Zhi Huang, PhD ORCID logo

Research Interests:

Artificial Intelligence
Human-AI Collaboration
Digital Pathology
Precision Medicine

Hi! I am a postdoctoral fellow at Stanford University. In August 2021, I received my Ph.D. degree from Purdue University, majoring in Electrical and Computer Engineering (ECE). My background is in the area of Artificial Intelligence, Human-AI Collaboration, Digital Pathology, and Precision Medicine.

I have broad experience in research and entrepreneurship. Since 2021, I have been at Stanford Medicine for 3 years, shadowing many clinicians in their day-to-day activities to learn about the challenges faced by both patients and doctors. In 2022, my mentors and I co-founded nuclei.io — the AI platform for digital pathology. It was selected as one of only 9 Stanford Catalyst 2023 cohort innovations.

[News] Starting July 2024, I will be joining the University of Pennsylvania as an incoming tenure-track assistant professor at the Perelman School of Medicine with multiple appointments. I am actively recruiting postdoc scholars, RAs, and software engineers in my future lab. See Opening page for more detail.

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

News

News

2024

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

[2024-04]
Huang et al. Pathologist-AI collaboration study is accepted at Nature Biomedical Engineering (in press).

[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.

[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 Highlights

Research Highlights

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.

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.