Meet the Coding it Forward Civic Digital Fellows

From June 13 to August 19, 2022, 15 Civic Digital Fellows participated in the 10-week program in 7 Institutes, Centers and Offices at the National Institutes of Health. The Fellows worked on projects that help to automate and streamline the ways that Program staff can extract and analyze data from the annual progress reports (RPPR), develop tools to clean grant-related data and visualize grant portfolio trends, conduct landscape analysis of data science-relevant topics in alignment with IC missions, and assess and report on research topics and the effectiveness of research user interfaces. Their presence, engagement and contributions have enriched the NIH community.

Gargi Mahadeshwar, Undergraduate, Duke University, Computer Science

Gargi worked in the National Institute on Drug Abuse (NIDA) under the supervision of Dr. Susan Wright and mentorship of Dr. Roger Little.

Her project was Developing and Optimizing Training Tools for NIH Program Staff.

She created a desktop app that returns a PDF with hyperlinked supporting text from multiple documents for checklist questions for program officers.

Supervisor and Mentor
Susan Wright, Ph.D., Roger Little, Ph.D.

Diana Qing, Undergraduate, University of California, Berkeley, Computer Science, Data Science

Diana worked in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) under the supervision of Dr. Sarah Glavin and mentorship of Christopher Belter.

Her project was Technical Documentation for Clinical Trials Classification Algorithm.

She created technical documentation for the algorithm to consolidate expert knowledge between institutes.

Supervisor and Mentor
Sarah Glavin, Ph.D., Christopher Belter

Ramya Chitturi, Undergraduate, UC Berkeley, Computer Science

Ramya worked in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) under the supervision of Dr. Sarah Glavin and mentorship of Christopher Belter.

Her project was BESH Flowchart for Clinical Trials Classification Algorithm.

She created a flowchart for principal investigators and an algorithm to identify Basic Experimental Studies Involving Humans (BESH) studies.

Supervisor and Mentor
Sarah Glavin, Ph.D., Christopher Belter

Jeremy Lee, Undergraduate, Harvard University, Statistics and Mathematics

Jeremy worked in the Office of AIDS Research (OAR) under the supervision of Robert Cregg and mentorship of Danny Murphy.

His project was Automating HIV/AIDS Grant Classification.

He built a machine learning model to classify HIV-related grants into one of 43 objective codes and one of 9 areas of emphasis.

Supervisor and Mentor
Robert Cregg, Danny Murphy

Warren Quan, Undergraduate, Princeton University, Computer Science

Warren worked in the Office of AIDS Research (OAR) under the supervision of Robert Cregg and mentorship of Danny Murphy.

His project was HIV/AIDS Grant Classifier Front-End Application.

He built a front-end application for scientific staff to input grant information which then runs an automated algorithm to classify HIV-related grants to objective codes (machine learning algorithm developed by Data Scientist Fellow Jeremy Lee).

Supervisor and Mentor
Robert Cregg, Danny Murphy

Becky Neufeld, Graduate, University of Utah, Quantitative Social Psychology

Becky worked in the National Institute of Neurological Disorders and Stroke (NINDS) under the supervision of Dr. Brian Haugen and mentorship of Dr. Michele Rankin and Dr. Rachel Tillage.

Her project was A Generalized Workflow for Creating Qlik Sense Dashboards with NIH Grants Data.

She created a dashboard to help enable NINDS and NIDA staff to easily and quickly investigate and evaluate research portfolios.

Supervisor and Mentor
Brian Haugen, Ph.D., Michele Rankin, Ph.D., Rachel Tillage, Ph.D.

Noreen Mayat, Undergraduate, Barnard College, Columbia University, Data Science

Noreen worked in the National Institutes of Health Helping to End Addiction Long-term (HEAL) Initiative under the supervision of Erin Spaniol and mentorship of Anthony Juehne.

Her project was Automating HEAL Grant Characteristics using NLP and Machine Learning.

She created an automated process for characterizing a study’s primary outcome, science types, and if it is/is not a milestone project.

Supervisor and Mentor
Erin Spaniol, Anthony Juehne

Julia Craciun, Undergraduate, UCLA, Data Theory

Julia worked in the National Institute of General Medical Sciences (NIGMS) under the supervision of Dr. Jake Basson and the mentorship of Dr. Andrew Miklos, Jessie Wang, Dr. Nathan Moore, and Jordan Jomsky.

Her project was NIGMS Portfolio Overview Dashboard.

She created an interactive Tableau dashboard to be used internally by NIGMS leadership to facilitate improvements in the grant funding process.

Supervisor and Mentor
Jake Basson, Ph.D., Andrew Miklos, Ph.D., Jessie Wang, Nathan Moore, Ph.D., Jordan Jomsky

Madeleine Wang, Undergraduate, UC Berkeley, Data Science

Madeleine worked in the National Institute of Neurological Disorders and Stroke (NINDS) under the supervision of Dr. Brian Haugen and mentorship of Victoria Bitzer-Wales.

Her project was NINDS Scientific Portfolio Clustering.

She created a Jupyter Notebook to help program directors distribute scientific portfolio management.

Supervisor and Mentor
Brian Haugen, Ph.D., Victoria Bitzer-Wales

Sarah Catherine Gillard, Undergraduate, University of Miami, Neuroscience

Sarah Catherine worked in the National Institute of Neurological Disorders and Stroke (NINDS) under the supervision of Dr. Brian Haugen and mentorship of Victoria Bitzer-Wales.

Her project was Visualizing Alzheimer’s Disease and Related Dementias Research Milestones.

She produced over 8 different types of interactive visualizations to summarize NIH's role in ADRD research.

Supervisor and Mentor
Brian Haugen, Ph.D., Victoria Bitzer-Wales

Erik Rozi, Undergraduate, Stanford University, Computer Science

Erik worked in the National Heart, Lung, and Blood Institute (NHLBI) under the supervision of Dr. Asif Rizwan.

His project was Trust in AI/ML: Directions to Take in the NIH.

He wrote an internal blog post and longer white paper to inform different communities about the need for trustworthy AI/ML systems in healthcare.

Supervisor
Asif Rizwan, Ph.D.

Cindy Xie, Undergraduate, Columbia University, Medical Humanities

Cindy worked in the National Heart, Lung, and Blood Institute (NHLBI) under the supervision of Dr. Asif Rizwan.

Her project was Digital Health at NIH.

She wrote a blog and white paper addressing trends in digital health at NIH.

Supervisor
Asif Rizwan, Ph.D.

Erin McGowan, Undergraduate, Rutgers University - New Brunswick, Mathematics

Erin worked in the National Center for Advancing Translational Sciences (NCATS) under the supervision of Dr. Qian Zhu.

Her project was Network Analysis-Based Drug Repositioning for Glioblastoma.

She conducted research identifying existing drugs that could potentially be repurposed to treat glioblastoma (GBM).

Supervisor
Qian Zhu, Ph.D.

Saanvi Juneja, Undergraduate, University of Michigan, Ann Arbor, Computer Science

Saanvi worked in the National Institutes of Health All of Us Research Program under the supervision of Margaret Farrell and mentorship of Kelsy Gibson Ferrara and Dr. Carrie Iwema.

Her project was Data Analytics to Support the Research to Participant Communications Pipeline in the All of Us Research Program.

She created tools, including multiple Jupyter notebooks, and resources, including and article, to facilitate robust communication and establish a data stories scope of work.

Supervisor and Mentor
Margaret Farrell, Kelsy Gibson Ferrara, Carrie Iwema, Ph.D.

Ben Nguyen, Graduate, University of California, Merced, Cognitive & Information Sciences

Ben worked in the National Institutes of Health All of Us Research Program under the supervision of Dr. Claire Schulkey.

His project was The All of Us Researcher Workbench User Characteristics.

He examined who are the All of Us Researcher Workbench users and how do they engage with the workbench.

Supervisor
Claire Schulkey, Ph.D.

Meet the previous fellows:

This page last reviewed on September 19, 2022