The Social Contagions, Artificial Intelligence, and Democracy workshop brings together scholars to explore how social contagions can be used to understand how AI and related digital technologies may challenge or, potentially, fortify democratic institutions and practices.

The Biocomplexity Institute at the University of Virginia (UVA) showcased its work at the 2024 Virginia Academy of Science, Engineering, and Medicine (VASEM) Energy Summit, held October 28-29, 2024. The summit, which brought together leaders in energy research, policy, and education, provided a platform for UVA researchers to present cutting-edge developments in energy systems and artificial intelligence.

Research Associate Professor Bryan Lewis Featured at NASEM Workshop

According to the Centers for Disease Control and Prevention (CDC), more than 63,600 people died from opioid overdoses in the United States in 2016, and more than 70,000 people died from the same cause in 2017. The opioid epidemic in the United States is showing no signs of abating, but researchers from the Biocomplexity Institute have identified potential geographic opioid misuse and abuse hotspots in Virginia, West Virginia, and North Carolina using network scan statistics – a methodology that may ultimately be used to save lives through targeted interventions in high-risk areas.

Have you ever wondered what a career combining data science and public service looks like? This summer, 12 undergraduate and graduate students from across the country convened at the Biocomplexity Institute's Arlington, Va. location to find out first-hand.

While vaccination is the primary and most effective way to prevent sickness and death caused by flu, the CDC reports that less than 40 percent of Americans age 18 and older typically receive a flu shot. This begs the question: what additional mitigation and prevention methods might improve the public health response and policy development for the flu? 

The use of artificial intelligence (AI) is everywhere. From making diagnoses in the medical profession to determining sentencing in court cases, we are increasingly relying on AI and machine learning algorithms to make decisions that can have a profound impact on people’s lives. As the use of AI becomes even more prevalent, how do we know that the algorithms and models used to make these critical decisions are correct, unbiased, and reliable?