SCHOOL OF TECHNOLOGY AND COMPUTING

School of Technology and Computing
Applied Research Symposium
Spring 2025

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

Join Symposium

Event details

Date: Thursday, Jun 12th, 2025
Time: 4:30PM-5:30PM PT
Contact: lenghiemminhhieu@cityuniversity.edu

Advisors

DR. Sam Chung
Professor,
School of Technology & Computing
(CS687)
TJ Kim
Associate Faculty,
School of Technology & Computing
(CS687)
Ahreum Ju
Associate Faculty,
School of Technology & Computing
(CS687)
Ann robinson
Associate Faculty,
School of Technology & Computing
(CS497)
Session Chairs
Ana Karina Balcazar Sanabria
ClarkNgo
Clark Ngo
Namrata Vijay Mali
Honorine Ndom Ndzah
Megha Narendra Simha
Ashwin Shastry Paturi
Harrison Le
Presenters

Name: Thi Hong Anh Nguyen

AI-Powered Study Quiz Generator: Quizai

Course: CS687

Description: QuizAI is an intelligent quiz generation system that transforms user-provided documents into personalized assessments. By leveraging large language models and content retrieval techniques, the system supports the creation of multiple-choice and open-ended questions.

Xavier Backus

Name: Xavier Backus

Innovating Healthcare with Artificial Intelligence

Course: CS497

Description: The Daedalus Suite is an integrated AI framework comprising four specialized components that revolutionize hospital operations. Isis optimizes patient triage and staff assignment using machine learning classification and the Hungarian algorithm. Hygeia monitors healthcare worker wellness through wearable sensors and reinforcement learning to prevent burnout. Heka provides real-time patient vital sign monitoring with anomaly detection for early intervention. Eunomia forecasts resource allocation needs using predictive analytics. Together, these systems achieve 28% overall hospital efficiency improvement, 42% workload variance reduction, and 6.4-hour earlier detection of patient deterioration, demonstrating superior performance through integrated AI collaboration.

Shahid

Name: Shahid Jamshed Khan

Medical Triage AI Assistant - MediBuddyAI

Course: CS687

Description:  The increasing demand for medical assistance has exposed critical limitations in traditional triage systems, including inefficiency, delayed care, and the risk of misdirected or inequitable treatment. This project presents MediBuddyAI, an AI-powered triage assistant designed to address these challenges by leveraging advanced machine learning and large language models. MediBuddyAI aims to provide accurate, rapid and personalized triage recommendations that support clinicians and patients in remote healthcare settings.

Sangeethaa

Name: Sangeetha Bhukya

Fin Sense: AI-Powered Personal Finance Companion

Course: CS687

Description: Fin Sense is a web-based personal finance tracker that offers user-friendly dashboards and planning tools to assist users in managing their income, expenses, and budgets. It provides real-time financial advice through an intelligent chatbot and personalized financial insights driven by generative AI.

Name: Matthew Emerson

Minute-Level Electrical Load Forecasting in Los Angeles at the Substation Transformers

Course: CS497

Description: Exploring the use of 5 different models for high-frequency electrical load forecasting at the transmission transformer bank level in Los Angeles.

Kairatbek Davranbekov USCIS

Name: Kairatbek Davranbekov

AI-Powered Conversational Assistant for Predictive Job Quote Estimation: EstiMate.AI

Course: CS687

Description: EstiMate.AI is a web-based assistant that helps small home repair businesses provide instant, AI-generated job quotes from customer descriptions. Using Natural Language Processing and Machine Learning, the assistant extracts key job details, asks follow-up questions, and predicts costs—all through a simple chat interface.

Name: Jonathan Koerber

Sweetening Honeypots with Realistic Network Activity

Course: CS687

Description: This paper presents the design and implementation of a high interaction honeynet that emulates a Supervisory Control and Data Acquisition (SCADA) environment. The system attracts, observes, and analyzes unauthorized network activity targeting Industrial Control Systems (ICS). 

Inderdeep_Rathore

Name: Inderdeep Kaur Rathore

Cloud powered Deep Learning mechanism for analyzing Natural Disasters

Course: CS687

Description: Multimodal deep learning pipeline integrating satellite imagery and auxiliary geospatial data, enhanced with Explainable AI (XAI) for interpretability. Incorporates both vision-language transformers and spatio-temporal analysis to provide comprehensive and interpretable disaster insights in near real-time.

Eric Gainey

Name: Eric Tyler Gainey

Securing FHIR Integrations: Automating JWKS Endpoint Exposure in the Cloud

Course: CS687

Description: This project delivers a cloud-based solution to automate the publication of public keys required for secure FHIR API authentication. Using Azure Functions and Azure Key Vault, the system dynamically serves a JSON Web Key Set (JWKS) endpoint that identity providers can trust. By leveraging serverless architecture, managed identities, and cryptographic lifecycle management, the solution ensures regulatory compliance, simplifies key rotation, and enhances the security posture of healthcare applications using SMART on FHIR.

Cj4KMlNuYXBjaGF0LzEzLjM3LjAuNDYgKGlQaG9uZTE1LDQ7IGlPUyAxOC4zLjI7IGd6aXApEgbtzrGM6wEgAg==

Name: Anum Noor Samma

AI-Based Gluten Identification from Food Images: A Mobile App Solution

Course: CS497

Description: This project introduces a mobile app that uses artificial intelligence to detect gluten in food images, supporting individuals with Celiac disease or gluten sensitivity. By leveraging a Convolutional Neural Network trained on a reclassified Food-101 dataset, the app classifies foods as “contains gluten” or “gluten-free.” Built with React Native. It delivers real-time predictions and educational content, offering a practical, accessible tool when ingredient details are unknown in social or dining settings.

Tray McElroy

Name: Tray McElroy

Email Phishing Detection Tool Using Python and Machine Learning

Course: CS497

Description: The Email Phishing Detection Tool is a pioneering project that aims to utilize Python and machine learning algorithms in order to successfully identify phishing emails. Because of the increased susceptibility to phishing attacks, which lead people and companies into revealing sensitive details, traditional spam filters will not prove effective. This software will employ natural language processing (NLP) abilities to inspect the text data in email and mark them as “safe” or “probable phishing.” With the application of a hybrid mechanism consisting of text preprocessing, feature extraction, and supervised learning algorithm, the software will offer real-time classification output through a user-friendly graphical interface. The project can assist in heightening the awareness of email security and providing an affordable solution to individuals and small organizations under attack by phish.

Ana Line Benavente Montante

Name: Ana Line Benavente Montante

Web Development for a Fire Safety Company 

Course: CS497

Description: This project aims to develop a secure, user-friendly website that helps a fire extinguisher company transition to the digital space, enhancing its visibility and customer engagement. By combining effective web design with business strategy, the platform will showcase the company’s products and services while supporting its growth in the fire safety industry.

Alaz

Name: Alaz Kalelioglu

TaskFlow: AI-Driven Project Manager



Course: CS687

Description:  An AI-driven project Manager Application that automates project planning and sprint generation.

Screenshot

Name: Ali Fathi

Real Time Robotic Arm Simulation with Inverse Kinematics


Course: CS687

Description: This project uses machine learning to improve wildfire risk prediction in Washington State, enhancing disaster preparedness and response. This capstone project presents a lightweight, interactive robotic arm simulator that demonstrates inverse kinematics in real time. The system supports API driven task input, visual feedback using Matplotlib, and modular design for educational use.

Naveena Moddu

Name: Naveena Moddu

An AI-Powered Itinerary for Personalized Trip Planning

Course: CS687

Description:  Trip Planner AI is a React Native application that uses artificial intelligence to generate personalized travel itineraries based on user preferences such as destination, budget, travel dates. The app integrates Firebase for authentication, and AI models (e.g.,Ollama) to suggest tailored activities, accommodations, and travel tips. It aims to simplify trip planning through a user-friendly interface and intelligent recommendations, enhancing the travel experience with convenience and customization.

Fernando McKenzie

Name: Fernando McKenzie

Disinformation Decoded: A Cloud-Native Pipeline for Analyzing Troll-Driven Influence on Decision Making 

Course: CS497

Description: Infrastructure as code using AWS

Juan Carlos Isordia Betancourt

Name: Juan Carlos Isordia Betancourt

Interactive platform for cryptocurrencies (CryptoSapp)

Course: CS497

Description:  Current cryptocurrency platforms tend to be complicated for beginners. What I’m looking for with CryptoSapp is to attract new people to learn about cryptocurrencies. CryptoSapp is a platform that’s understandable for all audiences.

Schedule

Contact Us

lenghiemminhhieu@cityuniversity.edu