The Parallel Computing and Data Science Lab (Saeed Lab) is a computational research lab based at Knight Foundation School of Computing and Information Sciences (KFSCIS), Florida International University in Miami, Florida, led by Dr. Fahad Saeed.

The Saeed Lab is located on FIU’s MMC Campus in the Computing, Arts, Sciences & Education (CASE) building (Room 261).

The Saeed Lab develops machine-learning models, combined with high-performance computing, and data science approaches, to study the functional genomics, and organization of the human brain.

Our work focuses on understanding the stochastic difference between identified peptides from high-throughput mass spectrometry data for applications related to human health, disease, and environment. In addition, our work focuses on understanding brain function in the context of prediction, diagnosis and characterization of biomarkers specific to disorders such as epilepsy, ADHD, Autism, and Alzheimer’s.

To achieve these goals, we embrace open science principles and adopt and develop best practices to promote reproducible computational results. If you would like to know more about specific projects, you are welcome to visit us on GitHub, Research and Software pages. Complete open project models and data are shared via Open Science Framework (OSF), FigShare, and Harvard Dataverse.

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.
You can send me a follow-up email at fsaeed@fiu.edu after you have filled out the relevant forms.

Recent Papers
[PREPRINT] Predicting peptide properties from mass spectrometry data using deep attention-based multitask network and uncertainty quantification
Tariq, Usman; Saeed, Fahad; , bioRxiv :1-22 (2024).
Published 22 Aug 2024
PVTAD: Alzheimer’s Disease Diagnosis Using Pyramid Vision Transformer Applied to White Matter of T1-Weighted Structural MRI Data
Aghdam, Maryam Akhavan; Bozdag, Serdar; Saeed, Fahad; Alzheimer’s Disease Neuroimaging Initiative; , Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI) :1-4 (2024).
Published 22 Aug 2024
[PREPRINT] MLSPred-Bench: ML-Ready Benchmark Leveraging Seizure Detection EEG data for Predictive Models
Mohammad, Umair; Saeed, Fahad; , bioRxiv :1-8 (2024).
Published 22 Jul 2024
Projects
Compressive and reductive analysis of genomic and proteomics data
Development of methods that can operate on compressed big data
HPC Engine for Mass Spectrometry based Omics Data
Design and development of high-performance computing algorithms for large-scale MS omics data using hetregenous architectures
MLSPred-Bench: Reference EEG Benchmark for Prediction of Epileptic Seizures
Reference EEG Benchmark for Prediction of Epileptic Seizures
Predicting Epileptic Seizures
Advance machine-learning models for prediction of Seizures using EEG data
ML Ecosystem for Mass Spectrometry Data
Development of interconnected set of open-source machine-learning tools for mass spectrometry based omics
Characterization and diagnosis of Autism Spectrum
Machine-learning models that can classify between autistic and neurotypical brains
News
Saeed Lab webpage is up and running

Saeed Lab webpage is now hosted via github for more collaborative science communication

Posted 29 Jun 2024