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In this talk, Bryan Moser of the MIT System Design and Management at the Massachusetts Institute of Technology explores how organizations—particularly in Japan—can evolve from experience-driven decision-making to model-based transformation (MBX). Drawing on decades of research and field experience, he explains why traditional R&D and management approaches are under pressure from globalization and rapid technological change, and how interactive, computational models can strengthen portfolio decisions, improve collaboration, and accelerate innovation.

The 2026 MIT Japan Conference showcased the innovation ecosystem of MIT, bringing together faculty, industry leaders, and MIT-connected startups to explore breakthroughs shaping the future of science, technology, and business transformation.

Alex Shalek, Director of the Institute for Medical Engineering and Science (IMES), examines how chronic environmental and metabolic stress alters cell behavior and drives tissue dysfunction. The talk highlights cutting-edge single-cell and spatial multi-omics research revealing how prolonged stress reshapes liver cell identity, promotes cancer-associated pathways, and predicts poorer health outcomes. It also introduces new computational and high-throughput screening platforms designed to identify regulators of cellular balance and accelerate discovery of strategies that strengthen tissue health and resilience.

Alex Shalek explores how chronic stress reshapes liver cell function and drives tissue dysfunction. Using single-cell multi-omics, spatial transcriptomics, and integrative computational methods, Shalek reveals early changes in hepatocytes that precede disease and demonstrates a new high-throughput platform to discover strategies for improving tissue health and resilience.

Introducing MIT Learn

Kathleen Kennedy
Executive Director, MIT Center for Collective Intelligence
Senior Director, MIT Horizon

By bringing together MIT’s digital learning portfolio and embedding AI-driven capabilities, MIT Learn is a platform for continuous, adaptive, and lifelong learning for the world.

Introducing MIT Learn Kathleen Kennedy, Executive Director, MIT Center for Collective Intelligence, Senior Director, MIT Horizon

MIT Learn | https://learn.mit.edu/ By bringing together MIT’s digital learning portfolio and embedding AI-driven capabilities,

MIT Learn is a platform for continuous, adaptive, and lifelong learning for the world. 

Associate Professor Faez Ahmed, Associate Professor, MIT Department of Mechanical Engineering, explores how generative AI is transforming engineering design beyond simple pattern-matching. The talk examines the challenges of applying AI to precision-driven fields, showcases case studies in areas like kinematics and topology optimization, and demonstrates AI co-pilots that merge multimodal models with engineering tools. It highlights how performance-focused generative AI can enable innovative, feasible, and high-functioning designs while accelerating innovation and democratizing access to advanced design capabilities.