harikrishnan_ss
$ whoami >> Full Stack Developer
Building innovative solutions with modern technologies. Currently pursuing B.Tech in CSE at IIIT Gwalior with a passion for Machine learning and Web development.
about_me
I'm a Computer Science student with a strong foundation in full-stack development and machine learning. My passion lies in building software that's not only functional and scalable but also solves real-world problems in meaningful ways. I've worked on projects like web applications to apps that leverage predictive models—to deepen my understanding across multiple domains of computer science.
I thrive at the intersection of development and problem-solving, and I'm always curious to explore new technologies, frameworks, and ideas. Whether it's designing intuitive user interfaces or optimizing backend performance, I enjoy the process of turning ideas into impactful digital solutions.
tech_stack
experience
- Building a modular full-stack Course Management platform using React and Node.js
- Designing RESTful APIs with Express and developed optimized MongoDB schema to handle Course and User data
- Supporting 500+ users and managing 10,000+ quiz records
- Improved content load times through optimized data retrieval
featured_projects
- Designed and developed a secure, cloud-native file-sharing platform optimized for high concurrency
- Architected a 4-tier microservices system (API Gateway, Encryption Service, Storage Service, Background Worker) with Docker Compose orchestration, health checks, and TLS-secured NGINX reverse proxy
- Built an asynchronous task system using Celery + Redis for tasks like file cleanup and usage statistics generation
- Integrated PostgreSQL (for metadata & logs) and MinIO (S3-compatible storage) with Redis caching to improve API throughput by up to 60%
- Configured full observability stack with Prometheus metrics, Grafana dashboards, and structured JSON logging; achieved zero-downtime deployments
- Designed a real-time IDS system integrating ML and Computer Networking
- Captured and parsed live traffic data using Python and TCP/IP stack
- Trained Random Forest on CICIDS 2018 dataset with 99% accuracy
- Visualized predictions using Chart.js, reducing debugging time by 25%
- Built real-time football player detection and tracking system
- Used YOLO for accurate player detection with high-speed inference
- Applied K-Means clustering for jersey color segmentation with 95% precision
- Implemented Optical Flow for camera movement compensation
- Developed end-to-end real estate platform with map-based listings and interactive UI
- Implemented Leaflet.js to display properties with accurate real-world geolocation on maps
- Used Prisma ORM and MongoDB Atlas for scalable backend services and user data storage
- Improved user session duration by 30% through intuitive design and fast-loading pages
connect
$ echo "Always open to discussing new opportunities and exciting projects!"