Teaching Assistant
Dhruvit Parmar is a Teaching Assistant in the Department of Computer Science and Engineering at the School of Engineering and Technology, Navrachana University. He completed his Bachelor of Technology (B.Tech.) in Computer Science and Engineering from Navrachana University in 2026.
Prior to joining the university, he completed a Machine Learning Engineer Internship at Next Embedded & Software Technologies Pvt. Ltd., Vadodara, where he contributed to the development of an AI-powered intelligent surveillance system integrating computer vision, machine learning, face recognition, anomaly detection, and real-time monitoring technologies.
His academic and professional interests include Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Artificial Intelligence of Things (AIoT), Software Engineering, Intelligent Systems, and Full-Stack Application Development. He is passionate about designing intelligent, scalable, and data-driven solutions that bridge academic concepts with real-world engineering challenges.
As a Teaching Assistant, he believes in creating an interactive learning environment where students are encouraged to think critically, explore concepts beyond the classroom, and develop practical problem-solving skills through hands-on learning and real-world applications.
• Bachelor of Technology (B.Tech.) – Computer Science & Engineering Navrachana University, Vadodara (2022–2026)
• Machine Learning Engineer Intern Next Embedded & Software Technologies Pvt. Ltd., Vadodara Duration: 6 Months
Areas of Teaching Interest
· Artificial Intelligence
· Machine Learning
· Deep Learning
· Natural Language Processing
· Computer Vision
· Artificial Intelligence of Things (AIoT)
· Python Programming
· Object-Oriented Programming
· Database Management Systems
· Digital Logic Design
Dhruvit believes that effective teaching extends beyond explaining concepts—it involves inspiring curiosity, encouraging analytical thinking, and helping students connect theory with practical implementation. His approach focuses on building strong conceptual foundations through interactive discussions, hands-on projects, and real-world problem-solving, enabling students to become confident and independent learners.
Programming Languages
· Python
· JavaScript
· Dart
· HTML
· CSS
AI & Intelligent Computing
· Artificial Intelligence
· Machine Learning
· Deep Learning
· Computer Vision
· Natural Language Processing
· AIoT
· Data Analytics
Software Development
· Flutter
· Flask
· FastAPI
· REST APIs
· Firebase
· Git
· Android Studio
Tools & Frameworks
· OpenCV
· YOLOv8
· InsightFace
· ArcFace
· MQTT
· ESP32
· Arduino
· Artificial Intelligence & Intelligent Systems
· Machine Learning & Deep Learning
· Computer Vision & Image Processing
· Natural Language Processing
· AIoT & Smart Automation
· Full-Stack Application Development
· Intelligent Surveillance Systems
· Data Analytics & Predictive Modeling
RESEARCH & ACADEMIC INTERESTS
· Artificial Intelligence
· Machine Learning
· Deep Learning
· Computer Vision
· Natural Language Processing
· AIoT
· Smart Cities & Intelligent Monitoring Systems
· Explainable AI
· Data Analytics
NEXUS — AI-Powered Intelligent Surveillance System
Designed and developed an intelligent surveillance platform capable of real-time object detection, multi-object tracking, face recognition, anomaly detection, and threat monitoring. The system integrates computer vision and machine learning techniques with a web-based dashboard for centralized monitoring, automated alert generation, and intelligent decision support.
Technology Stack: Python, OpenCV, YOLOv8, InsightFace, ArcFace, Flask, HTML, CSS, JavaScript
AIoT-Based Smart Air Quality Monitoring & AQI Prediction System
Designed and developed an AIoT-enabled smart environmental monitoring platform for real-time air quality assessment and intelligent pollution analysis. The system integrates multiple environmental sensors to continuously monitor air pollutants and atmospheric parameters, predicts the Air Quality Index (AQI) using machine learning models, detects abnormal environmental conditions, and provides automated ventilation control with instant notifications. A cloud-connected architecture enables real-time data visualization, remote monitoring, and historical analytics through interactive mobile and web dashboards.
Technology Stack: ESP32, Arduino, Python, Flask/FastAPI, Firebase, MQTT, Flutter, Machine Learning, Data Analytics, AIoT, REST APIs, Git
AttendAI — Smart Attendance & Workforce Management System
Developed a comprehensive attendance and workforce management platform featuring employee attendance tracking, leave management, task assignment, role-based access control, real-time communication, and administrative analytics. The system was designed to streamline organizational workflows while providing an intuitive user experience across mobile and web platforms.
Technology Stack: Flutter, Python, Firebase, REST APIs
Society Management System
Developed a mobile application for digital society management, incorporating resident communication, complaint management, visitor tracking, maintenance management, and event coordination to simplify day-to-day residential operations.
Technology Stack: Android Studio, Java, Firebase
