Hi, my name is

Nageen Chand

A budding backend developer

A dedicated Java backend developer, specializing in crafting robust RESTful applications and mastering SQL databases. I thrive in the realm of server-side development, where I turn ideas into functional realities. Let’s build the backbone of your digital ambitions.

About Me

I’m a software developer with a strong academic background, holding both Bachelor’s and Master’s degrees in computer science. Currently, I work as a software developer at Wunderman Thompson Commerce, specializing in Intershop-based E-commerce websites.

My responsibilities encompass backend development, overseeing database management with expertise in SQL and MSSQL, and delivering exceptional client support. I also stand ready as the dedicated point of contact for addressing priority issues, ensuring seamless service continuity.

Join me in crafting efficient and innovative backend solutions.

Here are a few technologies I've been working with recently:
  • Java
  • REST APIs
  • Spring Boot
  • InterShop
  • MicroServices

Experience

Associate Developer - Backend - WTC
Jul 2021 - present
  • In my current role, I’ve improved our client’s ecommerce site by implementing an Express checkout feature, resulting in increase in conversion rates. I specialize in e-commerce website development using Intershop, focusing on payment gateway integrations, order management, and inventory control to deliver comprehensive solutions.

  • Collaboration is key to my work. I partner with project managers, designers, and QA testers to ensure high-quality solutions for our clients.

  • Additionally, I contribute to the development of internal tools and processes, including RESTful APIs and Java code, to support project delivery. My expertise in MVC architecture ensures our e-commerce solutions are both scalable and maintainable.

To stay at the industry forefront, I actively adapt to new technologies and methodologies like Agile development, providing our clients with cutting-edge solutions.

Computer Vision Intern - Mirasys
May 2020 - Jul 2020
As a Computer Vision/Machine Learning intern, I gained practical experience working on real-world applications of object detection using Deep Learning. This hands-on internship provided valuable insights into applying cutting-edge technology to solve real-world problems.

Education

1
2016 - 2021
Master of Technology in Computer Science
National Institute of Technology, Hamipur
GPA: 9.22 out of 10

I have completed my Masters of Technology in Computer Science and Engineering from NITH, My Dissertation for the course was on

  • Data Fusion for IoT based Devices using Dempster-Shafer Evidence Theory : Focused on optimizing IoT data management by applying Dempster-Shafer Theory for efficient data fusion. Aimed to reduce data transmission and enhance privacy in heterogeneous sensor networks.

Research Project was on

  • Abnormal Vehicle Detection System : Developed real-time abnormal vehicle detection system using YOLOv3, optical flow analysis, and SVM classifier, achieving 93.57% accuracy. Leveraged deep learning for object detection and tracking, optical flow for motion analysis, and SVM for classification. Trained and validated model on large-scale BDD100K open dataset containing over 100K videos

Key takeaways from the course:

  • Proficiency in Python, Java, and C++
  • Specialization in data science, AI, and computer vision
  • Research experience in emerging technologies
  • Collaboration with professors and peers

Extracurricular Activities

  • Volunteering experience and active member of GLUG-NITH during graduation
2
2016 - 2021
Bachelor of Technology in Computer Science
National Institute of Technology, Hamipur
GPA: 8.2 out of 10

During my B.Tech. program, I immersed myself in computer science, programming, and software development. I tackled a notable project in my final year, which focused on:

  • Enhancing Pedestrian Movement Detection in Driving Assistant Systems : In this project, we addressed the critical challenge of accurately detecting the direction of pedestrian movement in driving assistance systems. Our goal was to develop software that would contribute to a safer driving experience for both pedestrians and drivers in various scenarios, including zebra crossings, public demonstrations, parking areas, and shopping centers.

Key components of the project included:

  • Utilizing the YOLO (You Only Look Once) algorithm for pedestrian detection and localization.
  • Calculating optical flow vectors for each detected pedestrian using dense optical flow analysis.
  • Inputting segmented pedestrian data into a neural network to predict movement direction.

Extracurricular Activities

  • Volunteering experience and active member of GLUG-NITH during graduation
3
Class XII
Vardhman Mahavir Pubic School, Sunder Nagar
Aggregate: 88.8 %
Course includes Physics, Chemistry, Mathematics, English (language) and Computer Science and its Applications.

Projects

JumboDeals
Java Spring Boot MongoDB Javascript
JumboDeals
Designed and built responsive web application with Spring Boot and Thymeleaf templating to aggregate and display product listings from e-commerce sites. Also implemented scheduler-driven automation for periodic data refresh and update, ensuring seamless user experience across devices
Abnormal Vehicle Detection System
Python Research Project Object Detection
Abnormal Vehicle Detection System
Developed real-time abnormal vehicle detection system using YOLOv3, optical flow analysis, and SVM classifier, achieving 93.57% accuracy. Leveraged deep learning for object detection and tracking, optical flow for motion analysis, and SVM for classification. Trained and validated model on large-scale BDD100K open dataset containing over 100K videos

Rewards and Recognition

Get in Touch

My inbox is always open. Whether you have a question or just want to say hi, I’ll try my best to get back to you!