How did you first learn about disease surveillance and when did you decide that it was an area of interest for you? When I graduated with my PhD, I moved to the University of Pittsburgh for a post-doc. The RODS Lab had just begun working on biosurveillance. They were attempting to leverage existing data sources, and much of the clinical data is in text format. My research is on extracting information from clinical texts (natural language processing, or NLP), so we began collaborating. Disease surveillance was fascinating to me, because it showed promise to impact population health, and there was little work at the time on applying NLP to the domain.
What do you do? I am faculty at the University of California, San Diego right now, continuing research on NLP applied to clinical text.
What do you enjoy most about your job? I like the variety of being in academics – it involves research, writing, presenting, teaching, and networking. I also enjoy the opportunities to travel to conferences, brainstorm with people, and listen to new ideas (although, I must admit I get overwhelmed sometimes and wonder why I don’t come up with all of those great ideas).
What excites you in the work you do? Patterns. I love finding patterns in language that can be leveraged. I also get excited when I think that someone might want to use a tool I have developed and when I am able to integrate initially disparate ideas into a model or framework.
Who or what inspires you professionally? I am inspired when I get to collaborate with diverse people on a hard problem. My work is so much more innovative and fruitful than it would be if I tried to solve the problems on my own. I appreciate the public health practitioners, the clinicians, the computer scientists, and the cognitive scientists who help me see problems and solutions from a different angle and who keep me focused on trying to make tools that are useful for real users.
What is your proudest professional accomplishment or achievement (related to disease surveillance)? I am most proud of the common syndromic definitions we formed as part of a group of 18 syndromic surveillance system developers and users. It was a daunting task to try to get 18 diverse people to agree on syndrome definitions in 24 hours, but good organization and a spirit to collaborate helped us do it.
How long have you been involved with ISDS? Since 2001
Why are you an ISDS member? I have always enjoyed the ISDS conference. The talks are of high quality, and the people involved in the area are as kind as they are diverse. I think there is a spirit of camaraderie and true desire to improve the world in ISDS.
What do you value most about your ISDS membership? Being part of a the community that brings together people from a variety of disciplines to attempt to solve real-world problems with real-world data.
What is the biggest issue in disease surveillance (in your opinion)? Knowing what to do with all of the data we have access to – how to integrate, visualize, and learn from the data without getting overwhelmed.