Visiting Researcher Program

My research goals include developing practical learning systems for natural language and knowledge that simultaneously enable compact and interpretable modeling trained from large-scale text data. I am excited to have an opportunity to work with world-leading researchers at the Google Brain team on establishing novel and innovative methodologies towards my research goals.

My research aims at modeling both content and interpersonal information in natural language communication, with applications to health, education, and social media. Visiting Google Research NYC has been a great learning experience, and an opportunity to collaborate with world-leading researchers on natural language related projects that can have real world benefits.

The Google Brain team is a unique place to perform cutting edge systems research to continuously meet the demands of AI computations and enable more breakthroughs. I am excited to have contributed towards addressing this problem while working on the MLIR project since its conception.

I prefer things that have a lot more impact, and influence on people — that's actually one of the reasons why I came to Google. It's a place that right now has enormous leverage to do things.

Machine Learning is increasingly becoming one of the biggest consumers of computational resources. As a systems researcher, I wanted to gain first-hand experience with how leading-edge ML is being developed and used at the largest scales.

At Google I'm working on explainable AI in the context of conversational recommender systems. Specifically, I'm developing recommendation approaches that can reveal to users how their preferences are generally understood, expose the reasoning behind the recommendation mechanism, and provide users with a direct and meaningful way to revise the system’s understanding of their preferences.

Vallor began working with Google Cloud in July 2018 as a consulting AI Ethicist assisting with the implementation of Cloud review processes for our AI Principles. While continuing to support these processes in Cloud, in December 2018 she expanded her work at Google as a Visiting Researcher, joining Global Affairs and serving as one of our Advanced Technology Advisors. She also has worked extensively with EngEDU to develop a series of workshops, presentations, and self-service training modules on tech ethics designed for a variety of audiences at Google.

Google Brain is an exceedingly interesting place where the frontiers of deep learning are being shaped continuously. My goal here is to engage in design of novel neural network architectures that can reason about programs, find and fix bugs in them, and ultimately synthesize programs automatically.

Google is pushing the limits of ML and systems to support it, and has amazing group of people engaged in that work. It's a fast, open, collaborative environment that makes you feel at the center of this wave of change.

My research goals are to improve the performance, energy efficiency, and reliability of computer systems. I am excited at the opportunity to work with world-leading engineers at Google on efficient warehouse-scale computing infrastructure.

My research looks at interactions between precipitation and hydrological systems, how they are affected by climate variations (including past and future climate change), and how they affect runoff and flood processes. At Google Research I have the opportunity to join AI experts that look at similar phenomena with a machine learning set of tools. With this multi-perspective view I hope we can improve both prediction skills and process understanding of those important environmental systems.

While visiting Google NYC, I am generally interested in understanding and improving optimization for deep learning and hope to obtain interesting empirical and theoretical results that will carry over to future research.