Megan Curtis

Megan Rose Curtis, MD

Assistant Professor of Medicine

Dr. Curtis specializes in clinical infectious diseases, with a particular focus on diseases impacting pregnant people living with substance use disorders, such as HIV, hepatitis C, and syphilis.

Portrait of Juliet Iwelunmor, PhD

Juliet Iwelunmor, PhD

Professor of Medicine

A passionate advocate for health equity and sustainability, Dr. Iwelunmor is widely regarded for understanding how to make evidence-based interventions last, reshaping the focus on community engagement using participatory research, improving the dissemination of health information, while amplifying the voices of young people in health interventions.

Laura Marks, MD, PhD

Laura Marks, MD, PhD

Assistant Professor of Medicine

Dr. Marks is a core faculty member of the ID Fellowship Training Program, serving as Director of Fellow Basic/Translational research, infectious diseases and substance use. She specializes in clinical infectious diseases with a special focus on infectious complications in people who inject drugs, such as infective endocarditis and Hepatitis B & C virus infections. Other core research interests include infections in pregnant women.

Portrait of Caline Mattar, MD

Caline Mattar, MD

Professor of Medicine and Public Health

Dr. Mattar is the section chief for General Infectious Disease and the Associate Program Director of the ID Fellowship Program. As ID Fellowship core faculty, she also serves as Director of Global Health Track. Dr. Mattar's research focuses on infection prevention and antimicrobial stewardship as well as global health with a specific focus on resource-limited settings and health policy.

Joshua Nordman, MD in white doctor's coat

Joshua Nordman, MD

Assistant Professor of Medicine

Dr. Joshua Nordman specializes in clinical infectious diseases, with a particular interest in the intersection of social vulnerability and infection. His research interests include antimicrobial research that leverages electronic health record (EHR) systems and large language models (LLMs) for improvement in patient care outcomes.