Reimagining 3D IC Design: Where Multiphysics Meets AI
AI-powered design space exploration for multiphysics-aware 3D IC and chiplet integration.
3D IC design has evolved beyond the point where traditional EDA flows can keep up. Stacking dozens of chiplets and millions of interconnects into a single package multiplies thermal, mechanical, and electrical interactions faster than engineering teams can analyze them. Power, performance, area, cost, and reliability decisions that once happened sequentially must now be evaluated concurrently at the system level.
The challenge is not simply predicting performance. Thermal hotspots, thermo-mechanical stress, and power/signal integrity issues are often determined by architectural and packaging decisions made long before detailed implementation begins. When these issues are discovered late in the design cycle, the cost of mitigation can be significant.
In this webinar, Andras Vass-Varnai and Sudarshan Deo will demonstrate how multiphysics-driven workflows bring thermal, thermo-mechanical, and signal and power integrity analysis into the earliest stages of 2.5D and 3D IC development, enabling engineers to identify and address reliability risks while there is still time to influence the architecture.
What you'll learn
How early thermal, thermo-mechanical, and power integrity analysis can uncover reliability risks before they become costly late-stage issues
Where multiphysics co-analysis should be introduced in the design flow to guide architecture and packaging decisions
How AI-powered design space exploration accelerates evaluation of chiplet, package, and system architectures while maintaining multiphysics insight
How AI agents can automate and orchestrate complex simulation workflows, enabling faster and more informed engineering decisions
Who should attend
This session is built for design, packaging, and reliability engineers working on chiplet-based or 2.5D/3D IC systems, along with engineering managers evaluating how AI fits into their multiphysics and reliability workflows.
Why Siemens
Siemens is uniquely positioned to help engineering teams address the challenges of advanced 3D ICs by bringing together robust 3D IC and package design technologies with comprehensive thermal, thermo-mechanical, and electrical multiphysics solutions. This enables reliability and performance considerations to be evaluated much earlier in the development process, when architectural decisions have the greatest influence on outcomes. By connecting design, multiphysics analysis, and AI-driven automation within a common workflow, Siemens helps teams gain insight into complex system interactions without requiring deep expertise in every physical domain, allowing them to identify issues sooner and converge on better designs faster.
Building on this foundation, they will show how AI technologies are transforming the design process. Attendees will see how AI-powered design space exploration can evaluate thousands of architecture and packaging options with far fewer simulations, and how AI agents can automate and orchestrate complex multiphysics workflows, helping engineering teams move from analysis-driven design to intelligence-driven design.
Meet the speakers
Andras holds MSc and PhD degrees in Electrical Engineering from the Budapest University of Technology and Economics. He spent over a decade at Mentor Graphics as a product manager, leading R&D projects focused on thermal test hardware and methodologies, and later served as a business development lead in South Korea and the United States.
Now based in Chicago and working as a 3D IC reliability solution engineer, he's contributing to the development of a novel 3D IC package toolchain, drawing on his background in thermal and reliability engineering. His interests include thermal management of electronic systems, thermal transient testing and modeling, semiconductor packaging, TIM material characterization, and reliability testing of semiconductor devices.
Sudarshan leads the development of AI-native engineering platforms for advanced semiconductor design at Siemens Digital Industries Software, enabling intelligent workflows for 3D ICs, chiplets, advanced packaging, and multiphysics analysis.
He holds a Master's degree in Computer Science from California State University, Sacramento, where his thesis focused on convolutional neural networks for image recognition. With experience spanning Siemens, Intel, Synopsys, and Cadence, he specializes in applying AI to accelerate semiconductor engineering and advance next-generation EDA technologies.
Samir Jaber is an editor, writer, and industry expert on topics of technology, science, and engineering. He is the editor-in-chief of the 2025, 2024, and 2023 Edge AI Technology reports with Wevolver. Samir is the Chief Editor and Founder of Wryters, a content marketing and consulting agency. He has comprehensive experience working with Fortune 500 companies and industry leaders as a writer, editor, content manager, and consultant.
He is an online content specialist with an academic background in mechanical engineering, nanotechnology, and scientific research. Samir is also a featured author in 30+ industrial magazines with a focus on Artificial Intelligence (AI), the Internet of Things (IoT), 3D printing, Autonomous Vehicles (AV), nanotechnology, materials science, and sustainability. His experience includes award-winning engineering research and patented engineering design in the fields of nanofabrication and microfluidics.