The Penn State Harrisburg School of Science, Engineering, and Technology Capstone Design Conference was held April 25, 2025. The conference was the culmination of students’ undergraduate studies and provided the opportunity to combine classroom learning with real-life applications and collaborate with industry sponsors.
MIDDLETOWN, Pa. — Outstanding student projects were recognized during the Penn State Harrisburg School of Science, Engineering, and Technology Capstone Design Conference held April 25. The conference was the culmination of students’ undergraduate studies and provided the opportunity to combine classroom learning with real-life applications and collaborate with industry sponsors.
Judges selected winners from several program categories: civil, construction and environmental engineering; computer science; electrical engineering/electrical engineering technology; and mechanical engineering/mechanical engineering technology; as well as awarding the James A. Andrews Award for Excellence in Capstone Design. A Student Choice Award was also given.
Outstanding student projects were recognized during the Penn State Harrisburg School of Science, Engineering, and Technology Capstone Design Conference held April 25.
Awards were given to outstanding group projects based on the criteria of overall appearance and quality of display; overall professional appearance of presenters; effectiveness of display, support materials and experimental set-ups; project summary by the team or individual; interaction with visitors; and innovation. Each program had its own judges.
View photos from the 2025 Capstone Design Conference.
The James A. Andrews Memorial Award for Excellence in Capstone Design recognizes and encourages students who best demonstrate interest, motivation and ability in identifying and solving an engineering problem that addresses a real-world concern. This sponsored award of $1,000 is intended to honor students who couple creative approaches with practical ability to successfully resolve a situation.
The award was established by the family of James "Jim" Andrews, who was an alumnus of Penn State and worked as a senior field support engineer for Rockwell Automation in York, Pennsylvania, in admiration of Andrews’ flexible, "can-do" spirit. The award is presented annually. The winner of this award was chosen from among the first-place winners in each category.
The winners were:
First place, Civil, Construction, and Environmental Engineering (two teams)
- Project: "Commercial Revitalization: Steps to a Sustainable Future"
- Team Members: Zachary Dellinger, Samantha Moore, Adam Russo, Nathanael Strohm, David Vreeland
- Project: "Rebuilding for Tomorrow: Sustainable Apartments from Repurposed Spaces"
- Team Members: Kira Kenny, Avery Price, Laura Saint Cyr, Emma Van Pelt, Allison Williams
- Advisers: Yen-Chih Chen, Shirley Clark, Shashi Marikunte
Project description: The teams repurposed an unused office building into a multi-use space, and added a new multi-use building and a public greenspace. The existing building will accommodate 32 affordable and market rate apartments and two restaurants with its own water treatment center, and the new building will have retail spaces and 18 apartments. Some sustainable features on site include solar panel car ports, pervious (permeable) pavement with a water collection system to feed the water treatment center which supplies to the existing building, a green roof, and public transportation system.
First place, Computer Science
- Project: "Hustle: A Secure Social Media App for Working Quick Jobs"
- Team Members: Daniel Marc Dsouza, John Nguyen, Hassan Sesay
- Adviser: Truong Tran
Project Description: Hustle is a mobile app that allows users to post and accept local or remote, one-and-done jobs. Improving upon existing job services, it aims to promote a community of productivity while acting as a social media platform. Hustle allows users to both work and hire, making it suitable for those who want to make money or advertise their skills to potential employers. The app utilizes artificial intelligence and machine learning to ensure information security, provide algorithmic feeds, and query relevant results to users.
First place, Electrical Engineering AND James A. Andrews Memorial Award for Excellence
- Project: "Universal Retro Controller Tester (URCT)"
- Team Member: Benjamin Westhafer
- Adviser: Mohammad-Reza Tofighi
Project Description: The Universal Retro Controller Tester (URCT) is a standalone device designed for efficiently testing controllers from nine retro gaming consoles of the 1980s and 1990s. It supports the Atari 2600, NES, SNES, Master System, Genesis, Saturn, Neo Geo, PC Engine, and TurboGrafx-16. Ideal for collectors, resellers, and repair enthusiasts, it ensures quick and accurate controller testing. The URCT utilizes digital logic circuitry, hardware multiplexing, and an Arduino Nano microcontroller to process input data. Test results are indicated through auditory tones, a controller-shaped LED array, and an LCD screen, providing clear feedback.
First place, Mechanical Engineering
- Project: "Spatially Confined Magnetic Nanoparticle Hyperthermia"
- Team Members: Christopher Geist, Jared Martin, Eric Williamson
- Adviser: Anilchandra Attaluri
Project Description: The team designed a device to control the position of opposing electromagnets to create a zone of destructive interference in the middle. Inside this zone is the only area where ferrous nanoparticles will be able to heat up from an alternating field induced over the area. This controlled zone of heat generation can potentially be used as a medical treatment for cancerous tumors. The heat can kill the cells inside the tumor itself or be used to assist in chemotherapy.
Student Choice Award
- Project: "Saur: Find What Matters, in Minutes"
- Team Members: Bhagawat Dulal, Narayan Dulal, Matta Harfy, Narayan Subedi
- Adviser: Bimal Ghimire
Project Description: Saur is an advanced AI-driven audio processing platform designed to transform audio into meaningful, structured data. It enables users to seamlessly transcribe recordings, filter specific words, identify speakers, search for keywords, and even enhance voice clarity in multi-speaker environments. This project leverages machine learning, cloud storage, and natural language processing (NLP) to provide fast, accurate, and secure audio transcription solutions for journalists, researchers, government agencies and general users.
