Welcome to my world
Senior Full Stack Developer | AI & Computer Vision Researcher

I'm a passionate software engineer pursuing my Master's in Computer Science at Northeastern University. With 9+ years of experience spanning full-stack development, game development, and AI/ML research, I bridge the gap between cutting-edge research and production-ready applications.
My research focuses on Computer Vision, Deep Learning, Medical Image Analysis, and Explainable AI. I've developed systems for skin cancer classification, monocular depth estimation, and multi-modal book detection using state-of-the-art architectures.
1st Place in Uzbekistan - First student from my high school to win at national level
Bookshelf Scanner - Computer Vision Course at Northeastern University
Built HIPAA-compliant healthcare platform for Alzheimer's care planning. Led AWS Amplify Gen 1 to Gen 2 migration. Implemented real-time messaging systems.
Developed MMO game "Chestnut" with real-time sync & Web3. Built AI healthcare app for medical imaging on Azure AKS. Created full-stack real estate platform with Next.js/NestJS.
Led migration from ASP.NET Web Forms to Blazor WebAssembly. Developed responsive UI components and optimized server applications.
Enhanced web app performance by 30%. Developed browser games with PhaserJS and created knowledge management platform with Node.js, Dgraph, and React.
Developed robotic cashier app and self-service kiosks integrated with POS systems using WPF, gRPC, and computer vision for product recognition.
Developed multiplayer VR smart city project in Unity. Integrated SteamVR and MLAPI networking for real-time collaboration.
Developed explainable deep learning system for multi-class skin lesion classification using EfficientNet V2 with GradCAM++ visualization. Implemented novel ABCDE criterion analysis for clinical interpretability across all 9 ISIC 2019 categories.
Designed lightweight depth estimation model with ResNet18 encoder and U-Net decoder, achieving 42% fewer parameters than Depth Anything V2, 72% faster inference, and better relative error metrics on NYU Depth V2 benchmark.
Implemented FSRCNN architecture achieving 40x speedup over SRCNN with end-to-end learned upsampling. Evaluated on Set5 (+1.78 dB PSNR) and Set14 (+1.26 dB PSNR) with comprehensive ablation studies.
HIPAA-compliant platform connecting to hospital PACS via DICOM for AI-powered analysis on X-ray, CT, and MRI studies with OHIF Viewer integration.
Enterprise-scale multi-tenant SaaS fleet management system with real-time tracking, SignalR messaging, admin/management web apps, and mobile driver application.
Online chess platform with PvP and AI opponents, supporting rated and unrated matches with real-time WebSocket communication.
End-to-end book detection from bookshelf images using YOLO segmentation and Moondream2 vision-language model for title/author extraction.
Comprehensive library for generating and managing forms in Blazor with drag-and-drop features and JSON schema generation.
ML-assisted matchmaking combining player clustering, XGBoost predictions, and ELO rating for balanced competitive Age of Empires IV matches.
Northeastern University, Boston, MA
January 2024 - May 2026
GPA: 4.0/4.0Suffolk University, Boston, MA
September 2021 - May 2023
Cum Laude | GPA: 3.5/4.0INTI International College, Malaysia
September 2019 - July 2021
TUIT, Uzbekistan
September 2017 - June 2019
GitHub
github.com/suxrobgmTelegram
@suxrobgm