Fahad Saeed, Ph.D.

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:Saeed Lab (Parallel Computing and Data Science Group)
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 BIBM 2022. Consider contributing a paper (deadline: Oct 23rd, 2022)
I am co-chairing HiCOMB workshop in conjunction with IEEE IPDPS 2022. Consider contributing a paper (deadline: Jan 21, 2023)

Page Contents: Bio Sketch Media Coverage Honors Funding Research Publications Software Prospective Students

Biosketch

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$ 3.4 million in external research funds - with more than US$ 2.7 million as a PI (since 2015). Out of this he has bought in US$ 2.1 million to CEC and KFSCIS at FIU as a PI (since Aug 2018). 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 Zürich, 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 Frontiersin 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

Recent Media Coverage

  • "NIH Awards FIU $1M to Develop Machine Learning Algorithms to Study Proteins", HPC Wire, June 2020 Article Link
  • "FIU researchers think of a way to speed up a vaccine for COVID-19", Miami Herald, June 2020 Article Link
  • "Research Grant Helps FIU Professor Reach One Step Closer To Coronavirus Vaccine", FIU PantherNow, July 2020 Article Link
  • "NIH awards FIU $1M to develop machine-learning algorithms to study proteins – important for understanding, treating diseases", FIU News, June 2020 Article Link
  • "Dr. Saeed awarded prestigious $1 Million R01 grant from National Institute of Health", SCIS FIU News, May 2020 Article Link
  • Distinguished Research and Creative Scholarship Award: Fahad Saeed",OVPR WMU, March 2018 Description YouTube
  • Algorithms for Life, WMU Annual Magazine, Summer 2017
  • Rising Stars in Research, WMU Annual Magazine, Summer 2017
  • Researchers Snag a prestigious National Prize, WMU News Link, 2017
  • WMU Assistant Professor receives NSF CAREER Award, CEAS WMU Article Link
  • Surfing with Algorithms, NSF Science Node, March 2016
  • Working with Powerful Supercomputers, WMU CEAS News, July 2015

    Recent Honors

  • FIU Top Scholar, Research and Creative Activities , Florida International University, Sept 2022 CEC News Page
  • Associate Editor, Experimental Results, Cambirdge University Press, April 2022 Editorial Board Page
  • Keynote Speaker at the 14th International Conference on Bioinformatics and Computational Biology (BICOB). More info here: BiCOB-2022
  • Excellence in Applied Research Award, School of Computing and Information Science (SCIS), Florida International University (FIU), Dec 2020
  • Distinguished Research and Creative Scholarship Award, Office of Vice President of Research WMU, Feb 2018
  • NSF CAREER Award, 2017-2022
  • Highest Funding Award in a year for computer scientist, WMU 2017
  • ACM Senior Member, May 2017
  • Outstanding New Researcher Award}, College of Engineering and Applied Science (CEAS), Western Michigan University, Jan 2016 (1 faculty member gets the award in a single year for the entire college consisting of 7 academic departments)
  • IEEE Senior Member, March 2015
  • NSF CISE Research Initiation Initiative (CRII) Award, Feb 2015 - Feb 2018
  • Fellows Award for Research Excellence (FARE), National Institutes of Health (NIH), June 2012 (Official award ceremony and US\$1000 travel grant)
  • Travel award from Swiss Institute of Bioinformatics (SIB), Summers 2009.
  • UIC Graduate Student Council (GSC) travel award for the BiCoB April 2009.
  • Recipient of Think Swiss Scholarship, by the Government of Switzerland for two years (2007 and 2008).
  • Travel award from D-BSSE ETH Zurich, Summers 2008.

    Funding

    I have been awarded over US$ 3.4 million in external research funds - with more than US$ 2.7 million as a PI (since 2015).
    Out of this I have bought in US$ 2.1 million to CEC and KFSCIS at FIU as a PI (since Aug 2018).
    Most of the external research funds are competitively awareded 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
    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 (Senior Personal), 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

    Current Research Thrusts

    The focus of my research is at the intersection of computational biology, big data, HPC and machine-learning. I am interested in devleoping 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.

    Publications

  • All my publications are available on this page: Publications.
  • A similar list is also available on my lab webpage: Publications Lab Webpage. Another way to get a list of my publications is via Google Scholar: Google Scholar Profile

    2023
    101. Mohammad Al Olaimat, Jared Martinez, Fahad Saeed, Serdar Bozdag, "PPAD: A deep learning architecture to predict progression of Alzheimer’s disease", Proceedings of 31st International conference on Intelligent Systems for Molecular Biology (ISMB/ECCB), July 2023
    100. Usman Tariq, and Fahad Saeed, "DeepAtles: Deep Attention-based Multitasking Network for Predicting Peptide Properties from Mass Spectrometry Data", submitted May 2023
    99. Oswaldo Artiles, Zeina Al Masry, and Fahad Saeed* , "Confounding effects on the performance of machine learning analysis of static functional connectivity computed from rs-fMRI multi-site data", submitted June 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, Jan 2023 

    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 Jaffé, 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 Jaffé, 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 of IEEE 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*, "MaSS‐Simulator: A Highly Configurable Simulator for Generating MS/MS Datasets for Benchmarking of Proteomics Algorithms", Wiley Proteomics, Oct 2018 Wiley| 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 Computers in 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 2018 MDPI | 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 of IEEE 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 of ACM Conference on Computing Frontiers (ACM-CF), Ischia, Italy, May 2018 ACM | Tech Report| Presentation (YouTube)

    2017
    53. Sandino Vargas-Pérez 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 of International Conference on Reconfigurable Computing and FPGAs (ReConFig), Cancun, Mexico, December 4-6, 2017 Tech 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 of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM),Kansas City, MO, USA, Nov 13-16, 2017 Tech 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 of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Boston MA, August 2017 Tech 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 of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Boston MA, August 2017 Tech Report| ACM
    48. Mohammed Aledhari, Ali Marhoon, Ali Al-Qaabi, and Fahad Saeed*, "A New Cryptography Algorithm to Protect Cloud-based Healthcare Services", Proceedings of Workshop 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 in Oxford Bioinformatics, Jan 2016 Tech Report| PubMed | Oxford
    45. Muaaz Gul 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| IEEE Xplore
    44. Majdi Maabreh, Ajay Gupta and Fahad Saeed*, "A Parallel Peptide Indexer and Decoy Generator for Crux Tide using OpenMP", Proceedings of Workshop on High Performance Computing Systems for Biomedical, Bioinformatics and Life Sciences, International Conference on High Performance Computing & Simulation (HPCS 2016), Innsbruck, Austria, July 2016 IEEE Xplore
    43. Mohammed Aledhari, Mohamed S Hefeida and Fahad Saeed*, "A Variable-Length Network Encoding Protocol for Big Genomic Data", Proceedings of International Conference on Wired & Wireless Internet Communications (WWIC 2016), Thessaloniki, Greece May 2016 Springer
    42. Mohamed S Hefeida and Fahad Saeed*, "Data Aware Communication for Energy Harvesting Sensor Networks", Proceedings of International Conference 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 2015 Nature| PubMed
    40. Fahad Saeed*,  "Big Data Proteogenomics and High Performance Computing: Challenges and Opportunities", 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 2015 Tech 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 Parallel and Distributed Processing with Applications (IEEE ISPA-15), Vol.3. pp. 196-201 Helsinki Finland, Aug 2015 Tech Report| IEEE Xplore
    37. Mohammed Aledhari and Fahad Saeed*, "Design and Implementation of Network Transfer Protocol for Big Genomic Data", Proceedings of IEEE 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 of Bioinformatics and Computational Biology (BICoB)Conference, Honolulu Hawaii, March 2015 Tech 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 2014 AJP| 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. 2014 AJP | 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 on Computational Biology and Bioinformatics,11, No.1, pp.128,141, Jan. 2014 Tech 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 Science Volume 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 of IEEE/ACM International Symposium on Network Enabled Health Informatics, Biomedicine and Bioinformatics (HI-BI-BI), August 2013 (25%  acceptance rate for 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 signaling network." 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, Hisham Al-Mubaid and Reda Al-Hajj (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 Program to Calculate and Visualize Evolutionarily Conserved Functional Phosphorylation Sites", Wiley PROTEOMICS,August 2012 Wiley | 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 Mass Spectrometry", American Journal of Physiology (AJP), June 2012 AJP| 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 2012 JPDC|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 2012 MCP | 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 2012 AJP | 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 Phosphorylation Site Assignment Algorithm for Mass Spectrometry Data using Multicore Systems", accepted in International 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 in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Philidelphia USA, Oct 2012. (62 short paper accepted out of 299 papers submitted: 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 International Conference 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 at International 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, 2011 arXiv: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 abstract Experimental Biology (EB), Washington DC USA April 2011

    2010
    9. Fahad Saeed, "High performance computational biology algorithms", (Doctoral dissertation). Retrieved from ProQuest 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" International conference 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 2009 arXiv: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, 2009 arXiv: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 Zurich Switzerland, 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 2007 arXiv:0901.2747
     

    Software and Code

  • 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

    Information for Prospective Students/Postdocs/VisitingScholars

    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 PhD students 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, please read my Prospective PhD Student Page Similarly if you are looking for a postdoctoral position or are interested in short term visiting faculty, please read Prospective Postdoc or Visiting Faculty Page

    Current and Former Students and Staff

    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 datascientists 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