Florida International University | School of Computing and Information Sciences
- August 31, 2018
- 2:00 PM
- ECS 241
Fahad Saeed is an Associate Professor in the School of Computing and Information Sciences at Florida International University (FIU), Miami FL. He also serves as visiting scientist at National Institutes of Health (NIH) Bethesda, Maryland. His research interests include parallel and distributed algorithms and architectures, computational proteomics & genomics and big data problems in computational biology and bioinformatics. Prior to joining FIU, Fahad Saeed was an Assistant Professor and then Associate Professor in the Department of Computer Science at Western Michigan University (WMU). He received the Ph.D. 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 a 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, 45 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), WMU Outstanding New Researcher Award (2016), WMU Distinguished Research and Creative Scholarship Award (2018), and NSF CAREER Award (2017).
We are currently in an era marked by extreme and pervasive data generation as a result of high-throughput omics technologies. 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. These dramatic changes in the scale and nature of cyberinfrastructure requirements such as modeling scientific data more holistically, desire (and the need) for near-real time processing and the scalability of the proposed infrastructure is exciting as well as challenging for computational scientists. The speaker will talk about the research efforts needed to address the challenges and opportunities presented as a result of this unprecedented data generation. We will discuss a spectrum of research problems related to computational, data, software, networking, high-performance computing and human capital development that collectively can enable new discoveries across science.