Md Rahatul Ashakin

About Me

I work on interpretable and trustworthy machine learning for biological and clinical data. My recent work spans multi‑omics modeling (including cancer datasets) and reproducible ML pipelines, with complementary experience in privacy‑preserving analytics (homomorphic encryption, secure aggregation, post‑quantum cryptography) and hybrid quantum-classical optimization (QAOA/VQE in Qiskit). I care about models that are not only accurate but also reliable, well‑validated, and useful for real scientific and clinical decisions.

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Rahatul Ashakin
Md Rahatul Ashakin
Prospective PhD Student


Education

  • Oct 2022 – Mar 2024 M.S., Information Technology — Washington University of Science and Technology, Alexandria, VA, USA
  • Sep 2013 – Aug 2018 B.S., Computer Science and Engineering — North South University, Dhaka, Bangladesh

Research Interests

  • Biomedical ML: multi-omics and clinical modeling (transformers/GNNs), plus clinical/financial NLP (risk, sentiment, information extraction)
  • Trustworthy ML: robustness, uncertainty/calibration, interpretability, leakage-aware evaluation
  • Privacy-preserving & federated learning: FHE/HE, secure aggregation, post-quantum cryptography for sensitive data
  • Optimization for reliable & efficient ML (classical + quantum-inspired): robust model selection/HPO
  • Hardware-/resource-aware deployment: cloud/GPU pipelines, edge/IoT constraints, and experiments on noisy quantum backends


Selected Publications

  1. Current Tools and Techniques of Artificial Intelligence in Healthcare (book chapter, 2026)
    In: Quantum Computing in Medicine: Transforming Drug Discovery, Protein Folding, and Genomics Research through AI Integration (ed. Don Roosan), Elsevier. ISBN 978-0-443-34193-9.

    Chapter on ScienceDirect →

  2. Under review
    Quantum Annealing of Financial Sentiment Analysis by Optimizing Large Language Model Hyperparameters
    Md Rahatul Ashakin, Christopher Stuetzle, Rubayat Khan, Saif Nirzhor, Don Roosan — under review at Financial Innovation (SpringerOpen).

    Manuscript available upon request.

  3. Variational Quantum Circuits for Molecular Classification Using Graph Neural Network
    Don Roosan, Md Rahatul Ashakin, Rubayat Khan, Hasiba Mashed Khan, Tiffany Khou, Maria-Isabel Carnasciali, Mohammad Rifat Haider
    International Conference on Quantum Communications, Networking, and Computing (QCNC), 2025

    Conference page doi:10.1109/QCNC64685.2025.00074

  4. A Blockchain-Enabled Deep Learning Framework for Secure Omics Data Sharing and Attack Detection
    Don Roosan, Md Rahatul Ashakin, Rubayat Khan, Mazharul Karim
    Computational Data Fusion Journal (CDFJ) · Vol. 1 (2025) · Published 2025-11-12 · Section: Articles

    Publisher doi: cdfjjournal.com/index.php/cdfj/article/view/5

  5. Quantum Variational Transformer Model for Enhanced Cancer Classification
    Don Roosan, Rubayat Khan, Md Rahatul Ashakin, Tiffany Khou, Saif Nirzhor, Mohammad Rifat Haider
    IEAI 2025 (Bali) · IOS Press, Advances in Transdisciplinary Engineering

    Publisher doi:10.3233/ATDE250557

  6. Adaptive Multimodal Artificial Intelligence with Liquid Neural Network for Edge Computing-Based Augmented Reality
    Don Roosan, Rubayat Khan, Md Rahatul Ashakin, Tiffany Khou
    IEAI 2025 (Bali) · IOS Press, Advances in Transdisciplinary Engineering

    Publisher doi:10.3233/ATDE250512

  7. Quantum AI Enhanced Blockchain Security for Drug Discovery
    Don Roosan, Tiffany Khou, Brian Pham, Yawen Li, Md Rahatul Ashakin, Hasiba Mashed Khan, Rubayat Khan, Mohammad Rifat Haider
    9th International Conference on Innovation in Artificial Intelligence (ICIAI 2025), Springer LNEE 1458.

    Publisher DOI: doi.org/10.1007/978-981-95-0887-7_1



Online Certificates



Skills

Programming & Platforms: Python (PyTorch, scikit-learn, NumPy, Pandas) · Git/Linux · Jupyter · Docker (basic) · GPUs · cloud · edge/IoT

Trustworthy ML & Stats: Transformers · GNNs · multimodal fusion · robust training · calibration & uncertainty · ablations & error analysis

Genomics & Functional Genomics: Multi-omics integration · CRISPR/perturbation data · ATAC-seq & regulatory signals · gene & target prioritization

Quantum & Optimization: Qiskit · VQE/QAOA · hybrid classical–quantum workflows · QUBO/Ising mappings · quantum-guided hyperparameter optimization

Privacy & Cryptography: Homomorphic Encryption (CKKS, BGV; OpenFHE/SEAL) · differential privacy · secure aggregation · post-quantum cryptography (KEMs & signatures; liboqs) · threat modeling

Data Engineering & Reproducibility: SQL · ETL pipelines · schema design · MLflow/W&B · environment pinning · unit tests · CI/CD (GitHub Actions) · DVC

Visualization & Writing: Matplotlib · dashboards · LaTeX/Overleaf · figure & table design

Domains: Regulatory genomics · functional genomics (CRISPR & epigenomics) · multi-omics integration · clinical prediction