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SUMMARY:MechE Seminar: Soft Matters - The Future of Human-Machine Interact
 ion
DTSTART:20250211T090000
DTEND:20250211T100000
DTSTAMP:20260503T033304Z
UID:29037b7ff67d23fa1bda43d8ef82646866d382b0fd1f509161fd663f
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Cosima Du Pasquier\, Department of Mechanical Engineering\
 , Stanford University\nAbstract: Would you trust a machine to bathe your g
 randmother\, comb her hair\, or blow her nose? The robotic systems of toda
 y are mostly used for the Three Ds (dull\, dirty\, or dangerous tasks). Wi
 th advances in computing efficiency\, AI\, and mobile sensing\, robotic sy
 stems are set to become ubiquitous in our daily lives\, creating new oppor
 tunities to better support our growing elderly population\, reduce workloa
 ds\, and improve both accessibility and quality of healthcare.\n\nOne cruc
 ial challenge remains: standard rigid machines are unsettling to interact 
 with. They can also be unsafe\, requiring massive computational effort to 
 prevent accidents. If we want to bring robots into hospitals and our homes
 \, they must be able to safely and naturally handle physical interaction w
 ith humans. In other words\, the future of human-machine interaction must 
 be soft.\n\nImagine medical systems as personalized as tailored suits—se
 amlessly interacting with soft tissues\, providing gentle yet strong suppo
 rt\, and delivering intuitive tactile feedback.\nCustomizing such devices 
 is complex\, and safe interactions are often hindered by slow\, trial-and-
 error development. Soft materials offer inherent safety and comfort by con
 forming to the body\, absorbing impacts\, and enabling adaptive interactio
 ns. Yet harnessing their potential for real-world applications requires so
 lving major hurdles in reproducible and scalable fabrication\, effective f
 orce transmission\, and accurate predictive modeling.\n\nIn this talk\, I 
 will show how I have started addressing these challenges\, streamlining de
 sign and reducing waste by using a combination of innovative manufacturing
  processes and\ncomputational methods. Ultimately\, these advances enable 
 scalable\, personalized\, and intrinsically safe solutions for communicati
 on\, clinical applications\, and beyond.\n\nBiography: Dr. Cosima du Pasqu
 ier is a Postdoctoral Scholar in the Department of Mechanical Engineering 
 at Stanford University\, working under the guidance of Allison Okamura. Co
 llaborating with academic partners at the Massachusetts Institute of Techn
 ology (MIT)\, Georgia Tech\, and the University of Houston. Her research c
 enters on computational modeling\, design\, and fabrication of soft materi
 als for human-robot interaction. Dr. du Pasquier earned her BSc\, MSc\, an
 d PhD in Mechanical Engineering from ETH Zurich in 2014\, 2017\, and 2022 
 respectively. Her PhD dissertation was awarded the ETH Medal. Dr. du Pasqu
 ier’s research combines structural mechanics\, materials\, and computati
 onal design. During her PhD at the Engineering Design and Computing (EDAC)
  Lab at ETH Zurich\, she focused on modeling and optimizing deformation of
  morphing structures using soft printed actuators. In her postdoc\, she fo
 cuses streamlining the design of assistive technologies\, such as rehabili
 tative devices for stroke survivors and wearable haptic platforms. Dr. du 
 Pasquier’s work has appeared in a number of leading journals\, including
  Science Robotics\, Soft Robotics\, Additive Manufacturing\, and Structura
 l and Multidisciplinary Optimization. During her MSc and PhD\, she collabo
 rated with academic partners from MIT\, which culminated in the founding o
 f the startup Rapid Liquid Printing Co.\, for which she is an advisor. Her
  current work is funded by the U.S. National Science Foundation through th
 e Convergence Accelerator and Human-Centered Computing programs. Dr. du Pa
 squier further broadens her perspective on the societal impact of emerging
  technologies through her affiliation with Stanford’s Hoover Institution
 \, where she contributes to interdisciplinary discussions on robotics and 
 policy.
LOCATION:BM 5202 https://plan.epfl.ch/?room==BM%205202 https://epfl.zoom.u
 s/j/68342218492
STATUS:CONFIRMED
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