Right now, I'm thinking about how to support the process and outcomes of feedback exchange in livestreaming. Below are some of the projects that I've worked or currently working on:
Analytics Needs of Video Game Streamers
Conducted an interview study to describe the ecology of analytics tools utilized, define streamers' areas of analytics needs, and identify opportunities to support streamers and their communities.
Content Distribution in English Wikipedia
Collected and analyzed 600k article pages from English Wikipedia to uunderstand how they reflect a distribution of topical content. Then, explored content distribution of events based on decadal temporal analysis using Wikipedia's link structure.
HCI Science Communication on Twitter
Collected and analyzed tweets from HCI researchers to understand their science communication practices and opportunities to support them. Designed and developed an web app to visualize science communication efforts.
I've spent my summers learning from really cool places and really smart folks below:
Research Intern, Microsoft Research
Utilized computer vision using OCR and entity recognition to extract information and develop insights to support personal informationmanagement. Developed a full stack web application using nodejs and azure cognitive services.
Research Intern, Microsoft Research
Investigated human-AI complementarity in high-stakes decision making scenario. Designed differentways to incorporate machine recommendations to leverage human-AI complementarity.
Research Collaborator, Microsoft Research
Designed and ran a study to examine the impact of different presentations of racial information onhuman judgment in the context of recidivism. Developed a full stack web application to gather data on MTurk and analyzed results to study significant differences across conditions.
Data Science Summer School, Microsoft Research NYC
Analyzed student trajectory in the NYC public school system by calculating student performance basedon test results, and then tracking individual student performance over the years. Developed predictive models for dropout rates of students in the system and acceptance rates of students in the NYC highschool application process.
MIT CODE 2017
I've also TA'd some cool classes listed below:
HCDE 538: Designing for Behavior Change
Students are introduced to existing behavior change theories, frameworks, and research to gain an understanding of why and how behavior changes. Utilizing these insights, students practice theory-driven design to nudge positive behavior change. They analyze current behavior change applications and utilize existing resources to guide their design process.
HCDE 539: Physical Prototyping
Students in this course design and prototype interactive prototype systems and environments using physical computing tools (a combination hardware and software). This quarter they have been exploring a range of applications using the Circuit Playground Express micro-controller (an Arduino).
HCDE 451: UX Prototyping
Students in this course have been exploring various user experience prototyping techniques such as model making, laser cutting, 3D printing, sewing, video, and interactive wire framing.
DRG in Analyzing and Supporting Twitter-based Science Communication
In this project, we will be designing a system that identifies what types of people have likely read an individual tweet (e.g., using techniques from NLP and beyond), and aggregates that information to help us summarize the current state of science communication in HCI.
"She is a smurf student" - Will, after catching Keri play Diner Dash in class
"Those are not pancakes" - Minsuk, after watching Keri make breakfast on stream