022 in the two days preceding the joint event: 6th Latin American Conference on Statistical Computing (LACSC 2022) and 16th Brazilian Meeting of Bayesian Statistics (EBEB 2022).

LACSC 2022 School: “Deep neural networks: Fundamentals, computational, mathematical aspects, and advances”

Deep neural networks (DNN) have boomed as a must-have technique in almost all machine-learning applications. After nearly a decade of evolution, many deep-based methods have been proposed considering more than only earlier convolutional operations in the hidden layers of an artificial neural network. The goal of this tutorial is not only to present the fundamentals of the computational and mathematical aspects of DNNs, considering from the very first proposed network of this kind – the Lenet-5 and its main components but also the more advanced architectures such as the Transformer networks that do not use convolution operations to do the job. All the technical aspects studied will rely on the digital image domain to exemplify and explain the fundamentals of the DNNs.

Instructor: Prof. Luciano Rebouças de Oliveira (Federal University of Bahia, Brazil)

Luciano Rebouças holds a Ph.D. in Electrical and Computer Engineering, from the Institute of Systems and Robotics University of Coimbra, a master’s degree in Mechatronics, and a bachelor’s in computer science at the Federal University of Bahia (UFBA). He is an Associate Professor at the Dept. of Computer Science, at Institute of Computing, UFBA, and head of the Intelligent Vision Research Lab. He is a specialist in the field of Computer Vision and Machine Learning, his research is focused mainly on robotics, smart cities, biometric systems, and biomedicine.

EBEB 2022 School: “Bayesian Survival Analysis with BUGS”

Survival analysis is one of the most important fields of statistics in medicine and biological sciences. Furthermore, the computational advances in the last decades have favored the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The goal of this tutorial is to summarize some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, competing risks, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programming language.

Instructor: Prof. Danilo Alvares (Pontifical Catholic University of Chile)

Danilo Alvares holds a post-doctorate in Biostatistics from Harvard School of Public Health, USA (2018), a doctorate in Statistics, a master’s degree in Biostatistics from the Universitat de València, Spain (2017 and 2015), a master’s degree in Computer Science and Computational Mathematics and a degree in Applied Mathematics and Scientific Computing by the University of São Paulo, Brazil (2013 and 2011). His research is focused on: Bayesian survival analysis for health policy research and education, joint models for longitudinal and time-to-event data, Bayesian approaches to computational methods, longitudinal models, statistical modeling, statistical methods in epidemiology, biostatistical analysis, methods for the analysis of observational data, and machine learning.

 

 

IASC – African Members Group: Webinar

Title: Webinar on Environmental statistics and statistical computing
Summary: The African Members group organizes a webinar on Environmental statistics and statistical computing on 17 December 2021.

Environmental applications are what make statistics “environmental.” Statistical application to environmental issues such as weather, air, water quality, climate, soil, fisheries and other environmental activities often come with some challenges since most environmental applications do not fit into experimental settings and even results from controlled experiments are used to infer patterns in an uncontrolled, dynamic, and noisy setting. This presentation will expose the participants to computational tools/ skills needed to navigate through as an “Environmental Statistician”, and inform them on where their expertise will be needed in Nigeria and beyond.

DATE: 17th December 2021
TIME: 2:30pm-3:30pm CET
Duration: 1 hour

Speaker: Dr. Oludare Ariyo

Oludare Ariyo is a lecturer at the department of the Statistics Federal University of Agriculture, Abeokuta. He received his PhD (Biostatistics) at the KU Leuven Belgium on Bayesian model selection for longitudinal random-effects models. He has gained expertise in various statistical topics with research interests, including Environmental Statistics, Bayesian methods, longitudinal analysis, statistical modelling, missing data/ survival analysis, and Mixed models / random-effects models / multilevel models. His research has led to several papers in highly qualified international journals (Statistical Neerdelica, Journal of Applied Statistics, Communication in Statistics, Sankhya B, Nigeria Statistical Association Journal, Computational Statistics etc.).

Before his appointment in FUNAAB, Dr Ariyo has worked as a Data Analyst at the Crop-Utilization Units, IITA, Ibadan, and as a senior statistician at National Horticultural Research Institutes (NIHORT), Ibadan. For over six years of working with these research institutes, Dr Ariyo had gain experience in applying Statistical methodology to real-life problems, especially in Agriculture. During his four and half years of stay at the Inter university Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Leuven, Belgium, Dr Ariyo further gained clinical trials experience and applied statistical methodology in Medical studies.

Dr Ariyo is an experienced R user with two R functions (https://github.com/OludareAriyo/Bayesselect and https://github.com/OludareAriyo/BayesselectGLMM ) and currently working on an R package. Besides, he has an excellent working knowledge of the following software: SAS, JAGS, STAN, SPSS, Epi Info etc

He is a member of many professional bodies, has presented papers in international conferences across continents, and has received several grants. He currently the coordinator of FUNAAB-LISA (FUNAAB-Laboratory for Interdisciplinary Statistical Analysis) and an advisor to Overleaf ( a collaborative cloud-based LaTeX editor used for writing, editing and publishing scientific documents.)

Co-organizer: Dr Adenomon Monday (adenomonmo@nsuk.edu.ng)
Co-organizer: Mr. Timothy A Ogunleye (thompsondx@gmail.com)
Co-organizer: Mr. Anthony Ekpo (ekpo.anthony@uam.edu.ng)

 

JDSSV First issues

Title: Publication of the first issues of the Journal of Data Science, Statistics and Visualization
Summary: JDSSV is completely open access. The papers can be accessed at
https://jdssv.org/index.php/jdssv/issue/archive

It is our great pleasure to announce that Journal of Data Science, Statistics, and Visualization (JDSSV) has now published its first issues. JDSSV is completely open access. The published papers can be accessed at
https://jdssv.org/index.php/jdssv/issue/archive

Feel free to send this announcement to all your colleagues with an interest in data science, statistics and/or visualisation.
JDSSV is an international refereed journal which creates a forum to present recent progress and ideas in the different disciplines of data science, statistics, and visualisation. JDSSV welcomes submissions to data science, statistics, and visualisation and, in particular, papers which link and integrate these subject areas.
Articles should be oriented towards a wide scientific audience, and can cover topics such as machine learning and statistical learning, the visualisation and verbalisation of data, visual analytics, big data infrastructures and analytics, interactive learning, and advanced computing. Scientific contributions should be of a high standard.
The journal explicitly welcomes contributions that include software with the aim of reproducibility of the results and application of the proposed methodology to other data by the reader. It is expected that data used in a paper are provided.
Initial submissions only require a pdf version of the manuscript with accompanying software code and necessary supplementary material. Manuscripts can be submitted online at https://jdssv.org.

Supported by

  • The International Association for Statistical Computing (IASC, owner)
  • International Statistical Institute (ISI)

Editorial Board

  • Patrick J.F. Groenen (Editor, Erasmus University Rotterdam, The Netherlands)
  • Stefan van Aelst (Editor, KU Leuven, Belgium)
  • Ann Maharaj (Copy Editor, Monash University, Australia)
  • Alexandre Francisco (Web Editor, Técnico Lisboa, Portugal)

Advisory Board

  • Jan de Leeuw (UCLA, USA)
  • David Hand (Imperial College, UK)
  • Trevor Hastie (Stanford University, USA)
  • Peter Rousseeuw (KU Leuven, Belgium)