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About Me

Hi, I am Abdullah Al - Mohaimin, a Computer Science & Engineering graduate from Bangladesh. I did my undergraduate study in Bangladesh University of Engineering & Technology. My undergraduate thesis was on "Resistance distances in Graphs". I enjoy coding, with a liking for backend development. In my free time, I read manga or books, watch tv series, anime or movies and play with(annoy) neighbourhood cats. Pic on 👈 is a local cat.

More About Me

I am a fan of C and C++. Given a choice, I have always done my courseworks in C/C++. However, I also have worked with Python and is learning Go. As almost everyone has one, I too have a favourite Javascript framework and that is Svelte. I find it very lightweight, easy to write code in and reasonably fast. For similar reasons, I also love the Postgresql database.

I love Linux and the Free & Open Source(FOSS) movement in general. I try to be a trouble shooter for problems my friends face with their Linux systems. I am also an avid user of git and github.

I wish to be a versatile learner and enjoy reading books about history, economy, science. Many a nights I have spent(wasted) in the depths of Wikipedia on any kind of subjects 😭. Also, I love reading books on different topics. Currently I am reading the book "The Geography of Imagination" by Guy Davenport.

Academics & CV

âš« Passed Secondary School Certificate(SSC) exam in 2017 with GPA 5.00

âš« Passed Higher Secondary School Certificate(HSC) exam in 2019 with GPA 5.00

âš« Undergraduate in Computer Science & Engineering: 2020-2025, with undergraduate research on "Resistance Distances in Graphs"

Here is my full Curriculum vitae

Some of my Recent Projects

AuthentiDocs

For my senior year software engineering lab project, me and my teammates made a digitally authenticated team collaboration platform. Here, we used digital signatures to verify formal interactions. We tried to combine the features of a document signing app with those of an organizational management application. We used Svelte hosted in Vercel and Supabase database for this project.

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Anidex

Me and my teammate made an collaborative anime database for our sophomore year database lab project. We tried to emulate the features of MyAnimeList and AniDB, letting users view, search, list and add anime, characters, voice actors, discuss about them in forums, schedule watch parties etc. I wrote the backend in ExpressJS with Postgresql with my friend coding the frontend in Svelte.

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Picture Puzzle

Me and my teammate made a picture puzzle solving website for my departments annual festival. Here users solved picture puzzles, while admins set up puzzles, checked submissions and contest situation. The website had over 700 verified users registered with around 100 concurrent users. We used SvelteKit with PostgreSQL database, hosting in DigitalOcean.

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Velociraptor Tutorial

Me and my teammate created a Bengali language tutorial for the Velociraptor Digital Forensin & Incident Response(DFIR) tool. It was part of our senior year Computer Security course. It was the first time Velociraptor was covered in Bengali language video tutorial. We tried to give an overview of DFIR and used Velociraptor to show its abilites, starting from compilation to various features.

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Safe n Secure Wheelchair Buddy

For our Microcontroller course project in junior year, we made a secure wheelchair system for elderly and/or disabled persons, using Arduino to control a electric motor powered wheelchair with sensors to detect falls and obstacles. I helped write code for the motor connections, sensor controls. My teammates also made an android app to connect to the wheelchair via bluetooth. We also used a sim card module to facilitate direct messaging with an caregiver. It was selected as one of the 10 top projects.

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Network Flow Classification

In our senior year Machine Learning lab project, we chose to use Transformer based architecture to perform network flow classifications. We used a well-known dataset and tried different Transformers such as BERT and variants, GPT2; coupling them with feature selection. Our findings indicate that with feature selection, Transformers can perform multi-class network flow classification with performance comparable to the state of the art models.

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My Top Skills

Reach Me At

Github Linkedin Kaggle leetcode