About Me

Current Status: CS Graduate (BRAC University) · Actively seeking Ph.D. positions & Graduate Research Opportunities abroad in Advanced Artificial Intelligence & Machine Learning.

Biography & Career Objective

I am S. M. Mohiuddin Khan Shiam, a Computer Science graduate with strong academic grounding in software systems, artificial intelligence, and peer-reviewed machine learning research. My long-term goal is to pursue a Ph.D. abroad in advanced artificial intelligence, focusing on computationally efficient architectures, explainable intelligence, and real-time edge vision.

My research spans Machine Learning, Deep Learning, Computer Vision, Explainable AI (XAI), High-Frequency Time-Series Forecasting, Quantum Machine Learning (QML), and Medical Image Diagnostics. I have authored peer-reviewed research published in international Q1 journals (Elsevier Array), submitted manuscripts to Scientific Reports (Nature Portfolio), and engineered ultra-compact neural models like Nano3D (a 486K-parameter 3D-CNN operating at 7.19 ms edge latency).

Beyond academic research, I am a passionate open-source contributor across 11+ global open-source organizations and 17+ mission-critical repositories—including the Microsoft developer ecosystem (VS Code, Windows Terminal, WSL, AutoGen), foundational ML libraries (scikit-learn, Keras, Ultralytics, OpenVINO), and distributed cloud infrastructure (Kubernetes, Apache Airflow, Flux CD).

Research Interests

Machine & Deep Learning

Efficient neural architectures, 3D Convolutional Neural Networks (3D-CNNs), spatiotemporal modeling, ConvLSTM, and Bayesian hyperparameter optimization.

Computer Vision & Edge AI

Real-time surveillance anomaly detection, edge-device model compression, latency minimization on embedded hardware, and Vision Transformers (ViT, ViViT).

Explainable AI (XAI)

Spatiotemporal Grad-CAM saliency mapping, TreeSHAP, Kernel SHAP, LIME, and Partial Dependence Plots (PDP) for trustworthy and verifiable predictions.

Time-Series Forecasting

High-frequency macro-financial modeling, multi-tier hybrid gradient-boosted ensembles (XGBoost, LightGBM, CatBoost), and non-stationary volatility forecasting.

Quantum Machine Learning

Hybrid quantum-classical algorithms, Parameterized Quantum Circuits (PQCs), and Variational Quantum Classifiers (VQCs) utilizing Qiskit and PennyLane.

Medical Image Diagnostics

Volumetric 3D Vision Transformers and CNNs for acute ischemic stroke lesion segmentation and oncological screening with interpretable attribution.

Education

BRAC University

Bachelor of Science in Computer Science · 2021 – 2026 | Dhaka, Bangladesh

Thesis: Deep Learning Frameworks for Suspicious Activity Detection (Supervised by Prof. Dr. Amitabha Chakrabarty & Prof. Dr. Md. Golam Rabiul Alam). Proposed Nano3D, an ultra-compact 3D-CNN achieving 88.7% accuracy, 0.947 AUC, and 7.19 ms latency with Grad-CAM visual interpretability.
Leadership: Treasurer, IEEE BRAC University Student Branch (2024). Directed branch fiscal budgeting, financial tracking, transparent accounting, and co-organized major workshops including “Smart City & IoT”.
Coursework Highlights: Artificial Intelligence, Machine Learning, Neural Networks, Computer Vision, Data Structures and Algorithms, Object-Oriented Programming, Discrete Mathematics, Software Engineering, Database Systems, Computer Networks, Quantum Computing, Natural Language Processing, and High-Performance Computing.

Hazera-Taju Degree College

Higher Secondary Certificate (HSC) – Science Group · 2018 – 2020 | Chattogram, Bangladesh

Curriculum: Physics, Chemistry, Higher Mathematics, Biology, Information & Communication Technology, Bangla, and English.
Recognized with Academic Excellence in National Board Examinations.

Nasirabad Govt. High School

Secondary School Certificate (SSC) – Science Group · 2012 – 2018 | Chattogram, Bangladesh

Strong foundational grounding in analytical mathematics and scientific inquiry.
Active participant in science fairs, hands-on laboratory experiments, and school sports.

Work & Research Experience

Machine Learning Researcher

Mahdy Research Academy · Dhaka, Bangladesh (Remote) | 2024 – Present (2026)

Conducted advanced research in high-frequency time-series forecasting, neural networks, and Bayesian-tuned hybrid ensemble architectures.
Engineered end-to-end machine learning data pipelines and authored peer-reviewed scientific articles published in international Q1 journals (Elsevier Array).
Formulated interpretable frameworks utilizing SHAP, LIME, and Partial Dependence Plots for policy-grade macroeconomic interpretability.

Treasurer

IEEE BRAC University Student Branch · Dhaka, Bangladesh | 2024

Managed student branch fiscal budgeting, financial auditing, funding allocations, and transparent institutional reporting.
Co-organized major technical workshops, seminars, and training programs, including the flagship “Smart City & IoT” workshop.

Technical Skills

Programming Languages: Python, C++, Java, MATLAB, JavaScript, TypeScript, SQL, HTML5/CSS3, PHP, Bash/Shell.
Machine Learning & Deep Learning: PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, LightGBM, CatBoost, OpenCV, Pandas, NumPy, SciPy, Matplotlib, Seaborn.
AI Paradigms & Methods: 3D CNNs, ConvLSTM, Vision Transformers (ViT, ViViT), Explainable AI (SHAP, LIME, Grad-CAM), Hybrid Ensembles, Bayesian Optimization, Time-Series Forecasting, Quantum Machine Learning (Qiskit, PennyLane).
Web & Cloud Technologies: Next.js, React, Node.js, Express, MongoDB, RESTful APIs, Docker, Kubernetes, Linux/Unix, Git, GitHub, Overleaf, $\LaTeX$, VS Code.

Honors & Awards

Top 10% Global Talent Issued by The Talent Games, Nov. 2024.
RS-60 Cricket Cup Champion Issued by BRAC University, Jul. 2022.
Academic Excellence in National Board Examinations: Awarded in the Higher Secondary Certificate (HSC 2020), Science Group.