Hazrat Maghaz
Bioinformatics & Computational BiologySchool of Interdisciplinary Engineering & Sciences (SINES), National University of Sciences & Technology (NUST), Sector H-12, Islamabad 44000, Pakistan
Education
Thesis: "NeuroBridge: A Bidirectional Multimodal Deep Learning Framework for CNS Tumor Analysis Using Histopathology and Gene-Expression Profiles" (Approved September 2026).
Core Areas: Multimodal Deep Learning, Cancer Genomics, Whole-Slide Computational Pathology, Structural Bioinformatics.
Undergraduate Thesis: "Discovering New HIV-1 Integrase Inhibitors: An Integrated Approach with QSAR Study, Molecular Docking, for Designing Effective Antiviral Compounds."
Foundation: Molecular biology, analytical biochemistry, enzymology, protein chemistry, and bio-organic mechanisms.
Research Appointments
- Formulated and evaluated deep representation models coupling Gigapixel Whole-Slide Image (WSI) tiles with bulk RNA-seq data across TCGA-GBM and TCGA-LGG cohorts.
- Evaluated cross-institutional generalization on independent CPTAC-GBM multi-site cases.
- Designed the Path2Omics (histology-to-transcriptome marker inference) and Gene2Morph (RNA-guided authentic histology patch retrieval) modules.
- Benchmarked missing-modality testing regimens to assess feature robustness under missing clinical data.
Theses & Scholarly Submissions
NeuroBridge: A Bidirectional Multimodal Deep Learning Framework for CNS Tumor Analysis Using Histopathology and Gene-Expression Profiles.
National University of Sciences & Technology (NUST) SINES.
Discovering New HIV-1 Integrase Inhibitors: An Integrated Approach with QSAR Study, Molecular Docking, for Designing Effective Antiviral Compounds.
Department of Biochemistry, Abdul Wali Khan University Mardan.
A Structural Bioinformatics Approach to Assess High-Impact nsSNPs and Their Functional Consequences in CD28.
Submitted for scholarly peer review (disclosed as submitted under technical review; not presented as accepted or published).
Technical & Computational Skills
PyTorch, TensorFlow, scikit-learn, CNNs, Vision Transformers, Contrastive Loss, Cross-Attention Mechanisms, SHAP (Explainable AI).
AutoDock Vina, PyRx, GROMACS (MD simulation trajectory analysis), Discovery Studio, MOE, PyMOL, AlphaFold protein modeling.
FastQC, Cutadapt, QIIME2, DESeq2, edgeR, STAR, featureCounts, 16S rRNA amplicon processing, taxonomic profiling.
Python (NumPy, pandas, SciPy, RDKit, Mordred, Matplotlib, Seaborn), R / Bioconductor, Bash scripting, Linux HPC environments, Git.
Laboratory Competencies (Biochemistry)
DNA extraction (SDS kit & column extraction), Polymerase Chain Reaction (PCR), Agarose Gel Electrophoresis, Enzyme-Linked Immunosorbent Assay (ELISA), Column Chromatography, UV-Vis Spectrophotometry, Enzyme activity kinetics.