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STEM Summer Research

STEM Summer Research 2026 applications are now open.
Applications due March 6, 2026.

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Summer Research Advisors

Headshot of Kerry Breno

Kerry Breno, Associate Professor of Chemistry

Synthesizing, Characterizing and Calculating Our Way to Better Bioimaging: Functionalized Diimine Tricarbonylrhenium(I) Complexes
This research seeks to develop diimine rhenium(I) complexes for potential use as biomedical imaging probes. Our research will focus on synthesis and characterization of ligands and complexes as well as studying luminescence and factors that influence luminescence (solvent, pH, environment). We will use molecular modeling to explain observed behavior and to guide synthetic work.
 
Accepting one student.

Headshot of Alisha Epps

Alisha Epps, Associate Professor of Psychology

Effects of Gut Microbiota in Depression and Social Behaviors
Depression is a serious mental health concern, impacting quality of life through effects on daily function, social interaction and stress-related impairments. The proposed research will determine if gut microbiota differences between two unique rodent models of depression and resilience are responsible for their differences in depression-related behavior and social interactions. This study will involve both behavioral testing and tissue/fecal sample analysis.

Accepting two students.

Headshot of Scott Griffith

Scott Griffith, Associate Professor of Mathematics & Computer Science

Development and Maintenance of Ecological Test Systems
We will be working on maintaining, updating and troubleshooting an existing distributed embedded system to control ecological experiment systems. Some work will be in physical system setup. Some work will be configuration of current system.
 
Major attention will be given to web development.
 
Most work will be done at Gonzaga University.
 
Accepting one student. This will be an eight-week position.

Headshot of Qian Mao

Qian Mao, Assistant Professor of Mathematics & Computer Science

Look Into Flow Clusters: A Novel Approach of Network Traffic Classification
This research will propose and implement network traffic classification models using AI classifiers. We will focus on feature engineering and AI classifier design and improve the classification accuracy and robustness.
 
Accepting one student.

Headshot of Philip Measor

Philip Measor, Associate Professor of Engineering & Physics

A 3D Printed Biosensor Microdevice
Come be a part of the Microdevices Lab at Whitworth. The Microdevices Lab is continuing its work on technology to miniaturize functions performed in an entire lab on a single chip. This is normally done using semiconductor processes (that require a cleanroom and are very expensive), but our lab utilizes micro-3D printing instead to reduce the cost and speed of manufacturing. The past few years, we have shown we can make miniaturized PCR devices, microfluidic worm sorting devices and 3D printed waveguides (or pipes for light used in quantum computing schemes). This summer, we will be extending the work to explore how to make a 3D printed optofluidic biosensor combining both techniques (waveguides and microfluidics).
 
This project will support a student researcher with an engineering or physics background. Come chat with Associate Professor Measor or visit the webpage (microdevices.whitworth.edu) to learn more.
 
Accepting one student.

Headshot of Deanna Ojennus

Deanna Ojennus, Professor of Chemistry

Structure and Activity of Bacterial Peptidases for the Detoxification of Gluten
The Ojennus Lab is interested in the structure and activity of the Lb. helveticus peptidases PepX, PepN and PepO, which when combined may be used to detoxify food allergens such as gluten. Individual projects may include the investigation of a calcium-binding site in the PepX enzyme, PepO activity assays against various substrates, kinetic screens of enzymes containing site-directed mutations at the substrate binding site, crystallization of enzymes for X-ray diffraction structural studies, and development of an enzyme cocktail for the complete detoxification of gluten in food and beverages.
 
Accepting two students. Part-time volunteers will also be considered.

Headshot of Jenny Onley

Jenny Onley, Assistant Professor of Biology

Microbial Pathways for Detoxifying Potato Peel Glycoalkaloids
Potato peels are a promising renewable resource because they contain beneficial chemicals, but they also contain toxic compounds called glycoalkaloids. We will isolate and characterize microbes that can remove these toxins. Identifying the genetic pathways for glycoalkaloid metabolism will enable us to turn agricultural waste into a valuable resource. 
 
Accepting one student.

Headshot of Kamesh Sankaran

Kamesh Sankaran, Professor of Engineering & Physics

Plasma Acceleration in Pulsed Inductive Thrusters for Spacecraft Propulsion
Computationally predict the properties of plasma in a novel spacecraft propulsion system and compare the results with experimental measurements made at the University of Washington. This work involves applying physics, math and computer science to develop a new aerospace engineering technology.
 
Accepting one student.

Headshot of Diana Schepens

Diana Schepens, Associate Professor of Mathematics & Computer Science

Quantitative Modeling of Molecular Shape Recognition 
Collaborating with Professor of Chemistry Kraig Wheeler
This NSF-funded project is a collaborative effort involving the mathematics, computer science and chemistry disciplines to develop mathematical and chemical models for probing complex recognition profiles of small organic molecules. This summer, we will be fine tuning and finalizing the model and developing a molecule analyzing tool.
 
Applicants should have coding skills – Python is preferred.
 
Accepting one student.

Headshot of David Schipf

David Schipf, Assistant Professor of Engineering & Physics

Optical Neural Network Computing for Wireless Endoscopy Applications
This project will investigate a physics-based form of artificial intelligence (AI) that can classify images by guiding light through an optimized diffractive deep neural network (DDNN). DDNNs will be designed to detect polyps in endoscopy datasets for a wireless capsule endoscopy application. You will be using Python and PyTorch libraries and working with an existing code base developed by previous Whitworth summer research students.

Students from engineering, physics, chemistry, math and computer science are welcome to apply.
 
Accepting one student.

Headshot of Pete Tucker

Pete Tucker, Professor of Mathematics & Computer Science

Innovation Incubator Project Development
Come work on real technology projects for real clients and help kick-start Whitworth's Innovation Incubator. Accepted students will be building technology that supports local nonprofits or startup companies and working closely with those clients.
 
Accepting two students.

Headshot of Kraig Wheeler

Kraig Wheeler, Professor of Chemistry

Targeted Structural Diversity & Assessments in Quasiracemates 
Collaborating with Associate Professor of Mathematics & Chemistry Diana Schepens
This work explores families of materials that align predictably in molecular crystals using the property of molecular shape. Students involved with this project can expect to receive hands-on experience with experimental work involving organic synthesis, crystal growth and various structure determination methods, including X-ray crystallography.
 
This project seeks motivated and committed students, ideally those with previous coursework in organic chemistry.
 
Accepting four students.

Collaborative Projects

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Jonathan Dawson, Assistant Professor of Engineering & Physics

Headshot of John Larkin

John Larkin, Associate Professor of Engineering & Physics

Quantitative Image & Data Analysis Based Biophysical Modeling of Collective Electrotactic Migration of Isolated Cranial Neural Crest Cells During Tissue Regeneration
Cell motility, an important process during tissue regeneration, is a collective phenomenon involving many interacting cells. This project involves (i) developing deep learning-based image and statistical data analysis tools to quantify single cell motion in microscopy images, and (ii) developing quantitative image and data analysis based biophysical model to identify mechanisms controlling single cell motility and collective behavior.
 
Interested students should be curious to learn about a new area of science. Basic exposure to Matlab-based scientific computing and mathematical reasoning is preferred for one position and basic exposure to Python-based scientific computing is preferred for the other position.
 
Accepting two students.

Headshot of Kent Jones

Kent Jones, Professor of Mathematics & Computer Science

Headshot of Philip Measor

Philip Measor, Associate Professor of Engineering & Physics

A 3D Printed Microdevice for Detecting Pathogens 
This project is a collaboration between Professor Kent Jones and Associate Professor Philip Measor in the further investigation and optimization of a 3D printed (3DP) microfluidic pathogen detection system.

Accepting four students:

  • One biochemistry student to help refine our existing PCR system and further miniaturize the work.
  • One engineering/physics student to work on optimization of a thermal cycling system.
  • Two computer science students to work on pathogen detecting image processing AI and microfluidic channel fluid control systems.
Headshot of Diana Schepens

Diana Schepens, Associate Professor of Mathematics & Computer Science

Headshot of Pete Tucker

Pete Tucker, Professor Mathematics & Computer Science

Website Development of Molecular Shape Recognition Analysis Tool.
Collaborating with Professor of Chemistry Kraig Wheeler
This NSF-funded project is a collaborative effort involving the mathematics, computer science and chemistry disciplines to develop mathematical models for probing complex recognition profiles of small organic molecules. This summer, we will be developing a website tool incorporating the current Python algorithm for use in crystal analysis.  
 
Applicants should have strong coding skills and ability to work with Python. 
 
Accepting one student.