RËHÅÑ ÑÂYÉÈM

About

B.Tech graduate in Artificial Intelligence & Machine Learning with hands-on experience in machine learning, deep learning, computer vision, and agentic multi-agent AI. Built and deployed classification, object-detection, and multi-agent systems using Python, TensorFlow, LangChain/LangGraph, and YOLO.

Experience

• AI/ML Intern
  Infosys
  Oct 2024 – Feb 2025

Education

• B.Tech in Artificial Intelligence & Machine Learning
  Sri Indu College of Engineering & Technology
  Artificial Intelligence & Machine Learning · Mar 2023 – Jul 2026

Skills

• SQL
• C
• FastAPI
• Python
• Classification
• Feature Engineering
• NumPy
• Pandas
• scikit-learn
• OpenCV
• React
• Flask
• PyTorch
• TensorFlow
• TypeScript
• Keras
• LangChain
• WebSockets
• Yolo
• RAG
• Multi-Agent Systems
• LLMs
• LangGraph
• Data Structures and Algorithms
• Hyperparameter Tuning
• CatBoost
• Advanced DBMS

Projects

• Obesity Level Prediction
  Python

  Built an ML model to predict obesity levels from lifestyle and physical-condition attributes, covering data preprocessing, feature engineering, and model evaluation.

• Multi-Agent AI System
  Python, LangChain, OpenRouter

  Built a Research → Analysis → Coding agent pipeline with multi-LLM access via OpenRouter and a pytest-based test suite.

• Steel Surface Defect Detection
  Python, CatBoost

  Built a CatBoost binary classifier over 49 parameters with 10-fold stratified cross-validation and top-N thresholding, reaching an 84.47% leaderboard score.

• Automatic Number Plate Recognition
  Python, YOLO, OpenCV

  Built an end-to-end YOLO + OCR pipeline for real-time vehicle plate detection and recognition across varied lighting conditions.

Courses & certifications

• AI/ML Certification · Infosys Springboard · 2025

🏆 Achievements & awards

• Top 40 nationwide — Tata Steel AI Hackathon · 2026

  Selected among the top 40 teams nationwide and presented the architecture in the final-round interview.