I'm Istiyak Amin Santo — a researcher and engineer working at the intersection of deep learning and biomedical imaging.
Currently completing my Master's by Research in AI (CGPA 4.0/4.0) at Multimedia University, Malaysia, I am pursuing a PhD focused on Advanced Deep Learning for Super-Resolution X-Nuclei MRI Reconstruction — a clinically significant challenge where AI can enable metabolic imaging of nuclei like ²³Na, ³¹P, and ³⁹K that standard MRI scanners struggle to resolve.
My background bridges research-grade AI (transformers, CNNs, XAI, medical imaging, computational pathology) with production engineering (full-stack, DevOps, blockchain). I am an IEEE-indexed author, a Gold Medalist at iNVENTEX Innovation Exhibition 2025, and a Three Minute Thesis Finalist at MMU.
Vision: Build clinically trustworthy AI systems that make non-proton MRI viable for early diagnosis of cancer, neurodegeneration, and metabolic disease.
Topic: Advanced Deep Learning Methods for Super-Resolution
Data Reconstruction for X-Nuclei (Non-Proton) MRI Imaging
X-Nuclei MRI (²³Na, ³¹P, ⁷Li, ³⁹K) reveals biochemical and metabolic information that proton MRI cannot — but suffers from inherently low SNR, sparse k-space data, and prohibitively long acquisition times. My PhD directly addresses these bottlenecks using deep learning.
| Area | Methods |
|---|---|
| Super-Resolution Reconstruction | CNN, Vision Transformer & Diffusion-based SR for 3D MRI volumes |
| Sparse K-Space Learning | Deep unrolling, compressed sensing + neural networks |
| Physics-Informed Deep Learning | Embedding MRI relaxometry & k-space priors into network design |
| Multi-Modal Fusion | Using ¹H proton MRI as structural guidance for X-Nuclei enhancement |
| Uncertainty Quantification | Bayesian networks & ensembles for clinical-grade reliability |
| Explainability (XAI) | Grad-CAM++, SHAP, Integrated Gradients for model interpretability |
- Oncology — Tumor metabolism mapping via ³¹P MRS
- Neurology — Stroke penumbra & neurodegeneration via ²³Na MRI
- Cardiology — Myocardial viability & tissue energetics
- Psychiatry — Lithium (⁷Li) distribution monitoring in bipolar disorder
IEEE Scopus-Indexed | Under Review in Q1 Journals
Journal Papers (Under Review)
- 📘 Tri-Objective Co-optimization of Waste-Cooking-Oil Biodiesel Using Machine Learning, NSGA-II, and Life-Cycle Assessment — Energy Reports
- 📘 Risk-Aware Route Optimization for Waste Cooking Oil Collection — Waste Management
Conference Papers (Accepted — IEEE InCIT 2025, Scopus)
- 📗 Travelling Salesman Problem: Classical to Quantum Era — A Comparative Review of Algorithms and Computational Complexity
- 📗 Hybrid Deep Learning Framework for Multi-Class Breast Cancer Scoring Using Grad-CAM++
- 📗 Real-Time Nuclei Classification and Allred Scoring in PR-IHC Stained Breast Cancer Histopathology Images
| Award | Year |
|---|---|
| 🥇 Gold Medal — iNVENTEX Innovation Exhibition (Biofuel LCA Toolkit) | 2025 |
| 🎤 Finalist — Three Minute Thesis (3MT) Competition, MMU | 2025 |
| 🎓 Fully Funded Government Linked University (GLU) Research Grant | 2024–2025 |
| 📊 CGPA 4.0/4.0 — MSc by Research in Artificial Intelligence, MMU | 2024–2025 |
| Role | Organization | Period |
|---|---|---|
| 🎓 PhD Researcher (pursuing) | Biomedical AI — X-Nuclei MRI Reconstruction | 2026 → |
| 🔬 Graduate Research Assistant | Data Science Lab, Multimedia University, Malaysia | Jul 2024 – Jun 2026 |
| 💼 Full Stack Developer | Royal Recruiter (Remote) | Mar 2023 – May 2024 |
| ⛓️ Blockchain Developer | King Apps Studio, Malaysia | Dec 2021 – Jul 2022 |
| 🌐 Web Developer | Chief ERP System | Sep 2017 – Nov 2021 |
| Degree | Institution | Result |
|---|---|---|
| 🔬 MSc by Research — Artificial Intelligence | Multimedia University, Malaysia | CGPA 4.0/4.0 |
| 💻 BSc — Computer Science & Engineering | Port City International University, Bangladesh | CGPA 3.63/4.0 |
| ⚡ Diploma — Electronics Engineering | Chittagong Polytechnic Institute | CGPA 3.01/4.0 |
I am actively looking to connect with:
- 🏥 Clinicians & Radiologists — seeking AI tools for MRI enhancement or pathology analysis
- 🔬 Medical Imaging Researchers — joint work on X-Nuclei MRI, histopathology AI, SR reconstruction
- 🚀 Healthtech Startups & VCs — building AI-powered diagnostic and imaging tools
- 🎓 PhD Programs & Labs — in computational pathology, medical image analysis, or biomedical AI
What I bring: Research rigor (IEEE publications, CGPA 4.0) + engineering depth (production systems, MLOps) + biomedical domain knowledge — a rare combination for a researcher at this stage.
📬 Reach me: LinkedIn
"The best diagnostic tool is one the clinician never has to think about — it just works."