> Decoding operator profile...
const me = {
name: "Chanvitha Praveen",
title: "Computer Engineer",
passions: ["Full-Stack Web", "Microservices", "Machine Learning", "Generative AI", "Computer Vision"],
mission: "Solving real-world problems with code",
currently: "Software Engineer @ Singapore-based Logistics SaaS",
stack: "Angular · NestJS · Java/Spring · Python · MongoDB · GCloud · K8s",
};
As a Computer Engineer, I'm passionate about Full Stack Web Development, Machine Learning & exploring emerging technologies. Currently shipping a 12-microservice logistics platform that serves 7 major clients and 20+ operations — building KPI dashboards, revamping the GPS module, and stabilising L1 issues with unit tests. Off-hours: generative AI, vision-transformer research, and photography. Hardworking, responsible team player and eager to contribute & learn within dynamic environments.
> Tracing operator's professional commits...
Contributing to a scalable product platform with 12 microservices, supporting 7 major clients and 20+ operations. Building a new KPI-focused dashboard, revamping the GPS module, and delivering urgent client requirements. Ensuring system stability & performance by fixing L1 issues, writing unit tests, and improving development efficiency using Cursor & other modern tooling in sprint-based workflows.
Delivered three contract ML projects: (1) Smart Attendance System for Workstation, (2) Dental Radiology Report Generator, and (3) Text-to-Video, Image-to-Video + Audio Generation Pipeline. Owned end-to-end work — data pipeline, model integration, and API delivery — for each engagement.
Extracted data from diagram images and converted them into textual format to feed an in-house LLM. Engaged in data collection, web scraping, preprocessing, and tested LLamaCPP locally. Designed React/Streamlit-based frontends for LLM prototype endpoint testing. Built a CLI tool to identify running AWS instances by user and region to reduce cost. Did anomaly detection with multiple algorithms and research on blockchain systems for the Stock Market.
Had a great work experience in sales assisting, cashiering and front office receptionist. Achieved maximum monthly sales targets and made significant commitments for the company.
> 8 files found · sorted by impact
A project for garment field that users input basic body measurements & the scratch Deep Learning model gives complex body measurements. Users can wear custom garments designed by super admins in virtual wardrobe before purchasing.
Developing separate services for User, Reservations, Flight Information, Frontend. Having Eureka service, load balancers, separate databases to have the microservice architecture. Try to maintain zero downtime with multi-servers (Blue/Green).
This project is a 9x9 & 16x16 Sudoku Puzzle Solver application. Detect the puzzle via a camera & OCR by Easy OCR. Then pass the puzzle and solve in C++ because fast execution. For 9x9 puzzle it takes ~2.6ms & for 16x16 puzzle it takes only ~16.5ms.
‘Elcare’ is developed for senior citizens to assist effectively. They will get digital assistance through this application to easily manage their medical routines, sleep deprivation, emergencies, and to reach the family doctor and share their medical info.
This project Analyzes Twitter hashtags data to understand user engagement trends over time & across cities for analyzing past macro-data, past micro-data, forecasting future data. Initial dataset had 11 columns, after feature engineering, could be able to have 22 columns. Hope to add real time data stream analysis part also using Kafka as further improvements.
A Web Application with translation functionality for improve the ethnic cohesion. Users can send messages in their language, then translated and displayed to the recipient's chosen language. All messages show in a common chat lobby.
The “Cryptanz” platform is developed for transferring digital currencies via the Ethereum chain and the Ropston network. Also can view the latest transactions. As future improvements hope to add sending messages via AES encrypted method and user login via a PGP mail server instead of google sign-in at the moment.
Classify High Realistic Stable Diffusion AI generated images and Real photographs of Human Faces to protect online privacy. Trained a custom dataset that assembled ~17000 images on ViT (Vision Transformer) model & developed an API to integrate into image uploaders in social media apps, web sites, etc. Currently got 99.97% accuracy & doing more optimizations.
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PHO> Tracing knowledge acquisition pipeline...
> Hash-verified academic & technical credentials
> 1 peer-reviewed paper · IEEE Xplore indexed
In the fashion industry, Augmented Reality (AR) is changing how customers experience garments; this holds good, especially in custom clothing. This research aims at resolving the problem of how a customer and a vendor can view the visualization of garment fitting correctly online. The research designs an interactive fitting room system using AR that allows customers to interactively visualize garments and find their size accurately for a vendor. This is achieved with the support of Marvelous Designer for the design of realistic 3D garment models and Lens Studio for the development of AR sessions in virtual try-ons. The main components of the system were precise garment modeling, integration of AR technologies, and development of a size prediction feature based on anthropometric measurements. The methods used in this research include data collection, 3D garment creation, AR session development, and integration of the back-end and front-end of the system. The results show a generally user-friendly experience with high accuracy of size recommendations and realism in garment visualization, which led to increased satisfaction among both customers and vendors. This approach has already indicated vast potential for improving online shopping experiences in the fashion industry.
U. B. R. A. Gunaratne, A. N. L. Illangarathna, E. D. C. Praveen, N. H. Wanigasingha and U. Wijenayake, "TryOnAI: Revolutionizing Online Shopping with Augmented Reality and Deep Learning for Virtual Try-Ons and Size Prediction," 2026 6th International Conference on Advanced Research in Computing (ICARC), Belihuloya, Sri Lanka, 2026, pp. 1-6, doi: 10.1109/ICARC68737.2026.11453617.
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