School of Technology and Computing
Applied Research Symposium
Fall 2021

Hosted by CityU’s Center for Cybersecurity Innovation and School of Technology and Computing (STC), the Applied Research Symposium is open to faculty, professionals, and students from any discipline, university, or professional organization.  At the end of each quarter, any students who would like to share their projects including capstone courses will present their outcomes. This symposium will provide opportunities for students, researchers, and practitioners to discuss the influence and impact of the applied computing on the future of our planet and our society

Event details

Date: Thursday, December 9th, 2021
Time: 4:30PM-5:30PM PDT


DR. Sam Chung
Dean, School of Technology & Computing
Dr. Ahreum Ju
Associate Faculty, School of Technology & Computing
DR. Sion Yoon
Associate Faculty, School of Technology & Computing

Curriculum Committee Submission Management Tool

Manual work increases the time complexity without providing the proper structure so that the data can live in one place and be accessed anytime conveniently. Currently, the university processes new and revised courses manually. A new application, “Curriculum Committee submission Management Tool,” will be built inside the PowerApps, where all the stakeholders will enter the data at the frontend web application. Later, it can be retrieved anytime from the data set “CC_Request” at SharePoint. It will also introduce a systematic and more organized way of handling data while maintaining the data integrity at the backend in SharePoint.

Hunardeep Kaur

Hunardeep Kaur - M.S. Computer Science

CS 687 MM - Computer Science Capstone

Preethi Balasubramaniam

Preethi Balasubramaniam - M.S. Computer Science

CS 687 MM - Computer Science Capstone

Traffic sign recognition Using Convolutional Neural Network

A system for recognizing traffic signs has indeed been developed to ensure autonomous vehicles in adhering to speed limits while also improving security and safety. The major purpose is to make it easier for autonomous driving cars to maintain their attention on the road and avoid accidents in everyday scenarios. Along with the advancement of deep learning, it is now feasible to utilize a deep learning model to detect and recognize traffic lights. In recent years, many high-accuracy computer vision and machine learning models have performed admirably on traffic sign recognition classification problems. However, these models have a restriction in that they can only identify huge objects and their detection speed is slower. This research focuses on using a convolutional neural network (CNN) to train the dataset to create a deep learning model to improve its recognition speed and accuracy. This model improves accuracy and works well during the object recognition process.

OneUI kitchen Remodeling Project (Web application)

OneUI kitchen remodeling website is going to provide the seamless experience to personalize their kitchen with many benefits for customers. And Through project mainly concentrate the developing the web application using serverless framework architecture and deployed an AWS cloud service.

Sravya Karnati

Sravya Karnati - M.S. Computer Science

CS 687 MM - Computer Science Capstone

Anil Erturk

Anil Erturk - M.S. Computer Science

CS 687 MM - Computer Science Capstone

Online Vaccine Scheduler

This project aims to help unvaccinated people socially distance by giving them the necessary tools. One of the things most unvaccinated people will do is get vaccinated. So, giving them the capability to remotely schedule/view/edit/cancel vaccine appointments will allow them to socially distance more.

Containerization for an Example Closed System

The current system is unnecessarily complicated due to the leftover requirements of legacy architecture. Containerization, through the use of tools such as Docker, can be used to reduce both the number of operating systems and the usage of system resources. Containerization has the additional benefit of making the system easier to install and maintain.
Adam Coffey

Adam Coffey - M.S. Computer Science

CS 687 : Computer Science Capstone


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