We open Season 5 of the CDFAM podcast with a keynote presentation from the CDFAM Computational Design Symposium NYC 2025 by Markus J. Buehler, McAfee Professor of Engineering at MIT.
In this session, Buehler outlines how AI is becoming an autonomous partner in scientific discovery—capable not only of analysis but of generating new knowledge. Drawing on examples from materials science and bioengineering, he presents multi-agent AI systems designed to reason, hypothesize, and evolve—creating a framework for discovery engines that extend the boundaries of human-led research.
Buehler’s work brings together reinforcement learning, graph-based reasoning, and physics-informed generative models, with case studies showing applications in medicine, food, agriculture, and beyond.
Organization:
MIT
Presenter:
Markus J. Buehler
McAfee Professor of Engineering
Massachusetts Institute of Technology
Presentation Abstract
AI is rapidly transitioning from a passive analytical assistant to an active, self-improving partner in scientific discovery.
In the material world, this shift means developing systems that not only recognize patterns but also reason, hypothesize, and autonomously explore new ideas for design, discovery and manufacturing.
This talk presents emerging approaches toward ‘superintelligent’ discovery engines -integrating reinforcement learning, graph-based reasoning, and physics-informed neural architectures with generative models capable of cross-domain synthesis.
We explore multi-agent systems inspired by collective intelligence in nature, enabling continuous self-evolution as they solve problems.
Case studies from materials science, engineering and biology illustrate how these systems can uncover hidden structure-property relationships, design novel materials, and accelerate innovations in medicine, food, and agriculture.
These advances chart a path toward AI that actively expands the boundaries of human knowledge in engineering.
Speaker Bio
Markus J. Buehler is the McAfee Professor of Engineering at MIT and a pioneer in AI‑driven knowledge discovery. He created powerful graph‑aware, multi‑agent AI platforms that turn heterogeneous data into science-grounded actionable insight, powering breakthroughs in materials science, biology and healthcare. Buehler is among the world’s most‑cited materials scientists and the recipient of numerous honors, including the Feynman Prize, ASME Drucker Medal, J. R. Rice Medal, and the Washington Award. He is a member of the U.S. National Academy of Engineering. For more than a decade he has also taught executive and technical professionals at MIT, shaping the next generation of leaders in engineering, knowledge discovery, and artificial intelligence.
