Zilong Yu

Programmer Analyst @ Weill Cornell Medicine

Zilong Yu is a Programmer Analyst at Weill Cornell Medicine, where he develops mobile and web applications to support clinical research in mental health, aging, and digital health. His work focuses on mobile health (mHealth), wearable integration, and real-time data collection systems that enable digital phenotyping, EMA-based interventions, and longitudinal behavioral studies.

He builds and maintains full-stack systems — from app design and data pipelines to backend infrastructure and cloud deployment — and works closely with clinical research teams to support both participant engagement and data-driven analysis.

With a background in Biostatistics, Data Science, Business Analytics, and Computer Science, Zilong brings a multidisciplinary perspective to his work. He is driven by the opportunity to build tools that improve research outcomes and help translate complex data into clinical insight.

Interests

  • mHealth Research
  • Full-Stack Development
  • Behavioral Data Science

Education

  • MS in Biostatistics and Data Science
    Cornell University, 2022
  • BS in Business Analytics, Computer Science
    University of Denver, 2021

Research

Banerjee Lab - mHealth, Digital Phenotyping, Machine Learning

This lab focuses on digital interventions, EMA-based data collection, and machine learning for behavioral health. Zilong contributes to mobile platform development, passive sensing pipelines, and analytic workflows supporting NIH- and institution-funded studies.

→ Visit Lab Website

Kiosses Lab - Emotion, Cognition, Psychotherapy Innovation

This lab develops psychosocial interventions for older adults with depression, suicidal ideation, and cognitive impairment. Zilong supports digital tool development for EMA delivery, behavioral data collection, and remote monitoring within clinical trials.

→ Visit Lab Website

Experience

Weill Cornell Medicine

New York City Metropolitan Area

Programmer Analyst

Aug 2022 - Present

Supporting digital health research by building mobile/web applications and backend systems for clinical studies in mental health, aging, and behavioral science.

  • Developed 6+ cross-platform apps with Flutter/Firebase for EMA, dashboards, and wearable data (Fitbit, Garmin, Withings).
  • Built backend infrastructure using Firestore, Cloud Functions, BigQuery, and Cloud SQL.
  • Managed APIs, data pipelines, and real-time messaging; implemented automation with Python.
  • Maintained REDCap/MySQL dashboards; deployed participant apps to Apple/Google stores.
  • Contributed to behavioral analysis workflows, IRB processes, and manuscript prep.

Tech: Flutter/Dart, Firebase, GCP, MySQL, NoSQL, Python, R, SAS, JavaScript, HTML/CSS, REDCap, Git

Teaching Assistant

Sep 2022 - Present

Supported instruction for 10 graduate-level courses in the MS in Biostatistics and Data Science program, assisting with labs, grading, and course coordination.

  • Big Data in Medicine (2023, 2024, 2025)
  • Data Science I (2023, 2024)
  • Data Science II: Statistical Learning (2023, 2024)
  • Statistical Programming with SAS (2022, 2023, 2024)

Research Assistant - mHealth Clinical Trials

Mar - Aug 2022

Supported mobile health research through mobile app maintenance, data preparation, and dashboard development for clinical trials. Contributed to wearable and survey-based data processing, prototyped passive sensing tools, and collaborated with research staff on organization and documentation of study data.

Portfolio Project - EMA & mHealth Engagement

Apr - Jul 2022

Completed a research project on ecological momentary assessment (EMA) and gamified mobile health interventions, as part of MS program requirements. Analyzed reward-driven engagement patterns using mixed models and worked with faculty to interpret behavioral trends and data quality issues.

Publications

2SpamH: A 2-Stage Pre-processing Algorithm for Passively Sensed mHealth Data

Sensors, 2024. Co-author. Developed mobile and passive sensing data workflows for quality control and modeling.

→ Read the Paper

Increasing Completion of Daily Patient-Reported Outcomes in Psychotherapies for Late-Life Depression through User-Centered Design

Applied Clinical Informatics, 2024. Co-author. Supported digital EMA tools and study implementation in older adult clinical populations.

→ Read the Paper