O Programa de Pós-Graduação de Informática convida alunos e professores para duas palestras: "Genomes Galore: Big Data Challenges in Computational Genomics", Prof. Srinivas Aluru, Georgia Tech e "Parallel Graph Analytics: Algorithms, Challenges, and Opportunities”, Prof. Ananth Kalyanaraman, Washington State University.

 

O Programa de Pós-Graduação de Informática convida alunos e professores para duas palestras a serem realizadas no dia 27/05/2019, das 08:30 as 10:30. Os titulos e palestrantes sao:

   

a) "Genomes Galore: Big Data Challenges in Computational Genomics", Prof. Srinivas Aluru, Georgia Tech
b) "Parallel Graph Analytics: Algorithms, Challenges, and Opportunities”, Prof. Ananth Kalyanaraman, Washington State University

Resumos das Palestras:

Title: Genomes Galore: Big Data Challenges in Computational Genomics

Abstract: While the big data revolution in the consumer, business, and social networks domains is widely known, a similar revolution is taking place in the sciences and engineering driven by high-throughput instrumentation. This talk will feature big data challenges in computational genomics, primarily due to advances in sequencing that resulted in several orders of magnitude throughput increases per unit cost during the last decade. These advances are democratizing big data generation capabilities and spawning new scientific inquiries that would not be feasible otherwise. High-throughput sequencers enable diverse applications, each requiring its own class of supporting algorithms. I will present an overview of my group's research in addressing some of these issues through the development of efficient sequential and parallel algorithms, engineering high performance software, and community building efforts.

Bio: Srinivas Aluru is co-Executive Director of the Institute for Data Engineering and Science (IDEaS) and a professor in the School of Computational Science and Engineering at Georgia Institute of Technology. He co-leads the NSF South Big Data Regional Innovation Hub which nurtures big data partnerships between organizations in the 16 Southern States and Washington D.C., and the NSF Transdisciplinary Research Institute for Advancing Data Science. Aluru conducts research in high performance computing, large-scale data analysis, bioinformatics and systems biology, combinatorial scientific computing, and applied algorithms. He is a recipient of the NSF Career award, IBM faculty award, Swarnajayanti Fellowship from the Government of India, the John. V. Atanasoff Discovery Award from Iowa State University; and the Outstanding Senior Faculty Research award, Outstanding Achievement in Research Program Development award, and the Dean's award for faculty excellence at Georgia Tech. He is a Fellow of the AAAS and the IEEE, and is a recipient of the IEEE Computer Society meritorious service and Golden Core awards.

Title: “Parallel Graph Analytics: Algorithms, Challenges, and Opportunities”

Speaker: Ananth Kalyanaraman, Washington State University, Pullman, WA USA

Abstract:The notion of networks is inherent in the structure, function and behavior of the natural and engineered world that surround us. Consequently, graph models and methods have assumed a prominent role to play in this modern era of Big Data, and are taking a center stage in the discovery pipelines of various data-driven scientific domains. This talk will focus on a set of widely used graph operations and related algorithmic needs and challenges. More specifically, we will describe our ongoing efforts in parallelizing iterative graph algorithms that are used to solve a wide variety of graph operations including (but not limited to): community detection, graph coloring, PageRank, etc. The talk will present generic abstractions, efficient parallel algorithms and approximate computing techniques, collectively designed to scale on a wide variety of parallel architectures including shared and distributed memory parallel computers. The talk will relate to some of the unique challenges that one faces while applying and scaling such graph methods on modern parallel architectures and for emerging application use-cases in bioinformatics.

Bio:Ananth Kalyanaraman is a Professor and Boeing Centennial Chair in Computer Science at the School of Electrical Engineering and Computer Science, Washington State University in Pullman. He also holds affiliate faculty positions at the Molecular Plant Sciences Graduate Program and the Paul G. Allen School for Global Animal Health. Ananth received his bachelors from Visvesvaraya National Institute of Technology in India; and subsequently M.S. and Ph.D. from Iowa State University. He works at the intersection of parallel computing, graph analytics, and bioinformatics/computational biology. His focus is on developing algorithms and software for scalable analysis of large-scale data from various scientific domains and particularly the life sciences. Ananth is a recipient of U.S. Department of Energy Early Career Research Award, and his student-led research works have received multiple conference best paper awards and a prestigious graph challenge award. Ananth serves on the editorial boards of several reputed journals (including TCBB, TPDS, JPDC, ParCo), and also regularly serves in various capacities at various conferences in the areas of parallel processing and bioinformatics. He is currently serving as a Vice-Chair for the IEEE Technical Committee on Parallel Programming (TCPP). Ananth is a member of ACM, IEEE and SIAM.