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Developers Profile

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Dr. Mainuddin

Chief Software Architect

Skill Set

AWS IoT Data Mining ASP.NET Elasticsearch XGBoost Random Forest Matplotlib Scikit-Learn Seaborn Deep Learning Autoencoders SPRT Software Architectural Design Team Lead DB Design

About Me

I hold a PhD in Computer Science from Florida State University, specializing in IoT security.

My research focuses on utilizing Machine Learning and Deep Learning techniques to identify and analyze compromised devices within smart networks, driving advancements in secure and intelligent connectivity.

With over 17 years of experience as a software engineer, I have successfully architected and delivered large-scale, efficient, and customized enterprise applications. My work has consistently provided high-quality, reliable solutions that empower businesses and foster success in a competitive market.

Areas of Expertise

Strategic Architect & Developer: Proven ability to design and implement large-scale, tailored applications that address complex business challenges.

AWS Cloud Expertise: Deep knowledge of cloud infrastructure for scalable, secure, and high-performing applications.

Collaborative Leader: Fostering team synergy and empowering individuals to achieve high-quality results through problem-solving and effective communication

Full-Stack Development: Adept at leveraging front-end frameworks, robust back-end systems, and AWS Cloud technologies to create scalable and innovative applications

Career Highlights

Full Stack Developer at Amazon

Jul 2022 – Present

Senior Software Engineer at Brain Station 23

Jan 2011 - May 2015

Programmer (Team Lead) at Technohaven Ltd

Feb 2010 - Jan 2011

Software Engineer at Infinity Solutions

Jun 2006 - Jan 2010

Detecting Compromised IoT Devices Using Deep Autoencoders and SPRT

Compromised IoT devices are the main origin of botnet attacks. Recent DDoS and other botnet attacks have caused significant harm, and have been facilitated by the use of IoT-based botnets. Due to the limited human interaction required for IoT devices to function, it can be difficult to monitor all of their activities. Therefore, it is crucial to identify compromised devices within a network. My model uses Deep autoencoder to learn the regular network behavior of IoT devices in a network and continue monitoring the network. If a device is compromised, it can be detected as fast as 7 network packets with an accuracy up to 99.98%.

Camera-Based Vehicle Detection and Alignment System

As the project owner, I led the architecture and implementation of a camera-based, machine learning-driven vehicle alignment system designed to replace legacy motion sensors. The system utilized advanced computer vision techniques and real-time object detection models to ensure precise, automated vehicle positioning within pallet boundaries. This initiative aimed to enhance operational efficiency, safety, and reliability in automated parking facilities.

I integrated high-resolution camera streams with machine learning frameworks for occupant and boundary detection, alongside image processing pipelines that processed frames at scale. Robust alert mechanisms were implemented to provide immediate, actionable insights into alignment issues or potential obstructions. This approach minimized manual intervention, enabling smooth, continuous operation and improved user satisfaction.

The solution leveraged Python, OpenCV, YOLO-based object detection, and scalable backend services, delivering a cost-effective, extensible platform tailored for the evolving needs of automated parking environments. This project exemplifies my ability to lead complex, ML-focused initiatives that drive significant improvements in system performance and stakeholder experience.

Rejoanul Alam

Sr. Software Engineer

Skill Set

PHP MySQL Laravel CodeIgniter WordPress CSS HTML JavaScript VueJS CI/CD AI chatGPT

About Me

A proud alumnus of Jahangirnagar University and BUET, I am a Zend Certified Engineer with a specialized degree in Web Application Development. With over 15 years of extensive experience in full-stack development, I have mastered the art of designing and delivering robust, scalable, and innovative software solutions that drive business success.

Areas of Expertise

Full-Stack Development: Extensive experience with front-end frameworks, robust back-end systems, and cloud technologies, ensuring the delivery of powerful and efficient software

Technical Leadership: A proven ability to lead teams, foster collaboration, and drive exceptional results through innovative problem-solving and clear communication.

Career Highlights

Senior Software Engineer at Freelance Marketplace

Top Rated Freelancer with 100% JSS in Upwork

Feb 2020 – 2025

Principal Software Engineer at BJIT Inc

Sep 2018 – 2020

Software Engineer at Spinytel Private Ltd (Now Kolpolok)

Dec 2013 – 2017

PocketTalk Language Learning System

Rosetta Stone Language score API integration. Oauth2 API development for authorization in laravel. Advanced Vuejs implementation for microphone setting

chatGPT OpenAI Assistant API

openAI chatGPT assistant API implementation including live chat window, big file analyzer window, chat history management etc

Shafayat

Shafayat Hussein Chowdhury

Sr. Software Engineer

Skill Set

C# ASP.NET MSSQL Server PostgreSQL Oracle

About Me

A proud alumnus of Jahangirnagar University. With over 15 years of extensive experience in full-stack development, I have mastered the art of designing and delivering robust, scalable, and innovative software solutions that drive business success.

Career Highlights

Senior Software Engineer at Millennium Information Solution Ltd

Jul 2014 – 2025

Asst. Programmer at Technohaven Company Ltd

Oct 2012 – 2014

to be added