Postdocs and Fellows
Causal inference, graphical models, machine learning in public policy and biomedicine
Daniel is a postdoctoral fellow working with Ilya Shpitser (JHU) and Eric Tchetgen Tchetgen (UPenn) on causal inference with graphical models. His primary interest has been causal structure learning, i.e., data-driven methods for selecting causal graphical models from observational data. Currently, he is thinking about missing data, semiparametric inference, and stochastic processes. Daniel has a BA from Columbia University and defended his PhD at Carnegie Mellon University in December 2017.
Medical image analysis; statistical shape modeling; deformable registration; disease detection
Ayushi is a Provost’s Postdoctoral Fellow working with Russ Taylor and Greg Hager on enhancing endoscopic navigation during clinical endoscopic exploration and endoscopic surgeries. Her primary interests include statistical analysis of large population data to understand anatomical variation and to improve deformable registration between different modalities. She is currently exploring methods to assign confidence to computed registrations which will allow clinicians to gauge when a registration is reliable. She is also interested in seamlessly integrating these navigation systems into clinical and surgical settings. Ayushi has a BS and BA from Providence College and an MSE and PhD from the Johns Hopkins University.
Using systems engineering to improve the delivery of healthcare; Gastroenterology & Liver Transplant; Health Disparities
Aly Strauss is a board-certified Internal Medicine physician, and she is currently in specialty training at Johns Hopkins as a Gastroenterology & Hepatology fellow. She is a Ph.D. student in the Graduate Training Program in Clinical Investigation (GTPCI) program in the Bloomberg School of Public Health. Building on her Masters in Industrial Engineering (with a focus in Health Systems Engineering), she will incorporate principles from public health to improve patient outcomes. Dr. Strauss’ primary research interest focuses on creating applicable models and useful clinical decision support tools to improve healthcare delivery and outcomes in gastrointestinal diseases and liver transplantation.
Dr. Strauss’ background in human factors engineering, data science, process improvement, and economics will help her to communicate and collaborate more easily in diverse interdisciplinary teams. She has applied these skills with a team of various types of healthcare providers and engineers at the main Johns Hopkins Hospital to improve the success rate of inpatient colonoscopies. This project has decreased unnecessary harm and decreased length of stay. Due to this success, the initiative has spread throughout the Johns Hopkins Health System.