As an Engineer for Amazon’s Alexa, Instructor Aansh Shah Designs AI That Changes the Way We Live

Aansh Shah is an engineer working on the Alexa AI at Amazon. Aansh did his undergrad at Brown University in Applied Mathematics and Computer Science and recently graduated with his Master's (class of 2020) at Brown in Computer Science. His areas of interest include explainability in AI and deploying models at scale in the world.

HOW DID YOU CHOOSE WHAT YOU STUDIED IN COLLEGE? HOW DID YOU END UP STUDYING AI?

“I concentrated in Applied Mathematics and Computer Science at Brown University though I entered with the intention of pursuing Applied Math and Philosophy. After I took my first Computer Science course, I was drawn in by the interdisciplinary applications touching on all of my interests in public policy and political science. I liked the idea that I could make a difference from anywhere with just a computer and an internet connection. During my sophomore year, I decided to take an Artificial Intelligence course at Brown and enjoyed the course; I was in awe at how AI could significantly change how we live. After taking the class, I became a teaching assistant, and subsequently, the head teaching assistant, which exposed me to even more within the field. I continued this passion by getting involved in several research groups: self-driving cars, intelligent robotics, neural computation and cognition, bioinformatics AI, and smartphones. I also worked on several interdisciplinary data science and machine learning projects in journalism while I was the Director of the Data Board on the Brown Political Review. I synthesized all this information my senior year when I helped design a course in advanced methods in data science and deep learning as the head teaching assistant for a class in the Data Science Master’s program. I ended up staying at Brown for another year to learn more about AI by continuing my research in AI, and graduated with a Master’s degree in Computer Science. Now, I am a Software Development Engineer at Amazon Alexa AI.”

WHAT RESEARCH/INDUSTRY WORK WITHIN AI HAVE YOU BEEN FOCUSED ON? WHAT EXCITES YOU ABOUT THE FUTURE OF AI?

“I am interested in unsupervised learning and explainable AI. Some of the projects that I have worked on include:

- Analyzing EEG data from participants in a study who took Tolcapone using targeted dimensionality reduction and regression techniques to determine electrophysiological signatures of enhanced prefrontal dopamine

- Using unsupervised learning techniques to create machine learning models to predict readmission within a 30-day window of a patient being released

- Leveraging knowledge graph embeddings and unsupervised learning to capture common-sense linguistic priors in reinforcement learning environments.

I am looking forward to all the advances in AI and how they will enable things that were previously thought to be impossible. I’m excited by the prospect of being able to walk outside, summon a car from anywhere, and be autonomously driven to my destination. I’m also looking forward to advances in AI in fairness and addressing inequality.”