Lanke Kiran Teja

Lanke Kiran Teja

React DeveloperFlutter DeveloperNode.js + FastAPIFull-Stack BuilderProblem SolverReact Developer
Full-Stack Developer
Hyderabad, Telangana, India

I'm a Computer Science student who loves building apps that solve real problems—comfortable with Flutter for mobile, React for web, and Node.js / FastAPI on the backend. I focus on readable code and interfaces that feel good to use.

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Tech Stack

Featured Projects

Kiden Hub

All-in-one productivity workspace: task management, focus tracking, and personal analytics with a Kanban board, Markdown notes, and offline-first sync to Supabase.

React
TypeScript
Supabase
Fillora

Mobile app to automate repetitive form filling with AI-assisted inputs, voice-to-text, multilingual support, and privacy-first local storage with biometrics and PDF export.

Flutter
Dart
SQLite
Greendot

Farmer’s assistant: crop disease identification from photos, real-time market prices, smart irrigation and harvest reminders, with offline-friendly caching for rural connectivity.

Flutter
Firebase
TensorFlow
MailX

ML-based email classification into work, personal, and spam using NLP feature extraction and tuned models so important messages surface reliably.

Python
React
n8n
FinScribe

Financial report generator: structured MD&A-style reports from raw financial data via a FastAPI backend and responsive React frontend.

React
Python
FastAPI

Experience

LifeMonk

Full-Stack Developer

LifeMonkHyderabad, India

Jan 2026 – Apr 2026

Educational platform with Vite CMS admin, React Expo mobile app, and Xano backend—challenges, courses, and school-scoped data.

  • -Built and debugged the platform; fixed critical school-level data isolation and course mapping with per-school templates
  • -Designed Challenges across CMS and mobile (course linking, time periods); managed 50+ Xano APIs with entitlement handling
Swecha

SoAI Hybrid Intern

SwechaHyderabad, India

2025

LLM inference in production: scalable APIs, latency optimization, and reliability under load.

  • -Deployed inference pipelines from local checkpoints to APIs handling 1000+ req/min
  • -Token-level optimizations and attention caching cut latency ~40% under concurrency; monitoring and fallbacks for ~99.5% uptime
AICTE Remote

AIML Virtual Intern

AICTE RemoteRemote

2023

Supervised learning on multiple datasets with full ML pipelines from preprocessing through evaluation.

  • -Tuned models to 85–92% accuracy on classification tasks across five datasets
  • -Built end-to-end workflows: preprocessing, feature engineering, training, and evaluation
HCL Tech Bee Scholar

Networking Development Intern

HCL Tech Bee ScholarLucknow, India

2022 – 2023

Production network diagnostics, QoS improvements, and Python automation for monitoring and logs.

  • -Resolved 20+ network bottlenecks; QoS changes improved throughput ~35%
  • -Python automation for monitoring and log analysis cut troubleshooting from hours to minutes per incident

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