I’m a Computer Science undergraduate interested in Machine Learning, Computer Vision, and Responsible AI, with hands-on experience building ML systems through hackathons and independent projects.

• Programming: Python, C
• Data & ML: Pandas, NumPy, Scikit-learn
• Computer Vision: YOLO, Object Detection
• Prototyping & Demos: Streamlit
• ML Concepts: Classification, Evaluation, Interpretability, Uncertainty Handling

Hackathon Project

Built and trained a YOLO-based object detection pipeline to identify and localize objects in images under hackathon constraints. Worked on dataset preparation, model training, inference, and evaluation using standard computer vision metrics such as IoU.

Independent Project (Prototype)

Developing an AI-powered travel companion matching platform to help first-time international travelers find compatible co-travellers and access structured country-wise visa and cultural guidance. The project focuses on modular design and scalable matching logic for future AI-driven enhancements.

Hackathon Project (AI 4 Alzheimer’s – Hack4Health)

Developed an interpretable machine learning prototype for early Alzheimer’s risk assessment, reframing detection as a risk stratification problem rather than a binary diagnosis.
The system uses transparent models, age-adjusted brain atrophy features, and uncertainty-aware risk bands (low, high, uncertain) to support safer and more responsible decision-making in healthcare contexts.
This project is not a diagnostic tool and is intended as a decision-support prototype.

📧 Email: [email protected]
🔗 GitHub: https://github.com/Kataki-Niv