N Aadesh

I'm

About

Backend AI Engineer skilled in building scalable systems, cloud-native applications, and high-performance search workflows. Passionate about developing innovative solutions using artificial intelligence and modern web technologies. I thrive on creating efficient, scalable applications that solve real-world problems.

Location: Ariyalur
Phone: +91-9790553886

City: Coimbatore, TN
State: Tamil Nadu

Interests

Software Development

Machine Learning

Computer Vision

Natural Language Processing

Software Engineering

Visualization

Algorithms

Image Processing

Education

B.Tech in Computer Science and Engineering

August 2023 - July 2027 (Expected)

CGPA: 7.06

Relevant Coursework

Machine Learning
Distributed Systems
Database Management
Data Analytics

Hackathons & Achievements

Adobe India Hackathon 2025 - Runner Up

Engineered a 4-stage document processing pipeline improving parsing accuracy by 35%
Developed real-time snippet extraction with FAISS similarity search, 1.2s latency
Integrated Azure TTS for multi-speaker audio, enhancing engagement by 50%

HP Power Lab 2.0

Implemented IMO EEOI tracking achieving 12.5% reduction in CO emissions (1,200 MT to 1,050 MT)
Reduced fleet scheduling from manual 2-3 days to automated solution in under 5 minutes

Alkimi Blockchain Hackathon

Reduced manual administrative overhead by 95% through automated claim process
Optimized on-chain traceability with Event Emission logic, providing 100% transparent logs

Experience

Infotact Solutions

Internship Duration

Full Stack Developer Intern

Developed secure JWT authentication along with real-time cart and order-tracking features, increasing overall user engagement by 40%.
Built a scalable Razorpay-ready payment layer for 500+ users and reduced payment setup effort by 60%.
Engineered scalable RESTful APIs and analytics dashboards, reducing query response times by 45%.

Projects

All
Web-App
Project

Alibaba RFQ Scraper

Python Web Scraper

Accelerated market intelligence gathering by developing a multi-page scraper that efficiently processes up to 20 pages of RFQ results, yielding detailed data on over 72 unique B2B sourcing requests from UAE buyers.

Kleid

Kleid E-Commerce Platform

Full Stack Web Application

Implemented JWT-based authentication with 2 user roles, engineered RESTful API with 10+ endpoints, and integrated Razorpay payment & Cloudinary for asset management.