Engineering Design Projects

The student design experience begins with freshmen team design projects, are continued throughout the curriculum, and culminate in a two-semester interdisciplinary design project as seniors.

For information about sponsoring or partnering with our students on a design project, please submit the form on this page or contact the Dean’s office at 423-425-2256.


Students present their research and design work annually at the Technology Symposium. Below are examples of recent student projects:


Undergraduate Research 

Concentration: Chemical Engineering

Student name(s): Armel Boutchuen, James Jur, Dell Zimmerman

Faculty Advisor(s): Soubantika Palchoudhury  

Title: Synthesis and characterization of poly(hydroxyethyl methacrylate) hydrogels for drug delivery applications    

Abstract: Nanoscale drugs offer immense potential as  next-generation pharmaceuticals, although applicability is limited by the lack of a reliable, nontoxic method of targeted delivery. As a demonstrated macroscopic drug dispersal technology, biocompatible poly(hydroxyethylmethacrylate) (PHEMA) hydrogels may provide a novel, economical approach to reliably administer nanoscale drugs. This study uses a multipronged approach to evaluate the short-term swelling behavior and decay of PHEMA hydrogels in aqueous environments. A side objective is to assess the feasibility of synthesizing PHEMA hydrogel with embedded iron oxide nanoparticles.

Concentration: Computer Science and Engineering  

Student name(s): Roche Sean  

Faculty Advisor(s): Mengjun Xie    

Title: Differential Privacy 

Abstract: Differential privacy seeks to enable the use and analysis of the datasets that contain sensitive personal information while simultaneously protecting privacy of individual entries in those datasets. Differential privacy protects individuals' privacy by adding random noise to each true answer, producing a new dataset of the original true answers with added statistical noise. In this study, we aim to apply differential privacy to better protect privacy in healthcare data sharing while keeping necessary utility of the data in healthcare research and analytics.

Concentration: Computer Science and Engineering   

Student name(s): Childers Tegan, Firat Connor, Patel Yatri   

Faculty Advisor(s): Mina Sartipi 

Title: Public Transport Optimization 

Abstract: Bus routes that adequately serve citizens are crucial for proper urban mobility. We are trying to optimize the current public transport system in order to increase ridership and accessibility. Using simulation tools to simulate different scenarios we are able to get various data about the number of passengers waiting and the time each bus is waiting at each stop. Overlaying household income, total population, unemployment, and walkability reveals neighborhoods under-served by the current public transit bus routes. Using that we are able to simulate new routes and calculate the effect to those neighboring areas.

Concentration: Electrical Engineering 

Student name(s): Diego Amaro, Berkay Dean    

Faculty Advisor(s): Daniel Loveless, Mary Loveless, Louie Elliot, Don Reising  

Title: A CubeSat Reaction Wheel-Based Attitude Control System 

Abstract: Cube Satellites (CubeSats) are small satellites that can be customized to perform a variety of missions in the space environment. Reorientation and stabilization are critical to mission success. This work illustrates a reaction wheel-based attitude control system. Reaction wheels utilize the conservation of angular momentum to reorient the CubeSat. One wheel is needed for each axis.

Concentration: Mechanical Engineering    

Student name(s): Drumm, Jefferson Tuna, Sertac

Faculty Advisor(s): Erkan Kaplanoglu 

Title: Biped Robot 

Abstract: In this project, the 6 DOF biped robot was controlled by bio signals. The robot has been adapted for remote control via a bluetooth MYO armband which uses electromyography (EMG) signals from the upper forearm to communicate motion to the robot.

Concentration: Mechanical Engineering  

Student name(s): Christopher Broadhurst, Miguel Mariscal, Eduardo Loredo Paez, Morgan Young 

Faculty Advisor(s): Kidambi Sreenivas     

Title: Gas Turbine Engine for a Supersonic Business Jet    

Abstract: To design a new engine for a supersonic business jet. The improvements most paramount are low weight, low take-off noise, reduction of emissions, and improve efficiency. Allowing for more affordable fares.

Graduate Research

Concentration: Chemical Engineering 

Student name(s): Boutchuen Armel, Ghasemi Amirehsan, Dey Preyanka, Oguoma Chimmezirim, Shamakoora Swetha    Abdollah 

Faculty Advisor(s): (Abi) Arabshahi, Soubantika Palchoudhury*    

Title: Understanding the transport of nanoparticles for biomedical and environmental applications    

Abstract: This project will investigate a unique experimental and computational approach to predict the flow of nanoscale particles under various flow conditions. We will also mimick practical environmental and biological conditions relevant to environmental fate and transport study and drug delivery for reliable predictions of nanoscale flow.

Concentration: Civil Engineering    

Student name(s): Kelvin Joseph Msechu   

Faculty Advisor(s): Mbakisya Onyango

Title: Sensitivity Analysis of PMED to Climatic Inputs and Water Table Depth    

Abstract: The transition of pavement design from the use of AASHTO 1993 to the Mechanistic-Empirical approach of design has brought about a variety of concerns and research on the Mechanistic-Empirical design method. The Mechanistic-Empirical Pavement design approach is faced with a high requirement of inputs for its implementation such as traffic data, material and climatic inputs. Furthermore, the inputs requirements for the Mechanistic-Empirical pavement design are divided into a three-level hierarchy where level 1 represents site observed data, level 2 representing inputs generated from models also known as regional values and level 3 are the defaults values or national values. With all these input information, several attempts have been done in studying the sensitivity of Mechanistic-Empirical method considering various conditions. One method that has to be considered for the sensitivity analysis of the Mechanistic Pavement design is the use of 2k Factorial design method, an unbiased method that studies the behaviour of each factor that affects the performance or the outcome of a process while giving equal considerations for each of the factors and their interactions. This study performed a sensitivity analysis on the climatic data inputs and ground water table depth in the prediction of pavement distresses (Terminal IRI, Permanent deformation of total pavement, permanent deformation of Asphalt only, Thermal cracking, Top-down cracking and Bottom-up cracking). The climatic inputs considered are Temperature, Wind speed, Percent sunshine and Relative humidity. Precipitation inputs were not considered in this study due to the insensitivity of the Mechanistic software AASHTOWare Pavement design to its input.

Concentration: Computational Science    

Student name(s): Hao-Bo Guo    

Faculty Advisor(s): Hong Qin    

Title: Association vs connection: Understanding gene sets, diseases and aging from network permutations 

Abstract: The genetic information are registered in physical interactions among gene products that are collectively termed the interactome. Here, we present a method to extract genetic knowledge of gene or gene sets from interactome using network permutations.

Concentration: Computational Science    

Student name(s): Ruipeng Zhang

Faculty Advisor(s): Mengjun Xie

Title: A Scalable Remote Live Forensics Framework for Android    

Abstract: Due to the high mobility of the smartphone and transience of these attacks, traditional physical and logical forensic approaches are becoming inadequate to the task of collecting criminal artifacts and incident response in time. We present a data extraction tool for large-scale remote live forensics of Android smartphones. It can report a wide range of user-generated data remotely from an Android device. Our evaluation shows that it has a low performance and energy overhead while preserving the data integrity. We also discuss the effectiveness of our tool for data extraction and offer advises on large-scale deployment.

Concentration: Computer Science and Engineering    

Student name(s): Mehran Ghafari

Faculty Advisor(s): Hong Qin

Title: Complementary Performances of Convolutional and CapsuleNeural Networks on Classifying Microfluidics Images of Dividing Yeast Cells    

Abstract: Microfluidic-based assays have become effective high-throughput approaches toexamining replicative aging of budding yeast cells. Deep learning may offer an efficientway to analyze a large number of images collected from microfluidic experiments. Here,we compare three deep learning architectures to classify microfluidic time-lapsed imagesof dividing yeast cells into categories that represent different stages in the yeastreplicative aging process. We found that convolutional neural networks outperformedcapsule networks in terms of accuracy, precision, and recall. The capsule networks hadthe most robust performance at detecting one specific category of cell images. Anensemble of three best-fitted single-architecture models achieves the highest overallaccuracy, precision, and recall due to complementary performances. In addition,extending classification classes and augmentation of the training dataset can improvethe predictions of the biological categories in our study. This work lays a usefulframework for sophisticated deep-learning processing of microfluidics-based assays ofyeast replicative aging.

Concentration: Electrical Engineering    

Student name(s): Cancelleri

Faculty Advisor(s): Daniel Loveless    

Title: Detecting and Identifying Single Event Transients using IRES and Machine Learning    

Abstract: This research aims to use machine learning and deep learning techniques to characterize events in Ionizing Radiation Effects Spectroscopy (IRES) images to identify the exact location of a SET within an electronic device.

Concentration: Engineering Management    

Student name(s): Adam Needham    

Faculty Advisor(s): Wolday Abrha, Seong Dae Kim, Alexandr M. Sokolov    

Title: The Development of a Systems Control Guide for Aligning Technology Projects to Stakeholders and Strategy    

Abstract: Projects should create value, but can be a source of much waste as organizations create tendencies to prioritize individual project successes ahead of measuring how far those successes propel strategy and satisfy stakeholders. In this study, literature is reviewed on various methods to obtain project alignment with stakeholders and strategy. A set of attributes are proposed which have the greatest impact on obtaining stakeholder and strategic alignment. Using these attributes, guidelines are then developed to help achieve the alignment. The aim is to bridge the gap between projects to strategy and projects to stakeholders.