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Venkata Anith Pavan Kumar Aluru

Computer Vision Engineer • a**************@gmail.com • +91*******207 • drivetube.ai/•••••

Professional Summary

Computer Vision Engineer with 4 months of experience building computer-vision models and integrating ML into production web applications; skilled in Python, TensorFlow/Keras, OpenCV and Flask for real-time inference and full-stack ML deployments.

Technical Skills

Programming Languages: Python,Java,JavaScript,TypeScript
Web Technologies: HTML,CSS
Frameworks and Libraries: Flask,Node.js,Express,React,React Native,Bootstrap,TensorFlow,Keras,PyTorch,OpenCV,DeepFace,Pandas
Databases: SQL,MongoDB,PostgreSQL
Cloud and DevOps: Docker,Jupyter,Render
Tools and Methodologies: Git,GitHub,VS Code
AI and ML Techniques: Deep Learning,Computer Vision,Convolutional Neural Networks,Image Classification,Face Recognition,Model Evaluation
APIs & Web: RESTful APIs,Frontend Development,Real-time Inference Integration

Work Experience

Blend Vidya EdTech
Bengaluru
Full Stack Developer Intern
Nov 2025 – Feb 2026
EdTech company in Bengaluru; contributed to production web applications and ML-enabled features used for internal tooling and employee tracking.
Tech Stack: Flask, Node.js, JavaScript, HTML, CSS, TensorFlow, Keras, OpenCV, DeepFace, MongoDB, PostgreSQL, Render, Git
  • Designed and implemented RESTful backend APIs with Flask to handle authentication, data flow, and application logic for internal EdTech tools; integrated APIs with frontend and MongoDB/PostgreSQL stores using JSON contracts.
  • Developed and deployed a full-stack employee self-tracking system (live at pleacements.cloud) using Flask backend and JavaScript/HTML/CSS frontend; managed end-to-end deployment on Render for production access.
  • Integrated ML models into web workflows to support automated tasks and predictions, implementing TensorFlow/Keras-based inference pipelines and OpenCV preprocessing for image inputs in the application.
  • Built real-time face-detection and recognition endpoints for attendance-style workflows by incorporating DeepFace/OpenCV; designed inference routes to accept camera frames and return identity/timestamp payloads.
  • Implemented frontend features and UX flows using vanilla JavaScript, HTML and CSS to consume REST endpoints and display model outputs; validated end-to-end behavior across browser clients.
  • Collaborated with product and QA contributors to triage defects, document API contracts, and deliver production-ready features with versioned deployments and Git-based source control.

Projects

AI Image Identification System
Tools Used: Python, Flask, TensorFlow, Keras, OpenCV, HTML, CSS, JavaScript
  • Trained convolutional neural networks to classify livestock (buffalo vs cattle) and multiple fruit types using labeled datasets and TensorFlow/Keras; performed data augmentation and preprocessing with OpenCV.
  • Packaged trained models into a Flask web application that performs real-time predictions from uploaded images and displays results in a responsive HTML/CSS/JS UI.
AI Face Detection for College Attendance
Tools Used: Python, OpenCV, DeepFace, Flask, Pandas
  • Built a real-time face recognition attendance system that auto-detects faces from live camera feeds, recognizes identities using DeepFace, and logs timestamped attendance records in a structured CSV/DB.
  • Handled variations in lighting and pose by combining OpenCV preprocessing with DeepFace embeddings and designed the Flask backend to serve recognition endpoints for the frontend camera client.
Crop Calendar Awareness System
Tools Used: Python, Flask, HTML, CSS, JavaScript, Bootstrap, Pandas
  • Built a Flask REST API backend with a dynamic frontend that filters crop recommendations by location and season, enabling region-specific agricultural planning.
  • Designed a responsive UI with Bootstrap and used Pandas for data processing to allow farmers to explore suitable crops for their region and season.

Education

Audisankara College of Engineering & Technology
Bachelor of Technology in Artificial Intelligence & Data Science • 2023 – 2027

Achievements

  • Open-source contributions to UNICEF Bebbo, JdeRobot, ML4SCI (Stingray), OpenAstronomy: Authored Windows environment setup guide for Android builds (UNICEF Bebbo PR #1045), contributed simulation and notebooks to JdeRobot and ML4SCI, and prepared GSoC proposals for OpenAstronomy.
  • Class Representative, Dept. of AI & Data Science, Audisankara College — Nov 2026 – Present: Elected class representative coordinating academic and departmental activities.
  • Participant, ICCVIP-26 (International Conference on Computer Vision & Image Processing) — May 2026: Attended technical sessions on computer vision, image processing, deep learning; research paper presented on automatic detection of temple & gopuram carvings using deep learning.
  • Presenter, RTIH Startup Idea Presentation — Jan 2026: Presented a startup idea at RTIH event focused on technology-driven solutions.
  • Participant, Cloud Computing workshop by APSSDC — Feb 2026: Completed a six-day hands-on workshop covering cloud fundamentals and services.

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