Leaf Disease Detection System
An AI-powered plant disease detection system using MobileNetV2 with a Flask backend, authentication, and SQLite-based prediction logging.

INITIALIZING SYSTEMS...
I'm A Roshini Krithi — a Computer Science undergraduate focused on Full-Stack Engineering, Artificial Intelligence, and building products that solve meaningful problems.
A snapshot of consistency, competitive programming, and problem-solving discipline across global competitive judges.
Knight Tier Trajectory
Pupil Rank — Active Competitor
2 Star Division Competitor
Across All Competitive Judges
Systems, products, and experiments built across full-stack engineering and artificial intelligence.
An AI-powered plant disease detection system using MobileNetV2 with a Flask backend, authentication, and SQLite-based prediction logging.

A full-stack competitive programming platform that aggregates coding contests across major judges and presents them through a unified high-performance experience.

An AI-enhanced luxury e-commerce platform combining personalized recommendations, secure Razorpay payments, and cinematic product interactions.

A custom language-model platform engineered from scratch, exploring transformer architecture, Byte-Pair Encoding tokenization, retrieval augmentation, and parameter-efficient fine-tuning.

Software engineering internships, leadership appointments, and competitive speaking distinctions.
Full Stack Development Intern
Full Stack Developer Intern
Secretary & Distinguished Speaker
LEARNLOGICIFY — Remote / Hybrid
Developed responsive web applications, built reusable UI components, worked across frontend and backend systems, and contributed to application performance optimization.
Technologies I use to design, build, debug, and ship software systems.
How I think about systems architecture, clean abstractions, and applied intelligence.
I'M INTERESTED IN THE SPACE WHERE ENGINEERING MEETS INTELLIGENCE.
I enjoy turning complex technical problems into simple, useful products — from full-stack systems and developer tools to AI-powered applications.
Whether formulating low-latency REST endpoints, training custom neural vision classifiers, or fine-tuning transformer weights, I prioritize rigorous algorithmic soundness, clean modular component hierarchies, and measurable performance.
Key research areas, technical deep-dives, and active engineering experiments.
Exploring AI Agents & Tool-Use Architectures
Engineering Aura GPT & Tokenizer Pipelines
Solving High-Difficulty DSA Problems
Learning Distributed Systems & System Design
Mastering Cloud Infrastructure & Fast Inference
Open to full-stack engineering roles, AI/ML initiatives, high-impact collaborations, and technical conversations.