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Meet some of our current DCDS students and learn about their background and research

Yehu Chen

Computational Methodologies 

My research interest lies in the interaction between Bayesian machine learning and political methodology, including but not limited to election forecasting and causal inference.

My current project is Bayesian difference in difference with mult-task gaussian process.

My paper ‘Polls, Context, and Time A Dynamic Bayesian Forecasting Model for US Senate Elections’ is under R&R of Journal of Political Analysis.

Tom Earnest

Psychological & Brain Sciences

In DCDS, I am interested in applying machine learning and data-driven approaches to study neurological and neuropsychiatric disorders. I just finished a first-year rotation in the lab of Aristeidis Sotiras, where I worked on using non-negative matrix factorization (NMF) to learn patterns of brain pathology in Alzheimer’s Disease neuroimaging.  In my next rotation with Todd Braver, I will evaluate the utility of the lab’s dynamic brain modeling method (MINDy) for predicting behavioral and psychological outcomes. 

Robert Jirsaraie

Psychological & Brain Sciences

My research interest includes mapping developmental trajectories of psychopathology to better understand biomarkers and predict risk. My first doctoral project aims to determine how generalizable existing brain age models are to capturing within-subject changes in brain development and mental health. Towards this end, I am actively building my skills in machine learning, longitudinal analysis, and multimodal brain imaging. 

Amanda Kube

Computational Methodologies

My research interests involve the intersection of computer science and the social sciences. I am especially interested in fair applications of AI to social-scientific questions.

My current work combines machine learning and human decision-making to inform fair and efficient service allocations for homeless families.

Joshua Landman

Social Work & Public Health

My research interests are, broadly speaking, biomedical data science and clinical predictive modeling with a focus on social determinants of health. Projects I’m currently working on include modeling the impact of social determinants of health on COVID-19 outcomes, predicting whether patients will be readmitted to the hospital following spinal fusion surgery, examining the performance of machine learning and statistical models on predicting autoimmune disease diagnosis, and exploring how social connectedness impacts new daily rates of COVID-19 cases across counties.

Messi (Hojun) Lee

Psychological & Brain Sciences

I am generally interested in how languages reflect implicit biases in society. My research specifically involves word embeddings – building relevant corpora through web scraping and APIs, training embedding models, and using association tests for bias detection. I am currently working on two projects: one is a project on perceptions of media bias trying to identify the specific proxies news consumers use to assess bias degree of news outlets, and the other is on detecting political biases in the media and studying their priming effect on the general public and political elites.

Abigail Lewis

Social Work & Public Health

I am interested in using data science to understand disparities in access to health care and patient outcome. Currently I am working on a project in the Institute for Informatics which aims to understand the use of biomarker testing in Alzheimer’s diagnoses and racial disparities in access to these tests.