With great power comes great responsibility. Machine Learning, like other technologies before it, is changing the status quo. Sometimes this is a good thing, such as when physicians use AI to do a better job taking care of patients. But other times, AI is thought of as a silver bullet that will solve way more problems than it actually can. My research explores a variety of aspects of technology and healthcare, including:
- Using ML to be more fast, scalable, and consistent for ordinary clinical tasks (e.g. readmission prediction or writing radiology reports).
- Using ML to better understand how mistrust in the doctor-patient relationship is associated with racial disparities in end-of-life care.
- Proposing policy interventions to mitigate bias in Diagnostic AI.
- Creating a how-to guide for ML researcher collaboration with clinical domain experts & stakeholders.
Technology can do a lot of good for people, but only if we build it and use it responsibly.
I’m a PhD student in the Clinical Decision Making Group (MEDG) at MIT CSAIL supported by an NSF Graduate Research Fellowship. My life goal is to make the world a better place, and I’m spending the next few years figuring out the most effective way I can work towards that.
For Summer 2020, I am looking for an internship in the public sector (probably in Massachusetts, though I’d be open to federal-level or potentially in another state, depending on the opportunity). I am assuming it won’t involve ML or research; I’m just excited to learn what public service would be like. I’m considering careers in health/tech policy, and this would be a very useful experience for me (even if it is working on something very unrelated)!
In 2018, I finished my Masters Thesis studying racial disparities in end-of-life care. Essentially, it appears that when you don’t trust your doctor (which is correlated with race) then you are not as prepared to handle difficult end-of-life situations. This results in more aggressive care being used by nonwhite patients (which is emotionally difficult and also very expensive).
In 2019, I spent my summer interning at Aledade deploying an ML model to identify patients who would benefit most from EOL planning conversations. A large amount of this effort involved making sure that the deployed model was fair and transparent, and that it didn’t exacerbate existing racial disparities.
In early 2020, I interned at IDA Science and Technology Policy Institute (STPI), where I worked on space policy. It was a very humbling experience (because I didn’t know anything about space when I started), and I learned so much about methods for interdisciplinary research, and how to be a good mentor.
I also TA’d two classes: Machine Learning for Healthcare (HST.956) and Foundations of Internet Policy (6.805). I learned a lot of lessons about teaching, managing logistics, and putting out fires. It was so much fun & was very rewarding!
This year, I am working on the following extra-curricular endeavors:
- CSC (President): Building a strong CSAIL community, with an emphasis on inclusivity.
- Dracut DI (Director): Expanding DI to Dracut’s middle school and building on our elementary school success!
- Dracut Girls Who Code (Supporter): Working with Dracut High to make sure they have a Girls Who Code chapter & they are supported with whatever they need.
Something I could be doing better at? Is it too awkward to mention to me in-person? Let me know anonymously!