Akindele O

Vision Attendance System

Uxtad hub

Apr 2023 - Jan 2026 • 2 yrs 9 mos

ole: Computer Vision Engineer | AI Developer Industry: Education Technology (EdTech) / Enterprise Automation Designed and developed a facial recognition–based attendance system to automate and digitize attendance tracking using deep learning and computer vision technologies. Key Contributions & Achievements: Built and trained a deep learning facial recognition model for accurate identity verification Implemented real-time face detection and recognition using computer vision algorithms Developed an automated attendance logging system integrated with a secure database Achieved high recognition accuracy under varying lighting and environmental conditions Reduced manual attendance processing time by over 70% Integrated anti-spoofing mechanisms to prevent fraudulent check-ins Designed a user-friendly admin dashboard for attendance monitoring and reporting Ensured data privacy and secure storage of biometric information Optimized system performance for scalability across multiple classrooms or office locations Technologies Used: Python, OpenCV, TensorFlow / PyTorch, Face Recognition Libraries, SQL Database, REST APIs, Cloud Deployment

AI-Powered Chatbot System

Xt Coder

May 2021 - May 2023 • 2 yrs

Role: AI Developer | NLP Engineer Developed and deployed an intelligent AI-powered chatbot using Natural Language Processing (NLP) to automate customer service operations and significantly enhance user engagement. Key Contributions & Achievements: Designed and trained NLP models to understand user intent and context with high accuracy Integrated Machine Learning algorithms for continuous improvement through user interactions Built conversational flows for handling FAQs, customer complaints, order tracking, and service inquiries Integrated the chatbot with web platforms and messaging channels (e.g., WhatsApp, website live chat) Implemented sentiment analysis to detect customer emotions and escalate complex cases to human agents Reduced customer response time by 60% Increased customer satisfaction and engagement rates Optimized backend APIs for seamless database interaction and real-time responses Deployed solution on cloud infrastructure ensuring scalability and high availability Technologies Used: Python, TensorFlow / PyTorch, NLP Libraries (NLTK / spaCy), REST APIs, Cloud Deployment