About Us
At our lab, we’re a passionate team dedicated to creating impactful health technologies that empower individuals on their health journeys. Our mission goes beyond innovation; we’re committed to bridging digital health disparities and ensuring that technology fosters health equity, not inequality. Our approach combines human-centered design with advanced computational methods, making our work both accessible and impactful. By focusing on inclusivity and accessibility, we aim to transform healthcare and make a positive difference for all communities, especially those underserved in traditional healthcare systems. We leverage cutting-edge natural language processing (NLP) and large language models (LLMs) to build AI-driven tools that make health information more understandable and accessible. Our work emphasizes creating solutions that are technically robust and socially conscious, using techniques like deep learning and data science to develop tools that adapt to diverse health needs and empower users.
Explore how we’re redefining healthcare with empathy, innovation, and a commitment to making technology a tool for everyone.
Latest News
Google Society-Centered AI Research Award, Building a Framework and Toolkit for Effective Participatory AI Engagement in Hard-to-Reach Populations
Dr. Reynolds will be leading a grant with PhD student, Md Alomgeer Hussein and community partner, Karim Butler of Butler's Community Health Workers Services, entitled, Building a Framework and Toolkit for Effective Participatory AI Engagement in Hard-to-Reach Populations: A Case Study in Leveraging AI to Empower Underserved Patients in Understanding and Using their Medical Records. Through this project I will partner with community health organizations (CHOs) in Baltimore, Maryland to engage and retain a diverse group of participants from a hard-to-reach population (individuals living in low-income neighborhoods) in a participatory artificial intelligence (AI) project that itself has the potential for social good – better supporting patients as they try to use their medical records. The research activities include key informant interviews, and a series of focus group and co-design sessions. Education about the benefits and limitations of generative AI (genAI) will be integrated into each of the touchpoints. Key outcomes of the project will include an open-source toolkit that offer practical tools (e.g., effective recruitment strategies) for engaging hard-to-reach populations in participatory AI.
UMBC Cybersecurity Institute Exploratory Grant Awarded: Analyzing Cybersecurity Risks in the Digital Health Ecosystem with Patients with Complex Care Needs
Dr. Reynolds will be leading a grant with PhD student, Zainab Balogun, entitled, Swiss Cheese Please: Analyzing Cybersecurity Risks in the Digital Health Ecosystem with Patients with Complex Care Needs. The goal of this grant is to use the Swiss Cheese Model – a model first developed to explain system failures by illustrating the layers of defense as slices of swiss cheese and the holes as the vulnerabilities in the defenses – to understand and communicate about cybersecurity across the digital health ecosystem with healthcare consumers with complex care needs. This ecosystem is growing more complex and includes various standalone and connected technologies – such as wearables, medical devices, patient portals, generative artificial intelligence (genAI), and myriad health apps – and many different types of data from lifestyle (e.g., diet and steps) to medical (e.g., laboratory test results). Those with complex care needs are more likely to use more of these technologies and are, thus, more vulnerable to their security risks. This project seeks to address the paucity of research on how patients are thinking about the complex cybersecurity landscape in the digital health ecosystem.
CARE Research Lab @ AMIA 2024
CARE Research Lab had a strong showing at AMIA 2024 with one workshop co-organized by Dr. Reynolds, two student oral presentations, and two posters. Here, we highlight two of the contributions, both presented by PhD student, Zainab Balogun...
