education
Academic background, coursework, and specialized training.
🎓 Education
North South University — Dhaka, Bangladesh
B.Sc. in Computer Science and Engineering · CGPA: 3.88/4.00 (top 2%) · Major GPA: 3.92/4.00
Jul 2020 – Jun 2024
Specialization Courses: Natural Language Processing, Machine Learning, Pattern Recognition
- Awarded Summa Cum Laude distinction (highest academic honor).
- Achieved an average of 97% marks.
- Received a 75% merit-based scholarship for academic excellence.
Thesis: Context-Aware Data Cleaning Pipeline for Clinical Text and Low-Resource Language Bangla
- Best Paper Award at IEEE International Conference on Intelligent Systems (IS) 2024, Varna, Bulgaria.
- Two papers on the data-cleaning pipeline published in IEEE IS 2024 and SN Computer Science (Springer Nature).
Relevant Coursework (with grade)
Grading note: A is considered the highest grade (equal to or above 93%).
| Course | Grade |
|---|---|
| Natural Language Processing (Special Topic, CSE495B) | A |
| Machine Learning (CSE445) | A |
| Design & Analysis of Algorithms (CSE373) | A |
| Data Structures & Algorithms (CSE225) | A |
| Theory of Computation (CSE273) | A |
| Concepts of Programming Languages (CSE425) | A |
| Database Management Systems (CSE311) | A |
| Computer Organization & Architecture (CSE332) | A |
| Probability & Statistics (MAT361) | A |
| Linear Algebra (MAT125) | A |
📜 Additional Programs & Certifications
Cohere Labs Open Science Community — ML Summer School (Summer 2025)
A free, open-science summer school hosted by Cohere Labs, featuring lectures and mentorship from researchers at META, DeepMind, INRIA, and Cohere Labs. Topics included distributed training, transformers, retrieval-augmented generation (RAG), and prompt evaluation. 🔗 Certificate: Verify on CredsVerse · Channel: Cohere Labs YouTube
Supervised Machine Learning: Regression and Classification — Coursera (Mar 2024)
Offered under Andrew Ng’s Machine Learning Specialization, this course covers the supervised learning toolkit—linear/logistic regression, gradient descent, regularization, bias–variance trade-offs, and evaluation metrics (precision, recall, ROC/AUC). Completed Python-based mini-projects focusing on feature engineering and hyperparameter tuning.
🔗 Certificate: Verify on Coursera
The Short Course on Data Science — Jennifer Widom (Instructional Odyssey, NSU, Mar 2024)
Delivered by Stanford Professor Jennifer Widom, this intensive short course focused on practical data-science fundamentals: data modeling and SQL, data cleaning/integration, exploratory analysis, and effective result communication. Included guided exercises to build reproducible analysis pipelines and visualization workflows.
🔗 Certificate: View on Google Drive