2018-19 Proposed Research Projects

Biomedical Engineering

Optimizing hemodynamics of engineered blood vessels by creating an endothelial cell lining
Blood vessel hemodynamics regulate blood pressure and blood flow. Abnormal hemodynamics results in disease. Using a cell perfusion system, flow will be used to seed endothelial cells into Dr. Mai Lam Lab's engineered blood vessels in order to establish normal hemodynamics as seen in a native human artery.
Faculty Advisor: Mai Lam

Developing a Fluorescent Imaging System to Image Amyloid Beta Proteins on the Retina for Early Detection of Alzheimer's
Alzheimer's is the most common form of dementia, affecting more than 5 million people in the United States. During the progression of Alzheimer's, a particular protein begins to accumulate in the brain and also in the extension of the brain, i.e., the retina. This protein, amyloid beta (Aβ), exhibits fluorescent properties. The purpose of this research is to explore the implications of designing a fluorescent imaging system to detect Amyloid-beta proteins and understand how a fluorescent imaging system could be developed with the intention to detect Alzheimer's disease in a clinical setting.
Faculty Advisor: Mohammad Avanaki

Towards ultrahigh resting-state functional connectivity in the mouse brain using photoacoustic microscopy
The increasing use of mouse models for human brain disease studies, coupled with the fact that existing high-resolution functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. In this project, an optical resolution photoacoustic microscopy (OR-PAM) with diode laser is developed. Images from this imaging system can then be used to study brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy.
Faculty Advisor: Mohammad Avanaki

Polypyrolle-Hyaluronic Acid scaffold for nerve regeneration
We will develop methods to combine polypyrolle with HA to develop a biocompatible material that can stimulate neural cells. Cells will be cultured on these materials and stimulated to evaluate cell behavior following electrical stimulation.
Faculty Advisor: Harini Sundararaghavan

Drug Delivery in Nerve Regeneration
We will develop materials to control growth factor release and sequestration in hyaluronic acid based scaffolds. Cell behavior on these materials will be evaluated.
Faculty Advisor: Harini Sundararaghavan

Chemical Engineering

Cyberattack Impacts on Irrigation, Food Processing, and Water Purification Control Systems
Cybersecurity of control systems for chemical processes is a significant concern, as many chemical processes can be brought to hazardous conditions by attacks that could kill or injure plant workers or residents living nearby the plants. Other controlled processes, such as controlled irrigation systems, food processing systems, or water purification systems, could be impacted by cyberattacks that impact their production or their products. In the proposed research, students will focus on exploring the characteristics of cyberattacks that could be performed on irrigation, food processing, and water purification control systems and developing models of attack scenarios in simulation studies.
Faculty Advisor: Helen Durand

Quantum Computing, Chemical Process Control Systems, and Cyberattacks
This project is an exploratory study on the implications of quantum computing for chemical process control and for cybersecurity of process control systems. Students will perform literature searches on quantum computing and its impacts on cybersecurity and propose ways that quantum computing could change process control design or be integrated with it, and what effects the success of quantum computing could have on current industrial control system cybersecurity.
Faculty Advisor: Helen Durand

OpenFOAM Simulation of Chemical Process Units for Profit Function Assessment
Computational fluid dynamics simulations can provide reasonably accurate data on how a process will behave if modeling assumptions are correct. In this study, we will explore how OpenFOAM can be utilized to develop models of the transport fields in several chemical process units with different configurations. We will use the results to make recommendations regarding how profit should be assessed (i.e., how a function representing profit can be developed) given how equipment configurations and chemistries impact transport fields.
Faculty Advisor: Helen Durand

Cybersecurity Risks of Image Data for Chemical Process Control
A potential idea for helping to locate hazards at a chemical plant is to utilize image, speech, and text processing as sensing elements that are not traditionally available at chemical plants for automating the plant response to hazards. A question that arises in this context is how this new data being utilized may pose additional cybersecurity concerns if cyber attackers obtain it. Students will investigate this question by generating images in the open source computer animation software Blender in which no leaks and leaks in a pipe are considered. They will subsequently explore the development of machine learning algorithms that allow the result of whether there is a leak or not to be correctly classified for the control system for the chemical process but difficult for a cyber attacker to falsify.
Faculty Advisor: Helen Durand

Developing, Testing, and Validating a Collagen-based 3D Cell Culture System
This project aims at improving a pre-exiting three-dimensional cell culture system that aims to model the foreign body response around an implanted neuroprosthetic. The student will be involved in literature searches, lab meetings, wet bench work, and data analysis.
Faculty Advisor: Carolyn Harris

From Trap Grease to Advanced Biofuel
In the U.S., over 1.8 billion kg/year of lipids could be recovered from grease trap waste, and can be converted to advanced biofuel to alleviate the dependence of fossil fuels. Novel catalysts and catalytic process will be developed to enhance the efficiency and cost-effectiveness of the process.
Faculty Advisors: Simon Ng and Steve Salley

CO2 electrochemical reduction using solid oxide electrolysis cells
Development of fabrication techniques for solid-oxide electrolysis cells (SOECs) for efficiency electrochemical reduction of carbon-dioxide. This includes optimization of methods to ensure synthesis of uniform, thin electrolyte layers, optimization of the electrode scaffold structure to maximizing triple-phase boundary area at the electrodes.
Faculty Advisor: Eranda Nikolla

Development of optimal catalysts for Li-air batteries
Lithium-oxygen batteries are a promising new technology, with theoretical energy output comparable to that of gasoline. One of the major challenges in making this technology practical is associated with the high over potential losses at the cathode. The objective is to gain mechanistic insight on how the incorporation of catalysts can improve the efficiency of these batteries.
Faculty Advisor: Eranda Nikolla

Multicomponent Materials for Cascade Reaction Networks
Development of synthetic approached for the cascade, multicomponent catalytic systems proposed in our parent project goals, the undergraduate researchers will employ a surfactant-guided, sol-gel synthesis approach. The student will vary the synthesis conditions to synthesize metal nanoparticles encapsulated by various porous oxide shells. These catalytic systems will be characterized using XRD, N2-physisorption, TEM with EDS, ICP. The catalytic activity and stability will be tested for hydrodeoxygenation of biomass derived alcohols.
Faculty Advisor: Eranda Nikolla

Civil and Environmental Engineering

Development of Sorption Technology for Extracting Rare Earth Elements from Coal Fly Ash
Rare earth elements (REEs) are a group of important metals that are used in many high tech applications such as electronics and high power magnets. Due to environmental challenges with mining and other geopolitical factors, China now controls >95% of the global supply, leaving the US economy and military potentially vulnerable to supply disruptions. Coal fly ash, the waste product left behind after coal is burned for power generation, has been identified as a potential domestic source of REEs. The goal of this project is to develop a 3-step process to: (1) dissolve fly ash to solubilize the REEs, (2) concentrate the dissolved REEs using advanced sorption materials developed at WSU, and (3) back-extract the sorbed metals to provide an industrial feedstock enriched in REEs. Student Responsibilities: Conduct site visits to collect fly ash from Detroit power plants, help with fly ash characterization and literature review, and conduct benchtop batch and flow-through column experiments.
Faculty Advisor: Tim Dittrich

Evaluating the Effectiveness of Bioswales for Treating WSU Parking Lot Runoff
Bioswales are shallow vegetated channels constructed to collect runoff from rain and snowmelt draining from paved surfaces. Bioswales are designed to reduce peak runoff rates while providing a place to concentrate and/or remove suspended material (e.g., silt, dirt) and pollution (e.g., automotive fluids) through mechanisms such as physical deposition, chemical sorption, and biogeochemical transformation. Better understanding and quantification of these mechanisms will enable design optimization to ensure economical, predictable, and reliable treatment of runoff from urban areas such as metro Detroit. Student Responsibilities: Collecting water and soil samples from bioswales on campus, analyzing samples for contaminants, and interpreting results to quantify bioswale effectiveness.
Faculty Advisor: Tim Dittrich

Engineering Solutions for Sustainable Urban Agriculture in Detroit
A sustainable urban farm requires many different skills and techniques to be successful including soil preparation, irrigation, planting schedules, plant maintenance, harvest planning, marketing, sales, and financial bookkeeping. One challenge of small urban farms in Detroit is to use technology to automate routine farm tasks to free up time to focus on growing the business. The goals of this project will be to: (1) work with the Detroit Biodiversity Network to design an automated irrigation system for the greenhouse on the top floor of Science Hall, (2) design a rain collection system for the greenhouse, and (3) design an integrated rain collection/soil sensor/irrigation system for the greenhouse and an outdoor garden on campus (the Warrior Garden).
Faculty Advisor: Tim Dittrich

Benchmarking Energy Efficiency and Emission Optimization of City of Detroit Municipal Buildings
Existing methods and guidelines can be used to create a dynamic database and model of the building energy consumption and emission generation characteristics of the City of Detroit building fleet. Equipped with this knowledge, the City can develop plans for more sustainable operation of the fleet. Student responsibilities: Work with a team on energy audits and marginal emission calculations associated with the City of Detroit owned building portfolio. Enter data into Energy Star and Portfolio Manager data bases.
Faculty Advisor: Carol Miller

Innovative Technologies for Rapid Beach Health Determination
Response time associated with beach pathogen testing can be significantly enhanced through adoption of next-gen biological and genetic approaches. Student responsibilities: Supervise experiments at two of the WSU Healthy Urban Waters field stations: Belle Isle and Lake St. Clair Metropark. Work with qPCR in the laboratory at those stations and collect field samples from the beach and connecting waterways.
Faculty Advisor: Carol Miller

Microplastics and Microbeads in Great Lakes
Microplastics and associated byproducts negatively impact the drinking water quality of the 10 Million consumers served by this Great Lakes water resource. Student responsibilities: Supervise experiments at the Water Works Drinking Water Treatment Plant, operated by the Great Lakes Water Authority (GLWA).
Faculty Advisor: Carol Miller

Computer Science

Identifying cell types using single cell data
In this project, we develop a method to discover the cell types using single cell gene expression data. The result of this analysis has great impact on identifying important, rare cells that play crucial roles in disease progress, and uncovering novel mechanisms of cell development and diseases.
Faculty Advisor: Sorin Draghici

Recreating Ancient Landscapes with Virtual Reality
The student will use Virtual Reality and Computer Game technologies to help recreate Paleo-Indian settlements that existed in Michigan over 10,000 years ago. This is part of a National Science Foundation project to bring ancient civilizations to life with modern technology. The current prototype focuses on a submerged land bridge that connects what is now Michigan to what is now Canada, the Alpen-Amberley. The Land Bridge was above water for over 2000 years and was the site of various Paleo-Indian hunting activities.
Faculty Advisor: Sorin Draghici

Modeling the Impact of Climate Change on the Local Fishing Economy in Cerro Azul, Peru
Cerro Azul is an import site on the coast of Peru. The area has been occupied by Fishing communities for an extensive period of time. It is also the subject of a Beach Boys song, Surfing Safari. In this study local offshore fishing trips were documented on a daily basis for over 2 and one half years, producing over 6000 records. Overlapping with this period was an El NIno, a warming of coastal waters due to shifting currents. It has been proposed that El Ninos have become more frequent recently as a result of climate change. The object of the study is to use techniques from Artificial Intelligence such as Data Mining and Machine learning to model how the decision of local fisherman are impacted by this climate change.
Faculty Advisor: Robert Reynolds

Data Processing Platform for Autonomous Driving
In this project, you will be working with a team of Ph.D. students developing an open data analytics platform for autonomous driving. More information can be found at our CAR lab. http://thecarlab.org.
Faculty Advisor: Weisong Shi

Event Detection using Multiple Cameras on the Edge
In this project, you will be working with a couple of senior Ph.D. students developing abnormal event using the data from multiple cameras at the scene. The data you will have access was collected in a real social event that has more than 80 cameras. I expect a research paper eventually will come out from this project.
Faculty Advisor: Weisong Shi

3D Deep Learning and Computer Graphics
This project focuses on developing novel algorithms on deep learning for 3D shapes and images, such as shape segmentation, object detection, cancer detection, etc.
Faculty Advisor: Zichun Zhong

3D/4D Medical Image Registration and Reconstruction
This project focuses on developing novel algorithms on real-time 3D and 4D medical imaging (e.g., CT, MRI, etc.) registration and reconstruction by using GPU-based parallel computations. The project is collaborating with School of Medicine and Karmanos Cancer Institute.
Faculty Advisor: Zichun Zhong

3D Graphical and Geometric Modeling
This project focuses on developing novel algorithms on 3D and 4D object modeling and the methods will be applied for shape and scene representations and reconstructions.
Faculty Advisor: Zichun Zhong

Electrical and Computer Engineering

Synthesis of Novel Two-dimensional Nanomaterials for Electronics, Sensors and Biological Applications
The objective of this project is to synthesize new 2D materials using chemical vapor deposition and to characterize these materials using SEM AFM and Raman. The students will have hands-on-experience in developing new materials and applications in electronics and biosensors.
Faculty Advisor: Mark Cheng

Electrochemical Sensors Using Nanomaterials
Dr. Cheng's lab is developing robust neural implants for brain machine interface, where he is adapting new nanoelectrodes to measuring biological samples. The student will have an opportunity to work in a multidisciplinary research environment and have access to the state-of-the-art facility for micro/nanofabrication and materials characterization.
Faculty Advisor: Mark Cheng

2D Materials for Sensors and Device Applications
2D nanomaterials (such as graphene and transition metal dichalcogenides) have recently been found many interesting properties, including optical transparency, mechanical flexibility, biocompatibility, high electronic mobility and nonlinear radio-frequency modulation. The project provides a unique opportunity for undergraduate students to participate in exciting research that includes material synthesis, modeling of electronics devices, and experimental implementation.
Faculty Advisor: Mark Cheng

Engineering Technology

New Paradigm for Robust Infrastructure Scalability for Autonomous Applications
The project purposes a new paradigm for the environment, pre/post data processing, integration, and system security for robust systems in mobility. The systems integration is based on a novel FPGA embedded system design and computing (EDGE) platform utilizing image processing.
Faculty Advisor: Ching-Ming (Jimmy) Chen

Industrial and Manufacturing Engineering

An Investigative Study into the Most Appropriate Location-Allocation Techniques for Manufacturing Facilities
Strategic facility location-allocation decisions involve many factors that may be conflicting in nature and can pose a difficult selection problem (Masood 1999). Various researchers have adopted several techniques in the selection of the most optimum location for a manufacturing plant. Some of the methods include AHP, multi-objective goal-programming, multi objective optimizations and other algorithms. Choosing the best location and assigning the right customers minimizes the overall cost of production (Dileep, 2008). This project intends to conduct a comprehensive review of the various location-allocation techniques used for manufacturing facilities and consider their effectiveness.
Faculty Advisor: Celestine Aguwa

Collaborative disassembly automation to access critical materials supply source for advanced technology manufacturing
The objective of this project is to advance product disassembly systems within the context of remanufacturing, maintenance, recycling, reuse, and disposal feedback cycles for critical materials supply and a circular economy. This project will characterize contact and non-contact interferences that control disassembly and execute hands-on disassembly experiments of end-of-use products, manually and with collaborative automation, to evaluate and develop disassembly operation guidelines.
Faculty Advisor: Jeremy Rickli

Mechanical Engineering

2D materials based bio-sensor
The objective of this project is to develop rapid methods for the detection of waterborne and foodborne pathogenic bacteria using novel nanomaterials based electrochemical sensor.
Faculty Advisor: Leela Arava

Banana Shaped Ionic Liquid Crystals as Electrolytes for Lithium Batteries
Ionic liquid crystals as electrolytes with their temperature dependent anisotropic property can help to suppress dendrite formation which results in longer battery life. This project will be focusing on the synthesis and characterization of banana shaped ionic liquid crystals and their application in lithium based batteries.
Faculty Advisor: Leela Arava

Additive Manufacturing of Nickel-Based Super alloys for Gas Turbine Applications
Ni-based super alloys are currently the materials of choice for the hottest and most severely stressed parts in gas turbines and aero engines. The objective of this research is to investigate the feasibility of Laser Additive Manufacturing of WSU 100 alloy for gas turbine application.
Faculty Advisor: Guru Dinda

Additive Manufacturing of Liquid Rocket Engine Components
Recent advances in laser technology and CAD/CAM have led to the development of modern manufacturing processes based on additive principles. The objective of this research is to design and development of multi-material rocket engine nozzle via laser additive manufacturing.
Faculty Advisor: Guru Dinda

ADAS Improvement for Unavoidable Collisions
ADAS (Advanced Driver-Assistance Systems) is the leading technology in accident avoidance for autonomous driving. However, there are some situations in which a collision is unavoidable. The objective for this project is to use information from YOLO object classifier/detector software with dynamics equations to build simulation models to improve ADAS performance in unavoidable collisions. The improvement of ADAS in these situations would minimize vehicle occupant injuries and could potentially save lives.
Faculty Advisor: Chin-An Tan