About
Bhavya Sri Gilakala is a 4th-year Bachelor of Engineering student specializing in Artificial Intelligence & Machine Learning at Acharya Institute of Technology. With a strong academic record (CGPA 8.83), Bhavya has developed several AI-powered projects, including a women's wellness and safety platform, an EOG-based assistive communication system, and an intelligent grievance redressal system. Bhavya possesses technical skills in Python, Java, web technologies, databases, and various AI/ML frameworks.
Education
Projects
Project Aura - AI-Powered Women's Wellness & Safety Platform
Built a full-stack wellness and safety platform using React, Tailwind CSS, Node.js/Express, Python FastAPI, and MongoDB Atlas. Developed SOS/Safety, Diet Planner, Health Analytics, and Symptom Checker modules. Integrated Google Gemini API for AI-driven features and implemented JWT/Google OAuth. Resolved backend issues including MongoDB Atlas SRV connectivity and URI-encoding errors.
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STAR: Spectro-Temporal Adaptive Recognition using Hybrid Deep Learning
Developing an EOG-based assistive communication system for ALS patients using deep learning and embedded systems. Utilized ESP32, ADS1115, signal processing, and 1D-CNN models for eye-movement classification. Completed Phase I: hardware assembly, signal acquisition, and proof-of-concept validation.
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Civitas: Intelligent Grievance Redressal and Monitoring System
Developed an AI-powered grievance dashboard using NLP for complaint categorization and analysis. Implemented complaint clustering, summarization, severity detection, and regional hotspot visualization. Built using Python, Machine Learning, and interactive dashboard technologies.
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Assignment Submission Tracker
Developed a DBMS-based web application for assignment management and tracking. Enabled teachers to upload assignments and students to submit, monitor deadlines, and track progress. Built using PHP and MySQL.
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Voice-Controlled Car with Smoke & Gas Detector using GSM Module
Designed and developed an Arduino-based vehicle controlled through voice commands. Integrated smoke and gas sensors with GSM-based alert notifications for real-time safety monitoring. Demonstrates IoT, automation, and embedded systems concepts.
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