Colloquium

Colloquium


Statistics Colloquium
April 6 Friday, 11 a.m.
Alavi Commons Room, 6625 Everett Tower

Data-Reduction Algorithms for Big Data Proteomics: Challenges, Opportunities and Progress

Fahad Saeed, Ph.D.
Department of Electrical & Computer Engineering and Department of Computer Science
Western Michigan University

Abstract:
The last two decades have seen an exponential increase in genomic and proteomics data from high-throughput technologies. Proteogenomics studies require combination and integration of mass spectrometry data (MS) for proteomics and next generation sequencing (NGS) data for genomics. The combination of big data from these omics technologies and unprecedented computational power and capabilities have dramatically changed the questions that can be addressed in biomedical sciences. However, this integration drastically increases the size of the data sets which will soon outstrip advances in computing power to perform current computational tasks. The design of efficient fast algorithmic and high performance computing solutions will be essential for viable solutions to big data computational biology problems.

In the talk, the speaker will discuss a new class of reductive algorithms for analysis of MS data using novel clustering and sampling approaches. This reduced form of big data allows peptide deductions in sublinear time and sub-linear space, and high performance computing algorithms that operate on lossy reduced-form of the data. The speaker will also discuss some of the opportunities and challenges in designing and building high performance computational infrastructure which would be useful for the broadest biological and ecological community.

Bio:
Fahad Saeed is an Assistant Professor in the Department of Computer Science and Electrical & Computer Engineering, Western Michigan University (WMU), Kalamazoo Michigan. He is the director of Parallel Computing and Data Science Lab and founding co-director of High Performance Computing and Big Data Center at WMU. He also serves as visiting scientist at National Institutes of Health (NIH) Bethesda, Maryland. Fahad Saeed received the PhD degree from the Department of Electrical and Computer Engineering, University of Illinois at Chicago (UIC), in 2010. He was a postdoctoral fellow from 2010-2011 and then research fellow in the National Institutes of Health (NIH) from 2011 to 2014. He has served as a visiting scientist in world-renowned prestigious institutions such as ETH Zurich, Swiss Institute of Bioinformatics (SIB), and National Institutes of Health (NIH). He has contributed to four edited conference proceedings, edited 3 special issue journals, 40 peer-reviewed papers in high-impact journals, and refereed conference papers. He is a Senior Member of the IEEE and has been elected as Senior Member of the ACM. His research has been supported by WMU, NVIDIA, Intel, National Science Foundation (NSF), and National Institutes of Health (NIH). His honors include ThinkSwiss Fellowship (2007, 2008), NIH Postdoctoral Fellowship Award (2010), Fellows Award for Research Excellence (FARE) at NIH (2012), NSF CRII Award (2015), Outstanding New Researcher Award at WMU (2016), and NSF CAREER Award (2017).
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All statistics graduate students are expected to attend.

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