Artificial Intelligence and Machine Learning

Researching the models, methods, uses, and impact of intelligent systems design for processing data and information

Researchers Working in this Area

Related Research Projects

Advancing STEM Online Learning by Augmenting Accessibility with Interactive Companionship

Time frame
2021-2024
Investigator
Yun Huang
Total funding to date
$526,006.00
Funding agency
National Science Foundation

Full title: Collaborative Research: Advancing STEM Online Learning by Augmenting Accessibility with Interactive Companionship

Videos are a popular option for online learning, and captions are essential for accessibility. Two types of captions exist: typical closed captions and explanatory captions. Closed captions…

interactive companionship

AEOLIAN (Artificial Intelligence for Cultural Organizations)

Time frame
2021-2023
Investigator
Glen Layne-Worthey
Total funding to date
$49,820.00
Funding agency
National Endowment for the Humanities

Many digital archival collections are limited due to factors such as privacy concerns and copyright. AEOLIAN combines innovative AI methods and the knowledge of scholars from multiple cultural institutions to address the accessibility of these collections, ultimately making them more accessible. Additionally, the project aims to foster collaboration amongst scholars and practitioners from…

artificial intelligence

AI Institute Artificial Intelligence for Future Agricultural Resilience Management and Sustainability (AIFARMS)

Time frame
2020-2022
Investigator
Jingrui He
Total funding to date
$7,909.00
Funding agency
National Science Foundation

This project brings together researchers in AI and agriculture, combining their expertise to promote advances in agriculture through AI. AIFARMS mission is to use core AI research areas such as computer vision, machine learning, data science, soft object manipulation, and intuitive human-robot interaction to address major challenges in agriculture:

  • Sustainable intensification…
AI farms

Automated Indexing for Publication Types and Study Design

Time frame
2023-Present
Investigators
Neil Smalheiser, Jodi Schneider, Halil Kilicoglu
Total funding to date
$947,925.00
Funding agency
National Institutes of Health

This project aims improve upon a tool clinicians, researchers, and systematic reviewers use to retrieve biomedical articles from bibliographic databases. Associate Professors Halil Kilicoglu and Jodi Schneider will work with Affiliate Professor Neil Smalheiser, professor of psychiatry at the University of Illinois Chicago, on the project, which has received funding from the National Institutes…

doctor typing on a laptop

Collaborative Research: Accelerating Synthetic Biology Discovery & Exploration through Knowledge Integration

Time frame
2019-Present
Investigator
J. Stephen Downie
Total funding to date
$211,699.00
Funding agency
National Science Foundation

The scientific challenge for this project is to accelerate discovery and exploration of the synthetic biology design space. In particular, many parts used in synthetic biology come from or are initially tested in a simple bacteria, E. coli, but many potential applications in energy, agriculture, materials, and health require either different bacteria or higher level organisms (yeast for…

synthetic biology

Crowd-Assisted Human-AI Teaming with Explanations

Time frame
2024-Present
Investigator
Dong Wang
Total funding to date
$599,999.00
Funding agency
National Science Foundation

This project investigates the problem of information integrity, that is, identifying faulty or ungrounded information online. It focuses on a specific domain, that of information produced during the COVID-19 pandemic, and processes both text and image data. While significant efforts in artificial intelligence (AI) and machine learning (ML) have addressed information integrity in this type of…

crowd of people

DeepCrowd: A Crowd-assisted Deep Learning-based Disaster Scene Assessment System with Active Human-AI Interactions

Time frame
2021-2023
Investigator
Dong Wang
Total funding to date
$499,786.00
Funding agency
National Science Foundation

Full title: CHS: Small: DeepCrowd: A Crowd-assisted Deep Learning-based Disaster Scene Assessment System with Active Human-AI Interactions

This project addresses the application of AI to disaster scene assessment (DSA). AI currently has limited success with DSA; this project…

DeepCrowd

Harnessing Artificial Intelligence for Cartel Smuggling Study

Time frame
2019-2020
Investigator
Jingrui He
Total funding to date
$78,917.00
Funding agency
Arizona State University and the Department of Homeland Security

This joint effort with Arizona State University’s CAOE team aims to create a suite of effective and efficient AI tools for analyzing cartel smuggling activities, building upon the team’s expertise in machine learning, data mining, and visual analytics.

U.S. Coast Guard

Identifying False HPV-Vaccine Information and Modeling Its Impact on Risk Perceptions

Time frame
2020-Present
Investigator
Jessie Chin
Total funding to date
$389,810.00
Funding agency
National Institutes of Health

Human papillomavirus (HPV) is the most common sexually transmitted infection in the U.S., with over 34,000 new HPV-related cancers diagnosed annually, according to the Centers for Disease Control and Prevention. An HPV vaccine, which was approved by the Food and Drug Administration (FDA) in 2006, is recommended as part of routine vaccinations for school-aged children. However, the vaccine's…

network

Machine Learning Modeling for the Reactivity of Organic Contaminants in Engineered and Natural Environments

Time frame
2021-Present
Investigator
Dong Wang
Total funding to date
$150,001.00
Funding agency
National Science Foundation

With support from the Environmental Chemical Sciences Program of the NSF Division of Chemistry, the researchers will develop machine learning models to predict the reactivity of thousands of organic contaminants (OCs) in engineered (water) and natural (soil and sediment) environments. To assess and mitigate risks associated with this vast number of OCs, accurate predictive models are needed to…

topography map

Natural Language Processing to Assess and Improve Citation Integrity in Biomedical Publications

Time frame
2022-Present
Investigators
Halil Kilicoglu, Jodi Schneider
Total funding to date
$300,000.00
Funding agency
Office of Research Integrity, U.S. Department of Health and Human Services

This project will assist researchers and journals in evaluating citation behavior in biomedical publications. While citations play a fundamental role in the diffusion of scientific knowledge and assessment of research on a topic, they are often inaccurate (e.g., citation of nonexistent findings, inappropriate interpretation). This inaccuracy undermines the integrity of scientific literature…

journals spines

Proactive Community Health Protection Against Airborne Diseases through Intelligent and Timely Pathogen Monitoring and Communication

Time frame
2024-Present
Investigator
Dong Wang
Total funding to date
$150,000.00
Funding agency
National Science Foundation

Infectious airborne pathogens and their spread have caused increased incidences of outbreaks and pandemics, which challenge our society with severe impacts on public health, economies, and social well-being. Controlling airborne pathogens is challenging because they are transmitted easily via respiratory aerosols, spread quickly over large distances, and can mutate to become more infectious…

yellow dots representing pathogens

RareXplain: A Computational Framework for Explainable Rare Category Analysis

Time frame
2021-Present
Investigator
Jingrui He
Total funding to date
$500,000.00
Funding agency
National Science Foundation

This project will focus on real-world problems where underrepresented, rare (abnormal) examples play critical roles, such as defective silicon wafers resulting from a new semiconductor manufacturing process and rare but severe complications (e.g., kidney failure) among diabetes patients.

"This problem of explainable rare category analysis was motivated by my collaboration with IBM…

circuits

Smart Water Crowdsensing: Examining How Innovative Data Analytics and Citizen Science Can Ensure Safe Drinking Water in Rural Versus Suburban Communities

Time frame
2021-Present
Investigator
Dong Wang
Total funding to date
$1,031,655.00
Funding agency
National Science Foundation

Monitoring drinking water contamination is vitally important to inform consumers about water safety, identify source water problems, and facilitate discussion of public health and the environment of our drinking water. The overall goal of this project is to develop a framework for reliable and timely detection of drinking water contamination to build sustainable and connected communities. It…

glass being filled with water

Teach High School Students about Cybersecurity and AI Ethics via Empathy-Driven Hands-On Projects

Time frame
2021-2023
Investigators
Yang Wang, Yun Huang
Total funding to date
$154,754.00
Funding agency
National Science Foundation

Full title: Collaborative Research: Advancing STEM Online Learning by Augmenting Accessibility with Interactive Companionship

Videos are a popular option for online learning, and captions are essential for accessibility. Two types of captions exist: typical closed captions and explanatory captions. Closed captions…

empathy driven AI

Towards a Computational Framework for Disinformation Trinity: Heterogeneity, Generation, and Explanation

Time frame
2020-Present
Investigator
Jingrui He
Total funding to date
$319,568.00
Funding agency
Arizona State University

This project will study foreign influence via the lens of disinformation on news media from a computational perspective. The researchers will use Explainable Heterogeneous Adversarial Machine Learning (EXHALE) to address the limitations of current techniques in terms of comprehension, characterization, and explainability.

code on a computer screen

Towards a Wearable Alcohol Biosensor: Examining the Accuracy of BAC Estimates from New-Generation Transdermal Technology using Large-Scale Human Testing and Machine Learning Algorithms

Time frame
2021-Present
Investigator
Nigel Bosch
Total funding to date
$21,267.00
Funding agency
National Institutes of Health

This NIH-funded project focuses on machine learning approaches for translating transdermal alcohol content (i.e., alcohol measured from a person’s skin) into blood alcohol content (“BAC”). Modern transdermal sensors are small, easy to use, and measure transdermal alcohol content frequently, but lag behind typical measures of BAC (especially breathalyzers) in terms of accuracy. This project…

wine glass on a table

Weakly Supervised Graph Neural Networks

Time frame
2021-Present
Investigator
Jingrui He
Total funding to date
$149,921.00
Funding agency
National Science Foundation

Graph Neural Networks have proven to be a powerful tool for harnessing graph data, which is widely used for representing rich relational information in multiple areas. However, the performance of graph neural networks largely depends on the amount of labeled data, which is subject to an expensive and time-consuming annotation process. This creates data without labels, or a label scarcity.…

graph on a computer screen

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