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Events
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Nov18
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The rotator cuff as a bi-material interface
Abstract:
Joining of dissimilar materials is a fundamental challenge in engineering. Nature presents a highly effective solution at the attachment of tendon to bone ("enthesis") in the rotator cuff of the shoulder’s humeral head. The natural enthesis does not regrow following healing or surgery, resulting in inferior tissue and in post-surgical tear recurrence rates as high as 94%. Pressing needs exist both to understand the mechanobiology of adhesion and toughening across hierarchical scales in the healthy enthesis, and to reconstitute these in healing.
Our results show the tendon to bone insertion to be a hierarchical, heterogeneous, disordered system that uses randomness to tailor strain fields, and to maximize the fraction of tissue involved in resisting injury-level stresses. Based upon this model, we are developing two new mechano-medicine products for clinical translation: a diagnostic technology to evaluate the degree to which an enthesis is succeeding in physiological strain redistribution, and a repair technology that mimics the mesoscale function of the healthy enthesis by maximizing the fraction of tissue involved in resisting injury-level stresses. This talk will summarize our understanding of the mechanics of tendon-to-bone attachment, and describe repair and imaging technologies under development that harness this with the goal of providing improved surgical outcomes.
Bio:
Guy M. Genin studies the mechanobiology of interfaces and adhesion. He is the Harold and Kathleen Faught Professor of Mechanical Engineering at Washington University in St. Louis, serving on the faculties of Mechanical Engineering & Materials Science, Biomedical Engineering, and Neurological Surgery. He is also Thousand Talents Plan Professor of Life Sciences at Xi'an Jiaotong University in Xi'an, China, and co-director of the Center for Engineering Mechanobiology, a joint NSF Science and Technology Center between Penn, Washington University, with several satellite sites. Prof. Genin serves as chief engineer for Washington University's Center for Innovation in Neuroscience and Technology and is active in several start-ups. He co-chairs the NIH/Interagency Modeling and Analysis Group's working group on integrated multiscale biomechanics experiment and modeling. Prof. Genin's training includes B.S.C.E. and M.S. degrees from Case Western Reserve University, S.M. and Ph.D. degrees in solid mechanics from Harvard, and post-doctoral training at Cambridge and Brown. Prof. Genin is the recipient of a number of awards for engineering design, teaching, and research, including a Research Career Award from the NIH, the ASME Skalak Medal, and the Changjiang Scholar Award from the Chinese Ministry of Education. He is a fellow of ASME and AIMBE.
TIME Monday, November 18, 2019 at 3:00 PM - 4:00 PM
LOCATION L211, Technological Institute map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering
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Feb19
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Future aerospace platforms, from aerial systems and spacecraft, need to meet rising demands for acoustic and electromagnetic interference (EMI) mitigation, operation in harsh environments, and payload maximization, all while reducing mass. In this talk, we will discuss our work addressing some of these challenges by uniting biological design principles with machine intelligence to create and reliably fabricate multifunctional structures. First, we will present our work on bioinspired aeroacoustic designs, where drawing inspiration from owl feathers and cicada insect wings, we create a three-dimensional sinusoidal-serration drone propeller that achieves quieter flight while improving propulsive efficiency relative to an industry benchmark. Second, we will share how electromagnetic response emerges from structure, as mechanical metamaterial lattices and chameleon-inspired reconfigurable architectures enable lightweight, load-bearing EMI shielding with switchable absorption and transmission. Finally, we will connect these multifunctional designs to smart additive manufacturing where computer vision and deep learning can detect and correct fused filament fabrication anomalies in real-time. We will discuss how vision transformer-based models can ensure process robustness even under noisy, limited-data conditions, and how we quantify environmental effects, such as humidity and vibration, to establish a pathway toward adaptive manufacturing in real-world environments. This work illustrates a new paradigm where geometry, intelligence, and manufacturing co-evolve to enable rapid development of next-generation multifunctional aerospace systems.
Bio
Dr. Grace X. Gu is an Associate Professor of Mechanical Engineering at the University of California, Berkeley and currently holds the Don M. Cunningham Endowed Professorship. She received her PhD and MS in Mechanical Engineering from the Massachusetts Institute of Technology and her BS in Mechanical Engineering from the University of Michigan, Ann Arbor. The research interests of the Gu Group focus on creating new materials and devices with superior properties for mechanical, biological, and aerospace applications through computational modeling and machine learning, as well as developing AI-driven manufacturing processes to realize complex material designs. Gu is the recipient of several awards, including the Presidential Early Career Award for Scientists and Engineers (PECASE), ARO Early Career Program Award, DARPA Young Faculty Award, AFOSR Young Investigator Award, ONR Young Investigator Award, LLNL Early Career UC Faculty Initiative Award, SES Young Investigator Medal, ASME Sia Nemat-Nasser Early Career Award, MIT Technology Review 35 Innovators Under 35, and Sloan Research Fellowship. Gu has co-organized symposiums at various conferences and serves as an editor of the Journal of Intelligent Materials Systems and Structures and Composites Science and Technology. She organizes an annual 3D printing workshop at Berkeley aimed at inspiring the next generation of students to pursue careers in science and engineering.
TIME Thursday, February 19, 2026 at 11:00 AM - 12:00 PM
LOCATION A230, Technological Institute map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering (ME)
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Mar9
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Formal methods - mathematical techniques for describing systems, capturing requirements, and providing guarantees - have been used to synthesize robot control from high-level specification, and to verify robot behavior. Given the recent advances in robot learning and data-driven models, what role can, and should, formal methods play in advancing robotics? In this talk I will give a few examples for what we can do with formal methods, discuss their promise and challenges, and describe the synergies I see with data-driven approaches.
Bio
Hadas Kress-Gazit is the Geoffrey S.M. Hedrick Sr. Professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University, and the Associate Dean for Diversity and Academic Affairs of Cornell Duffield College of Engineering. She received her Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania in 2008 and has been at Cornell since 2009. Her research focuses on formal methods for robotics and automation, and more specifically on high-level specifications and synthesis for robot control. Her group has explored different types of robotic systems including modular robots, soft robots, and swarms, and how formal methods can be used for human-robot interaction. She received an NSF CAREER award in 2010, a DARPA Young Faculty Award in 2012, Cornell Engineering’s Excellence in teaching award in 2013 and 2019, and excellence in research award in 2021. She is an IEEE Fellow and has served on DARPA’s Information Science and Technology study group (ISAT), as the program chair for Robotics: Science and Systems (RSS) 2018, the program chair for the International Conference on Robotics and Automation (ICRA) 2022, and the president of the RSS board (2019-2023), among other leadership positions in the robotics community.
TIME Monday, March 9, 2026 at 3:00 PM - 4:00 PM
LOCATION LR3, Technological Institute map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering (ME)
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Mar12
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Programmable materials and structures hold great potential for various applications, such as robotics, biomedical devices, and civil structures. The rational design, physical realization, and validation of programmed behaviors in these systems play important roles in enabling functional devices. To encode desired mechanical functionality into structures, we propose a multi-material multi-objective topology optimization approach to inverse design composite structures that achieve complex target mechanical responses under large deformations. The multi-material framework simultaneously optimizes both the geometry, material heterogeneity, and architecture to achieve target behaviors and functionalities. A library of diverse designs is created, showcasing a wide range of precisely programmed nonlinear responses, such as multi-bulking and multi-plateau. In general, the properties of materials and structures typically remain fixed after being constructed. To enable reprogrammable behaviors, we develop a multi-physics topology optimization approach to discover magneto-active and temperature-active materials that achieve tunable buckling and switchable shape morphing, controlled by magnetic fields and temperature fields, respectively. The obtained systems exhibit one response under one stimulus and switch to a distinct response by applying another stimulus. To bridge the gap between simulation and fabrication, we explore multi-material manufacturing techniques, introduce advanced path generation methods, and develop direct ink writing (DIW) techniques to fabricate a suite of mechanical, magnetic, and thermal metamaterials and metastructures and experimentally validate their programmed behaviors. The excellent agreement among target, simulation, and experiment demonstrates that the proposed optimization-driven framework, when integrated with hybrid manufacturing techniques, has the potential to systematically design, inform, and create innovative multi-functional materials and structures for various engineering applications.
Bio
Dr. Xiaojia Shelly Zhang is a David C. Crawford Faculty Scholar and Associate Professor at the Department of Civil and Environmental Engineering and the Department of Mechanical Science and Engineering at the University of Illinois at Urbana Champaign (UIUC). She directs the MISSION (MuIti-functional Structures and Systems desIgn OptimizatioN) Laboratory. Dr. Zhang holds B.S. and M.S. degrees from UIUC and a Ph.D. degree from Georgia Tech. Her research explores multi-physics topology optimization, inverse design, stochastic learning algorithms, and additive manufacturing to develop multi-functional, sustainable, and resilient materials, structures, and robots for applications at different scales. She is the recipient of the National Science Foundation CAREER Award (2021), the ASME Journal of Applied Mechanics Award (2022), the DARPA Young Faculty Award (2022), the AFOSR Young Investigator Award (2023), the Leonardo da Vinci Award from ASCE (2024), the DARPA Director's Fellowship (2024), UIUC Campus Distinguished Promotion Award (2025), the Thomas J.R. Hughes Young Investigator Award from ASME (2025), the ASME Henry Hess Early Career Publication Award (2025), the Haftka Young Investigator Award from International Society for Structural and Multidisciplinary Optimization (2025), and Huajian Gao Young Investigator Medal from SES (2026). Dr. Zhang serves on the Executive Committee of the International Society of Structural and Multidisciplinary Optimization (ISSMO) and is a Review Editor for the Journal of Structural and Multidisciplinary Optimization and an Associate Editor for the Journal of Applied Mechanics.
TIME Thursday, March 12, 2026 at 11:00 AM - 12:00 PM
LOCATION A230, Technological Institute map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering (ME)