Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency
Microsoft Research Summer 2023
Worked in the Human Understanding + Empathy Group to design and implement a personalized environment for collaborative writing with large language models (LLMs) using React, Typescript, and LangChain.
Visualizing Global Attention Patterns in Transformer Models
Harvard University 2022 - Present
Working in the Insight + Interaction Lab to design a new visualization technique for exploring self-attention trends in transformer models through creating a joint embedding space of query and key vectors.
Using this technique, we built an interactive tool using Deck.gl and Vue, which can be used to study attention at a global scale in language + vision transformers.
Imagining the Next-Gen Document Reader and Acronym Glossary
Adobe Research Summer 2022
Understanding Hybrid Workforce Productivity Through Self-Reflection Interventions
Microsoft Research Summer 2021
Worked in the Productivity + Intelligence Group to design scalable, automated self-reflection interventions for a longitudinal diary study on hybrid workforce productivity and well-being during the pandemic as part of the New Future of Work Initiative.
Designing for Replicability in Human Computation Studies
Williams College 2021 - 2022
Worked with Prof. Molly Feldman to study the current state of replicability in HCI.
Our overarching research question is: What are the necessary components that constitute a replicable human computation study and should be included in research publications?
Exploring the Impact of Algorithmic Understanding on Decision-Making for Learning
Williams College 2019 - 2022
Worked with Prof. Iris Howley to develop a human-centered, evidence-based framework for explainable AI.
We piloted this method on Bayesian Knowledge Tracing, an AI algorithm that predicts skill mastery in learning analytics systems.