Hi, I'm Dayna Dranitsaris.
A 3rd-year computer engineering student at Queen's University, with a degree focus in artificial intelligence.
About Me
Hello! I'm Dayna, a 3rd-year computer engineering student at Queen's University specializing in artificial intelligence. My tech journey began in grade 9, where my fascination with code and physical computing was fueled by competing in the Waterloo Centre for Education in Mathematics and Computing (CEMC) contests, including the Fermat (2022), Euclid (2023), and the Canadian Computing Competition (CCC) at both the Junior (2022) and Senior (2023) levels. This foundation seamlessly led to my involvement in a variety of web development and engineering projects in university.
I'm also an active member of the Queen's Engineering community, having joined the Queen's Racing Formula SAE Team and Queen's High Performance Computing, volunteering for The Queen's Engineering Society as an orientation leader, and serving as a Challenge Coordinator for the annual Queen's Engineering Competition and a Software Developer for ESSDev - Queen's Engineering Society.
Skills
Certifications
Projects
Queen's Hyperloop Design Team (QHDT) Machine Vision Sensor System
Designed and implemented an embedded system for a Hyperloop model to detect and classify custom-trained potential obstructions using YOLOv5.
NHL Goal Horn Machine
Built a Raspberry Pi system leveraging live NHL updates via API integration, with programmed LED sequences, audio playback, and an LCD showcasing team names and scores dynamically. Used Nmap, PuTTY, and RealTerm as well as the NHL API.
RFID Scanner System
Developed an embedded scanner system using a custom LCD to display real-time sensor data from an Arduino.
Human Activity Recognition
Preprocessed 100 Hz accelerometer data (Phyphox) with noise reduction and 5-s segmentation and engineered statistical features and trained logistic regression, achieving 94% accuracy (AUC = 0.98). Deployed model in a Tkinter app for real-time CSV classification and visualization.
Hydroponic Garden Monitoring System
Developed a sensor-integrated hydroponic garden for campus use, featuring real-time data monitoring of pH levels, temperature, and humidity (sent over WiFi, used Arduino) and a React Native app.
Charlene In The City
Built a professional real estate web application using IDX, HTML, CSS, and JavaScript. Monitored using Google Analytics.
Automated Powder/Fluid Dispenser
Built an automated powder/fluid dispenser using SolidWorks, an IR sensor, water pump, and an Arduino.
Course Grade & Productivity Application
Developed an academic performance tracking application in C++ leveraging Qt for UI and Firebase/Firestore for real-time data storage. Includes user authentication, multi-user data structures to manage friends lists, and dynamic data visualization for course statistics.