Hi there
My name is MD. Raiyan Bin Rafique. I’m a dedicated Computer Science and Engineering student at Rajshahi University of Engineering & Technology (RUET) with a strong foundation in Machine Learning (ML), Python, Julia, and practical AI/Automation projects.
I'm actively seeking research opportunities to apply my growing knowledge in coding and technical skills. Previously, I gained experience in the research and development wing of the Notre Dame Science Club.
Below are details of some of the projects I have developed to showcase my skills in AI, data, and software engineering.
Education
Rajshahi University of Engineering & Technology (RUET)
CGPA: 3.88/4.00 (1st Year Odd Semester)
Notre Dame College, Dhaka
GPA: 5.00/5.00
Domar Multilateral High School, Domar
GPA: 5.00/5.00
Skills
Programming & ML Frameworks
- Python
- Julia
- TensorFlow
- Keras
- Scikit-learn
- NumPy
- Pandas
Tools & Libraries
- Multisim
- pywinauto
- Streamlit
- Matplotlib
- CustomTkinter
- Skyfield
- Requests
- Google Gemini API
AI Concepts
- CNN
- Deep Learning
- Supervised Learning
- Generative AI
- Predictive Modeling
- Automation
Projects
Elecsyn (AI Multisim Automation Agent)
- Python
- pywinauto
- Google Gemini API
A sophisticated automation bridge that leverages Google Gemini 2.5 Pro to synthesize SPICE netlists from engineering prompts and orchestrates end-to-end simulations in NI Multisim using pywinauto.
Potato Disease Detection System
- Python
- CNN
- Streamlit
An AI-powered computer vision application utilizing Convolutional Neural Networks (CNN) to classify potato leaf diseases with high precision through automated feature extraction and live inference modes.
OrbiSense
- Python
- Skyfield
A high-performance satellite tracking suite using the Skyfield SGP4 physics engine to compute precision orbital trajectories and visualize interactive ground-track maps for real-time aerospace monitoring.
Diabetes Risk Classifier
- Python
- Machine Learning
A rigorous machine learning classifier developed with Scikit-Learn to assess diabetic risk by analyzing physiological markers through optimized predictive analytics and a user-friendly GUI.
Charged Particle Orbit Simulation
- Julia
- Physics
- Mathematical Modeling
A sophisticated physics simulation leveraging Julia to accurately model two charged particles interacting under Coulomb's Law. It implements Euler's method for precise numerical integration of orbital trajectories and utilizes Plots.jl to generate dynamic, animated visualizations.
Certifications
- CS50x: Introduction to Computer Science (Harvard)
- Machine Learning with Python (V2)
- Introduction to Generative AI
- Ethics in the Age of Generative AI
Contact
Reach out on Email: raiyanrohit10@gmail.com, GitHub, or LinkedIn