This page connects the academic, product, and experimental versions of the portfolio into one timeline: where the AI work began, where the interface craft matured, and what that combination now points toward.
2022
Chose Data Science as the foundation
Started B.E. in Computer Science and Engineering (Data Science) at MIT Mysore with a strong pull toward AI systems and practical engineering.
2023
Built the fundamentals in data + code
Worked through Python, analytics, databases, and research basics while sharpening communication and problem-solving.
2024
Moved into interactive ML experiences
Started combining live computer vision, browser interfaces, and experimentation-heavy workflows instead of keeping projects siloed.
2025
Shipped stronger products and earned proof
Completed internship work, went deeper on statistics and Power BI, and collected stronger public proof through workshops, certifications, and demos.
2026
Won recognition for applied AI work
The multimodal disease detection project secured second prize at Project Expo, strengthening my confidence in building impact-driven ML systems.
Next
Aiming for product-minded AI engineering
The current direction is clear: keep pairing AI depth with product quality and join teams where both technical accuracy and interface craft matter.