Hi, I’m Michelle, MPH - a Machine Learning and AI researcher with special interest in humanitarian action, digital health, and health equity.
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<aside> 📄 Publications
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<aside> 🐱 Github
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<aside> 📧 Email
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Junior Data Analyst | New York University Department of Population Health January 2022 - 23
Researched and implemented machine learning models for predicting missing demographic information in patient health data, conducted data management, and performed literature reviews related to machine learning methods and ethnicity prediction.
Data Science for Social Good Fellow | Stanford University Stanford Data Science (DELPHI Research group at Carnegie Mellon University, July 2021 - 2022
As a Fellow, I developed a Shiny app (R) for epidemiologists to compare COVID-19 forecasting models, along with a parameterized report tool to evaluate and rank model performances, while actively engaging in multidisciplinary workshops on data science and social issues.
User Experience (UX) Researcher | Sonic Sensory Inc. (Los Angeles) **2019 - 2020
As a UX researcher, I conducted and analyzed usability tests, managed data entry, optimized onboarding processes, and presented usability study results to facilitate improvements in user interaction with mobile applications and wearable technology.
3rd place | National Data AI Analytics Competition Ministry of Science and ICT, Seoul, South Korea (2023) **I developed an "SNS based Legal and Public Policy Prediction Model (NLP)" utilizing the KoBERT model to predict government policies and public reaction, and created a Tableau dashboard for analyzing the connection between public opinion and policy development. The dashboard contained a news data cartogram, sentiment analysis of SNS data using KoBERT model, news and sns data topic modeling using LDA analysis and GPT, and news summarization using kpfBERTsumm model.
Runner - up | Statistical Data Analysis Competition National Business Administration, Seoul, South Korea (2023) **I designed the "Smart-Merge System," a machine learning-based client expansion and merger and acquisition recommendation system, which involved developing a company recommendation platform utilizing k-means clustering, KNN, and Collaborative Filtering to foster new partnerships and mitigate business closures, particularly among aging CEOs, and conducted LDA-topic modeling of surveys from social venture companies to inform business-oriented policies.
Data Science for Social Good Fellowship, Stanford University (2021)
High Pass on Capstone Project, Columbia University (2021) Dean’s Scholarship, Columbia University (2019-21) Dean’s List, Wesleyan University (2016) Bill and Melinda Gates Millennium Scholarship (2012 - )