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Muaaz Awan

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Muaaz Gul Awan, Ph.D.
Application Performance Specialist
National Energy Research Scientific Computing Center (NERSC)
Lawrence Berkeley National Laboratory
1 Cyclotron Road
Bldg. 59, Room 4024N
Berkeley, California 94720 US


I received my PhD in Computer Science from Western Michigan University at Kalamazoo in April 2019. During my PhD, I worked on the development of high performance reductive strategies for Mass Spectrometry based proteomics. During the Summer of 2017 I worked at the Pacific Northwest National Laboratory's Earth and Molecular Science Division, where I developed GPU accelerated strategies for date mining. At NERSC I am working with the Application Performance Group where my focus is to design and implement acceleration strategies for Bioinformatics algorithms. 


  • Ph.D., Computer Science, Western Michigan University, Kalamazoo, MI
  • B.Sc., Electrical Engineering, University of Engineering and Technology, Lahore


Journal Publications (peer-reviewed)

  1. Yelick, Katherine, Aydın Buluç, Muaaz G. Awan, Ariful Azad, Benjamin Brock, Rob Egan, Saliya Ekanayake et al. "The parallelism motifs of genomic data analysis." Philosophical Transactions of the Royal Society A 378, no. 2166 (2020): 20190394
  2. Muaaz G. Awan and Fahad Saeed, "MaSS-Simulator: A highly con configurable simulator for generating MS/MS datasets for benchmarking of proteomics algorithms", Wiley Proteomics, September 2018
  3. Muaaz G. Awan, Taban Eslami and Fahad Saeed, "GPU-DAEMON: GPU algorithm design, data management & optimization template for array based big omics data", Elsevier Computers in Biology and Medicine, August 2018  Elsevier
  4. Muaaz G. Awan and Fahad Saeed, "MS-REDUCE: An ultrafast technique for reduction of Big Mass Spectrometry Data for high-throughput processing", Oxford Bioinformatics, Jan 2016 Tech Report | PubMed | Oxford


 Conference publications (peer-reviewed)

  1. Muaaz G. Awan and Fahad Saeed, "An Out-of-Core GPU based dimensionality reduction algorithm for Big Mass Spectrometry Data and its application in bottom-up Proteomics", Proceedings of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Boston MA, August 2017 Tech Report
  2. Taban Eslami, Muaaz G. Awan and Fahad Saeed, "GPU-PCC: A GPU based technique to compute pairwise Pearson's Correlation Coefficients for big fMRI data", Workshop on Parallel and Cloud-based Bioinformatics and Biomedicine (ParBio), Proceedings of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Boston MA, August 2017 Tech Report
  3. Muaaz G. Awan and Fahad Saeed, "GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays", Proceedings of Workshop on High Performance Computing for Big Data, International Conference on Parallel Processing (ICPP-2016), Philadelphia PA, August 2016 Tech Report
  4. Muaaz G. Awan and Fahad Saeed, "On the sampling of Big Mass Spectrometry Data", Proceedings of Bioinformatics and Computational Biology (BICoB)Conference, Honolulu Hawaii, March 2015 Tech Report


Talks and Posters



  1. Perlmutter- A way point for ECP teams, 2020 Exascale Computing Project Annual Meeting, Houston, Texas.
  2. Design of High-Performance Computational Techniques on Many Core Devices for LC-MS/MS Proteomics (2019), Lawrence Berkeley National Laboratory, Berkeley, California. 
  3. Enabling Massive Peptide Library Search Using GPU-FLASH, Cascadia Proteomics Symposium 2017, Seattle, Washington.


  1. Accelerating Metagenome analysis using Graphics Processing Units2020 Exascale Computing Project Annual Meeting, Houston, Texas.