Zepeng "Frazier" Huo

Population-level Pulmonary Embolism Outcome Prediction with Imaging and Clinical Data

• Research student role:
  1. Integrate a comprehensive EMR data set with radiology images to predict Pulmonary Embolism primary and secondary outcomes
• We published INSPECT dataset at NeurIPS'23 (D/B). Check out our website

Warfighter Analytics using Smartphones for Health (WASH)

• Student managerial leader on TA-2 team:
  1. organize meeting agend
  2. compile monthly report sent to DARPA
• Research student role:
  1. leading research project on symptom and medical diagnosis prediction using a Mixture-of-Experts (MoE) model on dynamic sensory data;
  2. develop dynamic data imputation for mobile data missingness context;
• Partial work of this project was presented at AISTATS’20 conference as an oral presentation

Precise Advanced Technologies and Health Systems for Underserved Population (PATHS-UP)

• Student managerial leader on Thrust-4 team:
  1. organize meeting agend
  2. compile monthly report sent to DARPA
• Research student role:
  1. Glucose monitoring study for diabetic patients by using a multi-task deep neural network for macro-nutrition prediction from postprandial glucose time-series data;
  2. Design a framework to visualize the glucose response and an interactive UI;
  3. A lead contributor on US patent application ‘PREDICTING FOOD MACRONUTRIENTS FROM BLOOD BIOMARKERS’
• Partial work of this project was presented at IEEE BHI’19 conference as an oral presentation

Interpretable patient phenotyping for Emergency department clinical data modeling

• Responsible for prototyping models and data handling
• Design a denoising auto-encoder with sparsity for interpretable patient outcome prediction
• This work was presented at IEEE EMBS’19 conference as a poster

Stanford University, Stanford, CA

Texas A&M University, College Station, TX

Texas A&M University, College Station, TX