Explore the principles and importance of unified simulation frameworks and how COMSOL enables engineers to model within a single computational environment.

How True Multiphysics Simulation Helps Engineers Design Better Products Faster

<h2 id="isPasted">Where Simulation Meets the People Building What's Next</h2>Modeling and simulation have moved from specialized engineering tools to a shared language across aerospace, energy, life sciences, mobility, semiconductor manufacturing, and electronics development. The COMSOL Conference exists to put the technical users, researchers, students, and the managers trying to get more out of their simulation teams in the same room to focus on solving one question: how is multiphysics modeling actually changing what gets built?<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789484701366-CC26_web_Keynotes-1.png" class="fr-fic fr-dii" />Keynotes. Source: COMSOL Conference. <h3>What to Expect</h3>Five editions run this fall, each drawing its own regional community into the same core program: keynote talks from industry leaders, poster and slideshow presentations on live research and design work, and 20+ minicourses that cut across engineering disciplines rather than sticking to one. Every pass includes access to keynotes, presentations, minicourses, the exhibition hall, evening events, receptions, meals, and refreshments.Minicourses form the technical backbone at both events: instructor-led, hour-long sessions covering modeling techniques, software functionality, and the theory underneath them, each with live demos in COMSOL Multiphysics® and a closing Q&amp;A. Sessions have been designed to serve both new users and experienced ones. Demo stations pair attendees one-on-one with COMSOL applications engineers on their own modeling projects rather than sending them home with a technique to test alone.<a href="https://www.comsol.com/conference">See the full conference program.</a><h3>COMSOL Conference 2026: Five Editions, One Community</h3>Same program architecture, different regional centers. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789485099244-COMSOL+Conference+2026+.2.jpg" class="fr-fic fr-dii" />Talks, Minicourses, &amp; User Presentations. Source: COMSOL Conference.<h3>COMSOL Conference 2026 Cambridge</h3>September 23–25 · Churchill College, CambridgeThe Cambridge edition draws technical teams and entrepreneurs from across EMEA, and the people who keep coming back describe the same value in different ways. Eleonora Manoli of Barilla Group has attended multiple editions and calls the mix of technical talks, plenaries, and hands-on minicourses a consistent source of fresh ideas across simulation fields. Alexey Popov of VTT Technical Research Centre of Finland points to the access itself — the chance to sit down with a COMSOL engineer and work through a specific simulation challenge in depth.Keynote talks include:<ul><li>Douglas Herbert of Rolls-Royce discusses the challenges and opportunities of developing advanced electrical machines for aerospace.</li><li>Dr. Jonathan Horne-Jones of the UK Atomic Energy Authority (UKAEA) presents his approach to identifying and evaluating simulation capabilities in fusion engineering solutions.</li><li>Raju Yalagada of Airbus will discuss how simulation plays a vital role in the aerospace industry.</li><li>James Ellis of Oxford Instruments Plasma Technology (OIPT), joins to talk about predictive science in plasma processing.</li><li>Dr. Christian Geitner of Fraunhofer UMSICHT presents a multiscale COMSOL model for a two-story moving DRI reactor with a 1.7 m reaction zone.</li><li>François Cornat of CorWave dives into the role of numerical simulation in the development of ventricular assist devices.</li><li>Robert Mathershaw of Dstl highlights case studies where the COMSOL Multiphysics® software addresses a range of defense challenges.</li></ul>Engineers and researchers from organizations like Tetra Pak, STMicroelectronics, and Johnson Matthey present their modeling work through slideshows and posters, walk through methodology, share results, and take questions directly, turning the exhibition hall into a working session rather than a trade floor.<a href="https://www.comsol.com/conference/cambridge#pricing-section" target="_blank" rel="noopener noreferrer">Register for Cambridge</a><h3> COMSOL Conference 2026 Boston</h3>October 7–9 · Boston Marriott BurlingtonSpeakers from NASA, Intel, General Motors, MIT, Formula E, Rice University, Vertex Pharmaceuticals, and Oak Ridge National Laboratory anchor the Boston program, each speaking to how modeling and simulation moves their work from concept to result. Keynote sessions put them on stage to walk through the modeling decisions behind their most demanding engineering problems, supplemented with Q&amp;A, plus a COMSOL-led keynote giving an early look at an upcoming version of the software.The Boston edition also runs the COMSOL Innovation Contest, raising the stakes on the user-presentation format: six finalists across aerospace and defense, automotive and mobility, energy, life sciences, manufacturing, and semiconductors present their work live, competing for a $50,000 grand prize and a $5,000 popular-vote award.<a href="https://www.comsol.com/conference/boston#pricing-section" target="_blank" rel="noopener noreferrer">Register for Boston</a><h3>COMSOL Conference 2026 Tokyo</h3>October 21–22 · Akasaka Intercity Conference, TokyoThe Tokyo edition brings the same architecture to Japan's simulation community: keynote talks from industry leaders, poster sessions, and presentations from invited speakers, aimed at giving technical users, R&amp;D-track students, and team leads a shared look at where modeling and simulation are heading next. As with every stop on the tour, the program is built to work through discipline lines rather than around them, so an attendee working in electronics can walk out with a technique that started in life sciences or energy.<a href="https://www.comsol.com/conference/tokyo#pricing-section" target="_blank" rel="noopener noreferrer">Register for Tokyo</a><h3>COMSOL Conference 2026 Shenzhen</h3>October 22–23 · Sheraton ShenzhenLanding the day after Tokyo closes, the Shenzhen edition gives China's simulation community its own stop on the tour, with the same keynote, minicourse, and poster-session structure running under it. Poster presentations carry particular weight here: attendees vote directly on their favorites, and the conference names up to three Best Poster by Popular Vote winners on the final day, judged by committee when submissions tie.<a href="https://www.comsol.com/conference/shenzhen#pricing-section" target="_blank" rel="noopener noreferrer">Register for Shenzhen</a><h3>COMSOL Conference 2026 Bengaluru</h3>December 3–4 · Hyatt Centric Hebbal, BengaluruThe Bengaluru edition brings minicourses in modeling workflow, electromagnetics, structural &amp; acoustics, fluid &amp; heat, chemical engineering, and more. Join us December 3 and 4 for minicourses, talks, six keynote sessions, and the COMSOL award ceremony. Attendees of the COMSOL Conference 2026 Bengaluru will have the opportunity to win various awards for innovative uses of the COMSOL Multiphysics®. 2026's awards include:<ul><li>2 Best Paper awards selected by the program chair</li><li>2 Best Poster awards selected by the program chair</li><li>1 Best Poster award by popular vote</li></ul><a href="https://www.comsol.com/conference/bengaluru" target="_blank" rel="noopener noreferrer">Register for Bengaluru</a>

The COMSOL Conference provides a space for technical teams and entrepreneurs to meet in person, exchange ideas, and learn from each other. Join us for the COMSOL Conference 2026 in a city near you.

COMSOL Conference 2026: Connecting the Minds Behind Innovation

Researchers in the Carnegie Mellon University School of Computer Science are rethinking how artificial intelligence learns about the physical world, with implications for everything from robotics to scientific discoveries. Their new project, Sim2Reason, explores a training approach that immerses AI systems in physics-based environments where they can learn through observation and interaction. Rather than relying solely on human-written explanations and static data, Sim2Reason places large language models inside virtual worlds governed by the laws of physics. “For a long time, AI has learned science by reading what humans have already written,” said Deepak Pathak, the Raj Reddy assistant professor in CMU’s <a href="https://www.ri.cmu.edu/" target="_blank" rel="noreferrer noopener">Robotics Institute</a>. “With Sim2Reason, we’re taking a different approach — letting models learn directly from the laws of nature through simulation. Instead of memorizing solutions, they learn by observing how the world evolves, much like scientists do.”By grounding AI in physical experience, this approach could help robots improve their ability to understand the physical world. It could also accelerate scientific discovery by enabling AI systems to generate and test hypotheses in simulated settings, uncovering patterns and insights that would be difficult for humans to explore alone. Early results show that models trained this way can solve complex physics problems, including those from the <a href="https://ipho-unofficial.org/" target="_blank" rel="noreferrer noopener">International Physics Olympiad</a>, a rigorous global competition for high school students that features challenging theoretical and experimental physics problems. Sim2Reason allows AI models to learn through simulated experimentation. Within these environments, objects collide, roll, oscillate and respond to forces to generate continuous streams of data. From these interactions, the system constructs its own reasoning challenges and learns to solve them, gradually building an internal model of how the physical world works. Because real-world physical data can be difficult, expensive or unsafe to collect at scale, this approach offers a way to generate unlimited, high-quality training data directly from simulation. In doing so, the system moves AI closer to how science itself progresses: not by memorizing answers, but by discovering the laws that generate them.The CMU team’s approach marks a departure from how many advanced language models are trained. Traditionally, these systems rely on a vault of human-written text, absorbing knowledge that has already been interpreted and distilled. Sim2Reason shifts learning toward direct observation, enabling models to form implicit hypotheses and reason about underlying laws based on what they “see” unfold in the simulations.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1778070472134-Sim2Reason-Embed-Photo.png" style="width:100%px" class="fr-fic fr-dib" />At the core of the project is a simple idea: physics simulators already encode the rules of nature, so they can and should serve as powerful teaching tools.  Sim2Reason constructs virtual scenarios such as blocks sliding down inclines, pulleys in motion or objects colliding, then simulates their dynamics over time. As the system records variables like force, velocity and momentum, it also generates questions about these scenes, such as when an object will hit the ground, how momentum evolves after a set period or what mass would produce a given trajectory. Because the simulator governs the environment, it also provides the correct answers, effectively transforming itself into a self-generating teacher capable of producing an unlimited supply of physically grounded problems.To learn from this data, the researchers trained language models to solve progressively more complex problems. Over time, the models learned to follow chains of physical interactions, estimate properties like mass or force, and then apply what they’d learned to new situations.  The work points toward a broader shift in how AI systems may be trained. Instead of relying solely on human-generated knowledge, future systems may learn by observing, experimenting and reasoning about the world.Along with Pathak, the Sim2Reason research team included RI Ph.D. student Mihir Prabhudesai; RI master’s student Aryan Satpathy; Yangmin Li, a CMU graduate now at Nvidia; Zheyang Qin, a CMU graduate now at SkildAI; SCS undergraduate Nikash Bhardwaj; Amir Zadeh, a CMU graduate now at Lambda; Chuan Li, chief science officer at Lambda; and Katerina Fragkiadaki, the JPMorgan Chase Associate Professor of Computer Science in CMU’s Machine Learning Department.

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How True Multiphysics Simulation Helps Engineers Design Better Products Faster

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