CV

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Basics

Name Asadullah Bin Rahman
Title Lecturer | AI/ML Researcher | Quantum Computing Enthusiast
Email galib.hstu.cse17@gmail.com
Url https://asadullahgalib007.github.io
Summary Lecturer of Computer Science and Engineering at World University of Bangladesh, specializing in quantum computing, machine learning, and biomedical image processing.
Location Dhaka, Bangladesh
Socials LinkedIn  |  GitHub  |  Google Scholar
Research interests Quantum Optimization, Quantum Key Distribution, Quantum Machine Learning

Work

  • 2025.07 - Present
    Lecturer of Computer Science and Engineering
    World University of Bangladesh
    Teaching undergraduate courses in Computer Science and Engineering. Mentoring students in research and academic projects.
    • Student mentorship and guidance
    • OBE curriculum
    • Bloom's taxonomy
  • 2023.07 - Present
    Research Assistant
    IoThink Lab, HSTU
    Conducting research in image processing and machine learning. Aiding my supervisor in facilitating research work.
    • Biomedical Image Processing
  • 2023.03 - 2023.09
    Lecturer of Computer Science and Engineering
    Govt. Shahid Akbar Ali Science and Technology College (SASTC)
    Taught: Theory of Computation, Computer Graphics, Machine Learning.
    • Designed and delivered courses.
    • Supervised project works

Volunteer

  • 2025.04 - Present
    Mentor
    QBangladesh (QWorld)
    Mentoring students and promoting quantum literacy in Bangladesh.

Education

Awards

Certificates

QClass24/25 Fall Semester
QWorld 2024-12
Womanium Global Quantum+AI 2024
WOMANIUM Foundation 2024-10-03
Quantum Algorithms Development - I
Classiq Technologies 2024-08-09
PennyLane Quantum Machine Learning Challenge
PennyLane 2024-08-09
Qiskit Global Summer School 2024 - Quantum Excellence
IBM 2024-08-01
QBronze
QWorld 2024-07-01
QNickel
QWorld 2024-07-01
Python for Everybody Specialization
Coursera 2020-09-01

Publications

Skills

Quantum Computing
Qiskit
Cirq
PennyLane
Classiq
Quantum Algorithms
Quantum Machine Learning
Quantum Key Distribution
Machine Learning
NumPy
Pandas
SciPy
Matplotlib
OpenCV
PyTorch
TensorFlow
Image Processing
Computer Vision
Programming
C++
Java
Python
Data Structures
Algorithms
Databases
Web Development
HTML
CSS
JavaScript
PHP
MySQL

Languages

English
Fluent (IELTS Academic: 6.5; L/R/S: 6.5, W: 6.0)
Bengali
Native

Interests

Competitive Programming
Codeforces: [Click here]
HackerRank: [Click here]
UVa: [Click here]
Chess
Lichess: [Click here]
Chess.com: [Click here]

References

Dr. Md. Abdulla Al Mamun
Professor of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur-5200, Bangladesh
Visit: https://hstu.ac.bd/teacher/mamun
Email: mamun@hstu.ac.bd
Masud Ibn Afjal
Associate Professor of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur-5200, Bangladesh
Visit: https://hstu.ac.bd/teacher/masud
Email: masud@hstu.ac.bd

Projects

  • 2023.01 - 2024.11
    Guava Fruit Disease Dataset @ IoThink Lab
    Collaborated on dataset collection for interdisciplinary research.
  • 2024.01 - Present
    MRI Image Denoising using Wavelet Transform
    Applying wavelet transform techniques to reduce noise in MRI images and comparing results using metrics such as MSE, PSNR, and SSIM.
    • Explored various wavelet functions (db3, bior6.8, sym4), decomposition leveds, optimal threshold value estimation (universal/bayes), thresholding methods (hard/soft) to find the best combination that can mitigate gaussian noise from image
  • 2024.08 - 2024.08
    Quantum Variational Classifier @ Womanium Program
    Implemented a quantum classifier for Penguin Species Classification.
  • 2024.08 - 2024.08
    Quanvolutional Neural Networks @ Womanium Program
    Developed a hybrid quantum convolutional model for MNIST Digit Classification.
  • 2024.08 - 2024.08
    Quantum Regression Model @ Womanium Program
    Implemented a Quantum Machine Learning Model to learn and predict the sine function on the interval [0, 2π].
  • 2024.07 - 2024.08
    QML for Conspicuity Detection in Production
    Final project for the Womanium Quantum + AI 2024 program that earned me the QSL fellowship nomination. I implemented a Hybrid Quantum Convolutional Neural Network to detect anomalies in production.
    • MNIST Digit Classification
    • Implemented a 3x3 kernel using Quantum Circuit along with a classical CNN.
    • Implemented various layers as ansatz(e) for a Quantum Regression Model and performed comparison.