Designing intelligent systems that transform data into insight and ideas into scalable solutions.
I am a software developer and AI/ML engineer with a strong foundation in computer science fundamentals, data structures, and machine learning systems.
I specialize in building intelligent, scalable, and production-ready applications that combine solid backend engineering with applied AI.
- Strong command of Python, C++, and Java
- Experienced in Machine Learning, NLP, and Computer Vision
- Hands-on with backend systems, APIs, and data pipelines
- Passionate about clean architecture, performance, and real-world impact
- Continuous learner focused on research-backed and industry-aligned development
- Python, C++, Java
- Data Structures & Algorithms
- Object-Oriented Design
- Linux & Shell Scripting
- Machine Learning & Model Evaluation
- Deep Learning (CNNs, NLP pipelines)
- Computer Vision (OpenCV, YOLO)
- Feature Engineering & Data Analysis
- Pandas, NumPy, scikit-learn
- PyTorch
- Streamlit
- FastAPI
- SQL & Relational Databases
AI-powered task intelligence platform
An intelligent task management system that automatically classifies, prioritizes, and assigns tasks using NLP and machine learning models. Designed for productivity optimization and enterprise workflows.
Tech Stack: Python, Streamlit, Pandas, ML
🔗 Live Demo: https://aitaskmanager28-bxahukjkzparonrie229uy.streamlit.app/
Personalized career guidance using NLP
An AI-driven chatbot that analyzes user input and recommends career paths, skills, and learning roadmaps using natural language understanding.
Tech Stack: JavaScript, OpenAI API, HTML, CSS
🔗 Live Demo: https://sunny-rabanadas-bd1f6f.netlify.app/
Computer vision–based traffic optimization
A real-time traffic monitoring system using YOLOv8 and OpenCV to detect vehicles and dynamically optimize traffic signals for smart city environments.
Tech Stack: Python, OpenCV, YOLOv8
AI-assisted safety & alert platform
A smart system designed to prevent animal–vehicle collisions using geolocation, ML analytics, and real-time alerts for highways and rural roads.
Tech Stack: FastAPI, Firebase, Android, ML
Personalized content recommendation system
A machine learning–based movie recommender using collaborative filtering and NLP-based similarity analysis, deployed as an interactive web app.
Tech Stack: Python, scikit-learn, Streamlit
- 💼 Open to internships, research roles, and software/AI engineering opportunities
- 🤝 Interested in collaborative AI & open-source projects
- 📚 Constantly improving skills through real-world problem solving
"Code with clarity. Build with purpose. Learn without limits."
— Abhijeet Kasera