My interests span Bayesian and probabilistic modeling approaches for addressing challenges associated with modeling and prediction in complex, real-world temporal systems. My recent work has focused on large scale modeling with Bayesian methods, methods for counterfactual reasoning, Bayesian nonparametrics, and Gaussian Processes. I am also excited about addressing challenges related to the use of data-driven tools for decision-making.
I direct the Machine Learning and Healthcare Lab at Johns Hopkins University. We are interested in enabling new classes of diagnostic and treatment planning tools for healthcare—tools that use statistical machine learning techniques to tease out subtle information from “messy” observational datasets, and provide reliable inferences for individualizing care decisions. In order to accomplish these goals, our lab (1) identifies domains/disease areas where such approaches can make an impact, (2) identifies gaps where current technologies fail, (3) designs new statistical machine learning techniques that solve associated fundamental computational challenges, and (4) develops and deploys solutions to measure impact.
October 10th is Ada Lovelace Day! Today the world celebrates all of the accomplishments of women in science, art, design, technology, engineering, and math. Each year, Adafruit highlights a number of women who are pioneering their fields and inspiring women of all ages to make their voices heard. Today we will be sharing the stories of women that we think are modern day “Adas” alongside historical women that have made impacts in science and math.
Please promote and share #ALD17 with your friends and family so we can promote and share with all of the world wide web!
Stop breadboarding and soldering – start making immediately! Adafruit’s Circuit Playground is jam-packed with LEDs, sensors, buttons, alligator clip pads and more. Build projects with Circuit Playground in a few minutes with the drag-and-drop MakeCode programming site, learn computer science using the CS Discoveries class on code.org, jump into CircuitPython to learn Python and hardware together, TinyGO, or even use the Arduino IDE. Circuit Playground Express is the newest and best Circuit Playground board, with support for CircuitPython, MakeCode, and Arduino. It has a powerful processor, 10 NeoPixels, mini speaker, InfraRed receive and transmit, two buttons, a switch, 14 alligator clip pads, and lots of sensors: capacitive touch, IR proximity, temperature, light, motion and sound. A whole wide world of electronics and coding is waiting for you, and it fits in the palm of your hand.