AI PHI team

Many AI PHI members are also part of the Shepherd Research Lab. The list below names the AI PHI–specific roles; for full SRL bios see our team page.

Leadership

John Shepherd

John Shepherd, PhD

Co-Director · Imaging Sciences

Chief Scientific Officer of the UH Cancer Center; B.H. and Alice C. Beams Endowed Professor in Cancer Research. Director of HIPIMR. Continuously NIH-funded since 2005.

Peter Sadowski

Peter Sadowski, PhD

Co-Director · Machine Learning

Assistant Professor in UH Computer Science. Expert in deep learning for scientific data, particularly high-dimensional medical imaging and health informatics.

Advisory Board

Margaretta Colangelo

Margaretta Colangelo

Co-founder & CEO, Jthereum

Over 30 years in the software industry, with deep cross-disciplinary experience in business, science, and technology. Has published 200+ articles on AI and spoken at conferences across multiple continents.

Members

Arianna Bunnell

Arianna Bunnell

Affinity Group Scientific Program Director

PhD student in Computer Science at UH, applying deep learning to breast ultrasound imaging.

Yannik Glaser

Yannik Glaser

Postdoc · UH Mānoa ICS

Research assistant at the UH Machine Learning Lab; deep learning for medical image analysis.

Thomas Wolfgruber

Thomas Wolfgruber

Postdoc · Shepherd Research Lab

Mammography for risk detection using machine learning; data scientist and software engineer.

Lydia Sollis

Lydia Sollis

PhD Student · UH Mānoa ICS

Machine learning for healthcare challenges; previously contributed to autism and Parkinson's screening tools.

Past contributors

Nusrat Zaman Zemi

Nusrat Zaman Zemi

MS Student · Shepherd Research Lab

MSc in Electrical and Computer Engineering at UH Mānoa; software/hardware for breast ultrasound imaging.

Lambert Leong

Lambert Leong, PhD

PhD Student · Shepherd Research Lab

Breast imaging and machine learning for cancer risk analysis and detection. lambertleong.com ↗

Xun Zhu

Xun Zhu, PhD

Postdoc · Shepherd Research Lab

Deep learning for biomedical imaging problems; background in mathematics and bioinformatics.

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