Next-Generation Big Data & Quantum-Inspired Computing Lab

Who We Are :

We are a research group working at the intersection of large-scale data science and quantum-inspired computation.

Our goal is to develop data-driven methods that address real societal challenges—especially in healthcare, environmental systems, and finance—while preparing for the computational landscape shaped by emerging quantum technologies.

We draw on ideas from quantum computing, but build solutions on today’s high-performance, massively parallel computing platforms.

What We Work On :

Healthcare Analytics at Scale

We analyze population-level medical claims and health records to study disease progression, preventive care, and connections between mental and dental health.

Our methods include deep learning, statistical modeling, and high-throughput data processing.

Environment, Weather & Agricultural Systems

Projects include optimizing drone-based medical delivery, environmental monitoring, wildfire-risk modeling, and international collaborations in smart agriculture.

Financial & Economic Data Science

We integrate data across health, environmental, and financial systems to model risks and markets.

We also explore quantum and quantum-inspired approaches to portfolio optimization and decision-making.

How We Work :

Infrastructure

Our lab runs large-scale computations using HPC clusters, quantum simulators, and leading cloud-based quantum platforms.

Roadmap

We follow a long-term, phased research strategy:

Phase 1 (ongoing): High-impact, real-world data-science outcomes

Phase 2 (3–5 years): Prototyping and validating quantum-inspired and quantum algorithms

Phase 3 (5–10 years): Transitioning to quantum-native workflows where feasible

Collaboration & Community: 

We value interdisciplinary research and maintain collaborations with universities, research institutes, and industry partners in Japan and abroad.

Our projects often bring together expertise from medicine, environmental science, computer science, and economics.

For Prospective Students :

We are looking for students who :

Want to work with large, complex datasets

Care about solving real-world problems

Are curious about healthcare, environmental systems, or finance

Are motivated to learn machine learning, statistics, and programming

Enjoy experimenting with new technologies, including quantum approaches

Appreciate an international and collaborative research environment

No prior background is required—only curiosity, motivation, and a willingness to learn.

Our Vision :

We aim to advance next-generation data science by uniting practical solutions with forward-looking computational innovation.

Our work is driven by a simple idea: big data, when used thoughtfully, can meaningfully improve the world.

Profile: Professor of Suwa University of Science, visiting associate professor of Division of Cardiovascular Medicine, Department of Internal Medicine, Kurume University School of Medicine.

Detailed achievements: Google Schalor, ORCID, Researchmap

Reference IDs: DA18461433, NDL: 00980363, VIAF ID: 256308865, WorldCat Identities: lccn-n2018006921, KAKEN: 60449238, Webcat Plus, Amazon

Contact: Kazuo Ishii, Ph.D.

Department of Applied Information Engineering, 

Faculty of Engineering, Suwa University of Science, 

5000-1 Toyohira, Chino-shi, Nagano 391-0292, JAPAN. 

Tel.(+81)-266-73-1201