HA NA CHO


EDUCATION


The University of California, Irvine September 2023 - present

Ph.D. Informatics

The University of Chicago September 2019 - August 2020

M.S. Biomedical Informatics

Roosevelt University September 2016 - June 2018

B.S. Biology

SKILLS


HCI: Coding Analysis, Interviews, Observation, Usability testing, Qualitative and quantitative

analysis, Surveys

Computer Programming: Python (Numpy, Pandas, Scikit-learn, Stellargraph, Matplotlib), R,

Stata, Neo4J, GIS, SQL, GitHub

Documentation: Microsoft Word, Microsoft Excel, Google Page

Communication: Korean (native), English (fluent)


WORK EXPERIENCE


University of California Irvine |Researcher Engagement Specialist September 2023 - present

Irvine, CA

  • Efficiently orchestrated and directed cross-functional collaboration, harmonizing project teams

and researchers to ensure precise project execution, and adhere to project timelines, while also

provisioning essential resources.


Asan Medical Center|Senior Data Scientist February 2021 - June 2023

Seoul, South Korea

  • Constructed a graph database leveraging electronic medical records, and with the HinSAGE algorithm, outperforming previous AI-informed models in predicting cardiac disease outcomes.
  • Developed diverse predictive models for accurate patient stay forecasts and used SHAP to explain the model’s insights, empowering clinical and management decisions.
  • Identified critical features through quantitative analysis, enhancing informed decision-making.
  • Led real-world health data preprocessing, offering insights into patient demographics.


RESEARCH EXPERIENCE


University of California Irvine |Graduate Student Researcher September 2023 - present

Irvine, CA

  • Conducted a qualitative study on online mental health counseling by analyzing survey responses and chat messages, aiming to discover behavior patterns among young adults and identify reasons behind their reluctance to seek counseling services.
  • Applied observational methods and performed thematic analysis on secure chat messages from college students, contributing valuable insights into the factors influencing their engagement with mental health support.


Northwestern University|Capstone Project January 2020 - August 2020

Chicago, IL

  • Found biomarkers for pneumonia patients through a building relational graph database on pneumonia patient’s data.
  • Demonstrated graph model performance with insightful query analyses and PageRank algorithm.
  • Orchestrated productive staff meetings, fostering effective collaboration.


University of Chicago |Research Technician July 2018 - February 2019

Chicago, IL

  • Discovered brain’s neocortical region functional distinctions during embryonic development.
  • Contributed to an innovative cortex patterning mouse model using genetic testing and analysis..
  • Orchestrated Excel database, streamlining data management.


Seoul National University Hospital|Student Researcher Intern Summer 2012 - 2014

Seoul, South Korea

  • Conducted advanced drug susceptibility genetic analysis for the Hepatitis B Virus.
  • Directed daily microbiology laboratory operations.
  • Organized key laboratory processes, generating comprehensive reports.


PUBLICATIONS


Scientific Reports 2023

Heejung Choi, Hee Jun Kang, Imjin Ahn, Hansle Gwon, Yunha Kim, Hyeram Seo, Ha Na

Cho, JiYe Han, Minkyoung Kim, Gaeun Kee, Seohyun Park, Osung Kwon, Jae-Hyung Roh,

Ah-Ram Kim, Ju Hyeon Kim, Tae Joon Jun , Young-Hak Kim.“Machine learning models to

predict the warfarin discharge dosage using clinical information of East Asian inpatients”

Scientific Reports (2023).


Computers in Biology and Medicine 2023

Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Heejung Choi, Ha Na

Cho, Minkyoung Kim, JiYe Han, Gaeun kee, Seohyun Park, Kye Hwa Lee, Tae Joon Jun, Young-Hak Kim. “LDP-GAN : Generative adversarial networks with local differential privacy

for patient medical records synthesis” Computers in Biology and Medicine (2023).


Health Care Management Science 2023

Hyeram Seo, Imjin Ahn, Hansle Gwon, Hee Jun Kang, Yunha Kim, Ha Na Cho, Heejung

Choi, Minkyoung Kim, Jiye Han, Gaeun Kee, Seohyun Park, Dong-Woo Seo, Tae Joon Jun, Young-Hak Kim. “Prediction of hospitalization and waiting time within 24 hours of emergency department patients with unstructured text data” Health Care Management Science (2023).


Scientific Reports 2022

Ha Na Cho, Imjin Ahn, Hansle Gwon, Hee Jun Kang, Yunha Kim, Hyeram Seo, Heejung Choi, Minkyoung Kim, Jiye Han, Gaeun Kee, Tae Joon Jun, Young-Hak Kim. "Heterogeneous

Semantic Graph Construction and HinSAGE Learning from Electronic Medical Records."

Scientific Reports (2022).


Computer Methods and Programs in Biomedicine 2022

Yunha Kim, Imjin Ahn, Ha Na Cho, Hansle Gwon, Hee Jun Kang, Hyeram Seo, Heejung

Choi, Kyu-Pyo Kim, Tae Joon Jun, Young-Hak Kim. "RIDAB: Electronic medical record-

integrated real-world data platform for predicting and summarizing interactions in biomedical

research." Computer Methods and Programs in Biomedicine (2022).


JMIR Med Inform 2021

Imjin Ahn, Hansle Gwon, Heejun Kang, Yoonha Kim, Hyeram Seo, Heejung Choi, Ha Na

Cho, MinKyung Kim, Tae Joon Jun, Young-Hak Kim.• "Machine Learning–Based Hospital

Discharge Prediction for Patients with Cardiovascular Diseases: Development and Usability

Study." JMIR Med Inform (2021).


JMIR Public Health Surveill 2021 Hansle Gwon, Imjin Ahn, YooKim, Hee Jun Kang, Hyeram Seo, Ha Na Cho, Heejung Choi, Tae Joon Jun, Young-Hak Kim.• "Self–Training with Quantile Errors for Multivariate Missing

Data Imputation for Regression Problems in Electronic Medical Records." JMIR Public Health

Surveill (2021).

PREPRINTS


JMIR 2023

Ha Na Cho, Tae Joon Jun, Young-Hak Kim, Hee Jun Kang, Imjin Ahn, Hansle Gwon, Yunha

Kim, Hyeram Seo, Heejung Choi, Minhyoung Kim, JiYe Han, Gaeun Kee, Seohyun Park, Soyoung Ko. "Task-Specific Transformer-Based Language Models in Medicine: A Survey." JMIR

(2023).


Scientific Reports 2022

Ha Na Cho, Imjin Ahn, Hansle Gwon, Hee Jun Kang, Yunha Kim, Hyeram Seo, Heejung Choi, Minkyoung Kim, Jiye Han, Gaeun Kee, Tae Joon Jun, Young-Hak Kim. "Explainable

predictions of a machine learning model to forecast the postoperative length of stay for severe

patients." Scientific Reports (2022).