Hi! I am Syed

Professional
Experience

- Aixelink Sàrl
- Software Engineer
July, 2021 ~ Present
Leading the Front-end team in developing highly complex web solutions for Critical Care environment of hospitals around the world. Working remotely with a cross-country team as a software engineer in the company’s enterprise solution. Mainly focusing on:
- JavaScript technologies for Web (Front-end Team Lead)
- .NET framework for hardware driver software development
Experience Highlights:
- Working as a team lead in an enterprise level software migration from WinForm solution to Web-based solution.
- Developed real-time data visualization solutions with d3.js
- Working on a multi-threaded Node.js application
- Worked on a version upgrade migration of a product from Vue 2 (JavaScript) to Vue 3 (TypeScript)
- Worked in a multi-framework front-end environment. Introduced state management and communication system for a jQuery application lying inside a Vue.js framework
- Developed automation tools with Rust programming language that works as a log parser.
- Mindfork Tech Ltd.
- Mobile Application Developer (Remote)
March, 2021 ~ June, 2021
Developed React Native based cross platform mobile application.
- ConnectAuz Pty Ltd.
- Mobile Application Developer (Remote)
- Part-time
June, 2020 ~ September, 2020
Worked on developing a cross-platform application with Flutter.

Education

- Chittagong University of Engineering & Technology (CUET)
- Bachelor of Science in Computer Science & Engineering
2017 ~ 2021
CGPA: 3.01/4.00
- Notre Dame College
- Higher Secondary Certificate (HSC)
2015 ~ 2017
GPA: 5.00/5.00
- Chittagong Collegiate School
- Secondary School Certificate (SSC)
2009 ~ 2015
GPA: 5.00/5.00

Achievements

- Expert
- codeforces.com
- 5^th position, Inter University Programming Competition
- CUET CSE Fest, 2019
- 7^th position, Inter University Programming Competition
- USTC Techtronics, 2019
- 25^th position, Inter University Programming Competition
- IUT 10th ICT Fest Programming Contest, 2019

Certification

Research

- An Approach to Identify Associated People in Crowd Based on Image Association Rule Mining
- Undergraduate Thesis
2020 ~ 2021
Introduces a system that can analyze video data in real time to provide prediction of groups of people in the crowd who are supposedly together with the help Association Rule Mining over video data.