Zhi Huang, PhD ORCID logo

Research Interests:
AI/ML model and human-AI collaboration
Digital pathology
Precision medicine

Hi! I am an incoming tenure-track assistant professor at the University of Pennsylvania, with multiple appointments & affiliations in the Perelman School of Medicine beginning in January 2025. I received my PhD in Electrical and Computer Engineering from Purdue University in August 2021. Since August 2021, I have been a postdoctoral fellow at Stanford University, working with Prof. James Zou and Prof. Thomas Montine.

My research focuses on AI/ML innovation and its application to medicine, with topics including vision-language foundation model for pathology (Nature Medicine'23 cover), human-AI collaboration (Nature BME'24), neurodegenerative diseases (Nature Communications'23), etc. My research has drawn wide public attention (including the New York Times, Stanford Magazine, and Stanford Scope) and has resulted in translational innovations. In 2022, my postdoc mentors and I co-founded nuclei.io — a human-in-the-loop AI platform for digital pathology. It was selected as one of only 9 Stanford Catalyst 2023 cohort innovations.

I am very fortunate to work with many amazing students and researchers. We are always looking for talented folks to join us. Feel free to contact me or visit Openings if you are interested to learn more about our research!

— Educate medical AI in the same way as humans. —

News

News

2024

[2024-06]
Huang et al. Pathologist-AI collaboration study is published in Nature Biomedical Engineering.

[2024-06]
We introduce : Automatic "Differentiation" via Text! Start optimizing prompts in your LLM system: Github stars

[2024-05]
Impact of ChatGPT in AI review (co-authored paper) is accepted at ICML 2024 (oral).

[2024-03]
New York Times opinion on AI-generated articles (co-authored manuscript).

[2024-01]
New study on off-label and off-guideline cancer therapy usage is accepted in Cell Reports Medicine.

2023

[2023-12]
New study on resilience to Alzheimer's disease is published in Frontiers in neuroscience.

[2023-11]
Flash talk at Stanford Pathology ( Video).

[2023-10]
Huang et al. invited commentary on resilience to AD is published in Neuroscience Insights.

[2023-09]
Visual-language AI for pathology is featured on Nature Medicine September 2023 cover story.

[2023-08]
Huang, Bianchi et al. Visual-language AI for pathology is published in Nature Medicine. Github stars

[2023-05]
Huang et al. Brain proteomic analysis is published in Nature Communications.

[2023-03]
nuclei.io is spotlighted in the Stanford Catalyst 2023 cohort [News].

[2023-01]
Huang et al. Multi-modal pathology imaging analysis is published in NPJ (Nature Partner Journals) Precision Oncology.

Research

Research

1. Foundation model for Pathology:

Learn our largest visual–language public dataset for pathology at here.


2. Human-AI collaboration

nuclei.io: AI platform for digital pathology [website]


3. Precision medicine

Resilience to Alzheimer’s Disease

Brain Proteomic Analysis Implicates Actin Filament Processes and Injury Response in Resilience to Alzheimer’s Disease [paper]
Zhi Huang, et al.
Nature Communications, 14 (1), 2747 (2023).

AI predicts Post-treatment outcome

Artificial Intelligence Reveals Features Associated with Breast Cancer Neoadjuvant Chemotherapy Responses from Multi-stain Histopathologic Images [paper] [news]
Zhi Huang, et al.
NPJ Precision Oncology, 7, no. 14 (2023)

Multi-omics deep learning prognosis

SALMON: Survival Analysis Learning with Multi-Omics Neural Networks on Breast Cancer [paper] [github]
Zhi Huang, et al.
Frontiers in genetics, 10 (2019): 166.


4. Vision & language model and compound AI systems.

Teachings & Talks

Teachings & Talks

Teaching
Stanford CS 273B: Deep Learning in Genomics and Biomedicine (BIODS 237, BIOMEDIN 273B, GENE 236)
Topic: From glass slides to diagnosis
April 10, 2023, Stanford University, Room 370-370.