Rodolfo Azevedo is an Associate Professor at University of Campinas - UNICAMP. He got his PhD degree in Computer Science at UNICAMP. During his career, he (co-)advised 9 PhD and 30 Master students. From 2007 to 2009 he coordinate UNICAMP Computer Science graduate program. His main research area is Computer Architecture, where he focuses on microarchitecture, memory systems and hardware design. He is also interested in Technology for Teaching as both a research area and as professor. During his career, he got 22 Awards, including the Zeferino Vaz Academic Award and the UNICAMP Teaching Award in 2012, 3 best papers in conferences, and 5 as advisor of awarded student. He was General Chair of SBAC-PAD 2017. Currently he is the Diretor of the Institute of Computing, at UNICAMP.

Antônio Tadeu Azevedo Gomes possui graduação em Informática - Magna Cum-Laude - pela UFRJ (1995), mestrado e doutorado em Informática pela PUC-Rio (1999 e 2005). Atualmente é pesquisador do LNCC/MCTI (Laboratório Nacional de Computação Científica), secretário executivo do SINAPAD (Sistema Nacional de Processamento de Alto Desempenho) e coordenador do Comitê Gestor do supercomputador Santos Dumont. Leciona na Pós-graduação em Modelagem Computacional do LNCC. Atua na área de Ciência da Computação, principalmente nos seguintes temas: Arquitetura e Modelagem de Software; Redes de Computadores e Sistemas Distribuídos; Computação de Alto Desempenho. É membro da Sociedade Brasileira de Computação (SBC) e da Association for Computing Machinery (ACM).

Mauricio Breternitz is a Research Fellow and Invited Auxiliary Professor in DLS group of ISTAR at ISCTE-Lisbon University Institute. He received a Ph.D. in Computer Engineering from Carnegie-Mellon University, is a Senior Member of the IEEE, holds 48 U.S. patents and has 52 more pending in areas related to compilation, code optimization, binary translation, processor, cache and memory system organization and cryptography, and his publications have been cited more than 1016 times. Mauricio's academic service include advising multiple Ph.D. internships and thesis committees, organizing ACM/IEEE conferences; service on multiple program committees as well as participation in successful grant submissions to the U.S. Dept. of Energy and European Horizon 2020. Mauricio's research interest focuses on real-life solutions with practical impact, developed at IBM (T.J. Watson and Austin), Motorola, Intel Labs, TimesN Systems (an Austin startup) and most recently at AMD Research in Austin, Texas where he worked on Exascale computing. His research areas include end-to-end applications of machine learning, and architecture and performance of computing systems. He worked on parallelizing compilers for a research multiprocessor, and for instruction-level parallel VLIW architectures; on binary translation of x86 codes; on IP telephony libraries and on parallelizing database server programs. At Intel, Mauricio conceived and pushed through product deployment innovative microcode compression inventions, now in every product, that had significant impact (estimated upwards of US$18M savings). His current research focuses on novel understanding and application of end-to-end deep neural networks to achieve efficient computation systems.

Mauricio is an energetic and innovative researcher with interest in real-life solutions with practical impact, currently researching end-to-end application of machine learning to enhanced living spaces via digital assistance. For a previous employer, Mauricio conceived and pushed through deployment innovative algorithmic & microarchitectural ideas that have had significant positive product impact (estimated upwards of $18M). He holds 48 U.S. patents and has 58 more pending in areas related to compilation, code optimization, binary translation, processor, cache and memory system organization and cryptography. Mauricio's academic service include ACM/IEEE conferences such as IISWC (general chair), HPCA(finance chair),AMAS-BT/ISCA Workshop (organizer & chair), CGO, ISCA, and multiple program committees. Mauricio received the Electronics Engineer degree with honors at ITA-Instituto Tecnologico de Aeronautica, Brazil, a MSc in Computer Science at UNICAMP, Brazil and the Ph.D. in Computer Engineering at Carnegie-Mellon University. He worked on parallelizing compilers for a research multiprocessor and for VLIW architectures, binary translation of x86 codes, on IP telephony libraries and on parallelizing database server programs. Recently he has worked on novel algorithms utilizing CPU and GPUs accelerating machine learning on Apache Spark, on system-level and architectural-level characterization of cloud workloads and on novel approaches to utilizing CPU and GPU in cloud workloads such as MapReduce and GraphLab. He is interested in scale-up and scale-out frameworks for Deep Neural Networks using CPUs and GPUs. He worked at IBM (TJWatson and Austin), Motorola, Intel Labs and TimesN Systems, an Austin startup. For more information, please visit:
https://fenix.iscte-iul.pt/homepage/mbjrz@iscte.pt/summary
https://ciencia.iscte-iul.pt/authors/mbreternitz/publications?view_mode=classic_view
https://scholar.google.com/citations?user=pnmGA74AAAAJ

Jose Nelson Amaral é professor de Ciências da Computação na University of Alberta, Canadá. Ele recebeu o Ph.D. em Electrical and Computer Engineering da The University of Texas at Austin, em 1994, um M.E. do Instituto Tecnológico de Aeronáutica, São José dos Campos, SP, Brasil, e um B.E. da Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), RS, Brasil. Os interesses atuais de pesquisa dele incluem Projeto de Compiladores, Análise Estática, Compilação por Realimentação, Arquitetura de Compiladores, Sistemas de Computação de Alto Desempenho, e a aplicação de métodos de aprendizado para o projeto de compiladores. Suas áreas anteriores de pesquisa incluíram algoritmos conscientes de caches, caches para roteadores de protocolo de internet, redes neurais artificiais, problemas de otimização combinatória, arquiteturas paralelas para sistemas simbólicos, arquiteturas multi-threaded, e modelos de programação. Prof. Amaral é um membro Sênior do IEEE, um Distinguished Engineer da ACM e foi um palestrante Distinto da ACM. Ele foi Chefe do comitê de programa para várias conferências e serviu como editor associado no IEEE Transactions on Computers e no IEEE Transactions of Parallel and Distributed Systems. Em 2012 ele foi selecionado o "Professor do Ano" pelo Centro para Estudos Avançados da IBM em Toronto no Canadá. Em 2015 ele recebeu o prêmio por excelência em ensino da Faculdade de Ciências da University of Alberta.

Veja esta reportagem do Prof. Nelson Amaral relacionada à sua palestra no WSCAD 2018: link

Jomar Silva é Engenheiro Eletrônico, especialista em Padrões Abertos e Open Source. É Technical Evangelist no grupo de software da Intel na América Latina.