Haruhisa Oda

Graduate School of Medicine
The University of Tokyo

Mathematics, AI & Biomedicine

Haruhisa Oda

Department of Preventive Medicine, The University of Tokyo
Melbourne School of Population and Global Health, The University of Melbourne

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News

2026/4/10: We will organize a symposium in BMB2026.
2025/12/20: We will hold IMAB2026 (The Second International Workshop on Mathematics and AI for Biomedicine) on November 30th, 2026. Registration is open!
2025/12/4: Organized IMAB2025 (The First International Workshop on Mathematics and AI for Biomedicine)
2025/12/3: Organized a symposium in MBSJ: "Future of mathematical data science driven biomedical research"

Mathematics, AI, and BioMedicine

Motivation

BioMedicine is becoming increasingly data-driven, characterized by greater complexity and diversity than ever before. To fully harness the value of this data, it is crucial to develop innovative analysis methods based on advanced mathematical sciences.

Challenges

A particularly significant challenge lies in how we recognize and interpret patterns, as biomedical data is abundant with various patterns, such as cell shapes and movements, branching morphologies in vessels and airways, and cell distribution patterns in histology and pathology. Recent advancements in data acquisition technologies, including 3D imaging, have also enabled us to access 3D and higher-dimensional data.

Approach

To analyze these patterns effectively, we can utilize concepts from topology, the study of shapes. We have been exploring the efficacy of topological information in the processing and understanding of biomedical data. We also combine these tools with machine learning method to build better performing frameworks.

Vision

Through the development of innovative tools and the generation of new knowledge, we are dedicated to advancing all domains of biomedical science—encompassing basic, clinical, and social aspects—in order to foster a transformative understanding of the world.

Recent Topics

Persistent homology based segmentation

A collection of image segmentation methods using persistent homology.

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Lung CT airway analysis

Quantification of 3D airway morphology based on persistent homology transform.

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Branch structure analysis

Defining internal and external structure in ambiguous branch images.

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Pathology patch analysis

Understanding pathology patch patterns by extracting topological information.

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Activities and Awards

Scientific Visits

The University of Melbourne

May-June 2025

Australian National University

June 2024

Institute for the Advanced Study of Human Biology (ASHBi, Kyoto University)

April-May 2024

Awards, Grants, Scholarships

AIP Challenge Director's Award (Award)

2026

AIP Challenge (Grant)

2025 (企画メンバーリーダー)

WINGS-LST (UTokyo)

2025-

BOOST NAIS (UTokyo)

2025-

SPRING-GX海外派遣支援

2025

Nakatani Foundation 大学院生奨学金8期生 (Scholarship)

2025-

令和6年度学部長賞 (Award)

2024

東大リトリートポスター発表特別賞 (Award)

2024

令和5年度有馬聡記念フェローシップ (Award)

2023

Reviewing activity

PLOS Computational Biology

1

Nature Methods

1

ICIAM 2023 Tokyo

2

Academic Society

Japan Society of Industrial and Applied Mathematics

日本応用数理学会

The Molecular Biology Society of Japan

日本分子生物学会

The Japanese Vascular Biology and Medicine Organization

日本血管生物医学会

The Japanese Cancer Association

日本癌学会