Armour R&D gives undergraduate engineering students at Illinois Tech opportunities for hands-on work and direct experience with the research and development process.
As an Armour R&D participant, you’ll receive a stipend to work with a faculty member, gaining valuable research and development experience and professional mentorship.
With a range of projects, including researching water desalination methods, detecting Alzheimer’s disease using MRI, and developing open-source GPS, Armour R&D offers opportunities both for students interested in discovering fundamental science and students who want to develop and implement technology that is based on research findings.
This year-round program offers you the chance to work on projects that tackle real-world problems while gaining skills that are highly valued in the engineering profession.
Participants selected for this competitive program conduct their project over the course of 10 weeks during the semester and showcase their work at the Armour R&D Expo.
Students may select a project proposed by a faculty member or develop a proposal for a project in conjunction with a faculty member.
The application for the summer 2025 semester is currently open and will be closed at 5 p.m. CST on April 25. The summer 2025 Armour R&D program runs from June 6 to July 25, 2025.
Students involved in the summer 2025 semester can expect to participate in the Armour R&D Expo.
For more information, contact engineering@iit.edu
Temporal Stimulation of Cells Using Microfluidics
Faculty: Abhinav Bhushan (BME)
Description: The goal of this project is to investigate how temporal stimulation of cells affects cell function and fate.
Microfluidic Devices for Patterning Cells
Faculty: Abhinav Bhushan (BME)
Description: The goal of this project is to pattern cells in specific locations within a microfluidic device.
Effects of Microgravity on Cell Function
Faculty: Abhinav Bhushan (BME)
Description: The goal of this project is to determine how microgravity affects function of different types of cells. We will analyze datasets from collaborators and generate hypothesis that can be verified through experiments.
Application of Embedded Systems and Microcontrollers in Buildings
Faculty: Mohammad Heidarinejad (CAEE)
Description: This project will focus on leveraging recent developments in low-cost sensors and microcontrollers to develop and deploy smart building sensing and controls solutions, especially for our steam systems (i.e., low-cost steam traps and radiator valve controls solutions). Students with a background in coding (e.g., in C/C++, Rust for embedded systems and microcontrollers, Python), prototyping (e.g., assembly and fabrication using 3D printers), or building test circuits on breadboards (e.g., design to a printed circuit board) will work together with the current undergraduate and graduate students.
Building Systems Semantic Models
Faculty: Mohammad Heidarinejad (CAEE)
Description: This project will focus on developing building systems semantic models that integrate best practices in computer science, such as knowledge representation, reasoning, machine learning techniques, with other engineering models (electrical, mechanical, architectural). Knowledge of working with object-oriented programming languages (e.g., Python/Java), understanding of semantic web technologies (e.g., XML, RDF, SHACL, SPARQL), or familiarity with building mechanical systems and tools (i.e., Revit, AutoCAD) would be beneficial.
Modeling and Deployment of Analog Circuits
Faculty: Mohammad Heidarinejad (CAEE)
Description: The student will utilize different filters (e.g., Elliptical, Butterworth, RC, and RF) using LTSpice or similar tools, as simulator, schematic capture and waveform viewer. Then, the waveform creation will occur in software tools (e.g., EasyWaveX) and the files will be uploaded into an oscilloscope. Basics understanding skills in Python or similar to help with data analysis would be beneficial. The application will be focused on heating systems in buildings.
Drone-Powered Disaster Relief: Ensuring Critical Supplies Reach Flood-Affected Communities
Faculty: Mohammad Miralinaghi (CAEE)
Description: During floods, delivering essential supplies like food, water, and medicine becomes extremely difficult, especially in areas where roads are blocked or completely underwater. This project explores the use of drones, mobile charging stations, and mini-depots placed on boats to create a flexible and efficient disaster relief system. By using real-time flood data and predictive analytics, we can ensure faster, more reliable deliveries to communities in need, even when traditional infrastructure fails.
Pandemic-Resistant Ride-Hailing: A Safer Mobility Solution for Public Transit Users
Faculty: Mohammad Miralinaghi (CAEE)
Description: Public transit ridership has struggled to recover after the COVID-19 pandemic due to concerns about infection risks in shared spaces like buses and trains. This project explores the potential of a pandemic-resistant ride-hailing platform (PRP)—a mobility service designed with enhanced safety features such as disinfected seating, better ventilation, and real-time travel recommendations to help reduce exposure. By integrating PRP with public transit and offering fare subsidies for high-risk travel segments, we aim to restore confidence in public transportation while ensuring safer, more accessible mobility options during future pandemics.
Smart Freight and Transit Integration: Reducing Congestion and Enhancing Urban Mobility
Faculty: Mohammad Miralinaghi (CAEE)
Description: With the rise of online shopping, cities are seeing an increase in delivery vehicles clogging streets, while public transit systems struggle with fluctuating ridership and financial strain. This project explores a solution by integrating freight deliveries with public transit vehicles, utilizing off-peak hours to transport goods efficiently. By optimizing transit infrastructure for shared use, we can reduce congestion, lower emissions, and generate additional revenue for transit agencies, ultimately making urban transportation more sustainable and efficient.
Mining Local Outdoor Air Quality Data in Â鶹APP
Faculty: Brent Stephens (CAEE)
Description: Low-cost sensors have enabled widespread monitoring of ambient air quality at high temporal and spatial resolution. Networks of sensors exist around Â鶹APP and all over the world. This project aims to mine these databases to better understand local air quality conditions in and around Â鶹APP.
Fluorescence Guided Surgery in Head and Neck Cancer Treatment
Faculty: Kenneth Tichauer (BME)
Description: Our lab has a partnership with a head and neck cancer surgical oncology clinic and builds fluorescent imaging devices to help the surgeons better identify cancer from healthy tissue to improve surgical outcomes. Anyone interested should apply. We can take up to 3 students.
In Vivo Analysis of Proangiogenic Nanoparticle Ointment Emulsions on Neovascularization of Diabetic Cutaneous Wounds
Faculty: Georgia Papavasiliou (BME) and Settimio Pacelli (BME)
Description: This project will focus on evaluating the effectiveness of topically applied proangiogenic nanoparticle ointment emulsions on promoting stable blood vessel formation in excisional cutaneous wounds of diabetic mice- critical for successful diabetic wound healing. Harvested sections of excised murine diabetic wounds following a 28-day wound healing study will be analyzed using immunohistochemistry, confocal imaging and statistical analyses to evaluate the efficacy the topical ointments in stimulating mature vessel formation.
Unsteady Wind Tunnel Flow Characterization
Faculty: Douglas Carter (MMAE)
Description: In this project the student will perform particle image velocimetry (PIV) in the Andrew Fejer unsteady wind tunnel. The measured velocity fields will be used to determine how the flow changes as a function of the wind tunnel louvre positions. Both steady (motionless louvres) and unsteady (moving louvres) configurations will be explored.
Controlled Flow Environment: Turbulence Box Facility Design
Faculty: Douglas Carter (MMAE)
Description: The study of vehicles, particles, or droplets and their response to turbulence requires an environment that can be precisely controlled. The most successfully built facilities of this kind use panels of pressurized air jets that are directed facing each other and turned on and off in such a way as to produce turbulence with controlled intensity. In this project, the student will work with a team to design the largest turbulence box facility ever built tailored specifically to foster state-of-the-art 3D particle tracking velocimetry in the boxes' central region.
