Huijuan Song

This publication record appears to combine work from multiple researchers sharing the name Huijuan Song, spanning infectious disease diagnostics (tuberculosis, sepsis, CRE infections), cancer biology and oncology trials, and mathematical modeling of tumor growth using partial differential equations. Topics include machine learning approaches to distinguish active from latent tuberculosis, immune profiling in sepsis, drug development for viral infections, and theoretical models of tumor growth with free boundaries. Prospective students should note the unusually broad and disconnected topic spread, which may indicate name overlap across distinct research groups rather than a single coherent research program.

Publication output peaked around 2020-2021 with 16-17 papers per year, then declined to a steadier pace of roughly 4-7 papers per year through 2022-2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026