B.Tech Artificial Intelligence student at SVNIT Surat focused on building backend-driven AI systems, scalable APIs, and optimization-focused platforms.

I enjoy designing workflow-oriented architectures, integrating machine learning into production-style systems, and building applications that balance engineering reliability with real-world usability.

• Backend Engineering
• AI Systems
• Workflow Automation
• Recommendation Systems
• Optimization Algorithms
• Distributed Systems (learning)

AI-powered logistics optimization platform supporting multimodal routing with delay prediction, traffic analysis, and explainable route reasoning.

• Dynamic route ranking using weather, traffic, and delay-risk analysis
• CatBoost-based delay prediction model achieving 0.77 ROC-AUC
• Explainable AI reasoning pipeline using Gemini
• Real-time API integration for logistics optimization workflows

FastAPI Next.js CatBoost Gemini TomTom API

• Live: https://logi-flow-solution-challenge-2026.vercel.app/
• GitHub: https://github.com/kvb1201/LogiFlow-Solution-Challenge-2026

Built during a 24-hour hackathon, AirHelp is a multilingual AI airport assistant designed for passenger support, airport navigation, and contextual travel assistance.

• Designed semantic context engine for contextual query understanding
• Acted as system orchestrator for backend AI workflow integration
• Integrated Whisper speech-to-text with conversational AI backend
• Supported multilingual and voice-based passenger interaction workflows

FastAPI Whisper Gemma Next.js Multilingual AI

• GitHub: https://github.com/kvb1201/AirHelp-AI-Airport-Assistant

Secure backend-driven counseling session management platform with approval workflows and scheduling APIs.

• Role-based booking and counselor approval workflow
• REST API architecture for secure multi-user scheduling
• Normalized relational database schema for workflow extensibility

Django REST SQL

• GitHub: https://github.com/kvb1201/Mindsettler-Backend

Automated analytics and reporting system for telemetry and operational datasets.

• Structured telemetry data processing and summarization
• CLI-based automated reporting workflows
• Modular analytics generation utilities

Python Pandas Automation

• GitHub: https://github.com/kvb1201/gtrisp-vehicle-analytics

Crash log parsing and diagnostics system for structured debugging workflows.

• Automated extraction of structured diagnostic information
• Modular parser utilities for crash trace analysis
• Formatted debugging and reporting pipeline

Python Parsing Log Processing

• GitHub: https://github.com/kvb1201/gtrisp-crash-parser

• Building scalable backend systems
• AI workflow orchestration
• Optimization-driven architectures
• Production-oriented AI integrations
• System design and backend scalability

• LinkedIn: https://www.linkedin.com/in/kavya-bhatiya-a4864a263
• GitHub: https://github.com/kvb1201
• Email: kavyabhatiya44@gmail.com