Organized by
Join us for a unique two-day event organized by the TEES Center of Innovation in Mechanics for Design and Manufacturing, that brings together practitioners and researchers to explore the intersection of mechanics, design, manufacturing, and artificial intelligence. The workshop will delve into how mechanics principles, physics-based modeling, data sensing, and actuation inform and expand the capabilities of physical AI—creating adaptive, high-performance engineered systems.
Sessions will feature technical talks, tutorials, poster presentations, and interactive case studies to promote collaboration and knowledge sharing.
Partnering with
Registration
Seats are limited! Please register early to secure your spot.
For any queries, contact
Megan Simison – [email protected]
Raj Kota – [email protected]
Venue
Texas A&M University School of Engineering Medicine
1020 Holcombe Blvd,
Houston, TX 77030
Hotel Accommodation
A room block has been reserved at the DoubleTree by Hilton Houston Medical Center Hotel & Suites for workshop attendees. Participants may book their accommodations using the link below:
Hotel Reservation Link: https://group.doubletree.com/m5mu8u
Workshop Highlights
Day 1 – Infusing Physics and Physical Constraints into Machine Learning
- Technical talks covering geometrical and manufacturing constraints in ML/AI tools
- Applied case studies
- In-depth anchor tutorial on integrating mechanics/physics/manufacturing constraints into AI models
- Q&A session
- Poster presentations and networking dinner
Day 2 – Embedding Intelligence in Physical Systems & Future Directions
- Technical talks addressing AI in cyber-physical systems, manufacturing operations, robotics, and digital twins
- Anchor tutorial
- Keynote/broad outlook session on foundation models for engineering
- Open discussion and participant survey to shape future research directions
- Networking opportunities
Speakers
N. K. Anand
Regents Professor and the Marcus C. Easterling Chair Professor, J. Mike Walker ’66 Department of Mechanical Engineering
Dr. N. K. Anand is a Regents Professor and the Marcus C. Easterling Chair Professor in the Department of Mechanical Engineering at Texas A&M University. Since joining the faculty in 1985, he has held numerous leadership positions, including Interim Dean of Engineering, Executive Associate Dean, Vice President and Vice Provost for Faculty Affairs. An expert in thermal sciences, fluid mechanics, and computational fluid dynamics, his research integrates advanced numerical techniques, physics-informed neural networks, and reduction-order modeling. He has authored over 100 technical articles and co-authored a foundational textbook on finite element and volume methods. An ASME Fellow, Dr. Anand’s contributions have earned top honors, including the ASME James Harry Potter Gold Medal (2020) and the Edwin F. Church Medal (2026). He earned his Ph.D. from Purdue University, where he also received the 2026 Outstanding Mechanical Engineer Award.
Ye Wang
Founder CEO – EverCurrent
Ye Wang is the Founder and CEO of EverCurrent, where she builds AI that aligns priorities and identifies execution risks across complex hardware and manufacturing operations. A researcher, engineer, and entrepreneur operating at the intersection of software and physical systems, Ye has spent nearly two decades scaling foundational platforms for the design and build ecosystem. Her track record includes shaping Onshape (the first cloud CAD platform), co-founding Join (a collaborative delivery platform for complex construction), and leading generative AI initiatives for automotive design at Autodesk Research.
As Physical AI advances, cross-functional complexity grows exponentially at the system level, rapidly increasing coordination overhead and cross-functional friction. Ye’s work directly addresses this bottleneck, pioneering the intelligent infrastructure needed to capture tacit engineering knowledge, streamline multi-tool workflows, and accelerate physical innovation.
Matthew Mueller
Academic Program Manager – nTop
Matthew Mueller earned his PhD in Mechanical Engineering from Tufts University, where his research focused on Engineering Education. After teaching engineering design for 2 years at Tufts, Matt spent 5 years working for Onshape by PTC where he pioneered research into collaborative CAD and CAD analytics, publishing in CAD & Applications and Advanced Engineering Informatics, as well as presenting work at ASEE and ASME IDETC-CIE conferences. He now leads the academic programs at nTop, collaborating with researchers pushing the boundaries of implicit modeling for aircraft design and AI engineering, publishing and presenting work at AIAA conferences and ASME IDETC-CIE.
Ulisses Braga-Neto
Professor, Electrical and Computer Engineering, Texas A&M University
Ulisses Braga-Neto received his Ph.D. in Electrical and Computer Engineering from The Johns Hopkins University in 2002. He is currently a Professor in the Electrical and Computer Engineering Department at Texas A&M University. His research focuses on Machine Learning and Statistical Signal Processing. Dr. Braga-Neto is the founding Director of the Scientific Machine Learning Lab at the Texas A&M Institute of Data Science (TAMIDS). He has published two textbooks and more than 170 peer-reviewed journal articles and conference papers. Dr. Braga-Neto received the NSF CAREER Award in 2009.
Jacob Moore
Research Professor, Mississippi State University
Dr. Jacob Moore is a Research Professor at Mississippi State University’s Institute for Systems Engineering Research (ISER). He has a PhD in Mechanical Engineering, and his research focuses on developing numerical methods for high-order hydrodynamics. For his dissertation, he developed the first arbitrary-order 3D nodal Discontinuous Galerkin method for Lagrangian hydrodynamics. He also has a background in simulation techniques for multi-scale materials modeling using the Integrated Computational Engineering approach, which builds models starting with density functional theory calculations and bridging each length scale. His current work focuses on automating the verification and validation of the solvers in the Fierro Mechanics code and adding new high-performance GPU portable solvers for engineering applications leveraging modern HPC systems.
Linqi Zhuang
Senior Staff Application Engineer, Synopsys
Linqi Zhuang is a Senior Staff Application Engineer at Synopsys, where he leads the development of simulation solutions for AI/ML-augmented engineering simulation, composite materials, structural durability, and electronics reliability using Ansys technologies within the Synopsys portfolio. Dr. Zhuang holds a Ph.D. in Polymeric Composites from Luleå University of Technology, Sweden, and a second Ph.D. in Aerospace Engineering from Texas A&M University.
Technical Committee
- Arun Srinivasa
Professor, Associate Dean for Student Success, J.N. Reddy Chair in Applied Mechanics, Mechanical Engineering - Kalyan Raj Kota
Senior Research Engineer III – TEES MKOC, Program Manager – OESI - Prabhakar Pagilla
Associate Dept. Head for Research and Operations, Professor, James J. Cain Professor II, Mechanical Engineering - Raj Kumar Pal
Assistant Professor, Mechanical Engineering - Vinayak Krishnamurthy
Associate Professor, J. Mike Walker ’66 Career Development Professor, Mechanical Engineering
Conference Secretariat
TEES Center of Innovation in Mechanics for Design and Manufacturing
J. Mike Walker ’66 Department of Mechanical Engineering,
Texas A&M University, College Station, Texas 77843-3123 USA
U.S. National Science Foundation
