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
Description: It’s a data science website for sharing information and preventing tribal knowledge lost to the brain drain.
Description: The face recognition attendance system aims to develop a robust and efficient Python-based tool that automates the process of taking attendance into more efficient and effective as compared to before. My research aims to address the limitations of traditional unimodal attendance systems by introducing a novel approach that combines the strengths of multiple modalities. By capitalizing on these modalities’ distinct features and leveraging deep learning techniques, the proposed system strives to enhance both accuracy and security, offering a more adaptable and dependable solution for attendance management.
Description: Using machine learning to predict future water scarcity vulnerability of local populations in Washington state.
Description: Advertising to the target audience has been a goal of most companies. With the ability to gather data and preferences while using consumer data, organizations have been able to direct their advertising to the audience they intended. Using data collected, companies learn about their customers and potential customers to implement new strategies and technologies while making the organization more profitable, more efficient, and operationally stronger. Being able to apply this technology in the medical field could be a massive change in how diseases are diagnosed and treated.
Description: This project uses advanced NLP techniques and transformer models like BERT to understand public sentiment on social media. By analyzing posts, comments, and reviews, we’ll gain insights into emotions and opinions. The goal is to create a powerful tool for businesses to make informed decisions, researchers to study public trends, and marketers to adapt strategies effectively in the digital world.
Description: Under the mechanism of parking payment machines, people in the United States unconsciously spend too much time on parking payments. Although this process may seem brief, in busy downtown areas and large parking lots, the accumulated waiting time for each individual can lead to significant time wastage. Therefore, developing a user-friendly parking payment system is a crucial issue. To address this, this paper proposes an intelligent parking payment system called “PayEasy” based on a deep convolutional neural network model for license plate recognition and facial recognition. The system aims to provide users with the most streamlined parking payment process, enabling a “park and go” experience with no need for manual payment.
Description: The project leverages artificial intelligence and fusion models to offer personalized news suggestions. After logging in, users can explore datasets, visualize data distributions, and receive personalized news recommendations based on user-news interactions. Utilizing resources such as the MIND dataset from Microsoft and real-time news scraped from Reuters, the system integrates the LDA topic model and a neural
Description: The process of gathering and distributing information to various medical facilities and doctors is tedious and time consuming due to different facilities having different systems and waiting for access and release from the patient. With creating a central database, patients and medical professionals will be able to access the records without having to wait for releases or if they still need to wait for a release, an archive of medical history of the patient is available immediately.
Description: A new approach to motivate different kinds of runners. A chatbot using Amazon Lex and Amazon Kendra to provide personalized, motivating messages to runners.
Description: This research explores the ethical concerns surrounding facial expression recognition systems, particularly in light of recent findings that challenge the reliability and specificity of facial expressions as accurate indicators of emotion. By building on these revelations, this study proposes a subjective, user-centered approach for the application of emotion AI, aiming to promote mental well-being while mitigating risks. The focus lies on ensuring that emotion AI implementations not only adhere to scientific rigor but also champion ethical considerations in their design and application.
Description: The problem statement is picking a good movie to watch is hard especially when we have 1000s of movies. My goal with this project is to recommend movies based on similarities using Machine Learning.
Description: This project has developed a turn-based strategy game using the Unity engine, combining natural language models and Roguelike elements for enhanced gameplay.
Description: The front-end development for my internship companies web and marketing team.
Description: Restroom finder app that will provide access to nearby available restroom with crowd-sourced important details at the touch of user’s fingertips. It will include review and rating system, geolocation and location-based search, social login, push notifications, photo and video uploading, user accounts, and analytics.
Description: Looking at American’s negligence of cyber security best practices in their ever day lives. This will cover what is causing this problem, currently proposed solutions and their effectiveness, as well as new solutions to this issue.
|4:30 PM – 4:35 PM|
Greeting & Announcement
Advisor: Dr. Sam Chung
Chair: Anahita Raeiszadeh
Teams link: Main
|4:35 PM – 4:55 PM|
Presenter 1: Tyray Fortune
Topic: Front-end development for my internship companies web and marketing team
Chair: Asia Shvets
Teams link: Session 01
Presentation: 15 Minutes
Q&A: 5 minutes
|4:55 PM – 5:15 PM|
Presenter 2: Thaddeus Thomas
Topic: Ruby on Rails DS Website
|5:15 PM – 5:35 PM|
Presenter 3: Yinghui Liu
Topic: Intelligent Parking Payment System: PayEasy