Intelligence and Sensing Lab.

Intelligence and Sensing Lab.

D3 Center

The University of Osaka

About ISLab

ISLab is a research group with Graduate School of Information Science and Technology, the University of Osaka, also known as Artificial Intelligence and Mathematics Group with D3 Center, the University of Osaka.

As a research institute with a mission to provide data science-related technologies to everyone, we are collaborating with various departments in the University of Osaka and other research institutes, as well as companies. As ISLab, a part of the Graduate School of Information Science and Technology, we work with students to motivate them and cultivate their interests in research as well as knowledge in related fields.

We are hiring!

We have multiple open postdoc positions. Click here for more details.

For prospective students

We welcome students who want to work with us. Click here for more details.

Interests

  • Computer Vision
  • Computational Photography
  • Natural Language Processing
  • Pattern Recognition
  • Machine Learning

News

  • 🧠 We will hold a kickoff symposium for the JST Top ASPIRE project at the University of Osaka on April 6, 2026! [link].
  • ✨ New members joined on April 1st, 2026: Prof. Satoshi Yagi, Dr. José Reinaldo, Toshiaki Tanaka, Taiga Hashida, Keiichiro Iwamoto, and Li Han. Welcome!
  • 🎉 Four papers are accepted to CVPR 2026 🎉
    • “BioVITA: Biological Dataset, Model, and Benchmark for Visual-Textual-Acoustic Alignment” by Risa Shinoda, Kaede Shiohara, Nakamasa Inoue, Kuniaki Saito, Hiroaki Santo, and Fumio Okura.
    • “Cell-Type Prototype-Informed Neural Network for Gene Expression Estimation from Pathology Images” by Kazuya Nishimura, Ryoma Bise, Shinnosuke Matsuo, Haruka Hirose, and Yasuhiro Kojima.
    • “EMMA: Concept Erasure Benchmark with Comprehensive Semantic Metrics and Diverse Categories” by Lu Wei, Yuta Nakashima, and Noa Garcia.
    • “Coded-E2LF: Coded Aperture Light Field Imaging from Events” by Tomoya Tsuchida, Keita Takahashi, Chihiro Tsutake, Toshiaki Fujii and Hajime Nagahara.
  • 🎉 One paper is accepted to ICLR 2026 🎉
    • “From Pixels to Semantics: Unified Facial Action Representation Learning for Micro-Expression Analysis” by Yicheng Deng, Hideaki Hayashi, and Hajime Nagahara.

Projects

JST Top ASPIRE 'Deep Sensing: Jointly optimizing sensing and processing for CV/AI applications'
An international collaborative project that aims to generalize the deep sensing framework by jointly optimizing sensing and processing, develop a new computational camera, and apply it to various vision and AI tasks to achieve high accuracy with less data and lower computational cost, while strengthening research collaboration between Japan and the US/Canada.
Construction of an Integrated Analysis Platform for Vision and Omics
We develop machine learning methods for the integrated analysis of image data (Vision) and omics data (Omics), aiming to generate new insights into disease mechanisms, diagnosis, and treatment through multi-modal data fusion.
Label-efficient Medical Image Analysis
We develop label-efficient learning methods—including semi-supervised and weakly supervised learning—to achieve high-accuracy medical image analysis with limited annotated data, reducing the burden of expert annotation in clinical settings.
Optimization of Physical Encoders for Recognition Tasks and an Application to Pathological Diagnosis
Computational Optical Imaging for Endoscopic Surgery
Computational Optical Imaging for Endoscopic Surgery
Knowledge VQA
Visual question answering (VQA) with knowledge is a task that requires knowledge to answer questions on images/video. This additional requirement of knowledge poses an interesting challenge on top of the classic VQA tasks.
Knowledge VQA
Australian History in Newspaper and AI
In collaboration with Prof. Fujikawa at Graduate School of Letters, the University of Osaka, we are working on exploring Australian history through public meetings, of which call for participation appears in newspapers from back then.
Australian History in Newspaper and AI
MLPhys: Foundation of Machine Learning Physics
Throughout its long history, physics has provided the most precise testing ground in the natural sciences, solving problems in various natural hierarchies in collaboration with the mathematical sciences. On the other hand, the field of machine learning is a major research field, a mathematical system that forms the foundation of artificial intelligence and has seen explosive progress in recent years due to advances in computational science. We are launching the transformative research area Machine Learning Physics to integrate these two major fields.
MLPhys: Foundation of Machine Learning Physics
CREST 3D Image Recognition AI for Cancer Diagnosis Support
CREST 3D Image Recognition AI for Cancer Diagnosis Support
Society 5.0 Projects
D3 Center, the University of Osaka is now working on Society 5.0 using information science and technology. In the world of Society 5.0, innovations in IoT, Big Data, robotics, and AI will be part of everyday life, helping people lead active and high-quality lives, creating a super-smart society.
Society 5.0 Projects
Esthetic Dentistry and Optical Analysis
By analyzing the optical properties of various dental restoration materials and dental tissues via optical simulation, the behavior of light in natural teeth and dental restorations is visualized and analyzed for esthetic tooth restorations.
Esthetic Dentistry and Optical Analysis
Brain Pharmaceutics
Coming soon
Brain Pharmaceutics
AI Hospital
The University of Osaka Medical Hospital has launched Artificical Intelligence Center for Medical Research and Application (AIM), which supports physicians, nurses, and all the medical staff collaborating with medical information specialists and data scientists to boost the medical application of AI in daily practices of the hospital.
AI Hospital
Law and AI
This work investigates legal evaluation criteria on the green laws’ participation principle, analyzes Japanese participation system’s pros and cons in a comparative perspective, and propose some recommendations to establish the environmental democracy.
Law and AI
Buddha Face and AI
In collaboration with Prof. Fujioka with Graduate School of Letters/School of Letters, the University of Osaka, we are attempting to create an AI for analyzing various aspects of Buddha faces in images.
Buddha Face and AI

People

View alumni

Faculty

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Hajime Nagahara

Professor

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Hideaki Hayashi

Associate Professor

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Hiroaki Santo

Associate Professor

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Kazuya Nishimura

Assistant Professor

Researchers

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Noa Garcia

Associate Professor (Concurrent)

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Satoshi Yagi

Specially-Appointed Associate Professor

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Atsushi Ashida

Specially-Appointed Assistant Professor

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Bilel Daoud

Specially-Appointed Assistant Professor

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Jovana Panic

Specially-Appointed Researcher/Fellow

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Yankun Wu

Specially-Appointed Researcher/Fellow

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Lucas Deregnaucourt

Specially-Appointed Researcher/Fellow

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José Reinaldo Cunha Santos A. V. Silva Neto

Specially-Appointed Researcher/Fellow

Guest Researchers

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Yuta Nakashima

Professor

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Benjamin Renoust

Guest Associate Professor

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Chenhui Chu

Guest Associate Professor

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Noriko Takemura

Guest Associate Professor

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Hirohiko Niioka

Guest Associate Professor

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Liangzhi Li

Guest Assistant Professor

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Tomoyuki Kajiwara

Guest Associate Professor

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Yiming Qian

Guest Researcher

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Trung Thanh Ngo

Guest Researcher

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Jiachen Cui

Visiting Researcher

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Lee Tsung-Yen

Visiting Researcher

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Niccolo’ Fineschi

Visiting Researcher

Students

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Hugo Lemarchant

PhD Student

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Ziyi Chen

PhD Student

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Yicheng Deng

PhD Student

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Tong Xiang

PhD Student

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Ryan Caesar Ramos

PhD Student

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Patrick John Ramos

PhD Student

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Lu Wei

PhD Student

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Yi Liu

PhD Student

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Varsha Sharma

PhD Student

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Toshiaki Tanaka

PhD Student

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Taiga Hashida

PhD Student

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Lorenzo Querol

Graduate Student

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Naoya Fukui

Graduate Student

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Yuta Murakami

Graduate Student

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Kim Hakumin

Graduate Student

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Ryota Manaka

Graduate Student

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Junqi Wang

Graduate Student

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Bai Jihong

Graduate Student

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Meng Siyuan

Graduate Student

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Keiichiro Iwamoto

Graduate Student

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Shunsuke Anzai

Graduate Student

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Yuji Katagi

Graduate Student

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Kakeru Sako

Graduate Student

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Tushir Sahu

Graduate Student

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Li Han

Graduate Student

Recent Papers

A Hybrid of Generative and Discriminative Models Based on the Gaussian-coupled Softmax Layer
Generative models offer advantageous characteristics for classification tasks, such as the availability of unsupervised data and …
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Applicability of Facial Video-Based Alertness Estimation Model in Real Online and In-Person Classrooms
Accurately capturing learners’ internal states is essential in modern educational environments to support effective teaching and the …
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Auxiliary Gene Learning: Spatial Gene Expression Estimation by Auxiliary Gene Selection
Spatial transcriptomics (ST) is a novel technology that enables the observation of gene expression at the resolution of individual …
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Discriminative Analysis of Autistic Tendencies at 18 Months of Age Using Eye Gaze Characteristics in 4-, 10-, and 18-month-old Infants
Anomalies in motor function and social communication skills constitute early signs of autism spectrum disorder (ASD). In recent years, …
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Gaussian-Based Instance-Adaptive Intensity Modeling for Point-Supervised Facial Expression Spotting
Point-supervised facial expression spotting (P-FES) aims to localize facial expression instances in untrimmed videos, requiring only a …
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See all publications

Contact

  • +81-6-6105-6074
  • 2-8 Yamadaoka, Suita, Osaka 565-0871
  • Enter Techno-Alliance Building C and take the elevator to C503 on Floor 5
  • 9:00 - 17:00
  • DM Me