Associate Professor (Tenured), Knight Foundation School of Computing and Information Sciences,
Associate Professor, Biomolecular Sciences Institute (BSI),
Associate Professor, Herbert Wertheim School of Medicine,
Florida International University (FIU) - The State University of Florida at Miami, FL USA
Director: Parallel Computing and Data Science Lab (Saeed Lab)
Founder & CEO: AI-NeoTech LLC
Mailing Address: 11200 SW 8th St, Room CASE 261, Miami, FL 33199, USA
E-mail: fsaeed@fiu.edu Twitter: @Prof_FahadSaeed
Phone: +1-305-348-3131 Office: CASE 261
Long CV (pdf)
Google Scholar Profile
I am co-chairing HPC-BOD workshop in conjunction with IEEE BigData 2024. Consider contributing a paper (deadline: Oct 23rd, 2024)
Fahad Saeed is an Award-winning Scientist, Entrepreneur, and Tenured Associate Professor in the School of Computing and Information Sciences at Florida International University (FIU), Miami FL and is the director of Saeed Lab at FIU. Dr. Saeed's research interests are at the intersection of machine-learning, high performance computing and real-world applications, especially in computational biology.
Dr. Saeed has published 90+ peer-reviewed research papers in leading proceedings, and journals, and 1 Book Chapter, edited 4 Conference Proceedings, 3 special issue journals, and 1 Book. His research is supported by highly competitive grants mainly from National Science Foundation (NSF) and National Institutes of Health (NIH). He has been awarded over US$ 6.85 million in external research funds - with more than US$ 5.45 million as a PI. He was awarded the NSF Research Initiation Initiative (CRII) Award bestowed to young and promising scientists in the first two years of their tenure-track position. Most recently he was awarded the NSF Faculty Early Career Development (CAREER) Award which is NSF's most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education. His research has been supported by NVIDIA, Intel/Altera, Xilinx, National Science Foundation (NSF) and National Institutes of Health (NIH).
Prior to joining FIU, Prof. Saeed was a tenure-track Assistant Professor in the Department of Electrical & Computer Engineering and Department of Computer Science at Western Michigan University (WMU), Kalamazoo Michigan since Jan 2014. He was tenured and promoted to the rank of Associate Professor at WMU in August 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 June 2011 and from June 2011 to January 2014 respectively. He received his PhD in the Department of Electrical and Computer Engineering, University of Illinois at Chicago (UIC) in 2010. He has served as a visiting scientist in world-renowned prestigious institutions such as Department of Bio-Systems Science and Engineering (D-BSSE), ETH Zurich, Swiss Institute of Bioinformatics (SIB) and Epithelial Systems Biology Laboratory (ESBL) at National Institutes of Health (NIH) Bethesda, Maryland.
Dr. Saeed has established a global profile as an Independent Researcher and leader in the field, and has been sought as panelist at the National and International funding agencies. These inlucde serving as panelist at various study sections at National Institutes of Health (NIH), National Science Foundation (NSF), NIH NIDDK, National Nuclear Security Administration (NNSA) Department of Energy (DOE), and as International expert and panelist for Croatian Science Foundation (CSF), University of Queensland Diamantina Institute in Australia, Belgium Fund for Scientific Research (F.R.S.- FNRS), and Natural Sciences & Engineering Research Council of Canada. He 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 also a 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, on the Editorial board of Journal of the American Society of Nephrology, and as Associate Editor for Frontiers of Digital Public Health (specialty section of Frontiers in Public Health, Frontiers in ICT and Frontiers in Computer Science). He has served on numerous IEEE/ACM program committees and is peer-reviewer for more than a two 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), , NSF CAREER Award (2017), FIU KFSCIS Excellence in Applied Research Award (2020). More recently he was recognized as "Top Scholar” in "Research and Creative Activities" by FIU in 2022
Prof. Saeed has been awarded over US$ 6.85 million in external research funds - with more than US$ 5.45 million as a PI since 2014 (approx. US$ 700k per year)
Most of the external research funds are competitively awarded from Federal Agencies such as National Science Foundation (NSF) and National Institutes of Health (NIH). Intramural funds and computing allocations are not included in this amount.
External Research Funds
17. National Institutes of Health (NIH) R35GM153434 [US$ 1.75 million], “Machine Learning Models for big data omics”, Fahad Saeed (PI), June 2024 - June 2029 (single PI grant: MIRA R35 Outstanding Investigator mechanism) | NIH Reporter Award Page
16. National Science Foundation (NSF) OAC-2312599 [US$ 600,000], ``OAC Core: High Performance Computing Algorithms and Software for large-scale Mass Spectrometry based Omics", Fahad Saeed (PI), Sept 2023 - Aug 2026 | NSF Award Page
15. National Science Foundation (NSF) TI-2322346 [US$ 275,000], ``STTR Phase I: Patient-Specific System for Early Detection and Identification of Epileptic Seizures ", Saba Mehmood (PI), Fahad Saeed (Co-PI), Oct 2023 - Sept 2024 | NSF Award Page
14. National Science Foundation (NSF) CHE-2304837 [US$ 500,000], ``Development of Multidimensional Ion Mobility-Tandem Mass Spectrometry (IMSn-FT-ICR MSn) Tools for the Characterization of Complex Mixtures", Francisco Lima (PI), Fahad Saeed (Co-PI), Sept 2023 - August 2026 | NSF Award Page
13. National Science Foundation (NSF) TI-2213951 [US$ 250,000], ``PFI-TT: Artificial Intelligence-enabled Real-time System for Early Epileptic Seizure Detection and Prediction", Fahad Saeed (PI), August 2022 - July 2024 | NSF Award Page
12. National Science Foundation (NSF) IIP-2143515 [US$ 50,000], ``I-Corps: Utilizing Machine learning and Artificial Intelligence (AI) for Early Detection and Identification of Mental Disorders", Fahad Saeed (PI), Sept 2021 - Sept 2022 | NSF Award Page
11. National Institutes of Health (NIH) Supplemental- 3R01GM134384-02S1[US$ 100,000],"Compute-Cluster for Deep-Learning Models for Mass Spectrometry based Proteomics data" Fahad Saeed (PI), August 2021 - May 2023 | NIH Reporter Award Page
10. National Science Foundation (NSF) OAC-2126253 [US$ 400,000], ``CC* Compute: RAPTOR - Reconfigurable Advanced Platform for Transdisciplinary Open Research", Jason Liu (PI), Jayantha Obeysekera (Co-PI), Keqi Zhang (Co-PI), Cassian D'Cunha (Co-PI), Mike Kirgan (SI), Yuepeng Li (SI), Vasilka Chergarova (SI), Yagya Joshi (SI), Jonathan Casco (SI), and Fahad Saeed (Co-PI), Sept 2021 - Sept 2023 | NSF Award Page
9. National Institutes of Health (NIH) Supplemental- 3R01GM134384-01A1S1 [US$ 205,291],"Multimodal Machine-Learning Algorithms for Early Detection, and Classification for Alzheimer Disorder and Related Dementia's" Fahad Saeed (PI), May 2021 - May 2023 | NIH Reporter Award Page
8. National Institutes of Health (NIH), [R01GM134384] [US$ 965,874], "Multimodal Machine-Learning and High Performance Computing Strategies for Big MS Proteomics Data", Fahad Saeed (PI) with Shu-Ching Chen (Co-Investigator), Jason Liu (Co-Investigator), Francisco Alberto Fernandez-Lima (Co-Investigator), and Sitharama Iyengar (Senior Personal), June 2020 - May 2023 | NIH Reporter Award Page
7. National Science Foundation (NSF) OAC-1925960 [US$ 415,950], "CAREER: Towards Fast and Scalable Algorithms for Big Proteogenomics Data Analytics" Fahad Saeed (PI), Sept 2018-April 2023 | NSF Award Page
6. National Science Foundation (NSF) CCF-1855441 [US$ 7,708], "CRII: SHF: HPC Solutions to Big NGS Data Compression", Fahad Saeed (PI), Sept 2018 - Jan 31, 2020 | NSF Award Page
5. National Science Foundation (NSF) ACI-1651724 [US$ 499,999], "CAREER: Towards Fast and Scalable Algorithms for Big Proteogenomics Data Analytics" Fahad Saeed (PI), April 2017-April 2019 | NSF Award Page
4. National Institutes of Health (NIH) R15GM120820 [US$ 418,533], "Parallel Algorithms for Big Data from Mass Spectrometry based Proteomics" Fahad Saeed (PI), April 2017 - April 2020 | NIH Reporter Award Page (change of PI when Dr. Saeed changed institution to FIU)
3. National Science Foundation (NSF) REU Supplement [US$ 16,000], "CRII: SHF: HPC Solutions to Big NGS Data Compression" Fahad Saeed (PI), Feb 2016 - Feb 2018 | NSF Award Page
2. National Science Foundation (NSF) CCF-1464268 [US$ 171,341], "CRII: SHF: HPC Solutions to Big NGS Data Compression" Fahad Saeed (PI), (Feb 2015 - Feb 2018 | NSF Award Page
1. National Science Foundation (NSF) CNS-1250264 [US$ 200,000], "EAGER: High Performance Algorithms and Implementations for Biological Sequence Analysis and Genome Alignment" Ashfaq Khokhar, Fahad Saeed (Co-PI) (Sept 2012 - Aug 2015) | NSF Award Page
Equipment/Computing Allocations
12. Xilinx [US$ 13,195]}, ``Design and development of FPGA based MS omics pipeline", Fahad Saeed(PI) (Equipment Grant, Versal AI Core EK-VCK190-G FPGA), March 2022
11. NSF XSEDE Extended Collaborative Support Service (ECSS) [US$ 50,000,], ``DeepSNAP: Scalable Machine Learning for Mass Spectrometry based Proteomics", Fahad Saeed (PI), (Jan 2021 - Dec 2021) 10. National Science Foundation XSEDE ASC200004 [125,000.0 Service Units (SU)/10,000.0 GB SDSC Medium-term disk storage (Data Oasis)/10,000.0 GPU Hours/75,000 Core hours on Clusters: US$ 43,161.42], ``DeepSNAP: Scalable Machine Learning for Mass Spectrometry based Proteomics", Fahad Saeed (PI), (Jan 2021 - Dec 2021)
9. National Science Foundation XSEDE ASC200004 [100,000.0 Service Units (SU)/10,000.0 GB SDSC Medium-term disk storage (Data Oasis)/5,000.0 GPU Hours: US$ 6,190], "DeepSNAP: Scalable Machine Learning for Mass Spectrometry based Proteomics", Fahad Saeed (PI), (March 2020 - Sept 2020)
8. Intel Altera [US$ 7,900], "MS proteomics analysis using reconfigurable hardware", Fahad Saeed(PI) (Equipment Grant, DE10-PRO-SX FPGA), Nov 2019
7. National Science Foundation XSEDE supplemental grant TG-CCR150017 [30,000 Service Units (SU)/6TB SDSC Disk Storage/2500 GPU Hours: US$ 450], "Smart Index and Search for De Novo Proteogenomics", Fahad Saeed (PI), (March 2019 - June 2020)
6. National Science Foundation XSEDE renewal grant TG-CCR150017 [30,000 Service Units (SU)/6TB SDSC Disk Storage/2500 GPU Hours: US$ 3,159], "Smart Index and Search for De Novo Proteogenomics", Fahad Saeed (PI), (March 2019 - March 2020)
5. NVIDIA [US$ 1149], "High Performance Algorithms for Big Data Proteomics" Fahad Saeed (PI) (Equipment Grant for NVIDIA TITAN Xp GPU), August 2018
4. National Science Foundation XSEDE renewal grant TG-CCR150017 [30,000 Service Units (SU)/6TB SDSC Disk Storage: US$ 6564], "A Distributed-Shared Memory Strategy to Speedup the Compression of Big Next-Generation Sequencing Datasets" Fahad Saeed (PI), (June 2016 - June 2018)
3. National Science Foundation XSEDE startup grant TG-CCR150017 [30,000 Service Units (SU)], "Scalability study of compression algorithms for peta scale NGS data" Fahad Saeed (PI), (June 2015 - June 2016)
2. Intel Altera [US$ 16,000], "Short Reads mapping to the genome using reconfigurable hardware" Fahad Saeed(PI) (Equipment Grant, 2 DE5-NET-450 FPGA's), April 2014
1. NVIDIA [US$ 5499], "High Performance Algorithms for Genome Alignments" Fahad Saeed (PI) (Equipment Grant for Tesla K40 GPU), Feb 2014
Intramural Grants
2. Office of Vice President of Research,Western Michigan University (WMU) [US$ 129,570], "Scalable Algorithms for Big Proteogenomics Data Analytics" Fahad Saeed (PI), April 2017 - April 2020
1. College and Engineering and Applied Science (CEAS), Western Michigan University (WMU) [US$ 41,650], "Developing HPC solutions to big fMRI data" Fahad Saeed (PI), April 2017 - June 2018
The focus of my research is at the intersection of computational biology, big data, HPC and machine-learning. I am interested in developing machine-learning models for neuroscience and proteomics problems. I am also interested in designing and developing high-performance computing (HPC) algorithms for scientific problems. With my extensive experience working in interdisciplinary research I use novel ways to dealing with big data and domain specific knowledge and AI models including machine-learning and deep-learning algorithms.
Machine-Learning Models for typical and a-typical brains using MRI/EEG data sets
Machine-Learning Models for Mass Spectrometry based omics data sets
High performance computing algorithms for big data from MS based omics
Hardware/Software co-design for large scale omics
Development of Network analysis methods for Scientific Data.
All my publications are available on this page.
In addition a similar list is also available on my lab webpage: SaeedLab papers webpage. Another way to get a list of my publications is via Google Scholar: Google Scholar Profile
2024
105. Umair Mohammad, Fahad Saeed, “MLSPred-Bench: ML-Ready Benchmark Leveraging Seizure Detection EEG data for Predictive Models”, Preprint bioRxiv, July 2024
104. Umair Mohammad, Fahad Saeed, “Heterogeneity Aware Distributed Machine Learning at the Wireless Edge for Health IoT Applications: An EEG Data Case Study”, pages 33 - 70, Book Chapter in Springer Distributed Machine Learning and Computing: Theory and Applications, March 2024
103. Abhishek Bhattarai, Umair Mohammad, Fahad Saeed, “Communication Evaluation of a Wireless 4-Channel Wearable EEG for Brain-Computer Interface (BCI) and Healthcare Applications”, Proceedings of IEEE SoutheastCon, March 2024
102. Muhammad Usman Tariq, Samuel Ebert, Fahad Saeed, “Making MS Omics Data ML-Ready: SpeCollate Protocols”, Book Chapter in Springer Protein Bioinformatics, pages 135-155, July 2024
2023
101. Oswaldo Artiles, Zeina Al Masry, Fahad Saeed*, "Confounding effects on the performance of machine learning analysis of static functional connectivity computed from rs-fMRI multi-site data", Springer Neuroinformatics, Pages 1-18, August 2023 Springer
100. Mohammad Al Olaimat, Jared Martinez, Fahad Saeed, Serdar Bozdag, "PPAD: A deep learning architecture to predict progression of Alzheimer's disease", Oxford Bioinformatics , Volume 39, Issue Supplement 1, June 2023, Pages i149-i157, July 2023 Oxford
99. Usman Tariq, and Fahad Saeed, "DeepAtles: Deep Attention-based Multitasking Network for Predicting Peptide Properties from Mass Spectrometry Data", submitted May 2023
98. Muhammad Haseeb, and Fahad Saeed*, "GPU-Acceleration of the Distributed-Memory Database Peptide Search of Mass Spectrometry Data ", Submitted June 2023
97. Leyva, Dennys, Muhammad Usman Tariq, Jaffe Rudolf, Fahad Saeed, Francisco Fernández-Lima, "Description of Dissolved Organic Matter transformational networks at the molecular level", ACS Journal of Environmental Science & Technology,, Vol 57, No. 6, pages 2672-2681 Jan 2023American Chemical Society (ACS)
2022
96. Tianren Yang, Mai Al-Duailij, Serdar Bozdag, and Fahad Saeed* , "Classification of Autism Spectrum Disorder using Graph Convolutional Network and Graphlet Counting", 2nd International Workshop on Multi-Modal Medical Data Analysis, Proceedings of IEEE International Conference on Big Data (IEEE BigData 2022), Osaka Japan, Dec 17-20 2022.
95. Fahad Saeed* , and Muhammad Haseeb, "High-Performance Algorithms for Mass Spectrometry-Based Omics" ISBN-10: 3031019598, ISBN-13: 978-3031019593, Springer Nature Switzerland AG; 1st edition (September 3, 2022). Springer (Book: 10 Chapters, 156 pages)
94. Dennys Leyva, Rudolf Jaff, Jessica Courson, John S. Kominoski, Muhammad Usman Tariq, Fahad Saeed and Francisco Fernandez-Lima "Molecular level characterization of DOM along a freshwater-to-estuarine coastal gradient in the Florida Everglades ", Springer Aquatic Sciences, volume 84, Article number: 63, Oct 2022 Springer
93. Umair Muhammad, and Fahad Saeed* "SPERTL: Epileptic Seizure Prediction using EEG with ResNets and Transfer Learning", Proceedings of IEEE International Conference on Biomedical and Health Informatics (BHI), Ioannina Greece, 27-30 September 2022.
92. Fahad Saeed*, and Fahad Almuqhim, "Systems And Methods For Diagnosing Autism Spectrum Disorder Using fMRI Data", U.S. Patent US 11379981 B1, Issued July 5th 2022 Local Copy | US Patent
91. Fahad Saeed*, and Muhammad Haseeb, "Systems and methods for peptide identification", U.S. Patent 11,309,061 B1, Issued April 19, 2022 Local Copy | US Patent
90. Aledhari, Mohammed, Rehma Razzak, Basheer Qolomany, Ala Al-Fuqaha, and Fahad Saeed. "Biomedical IoT: Enabling Technologies, Architectural Elements, Challenges, and Future Directions." IEEE Access, vol. 10, pp. 31306-31339, 2022. IEEE
89. Leyva, Dennys, Muhammad Usman Tariq, Rudolf Jaff, Fahad Saeed*, and Francisco Fernandez Lima. "Unsupervised Structural Classification of Dissolved Organic Matter Based on Fragmentation Pathways." Environmental science & technology, 56(2), 1458-1468 March 2022 ACS
88. Fahad Saeed*, and Muhammad Usman Tariq. "Systems and methods for measuring similarity between mass spectra and peptides." U.S. Patent 11,251,031, issued February 15, 2022. US Patent
87. Fahad Saeed*, Muhammad Haseeb, and SS Iyengar, "Communication lower-bounds for distributed-memory computations for mass spectrometry-based omics data" Journal of Parallel and Distributed Computing (JPDC), Volume 161, Pages 37-47, March 2022 arXiv | JPDC
2021
86. Oswaldo Artiles and Fahad Saeed*, "A Multi-Factorial Assessment of Functional HumanAutistic Spectrum Brain Network Analysis" International workshop on Reproducibility and Robustness in Biological Data Analysis (RROBIN), Proceedings of IEEE InternationalConference on Bioinformatics and Biomedicine (BIBM), December 9-12, 2021 IEEE | PubMed
85. Khandaker Mamun Ahmed, Taban Eslami, Fahad Saeed*, and M. Hadi Amini, "Deep-COVIDNet: Deep Convolutional Neural Network for COVID-19 Detection from Chest Ra-diographic Images" International workshop on Machine Learning for Biological and MedicalImage Big Data, Proceedings ofIEEE International Conference on Bioinformatics and Biomedicine(BIBM), December 9-12, 2021 IEEE Xplore | PubMed
84. Muhammad Usman Tariq, Dennys Leyva, Francisco Fernandez Lima, and Fahad Saeed*, "Graph Theoretic Approach for the Analysis of Comprehensive Mass-Spectrometry (MS/MS) Data of Dissolved Organic Matter", International Workshop on Biological Network Analysis and Integrative Graph-Based Approaches (IWBNA), Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), December 9-12, 2021 IEEE Xplore | PubMed
83. Usman Tariq, and Fahad Saeed* , "SpeCollate: Deep cross-modal similarity network for mass spectrometry data based peptide deductions", PLoS ONE, Vol. 16, Issue 10, Oct 2021 PubMed | PLoS
82. Muhammad Haseeb, and Fahad Saeed* , "High performance computing framework for tera-scale database search of mass spectrometry data", Nature Computational Science, Vol. 1, 550-561, August 2021 Arxiv | PubMed | Technical Report | Nature
81. Oswaldo Artiles, and Fahad Saeed*, "TurboBC: A Memory Efficient and Scalable GPU Based Betweenness Centrality Algorithm in the Language of Linear Algebra", International Workshop on Deployment and Use of Accelerators (DUAC), Proceedings of 50th International Conference on Parallel Processing (ICPP), Chicago IL, August 2021 PubMed | ACM Digital Library
80. Umair Muhammad, and Fahad Saeed*, "Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure", Proceedings of 7th IEEE International Conference on Big Data Service and Applications (IEEE BIGDATASERVICE), August 2021 IEEE Xplore
79. Umair Muhammad, and Fahad Saeed*, "Search Feasibility in Distributed MS-Proteomics Big Data", Workshop on High Performance Computing, Big Data Analytics and Integration for Multi-Omics Biomedical Data (HPC-BOD), Proceedings of 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), August 2021 (extended abstract) ACM Digital Library
78. Sumesh Kumar, and Fahad Saeed*, "Real-time peptide identification from high-throughput Mass-spectrometry data", Workshop on High Performance Computing, Big Data Analytics and Integration for Multi-Omics Biomedical Data (HPC-BOD), Proceedings of 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), August 2021 (extended abstract) ACM Digital Library
77. Sumesh Kumar, and Fahad Saeed*, "Communication-optimized micro-architecture to compute Xcorr scores for peptide identification", Proceedings of International Conference on Field-Programmable Logic and Applications (FPL), May 2021 IEEE Xplore | PubMed | Arxiv
76. Fahad Almuqhim, and Fahad Saeed*, "ASD-SAENet: Sparse Autoencoder for detecting Autism Spectrum Disorder (ASD) using fMRI data", Frontiers in Computational Neuroscience, Vol. 15, p. 27, March 2021 Frontiers
75. Muaaz Awan, Abdullah Awan, and Fahad Saeed*, "Benchmarking Mass Spectrometry based Proteomics Algorithms using a Simulated Database", Springer Network Modeling Analysis in Health Informatics and Bioinformatics, Vol. 10, Article 23, March 2021 Springer
74. Oswaldo Artiles, and Fahad Saeed*, ``TurboBFS: GPU Based Breadth-First Search (BFS) Algorithms in the Language of Linear Algebra", 11th IEEE Workshop Parallel/ Distributed Combinatorics and Optimization (PDCO 2021), Proceedings of IEEE International Parallel and Distributed Processing Symposium Workshops (IEEE IPDPSW), May 2021
73. Taban Eslami, Fahad Almuqhim, Joseph S. Raiker, Fahad Saeed*, "Machine Learning Methods for Diagnosing Autism Spectrum Disorder and Attention- Deficit/Hyperactivity Disorder Using Functional and Structural MRI: A Survey", Frontiers of Neuroinformatics, Vol. 14, pp 62, 2021 Frontiers
72. Muhammad Usman Tariq, Muhammad Haseeb, Mohammed Aledhari, Rehma Razzak, Reza M Parizi, and Fahad Saeed*, "Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey", IEEE Access, vol. 9, pp. 5497-5516, 2021 IEEE Access
2020
71. Taban Eslami, Joseph S Raiker, Fahad Saeed, "Explainable and Scalable Machine-Learning Algorithms for Detection of Autism Spectrum Disorder using fMRI Data" Book Chapter arXiv preprint arXiv:2003.01541, 2020 arXiv
70. Bronte Wen, Hyun Jun Jung, Lihe Chen, Fahad Saeed, and Mark Knepper, "NGS-Integrator: An efficient tool for combining multiple NGS data tracks using minimum Bayes" factors", BMC Genomics, Nov 2020 BMC
69. Mohammed Aledhari, Rehma Razzak, Reza Parizi, and Fahad Saeed*, "Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications", IEEE Access, Vol. 8, pp. 140699--140725, July 2020 IEEE Access
2019
68. Taban Eslami, Vahid Mirjalili, Alvis Fong, Angela R. Laird, and Fahad Saeed*, "ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data" Frontiers of Neuroinformatics, vol. 13, pages 70, Nov 2019 arXiv | Frontiers
67. Oswaldo Artiles, and Fahad Saeed*, "GPU-SFFT: A GPU based parallel algorithm for computing the Sparse Fast Fourier Transform (SFFT) of k-sparse signals" Workshop on Performance Engineering with Advances in Software and Hardware for Big Data Sciences (PEASH), Proceedings of IEEE Conference on Big Data (IEEE BigData 2019), Los Angeles, CA, USA, Dec. 09-12, 2019 Tech Report | IEEE Xplore
66. Muhammad Haseeb, and Fahad Saeed*, "Efficient Shared Peak Counting in Database Peptide Search Using Compact Data Structure for Fragment-Ion Index" Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), San Diego, CA, Nov 2019 (Acceptance Rate: 100/543=18%) Tech Report | IEEE Xplore
65. Mohammed Aledhari, Shelby Joji, Mohamed Hefeida, and Fahad Saeed*, "Optimized CNNbased Diagnosis System to Detect the Pneumonia from Chest Radiographs" Workshop on Computational Aspects for Clinical Diagnostics and Decision Making in Healthcare using Biomedical Signal and Image, Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), San Diego, CA, Nov 2019 Tech Report | IEEE Xplore
64. Taban Eslami, and Fahad Saeed*, "Auto-ASD-Network: A technique based on Deep Learning and Support Vector Machines for diagnosing Autism Spectrum Disorder using fMRI data" Workshop on Machine Learning Models for Multi-omics Data Integration, in Proceedings of 10th ACM Conference on Bioinformatics, Computational Biology (ACM BCB), Niagara Falls, New York, September 7-10, 2019. ACM | Tech Report
63. Muhammad Haseeb, Fatima Afzali, and Fahad Saeed*, "LBE: A Computational Load Balancing Algorithm for Speeding up Parallel Peptide Search in Mass-Spectrometry based Proteomics ", Proceedings of IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPSW), Brazil, May 20, 2019 IEEE Xplore | Tech Report
62. Taban Eslami, and Fahad Saeed*, "GPU-DFC: A GPU-based parallel algorithm for computing dynamic-functional connectivity of big fMRI data",Proceedings ofIEEE International Conference On Big Data Service And Applications (IEEE Big Data Service 2019),San Francisco East Bay, California, USA, April 4 - 9, 2019 IEEE Xplore | Tech Report
2018
61. Muaaz Awan, and Fahad Saeed*,"MaSSâ€Simulator: A Highly Configurable Simulator for Generating MS/MS Datasets for Benchmarking of Proteomics Algorithms",Wiley Proteomics,Oct 2018Wiley|PubMed
60. Muaaz Awan, Taban Eslami, and Fahad Saeed*, "GPU-DAEMON: GPU Algorithm Design,Data Management & Optimization template for array based big omics data" Elsevier Computersin Biology and Medicine, Aug 2018 Elsevier | PubMed
59. Fahad Saeed*, "Towards quantifying psychiatric diagnosis using machine learning algorithms and big fMRI data" BMC Big Data Analytics, Vol. 3, No. 1, pp. 1-7, May 2018 Springer | BMC
58. Taban Eslami, and Fahad Saeed*, "Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data - An fMRI Study",MDPI High-Throughput,April 2018MDPI|PubMed
57. Mohammed Aledhari, Marianne Di Pierro, Mohamed Hefeida, and Fahad Saeed*, "A Deep Learning-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets",IEEE Transactions on Big Data, Feb 2018 IEEE Xplore
56. Usman Tariq, and Fahad Saeed*, "Parallel Sampling-Pipeline for Indefinite Stream of Heterogeneous Graphs using OpenCL for FPGAs" Workshop on Energy-Efficient Big Data Analytics,Proceedings of IEEE International Conference on Big Data (IEEE BigData), pp. 1-10, Seattle, WA Dec 10-13, 2018 IEEE Xplore
55. Mohammed Aledhari, Marianne Di Pierro, and Fahad Saeed*, "A Fourier-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets" Proceedings ofIEEE Big Data Congress, San Francisco CA USA, July 2-7, 2018 IEEE Xplore
54. Taban Eslami, and Fahad Saeed*, "Similarity based classification of ADHD using Singular Value Decomposition",Proceedings ofACM Conference on Computing Frontiers (ACM-CF), Ischia, Italy, May 2018 ACM | Tech Report|Presentation (YouTube)
2017
53. Sandino Vargas-Prez and Fahad Saeed*, "A Hybrid MPI-OpenMP Strategy to Speedup the Compression of Big Next-Generation Sequencing Datasets",IEEE Transactions on Parallel and Distributed Systems,March 2017 Tech Report|IEEE Xplore
52. Usman Tariq, Umer Cheema and Fahad Saeed*,"Power-Efficient and Highly Scalable Parallel Graph Sampling using FPGAs", Proceedings ofInternational Conference on Reconfigurable Computing and FPGAs (ReConFig), Cancun, Mexico, December 4-6, 2017Tech Report|IEEE Xplore
51. Sandino Vargas-P'erez and Fahad Saeed*, "Scalable Data Structure to Compress Next-Generation Sequencing Files and its Application to Compressive Genomics", Proceedings ofIEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM),Kansas City, MO, USA, Nov 13-16, 2017Tech Report|IEEE Xplore
50. Muaaz Gul 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 ofACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB),Boston MA, August 2017Tech Report|ACM|PubMed
49. Taban Eslami, Muaaz Gul 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 ofACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB),Boston MA, August 2017Tech Report|ACM
48. Mohammed Aledhari, Ali Marhoon, Ali Al-Qaabi, and Fahad Saeed*,"A New Cryptography Algorithm to Protect Cloud-based Healthcare Services",Proceedings ofWorkshop on Safe, Energy-Aware, & Reliable Connected Health, IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (IEEE/ACM CHASE-SEARCH),Philadelphia PA, July 2017 IEEE Xplore
2016
47. Pablo C. Sandoval, J'Neka S. Claxton, Jae Wook Lee, Fahad Saeed, Jason D. Hoffert and Mark A. Knepper, "Systems-level analysis reveals selective regulation of Aqp2 gene expression by vasopressin",Nature Scientific Reports, Vol. 6, article number 34863, October 2016 Nature|PubMed
46. Muaaz Awan and Fahad Saeed*,"MS-REDUCE: An ultrafast technique for reduction of Big Mass Spectrometry Data for high-throughput processing", accepted inOxford Bioinformatics, Jan 2016Tech Report|PubMed|Oxford
45. Muaaz Gul Awan and Fahad Saeed*, "GPU-ArraySort: A parallel, in-place algorithm forsorting large number of arrays", Proceedings ofWorkshop on High Performance Computingfor Big Data, International Conference on Parallel Processing (ICPP-2016), Philadelphia PA,August 2016Tech Report|IEEE Xplore
44. Majdi Maabreh, Ajay Gupta and Fahad Saeed*, "A Parallel Peptide Indexer and DecoyGenerator for Crux Tide using OpenMP", Proceedings ofWorkshop on High PerformanceComputing Systems for Biomedical, Bioinformatics and Life Sciences, International Conference on High Performance Computing & Simulation (HPCS 2016), Innsbruck, Austria, July2016 IEEE Xplore
43. Mohammed Aledhari, Mohamed S Hefeida and Fahad Saeed*, "A Variable-Length Network Encoding Protocol for Big Genomic Data", Proceedings ofInternational Conference on Wired & Wireless Internet Communications (WWIC 2016), Thessaloniki, Greece May 2016 Springer
42. Mohamed S Hefeida and FahadSaeed*, "Data Aware Communication for Energy Harvesting Sensor Networks", Proceedings ofInternationalConference on Wired & Wireless Internet Communications (WWIC 2016), Thessaloniki, Greece May 2016 Springer
2015
41. Sookkasem Khositseth, Panapat Uawithya, Poorichaya Somparn, Komgrid Charngkaew, Nattakan Thippamom, Jason D. Hoffert, Fahad Saeed, D. Michael Payne, Shu Hui Chen, Robert A. Fenton and Trairak Pisitkun, "Autophagic degradation of aquaporin-2 is an early event in hypokalemia-induced nephrogenic diabetes insipidus",Nature Scientific Reports, Dec 2015Nature|PubMed
40. Fahad Saeed*, "Big Data Proteogenomics and High Performance Computing: Challenges andOpportunities",Symposium on Signal and Information Processing for Software-Defined Ecosystems, and Green Computing, Proceedings of IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP),Orlando Florida, Dec 2015Tech Report|IEEE Xplore
39. Proceedings of 7th International Conference on Bioinformatics and Computational Biology (BICoB), with Hisham Al-Mubaid and Nurit Haspel, March 2015.
38. Sandino N. V. Perez and Fahad Saeed*, "A Parallel Algorithm for Compression of Big Next-Generation Sequencing (NGS) Datasets",Proceedings of Paralleland Distributed Processing with Applications (IEEE ISPA-15), Vol.3. pp. 196-201 Helsinki Finland, Aug 2015Tech Report|IEEE Xplore
37. Mohammed Aledhari and Fahad Saeed*,"Design and Implementation of Network Transfer Protocol for BigGenomic Data",Proceedings ofIEEE International Congress on Big Data (IEEE BigData Congress), pp. 281-288, New York City, USA, June 2015 (18% acceptance rate)Tech Report|IEEE Xplore
36. Muaaz Awan and Fahad Saeed*,"On the sampling of Big Mass Spectrometry Data", Proceedings ofBioinformatics and Computational Biology (BICoB)Conference, Honolulu Hawaii, March 2015Tech Report
2014
35. Akshay Sanghi, Matthew Zaringhalam, Callan Corcoran, Fahad Saeed, Jason D. Hoffert, Pablo C Sandoval, Trairak Pisitkun, and Mark A. Knepper, "A Knowledge Base of Vasopressin Actions in Kidney",American Journal of Physiology, July 2014AJP|PubMed
34. Fahad Saeed*, Jason Hoffert, Trairak Pisitkun, Mark Knepper,"Exploiting thread-level and instruction-level parallelism to cluster mass spectrometry data using multicore architectures",Network Modeling Analysis in Health Informatics and Bioinformatics, 3, No. 1, pp 1-19, Feb. 2014 Springer|PubMed
33. Jason D. Hoffert, Trairak Pisitkun, Fahad Saeed, Justin L. Wilson and, Mark A. Knepper, "Global analysis of the effects of the V2 receptor antagonist satavaptan on protein phosphorylation in collecting duct",American Journal of Physiology, Vol. 306, No. 410-421,Feb. 2014AJP|PubMed
32. Proceedings of 6th International Conference on Bioinformatics and Computational Biology (BICoB), with Bhaskar Dasgupta, Hisham Al-Mubaid and Nurit Haspel, March 2014.
31. Fahad Saeed*, Jason Hoffert and Mark Knepper, "CAMS-RS: Clustering Algorithm for Large-Scale Mass Spectrometry Data using Restricted Search Space and Intelligent Random-Sampling",IEEE/ACM Transactions onComputational Biology and Bioinformatics,11, No.1, pp.128,141, Jan. 2014Tech Report|PubMed|IEEE Xplore
2013
30. Fahad Saeed*, Trairak Pisitkun, Jason D. Hoffert, Sara Rashidian, Guanghui Wang, Marjan Gucek, and Mark A. Knepper,"PhosSA: Fast and Accurate Phosphorylation Site Assignment Algorithm for Mass Spectrometry Data",Proteome ScienceVolume 11, Supplement 1, November 2013 Proteome Science| PubMed
29. Pablo C. Sandoval, Dane H. Slentz, Trairak Pisitkun, Fahad Saeed, Jason D. Hoffert and Mark A. Knepper, "Proteome-wide measurement of protein half-lives and translation rates in vasopressin-sensitive collecting duct cells",Journal of the American Society of Nephrology (JASN), March 2013 JASN|PubMed
28. Fahad Saeed*, Jason D. Hoffert, and Mark A. Knepper, "A High Performance Algorithm for Clustering of Large-Scale Protein Mass Spectrometry Data using Multi-Core Architectures", proceedings ofIEEE/ACM International Symposium on Network Enabled Health Informatics, Biomedicine and Bioinformatics (HI-BI-BI), August 2013 (25% acceptance ratefor full papers)Tech Report|IEEE Xplore
27. Steven J Bolger, Patricia A Gonzales, Jason D Hoffert, Fahad Saeed, Trairak Pisitkun and Mark A Knepper,"Quantitative phosphoproteomics implicates clusters of proteins involved in cell-cell adhesion and transcriptional regulation in the vasopressin signalingnetwork."FASEB JOURNAL. Vol. 27. 9650 ROCKVILLE PIKE, BETHESDA, MD 20814-3998 USA: FEDERATION AMER SOC EXP BIOL, 2013.
26. Special issue on selected papers from the 5th international conference on bioinformatics and computational biology (BICoB 2013) with Bhaskar Dasgupta and Hisham Al-Mubaid, Journal of Bioinformatics and Computational Biology (JBCB) Volume 11, Issue 05, October 2013
25. Proceedings of 5th International Conference on Bioinformatics and Computational Biology (BICoB), with Bhaskar Dasgupta, and Hisham Al-Mubaid (ISBN: 978-1-880843-89-5), March 2013
2012
24. Steven Bolger, Patricia Gonzales Hurtado, Jason Hoffert, Fahad Saeed, Trairak Pisitkun, and Mark Knepper, "Quantitative Phosphoproteomics in Nuclei of Vasopressin-Sensitive Renal Collecting Duct Cells",American Journal of Physiology (AJP), September 2012 AJP|PubMed
23. Boyang Zhao, Trairak Pisitkun, Jason D. Hoffert, Mark A. Knepper, and Fahad Saeed*, "CPhos: A Programto Calculate and Visualize Evolutionarily Conserved Functional Phosphorylation Sites", WileyPROTEOMICS,August 2012Wiley|PubMed
22. Jacqueline Douglass, Ruwan Gunaratne, Davis Bradford, Fahad Saeed, Jason D. Hoffert, Peter J. Steinbach,Mark A. Knepper, and Trairak Pisitkun, "Identifying Protein Kinase Target Preferences Using MassSpectrometry",American Journal of Physiology (AJP), June 2012AJP|PubMed
21. Fahad Saeed, Alan Perez-Rathke, Jaroslaw Gwarnicki, Tanya Berger-Wolf, Ashfaq Khokhar, "A High Performance Multiple Sequence Alignment System for Pyrosequencing Reads from Multiple Reference Genomes",Journal of Parallel and Distributed Computing (JPDC), Volume 72, Issue 1, Pages 83-93,January 2012JPDC|PubMed
20. Jason D. Hoffert, Trairak Pisitkun, Fahad Saeed, Jae H. Song, Chung-Lin Chou, and Mark A. Knepper, "Dynamics of the G protein-coupled vasopressin V2 receptor Signaling Network revealed by Quantitative Phosphoproteomics"Mol Cell Proteomics (MCP),Feb 2012MCP|PubMed
19. Trairak Pisitkun, Jason D. Hoffert, Fahad Saeedand Mark Knepper, "NHLBI-AbDesigner: An online tool for design of peptide-directed antibodies",American Journal of Physiology (AJP), Jan 2012AJP|PubMed
18. Fahad Saeed*, Trairak Pisitkun, Jason Hoffert, Guanghui Wang, Marjan Gucek, and Mark Knepper, "An Efficient Dynamic Programming Algorithm for Phosphorylation Site Assignment of Large-Scale Mass Spectrometry Data",International Workshop on Computational Proteomics, proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philadelphia USA, Oct 2012 (20% acceptance rate) IEEE Xplore|PubMed
17. Fahad Saeed*, Trairak Pisitkun, Jason Hoffert, and Mark A. Knepper, "High Performance PhosphorylationSite Assignment Algorithm for Mass Spectrometry Data using Multicore Systems", accepted inInternational Workshop on Parallel and Cloud-based Bioinformatics and Biomedicine (ParBio),ACM Conference on Bioinformatics,Computational Biology and Biomedicine (ACM-BCB), Orlando Florida USA, Oct 2012(33 papers accepted out of 159 papers submitted: 21% acceptance rate)ACM|Tech Report
16. Fahad Saeed*, Trairak Pisitkun, Mark Knepper, and Jason Hoffert, "An Efficient Algorithm for Clustering of Large-Scale Mass Spectrometry Data", accepted inIEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philidelphia USA, Oct 2012. (62 short paper accepted out of 299 paperssubmitted: 20.7 % acceptance rate)IEEE Xplore|arXiv:1301.0834|PubMed
15. Fahad Saeed*and Ashfaq Khokhar, "Parallel Algorithm for Center-Star Sequence Alignments with applications to Short Reads" accepted in 4th InternationalConference on Bioinformatics and Computational Biology (BICoB), Las Vegas, Nevada, USA, March 12 - 14, 2012
14. Boyang Zhao, Trairak Pisitkun, Jason D. Hoffert, Mark A. Knepper, and Fahad Saeed, "An Information Theory-Based Approach to Assess the Functional Significance of Phosphorylation Sites in Proteomes of Renal Tubule Epithelia", poster atInternational Society of Nephrology (ISN) Symposium, Ann Arbor Michigan, USA, June 2012
13. Proceedings of 4th International Conference on Bioinformatics and Computational Biology (BICoB), with Hisham Al-Mubaid and Ashfaq Khokhar (ISBN: 978-1-880843-85-7), March 2012
2011
12. Fahad Saeed*, Trairak Pisitkun, Mark A. Knepper, and Jason D. Hoffert, "Mining Temporal Patterns from iTRAQ Mass Spectrometry(LC-MS/MS) Data" In proceedings ofBioinformatics and Computational Biology Conference (BICoB)pp 152-159, New Orleans USA, March 23-25, 2011arXiv:1104.5510v1
11. Fahad Saeed, J. Hoffert, P. Pisitkun, M. Knepper, "Mapping-based temporal pattern mining algorithm identifies unique clusters of phosphopeptides regulated by vasopressin in collecting duct", meeting abstractsExperimental Biology (EB), Washington DC, USA April 2011
10. Hoffert, T. Pisitkun, Fahad Saeed, J. Song, M. Knepper, "Large-scale iTRAQ-based quantification of phosphorylation changes during vasopressin signaling", Featured Topic and abstractExperimental Biology (EB), Washington DC USA April 2011
2010
9. Fahad Saeed, "High performance computational biology algorithms", (Doctoral dissertation). Retrieved fromProQuest Dissertations and Theses(Accession Order No. AAT 3431281, ISBN: 9781124308067)ProQuest
8. Fahad Saeedand Ashfaq Khokhar, "Parallel Algorithm for Center Star Sequence and Alignments with applications to short reads"Internationalconference on bioinformatics and computational biology (ACM-BCB)Poster Session, in August 2010
7. Fahad Saeed, Lukas Burger, Ashfaq Khokhar, and Mihaela Zavolan, "A graph-theoretic framework for efficient computation of HMM based motif finder",Technical Report, University of Illinois at Chicago, Jan 2010
2009
6. Fahad Saeed, Ashfaq Khokhar, "A Domain Decomposition Strategy for Alignment of Multiple Biological Sequences on Multiprocessor Platforms",Journal of Parallel and Distributed Computing (JPDC)Vol 69, Issue 7, July 2009arXiv:0905.1744v1|JPDC
5. Fahad Saeedand Lukas Burger "High Performance Graph Theoretic model for finding Regulatory Elements and motifs",Technical Report, Zavolan Group, Swiss Institute of Bioinformatics (SIB), University of Basel Switzerland, August 2009
4. Fahad Saeed, Ashfaq Khokhar, Osvaldo Zagordi and Niko Beerenwinkel. "Multiple Sequence Alignment System for Pyrosequencing Reads"Lecture Notes in Computer Science (LNCS), Volume 5462/2009, 2009arXiv:0901.2753|Springer
2008 and earlier
3. Fahad Saeedand Ashfaq Khokhar, "Sample-Align-D: A High Performance Multiple Sequence Alignment System using Phylogenetic Sampling and Domain Decomposition", in Proc.IEEE International Workshop on High Performance Computational Biology (HiCOMB 2008), IPDPS,Monday, April 14, 2008.arXiv:0901.2742|IEEE Xplore
2. Fahad Saeed,"Pyro-Align: Sample-Align based Multiple Alignment system for Pyrosequencing Reads of Large Number",Technical Report, Beerenwinkel Group Computational Biology, Department of Biosystems Science and Engineering, Eth ZurichSwitzerland, August 2008.arXiv:0901.2751
1. Fahad Saeedand Ashfaq Khokhar, "An overview of multiple sequence alignments and their limitations",Technical Report, Multimedia System Laboratory, University of Illinois at Chicago, May 2007arXiv:0901.2747
Most of the code that we develop can be found listed at our Lab Software Page
We also maintain a very healthy GitHub page at Github Page
We are always seeking creative people with solid analytical capabilities, versatile computational skills applicable to parallel computing, machine learning, and computational biology. Our group is committed to conducting research in computational, data, and engineering sciences in the context of biomedical, clinical, and public health disciplines and applying this knowledge to support the nation’s leading health initiatives. I am always looking for bright, hardworking students and trainees to join my group. If you are seeking a research career in machine learning, data mining, high-performance computing, bioinformatics and related areas, and you have a strong background in mathematics and programming, do reach out. The current opening are below:
If you are a prospective PhD student please read and fill out the details here.
If you are a prospective Post-Doctoral Fellow, please read and fill out the details here.
We have a track record of mentoring students in attaining high impact positions including but not limited to Staff Scientists positions at UC Berkeley, Tenure-track position in Kennesaw State University and Kalamazoo College, as well as data scientists in industrial research positions. A list of current and former students in my group can be found at this link: Current and Former Group Members