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Zheng Rong JIA

I learn for the future.

Medical AI Predictive Modeling Independent Researcher

B.Sc. Software Engineering · Macau University of Science and Technology, 2025

Zheng Rong JIA

Medical AI

Deep learning on EHR data for ICU risk stratification and clinical decision support

Predictive Modeling

Transformer-based temporal models for early warning systems in critical care

Health Informatics

Multicenter clinical databases, missing-data-aware architectures, reproducible pipelines

Explainable AI

Attention-based saliency and faithfulness evaluation for clinical interpretability

Digital Biomarkers

Feature importance analysis and physiological signal modeling for mortality prediction

CCAI 2026 ★ Best Industrial Paper ★ Best Presentation

Deep Learning for Stroke Mortality Prediction in eICU: A Dual-Tower Transformer Framework

Zheng Rong JIA*, Kwong-Cheong Wong*

The 6th International Conference on Computer Communication and Artificial Intelligence · Nanjing, May 2026

  • May 22–24, 2026 Received Best Industrial Paper Award & Best Presentation Award at CCAI 2026 — Nanjing.
  • May 22–24, 2026 Attended CCAI 2026 in Nanjing — delivered oral presentation of DT-Transformer for Stroke Mortality Prediction. Slides and photos now available.
  • May 2026 Finalizing the open-source release of the DT-Transformer framework for reproducible clinical AI research.
  • Feb 2, 2026 Paper accepted at CCAI 2026Deep Learning for Stroke Mortality Prediction in eICU: A Dual-Tower Transformer Framework.
  • Aug 2025 Earned B.Sc. in Software Engineering from Macau University of Science and Technology.

I am drawn to problems where machine learning meets real clinical stakes — where a model's failure is not an accuracy number but a missed diagnosis. My work focuses on building deep learning systems for electronic health records that are not only accurate, but interpretable and honest about their limits. I believe the most durable research is reproducible, open, and built with the long game in mind.