Aravind Nagarajan
Computer Science and Engineering Undergraduate
Building at the intersection of code, data, and intelligence.
Skills & Technologies
A comprehensive overview of the technologies and tools I work with
Experience
My professional journey in software engineering, research, and innovation
- Developed MLOps automation workflows in Zoho Analytics (platform serving 20k+ businesses worldwide)
- Published a scientific article in Elsevier- Results in Engineering (Gold Open Access, Impact Factor 2025: 7.9) on damaged civil infrastructure surveying with Image Segmentation and 3D Point Cloud Analysis
Featured Projects
A showcase of my recent work & the technologies I've used to bring ideas to life
Advanced machine learning solution for mental health prediction using ensemble modeling and hyperparameter optimization. Achieved near-benchmark performance on Kaggle competition.
Key Features:
- ●Exploratory Data Analysis and advanced preprocessing
- ●Dataset splitting based on unique & null patterns
- ●Hyperparameter tuning with Optuna for performance optimization
- ●Ensemble modeling for improved predictions
- ●Achieved Kaggle score of 0.9396 (near global benchmark of ≈ 0.941)
Technologies:
Edge Software in the Loop system with real-time person tracking and autonomous drone navigation using computer vision and MAVLink protocol.
Key Features:
- ●Edge Software in the Loop system with Jetson and RealSense D455 camera
- ●RGB-D data streaming via TCP for real-time processing
- ●YOLOv8n depth-aware tracking with ArduCopter navigation
- ●MAVLink protocol implementation with <3 sec response time
- ●TensorRT acceleration achieving <20 FPS latency
Technologies:
Custom ML model building and deployment platform integrated into Zoho Analytics, serving 20k+ businesses worldwide.
Key Features:
- ●Full-stack ML model deployment platform
- ●Vue3 frontend with intuitive UI/UX
- ●Java backend with optimized database operations
- ●Normalized database schema design
- ●75% latency reduction through optimization
- ●Comprehensive API documentation
Technologies:
Web application for real-time inference of crack segmentation models on civil infrastructure images with sub-second response time.
Key Features:
- ●Real-time image processing (<1 sec/image)
- ●Advanced crack segmentation algorithms
- ●User-friendly web interface
- ●High-performance inference pipeline
- ●Integration with research findings