Fahad Saeed is a tenured Associate Professor in the Knight Foundation School of Computing and Information Sciences at Florida International University (FIU), Miami FL and is the director of Saeed Lab which is a parallel computing and data science group (https://saeedlab.cis.fiu.edu/). His research interests include parallel and distributed algorithms and architectures, computational proteomics, genomics, connectomics and big data problems in computational biology and bioinformatics.
Prior to joining FIU, Prof. Saeed was an Assistant Professor (2014-2018) in the Department of Electrical & Computer Engineering and Department of Computer Science at Western Michigan University (WMU), Kalamazoo Michigan. He was tenured and promoted to the rank of Associate Professor at WMU in July 2018. Dr. Saeed was a Post-Doctoral Fellow and then a Research Fellow in the Systems Biology Center at National Institutes of Health (NIH), Bethesda MD from Aug 2010 to January 2014. He received his PhD in the Department of Electrical and Computer Engineering, University of Illinois at Chicago (UIC) in 2010.
Dr. Saeed has served as the program co-chair of the Bioinformatics and Computational Biology (BICoB) Conference and IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM). He is the founding chair of IEEE Workshop on HPC solutions to Big Data Computational Biology (IEEE HPC-BCB). He also serves on the editorial board of Springer Journal of Network Modeling Analysis in Health Informatics and Bioinformatics since 2014. He has served on numerous IEEE/ACM program committees and is peer-reviewer for more than a dozen journals.
Dr. Saeed is a Senior Member of ACM and also a Senior Member of IEEE. 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).
High performance computing, big data, machine-leanrning, bioinformatics (Proteomics/neuroinformatics)