Dr. Satyandra K. Gupta
Director of the Center for Advanced Manufacturing
University of Southern California
Co-Founder and Chief Scientist at GrayMatter Robotics

Dr. Satyandra K. Gupta holds Smith International Professorship in the Viterbi School of Engineering at the University of Southern California and serves as the Director of the Center for Advanced Manufacturing. He is also Co-Founder and Chief Scientist at GrayMatter Robotics. His research interests are embodied artificial intelligence, computational foundations for decision-making, and human-centered automation. He works on applications related to Manufacturing Automation and Robotics. He has published more than five hundred technical articles in journals, conference proceedings, and edited books. He also holds twenty four patents. He is a fellow of the American Association for the Advancement of Science (AAAS), American Society of Mechanical Engineers (ASME), Institute of Electrical and Electronics Engineers (IEEE), Solid Modeling Association (SMA), and Society of Manufacturing Engineers (SME). He is a former editor-in-chief of the ASME Journal of Computing and Information Science in Engineering. He has received numerous honors and awards for his scholarly contributions. Representative examples include a Young Investigator Award from the Office of Naval Research in 2000, Robert W. Galvin Outstanding Young Manufacturing Engineer Award from SME in 2001, a CAREER Award from the National Science Foundation in 2001, a Presidential Early Career Award for Scientists and Engineers in 2001, Invention of the Year Award at the University of Maryland in 2007, Kos Ishii-Toshiba Award from ASME in 2011, Excellence in Research Award from ASME Computers and Information in Engineering Division in 2013, Distinguished Alumnus Award from Indian Institute of Technology, Roorkee in 2014, ASME Design Automation Award in 2021, Distinguished Alumni Award from Indian Institute of Technology, Delhi in 2022, and Lifetime Achievement Award from ASME Computers and Information in Engineering Division in 2024. He has also received eleven best paper awards at international conferences. He serves as a member of the Technical Advisory Committee for Advanced Robotics for Manufacturing (ARM) Institute and a member of the National Materials and Manufacturing Board (NMMB).

Lorenzo Masia, PhD
Professor Dr (W3)
Chair in "Intelligent BioRobotics Systems"
Executive Director of Munich Institute for Robotics and Machine Intelligence (MIRMI)
School of Computation Information and Technology
Department of Computer Engineering
Technische Universität München
Germany

Keynote Title: Enhancing Human Performance with Wearable Robotics and Machine Learning

Abstract: In the dynamic field of assistive technology, soft wearable exosuits represent a significant breakthrough, setting them apart from traditional rigid exoskeletons. However, the complexity of mastering soft structures is significant: it involves not just handling the non-linear dynamics of the device but also accurately interpreting the physiological signals that are crucial to the exploit a human control loop control. My talk will cover the latest advancements from my team over the past five years, detailing our development of compact, robust, reliable, and efficient exosuits. I will discuss the critical role of integrating biomechanical modelling into control strategies to customize how the machine interacts with the user’s biomechanics, aiming to enhance human performance in tasks like collaborating with industrial manipuilators or improving running endurance. I will also introduce a new method called 'Context Aware Control,' which combines traditional control techniques with machine learning, including artificial vision, to fine-tune the assistance provided. This approach endows our exosuits with the unique ability to adapt to varying external conditions or environmental changes, significantly improving the user's integration with these wearable robotic systems.

Biography: Lorenzo Masia began his career in mechanical engineering with a degree from Sapienza University of Rome in 2003, followed by a PhD from the University of Padua in 2007. His initial steps into robotics were marked by two-year as researcher at MIT's Newman Lab for Biomechanics and Human Rehabilitation, spanning from January 2005 to December 2006.

He took on the role of Team Leader at the Italian Institute of Technology, specifically in the Robotics Brain and Cognitive Sciences Department. By 2013, Masia he was an Assistant Professor at Nanyang Technological University of Singapore in the School of Mechanical & Aerospace Engineering, where he remained until 2018 and later progressed at the University of Twente, where he held the position of Associate Professor in Biodesign. Professor Masia has been at Heidelberg University in Germany (2019-2024), serving as a Full Professor in Biorobotics & Medical Technology, where he founded the ARIES Lab, focusing on Assistive Robotics and Interactive ExoSuits at the Institute of Computer Engineering (ZITI).

From the 1st of October 2024, he is Professor in “Intelligent BioRobotic Systems” and Deputy Director of the Munich Institute for Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM).

Professor Masia's work has garnered international acclaim, evidenced by multiple awards at leading conferences in Biorobotics and Robotic Rehabilitation, including two IEEE Best Paper Awards and three IEEE Best Student Paper Awards, among others. In addition to his research and teaching, Professor Masia holds significant editorial roles with several prestigious journals, IEEE TRO, IEEE RAL, IEEE TNSRE, JNER and Wearable Technologies. He has also played key roles as Program Chair in organizing major IEEE RAS conferences in the field, and he has been the General Chair for IEEE RAS EMBS BIOROB 2024 (1-4 September 2024, Heidelberg, Germany).

Ritu Raman, PhD
Eugene Bell Career Development Assistant Professor
Massachusetts Institute of Technology (MIT)

Keynote Title: Leveraging Biological Actuators for Soft Robotics

Abstract: Human beings and other biological creatures navigate unpredictable and dynamic environments by combining compliant mechanical actuators (skeletal muscle) with neural control and sensory feedback. Abiotic actuators, by contrast, have yet to match their biological counterparts in their ability to autonomously sense and adapt their form and function to changing environments. We have shown that engineered skeletal muscle actuators, controlled by neuronal networks, can generate force and power functional behaviors such as walking and pumping in a range of untethered robots. These muscle-powered robots are dynamically responsive to mechanical stimuli and are capable of complex functional behaviors like exercise-mediated strengthening and healing in response to damage. Our lab uses engineered bioactuators as a platform to understand neuromuscular architecture and function in physiological and pathological states, restore mobility after disease and damage, and power adaptive soft machines. This talk will cover the advantages, challenges, and future directions of understanding and manipulating the mechanics of biological motor control systems.

Biography: Ritu Raman, PhD is the Eugene Bell Career Development Assistant Professor of Mechanical Engineering at MIT. Her lab is centered on 4D tissue engineering of biological actuators for applications in medicine and machines. Ritu's research has received several recognitions including the PECASE, the NSF CAREER Award, the Army Research Office YIP Award, and the Office of Naval Research YIP Award, as well as Rising Star Junior Faculty Awards from the Biomedical Engineering Society and the American Society of Mechanical Engineers. She is also the recipient of the Spira Award for Excellence in Teaching at MIT and the author of the MIT Press book Biofabrication. Ritu received her BS from Cornell University and her PhD as an NSF Fellow with Prof. Rashid Bashir at the University of Illinois at Urbana-Champaign. She completed her postdoctoral research as a L'Oréal For Women in Science Fellow and NASEM Ford Foundation Fellow with Prof. Robert Langer at MIT.

George Haller
ETH

Keynote Title: Nonlinear Spectral Modeling from Data

Abstract: I discuss a dynamical systems alternative to neural networks in the data-driven reduced-order modeling of nonlinear phenomena. Specifically, I show that the recent concept of spectral submanifolds (SSMs) provides very low-dimensional attractors in a large family of mechanics problems ranging from wing oscillations to transitions in shear flows. A data-driven identification of the reduced dynamics on these SSMs gives a mathematically justified way to construct accurate and predictive reduced-order models for solids, fluids and controls without the use of governing equations. I illustrate this on physical problems including the accelerated finite-element simulations of large structures, prediction of transitions to turbulence, reduced-order modeling of fluid-structure interactions, extraction of reduced equations of motion from videos, and model-predictive control of soft robots.

Biography: George Haller is a professor of Mechanical Engineering at ETH Zürich, where he holds the Chair in Nonlinear Dynamics and heads the Institute for Mechanical Systems. His prior appointments include tenured faculty positions at Brown, McGill and MIT. He also served as the inaugural director of Morgan Stanley's fixed income modeling center. Professor Haller is a recipient of a Sloan Fellowship, an ASME Thomas Hughes Young Investigator Award, the Stanley Corrsin Award of the APS, and the Lyapunov Award of the ASME. He is an external member of the Hungarian Academy of Science and an elected fellow of SIAM, APS and ASME.

He currently serves as feature editor at Nonlinear Dynamics and senior editor at the Journal of Nonlinear Science. His research focuses on nonlinear dynamical systems with applications to mechanical vibrations, coherent structures in turbulence, and data- and equation-driven model reduction for physical systems. He has authored three monographs in these areas.

Johannes Gerstmayr
University of Innsbruck

Keynote Title: Applications and opportunities for AI in multibody dynamics

Abstract: Artificial intelligence (AI) and machine learning are redefining the landscape of engineering, in particular multibody dynamics (MBD), opening unprecedented opportunities in simulation, teaching, and industrial applications. Large language models (LLMs) and advanced neural networks are driving innovations that enhance computational efficiency, accuracy, and accessibility in this traditionally complex domain. We present a novel "lab-in-the-loop" approach to systematically evaluate and validate the ability of LLMs to perform virtual MBD experiments. This framework automates the generation of simulation code, validation of conjectures, and extraction of results. For example, the LLM generates a Python-based simulation model to validate a hypothesis about the degrees of freedom in an MBD system, leading to the creation of a synthetic yet validated knowledge base. Preliminary results highlight the potential of this method to automate the assessment of LLM capabilities and fine-tune models for MBD tasks, enabling direct interaction with simulation tools using natural language. We also show that neural networks provide computationally efficient alternatives for tasks like simulating multibody systems at the component level, integrating seamlessly with classical numerical methods such as implicit time integration methods. Furthermore, machine learning techniques excel in real-world applications, such as classifying operating states in multibody dynamic systems using raw acceleration signals, overcoming challenges posed by limited and noisy datasets. Finally, we introduce SLIDE, a deep-learning-based method for predicting dynamic responses in MBD systems. In case of forced oscillations or controlled machines, this method allows to independently estimate input-output sequences, achieving remarkable speedups—up to million times faster—compared to traditional simulations. This method incorporates an error estimator, ensuring a safe application of the method. By highlighting the latest advancements of AI applications for engineering, this presentation emphasizes the outstanding potential of AI in MBD and beyond.

Biography: After finishing his studies in mechatronics, Johannes Gerstmayr started as a research assistant in the special research area SFB13 on Numerical and Symbolical Mathematics within the project “Structural dynamics of elasto-plastic multibody systems” in 1998. He received his doctoral degree at the Johannes Kepler University Linz in 2001. After several research visits to UIC Chicago, IST Lisbon and University Duisburg-Essen with research focus on computational methods for flexible multibody systems, he finished his habilitation in Technical Mechanics in 2007.

In the same year, he joined the Linz Center of Mechatronics (LCM) as a key researcher and became leader of the business unit Dynamics and Control. In 2014 he became full professor at the newly funded Department of Mechatronics at the University of Innsbruck. He received the Wilhelm Macke-Prize in 2005, the Upper Austrian Innovation Award in 2013, and several best paper awards hereafter. His research interests are computational methods for multibody systems, deformable bodies, robotics, machine learning methods and AI. He is associate editor of Multibody System Dynamics and in the editorial advisory board of Acta Mechanica. He served as a reviewer for more than 25 scientific journals, co-authored 70 papers in scientific journals and more than 120 proceedings papers, book chapters and patents.

Walter Lacarbonara
Sapienza University of Rome

Keynote Title: Multi-Bandgap Nonlinear Metamaterials

Abstract: This talk explores 1D and 2D metamaterials featuring a periodic arrangement of highly tunable infinite-dimensional resonators, such as cantilevers with tip masses and spider-web membranes. These resonator-embedded metamaterials exhibit distinctive dispersion characteristics, including the emergence of single and multiple band gaps. The sensitivity of these band gaps to key design parameters is examined. By harnessing tailored geometric and material nonlinearities, the resonators significantly enhance band gap behavior. Using a perturbation approach, we compute nonlinear wave frequencies and waveforms both near and away from internal resonances, showcasing remarkable nonlinear tunability—an essential attribute for advanced applications. To validate our theoretical predictions, we experimentally test various 3D-printed metamaterial samples using 3D laser scanning vibrometry. The results reveal fascinating wave propagation properties and confirm the enhanced performance driven by nonlinear effects.

Biography: Walter Lacarbonara is a Professor of Nonlinear Dynamics at Sapienza University and Director of the Sapienza Center for Dynamics. During his graduate education he was awarded a MS in Structural Engineering (Sapienza University) and a MS in Engineering Mechanics (Virginia Tech, USA), and a PhD in Structural Engineering (Sapienza/Virginia Tech). His research interests cover nonlinear structural dynamics; metamaterials and nanostructured composites; asymptotic techniques; nonlinear control of vibrations; experimental nonlinear dynamics; dynamic stability of structures.

He is Editor-in-Chief of Nonlinear Dynamics, former Associate Editor for ASME Journal of Applied Mechanics, Journal of Vibration and Acoustics, Journal of Sound and Vibration. He served as Chair of the ASME Technical Committee on Multibody Systems and Nonlinear Dynamics, General Co-Chair and technical program Co-Chair of the ASME 2015 (Boston, USA) and 2013 (Portland, USA) IDETC Conferences. He has organized over 10 international symposia/conference sessions and, very recently, the 1st, 2nd, 3rd, and 4th International Nonlinear Dynamics Conferences (NODYCON). His research is supported by national and international sources (EOARD/AFOSR, NSF, European Commission, Italian Ministry of Science and Education). He has published over 250 papers and conference proceedings, 5 international patents (EU/USA/China), 26 book chapters, 9 co-edited Springer books and a single-authored book (Nonlinear Structural Mechanics, Springer, NY) for which he received the 2013 Texty Award nomination by Springer US.