Research Projects

The following is a selection of past and current research projects on artificial intelligence at WSU. This list is not exhaustive but gives a sense of the range of AI research taking place across the WSU system.

AgAID: AI Institute for Transforming Workforce & Decision Support

AgAID is a multi-institutional research center established with funding from the National Science Foundation and the US Department of Agriculture. Led by WSU faculty member Ananth Kalyanaraman, the AgAID Institute’s mission is to build and foster partnerships between AI and Ag communities and create a transdisciplinary ecosystem for technology innovation and knowledge transfer. The institute will develop AI solutions to address some of agriculture’s biggest challenges, including labor shortages, water availability, and climate change.


VICEROY Northwest Institute for Cybersecurity Education and Research (CySER)

Funded by the Department of Defense (DoD), the VICEROY Northwest Institute for Cybersecurity Education and Research (CySER) was established to train the next generation of military and national defense-aligned civilian workforce in cybersecurity. CySER is a consortium of five institutions in the Northwest led by Washington State University (WSU). Research in AI and Machine Learning is one of the five topics of research focused on within CySER, along with cyber-physical systems, networks and information security, software security and quality assurance, and cyber education.

Contact: Assefaw Gebremedhin (

Using Artificial Intelligence to Monitor Soil Health in Nigeria

Soils have important direct and indirect impacts on agricultural productivity, water quality, and the global climate. Specifically, soil organic matter (SOM) provides a wide variety of physical, chemical, and biological services and is a critical support of agricultural productivity and global ecosystem health. WSU researchers Lynne Carpenter-Boggs and Cornelius Adewale (Farmwella) have been leveraging technology to develop algorithms to estimate SOM concentration in different classes of soils in Nigeria. This effort will culminate in development of a soil health monitoring and management tool that is usable by Nigerian farmers.

Contacts: Lynne Carpenter-Boggs (, Cornelius Adewale (

Artificial Intelligence Quotient (AIQ)

With funding from the Department of Defense, WSU faculty members Larry Holder and Diane Cook are working on the Artificial Intelligence Quotient (AIQ), a framework that evaluates an AI system’s open-world novelty through its performance on a diversity of tests. The AIQ score is derived as a weighted combination of individual test scores, where the weight is based on an empirically-derived test difficulty, and the test scores include different aspects of performance including accuracy, correctness, time, and requested amount of training data. The AIQ framework provides a way to quantitatively evaluate the general intelligence of an AI system and compare the intelligence of different AI systems.

Contacts: Larry Holder (, Diane Cook (

Determining the Impact of Emotive Intelligent Space on Children’s Self-Regulation and Cognitive Performance

This project, led by researchers from University of Idaho in partnership with WSU faculty members Mona Ghandi and Minyoung Cerruti, aims to address health and education gaps in children living in the Mountain West by testing the effectiveness of an innovative intervention mechanism, the Emotive Intelligent Space (EIS). The EIS harnesses the power of artificial intelligence to detect children’s emotions from physiological data in real-time and to translate physiological signals into environmental changes (i.e., adaptable colored lighting) that adequately respond to children’s emotions, resulting in improved self-regulation, physiological stress responses, and cognitive performance.

Contacts: Mona Ghandi (, Minyoung Cerruti (

A Novel Imitation Learning Framework for Self-Optimizing Systems

A key challenge for computing systems ranging from mobile platforms and large manycore chips to data centers is to trade-off power, performance, reliability, and quality of service under rapidly varying application workloads. Despite the growing hardware and software complexity of these systems, existing dynamic resource management (DRM) techniques to control different knobs such as power management, scheduling, and task mapping are limited. Recent advances in artificial intelligence (AI) and machine learning (ML) have the potential to enable groundbreaking DRM solutions that can pave the way to enable intelligent self-optimizing computing systems. Led by WSU faculty member Jana Doppa, this project will develop a novel imitation learning framework for dynamic resource management to enable self-optimizing systems.

Contact: Jana Doppa (

Development of an adaptive machine learning platform for automated detection and quantification of histological or pathological biomarkers in biomedical images

Identification of biomarkers and cellular targets following microscopy requires manual analysis of the images, which is time intensive, difficult for humans, and prone to errors. To address these problems, WSU researchers have developed a software tool, called “PIPSQUEAK” (Perineuronal net Intensity Program for the Standardization and Quantification of Extra cellular matrix Analysis Kit). With NIH funding, this project will develop machine learning (ML) capabilities for application with the PIPSQUEAK analysis platform through a collaboration between Rewire AI and researchers Allison Coffin and Barbara Sorg.

Contacts: Barbara Sorg (, Allison Coffin (, Rewire AI (

Machine learning of carbon fiber reinforced plastics machining processes for real-time monitoring and validation

Led by faculty members Dave Kim and Scott Wallace, this project will develop applied machine learning and big data (artificial intelligence) techniques to monitor, validate, and predict the conventional machining processes of carbon fiber reinforced plastics (CFRP) in the aircraft product/structure manufacturing environment.

Contacts: Dave Kim (, Scott Wallace (

Discovering the influence of culture on health-assistive smart home adoption by Asian immigrant older adults for infusion in artificial intelligence: Community-engaged research

Faculty member Connie Nguyen-Truong received a WSU Vancouver Mini-Grant to (1) explore Asian immigrant older adults’ knowledge and perceptions of smart home monitoring as they relate to culturally-specific expectations, and (2) define the influence of socially-constructed predictors and barriers to adopting smart home monitoring. The project’s long-term goal is to explore culturally safe and efficacious use of smart homes for health improvement in the Asian immigrant older adult population. Inclusion of diversity is critical to the future of smart home research and development of a culturally safe high AI health product.

Contact: Connie Nguyen-Truong (