Mir Abrar
@mirabrar1
I'm a computer science undergraduate building Python, NLP, machine learning, and full-stack projects.
What I'm looking for
I've built and compared sentiment-analysis models for IMDB movie reviews, where Logistic Regression with Bag-of-Words achieved 88% accuracy. I'm also researching LLM quantization techniques to reduce memory usage and improve inference efficiency.
Through academic and personal projects, I've developed full-stack applications with React, Node.js, Express.js, MySQL, REST APIs, and Git/GitHub. I enjoy translating research ideas into Python experiments, documenting findings clearly, and working across data, models, and user-focused workflows.
Experience
Work history, roles, and key accomplishments
LLM Quantization Research
Independent Research
Researching Large Language Model quantization techniques for reducing memory usage and improving inference efficiency, including reviewing technical papers and documenting findings.
Sentiment Analysis Project
BRAC University
Built and compared multiple machine learning and deep learning models for IMDB movie review sentiment classification, achieving 88% accuracy with Logistic Regression and Bag-of-Words.
Computer Science Undergraduate
BRAC University
Pursuing a Bachelor of Science in Computer Science with a focus on Python, SQL, data analysis, machine learning, NLP, and LLM research.
Pastport
Built a time-capsule style web application that allows users to draft and schedule future messages, notes, and invitations, with public/private visibility logic and contingency-based message release.
Education
Degrees, certifications, and relevant coursework
BRAC University
Bachelor of Science, Computer Science
Grade: 3.55/4.00
Pursuing a Bachelor of Science in Computer Science with a CGPA of 3.55/4.00, expected to graduate in 2026.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Website
abrarui12.github.ioPortfolio
github.com/AbrarUI12/PastportJob categories
Skills
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