Mechanical Engineering
Showing 101-120 of 592 Results
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Steven Hartley Collins
Associate Professor of Mechanical Engineering and, by courtesy, of Bioengineering
BioSteve Collins is an Associate Professor of Mechanical Engineering at Stanford University, where he teaches courses on design and robotics and directs the Stanford Biomechatronics Laboratory. His primary focus is to speed and systematize the design and prescription of prostheses and exoskeletons using versatile device emulator hardware and human-in-the-loop optimization algorithms (Zhang et al. 2017, Science). Another interest is efficient autonomous devices, such as highly energy-efficient walking robots (Collins et al. 2005, Science) and exoskeletons that use no energy yet reduce the metabolic energy cost of human walking (Collins et al. 2015, Nature).
Prof. Collins received his B.S. in Mechanical Engineering in 2002 from Cornell University, where he performed undergraduate research on passive dynamic walking robots. He received his Ph.D. in Mechanical Engineering in 2008 from the University of Michigan, where he performed research on the dynamics and control of human walking. He performed postdoctoral research on humanoid robots at T. U. Delft in the Netherlands. He was a professor of Mechanical Engineering and Robotics at Carnegie Mellon University for seven years. In 2017, he joined the faculty of Mechanical Engineering at Stanford University.
Prof. Collins is a member of the Scientific Board of Dynamic Walking and the Editorial Board of Science Robotics. He has received the Young Scientist Award from the American Society of Biomechanics, the Best Medical Devices Paper from the International Conference on Robotics and Automation, and the student-voted Professor of the Year in his department. -
Murray Connelly Cutforth
Affiliate, Mechanical Engineering - Mechanics and Computation
BioMurray Cutforth is a research scientist on the PSAAP III project at the Center for Turbulence Research. He works with Professor Eric Darve on uncertainty quantification of laser-ignited turbulent combustion. During his PhD at the University of Cambridge, Murray studied sharp interface methods for multi-material flow, and subsequently has worked on applications of machine learning in medical image and text analysis in industry.
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Mark Cutkosky
Fletcher Jones Professor in the School of Engineering
BioCutkosky applies analyses, simulations, and experiments to the design and control of robotic hands, tactile sensors, and devices for human/computer interaction. In manufacturing, his work focuses on design tools for rapid prototyping.
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Rafaela Da Silva Presa
Graduate Visiting Researcher Student, Mechanical Engineering
BioRafaela is a master in Bioengineering (Molecular Biotechnology branch) since 2019 by Faculty of Engineering of University of Porto, Portugal (FEUP)/ School of Medicine and Biomedical Sciences of University of Porto (ICBAS) with her MSc thesis done in the field of biomaterials for bone cancer treatment and regeneration simultaneously.
Rafaela is performing her PhD project in Biofabrication Group in the Institute for Innovation and Research in Health from University of Porto (i3s). The project is focused on the development of mechano-modulatory 3D in vitro model of human skin fibrosis. Currently, Rafaela is doing a period abroad at Chaudhuri Lab, Mechanical Engineering department at Stanford University, to study the impact of viscoelasticity in fibroblast fate and activation.
Moreover, she is enrolled in the International Doctoral Program in Cellular and Molecular Biotechnology Applied to Health Sciences (BiotechHealth) in ICBAS from University of Porto.
Her multidisciplinary background in bioengineering and biomaterials allowed her to develop strong skills in complementary research areas ranging from materials synthesis and biofabrication to cellular biology.
Rafaela has excellent communication skills and experience in presenting scientific data in national and international meetings. -
Eric Darve
Director, Institute for Computational and Mathematical Engineering (ICME) and Professor of Mechanical Engineering
Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for science and engineering, large-language models, transformer models, surrogate and reduced order modeling, stochastic inversing, anomaly detection, numerical linear algebra, high-performance, parallel, and GPU computing.
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David Davidson
Sr Research Engineer, Mechanical Engineering
BioEducation
University of Toronto Physics B.S (1978)
University of Toronto Aerospace Sciences M.Sc. (1980)
York University Physics Ph.D. (1986)
Appointment:
1986-present Senior Research Engineer, Mechanical Engineering Department
Research Activities:
Dr. Davidson’s research interests span the fields of gas dynamics and combustion kinetics. During his tenure at Stanford University he investigated the chemical kinetics of combustion using a wide array of optical and laser-based diagnostic methods and advanced the use of these diagnostics in shock tubes. He co-authored over 350 research publications with his students and Professor Ronald Hanson. He continues to advise and mentor the graduate students who use shock tubes in the High Temperature Gasdynamics Laboratories. An overview of the shock tube studies performed at Stanford under Prof. Hanson’s and Dr. Davidson’s supervision can be found in the report entitled “Fundamental Kinetics Database Utilizing Shock Tube Measurements” available at http://purl.stanford.edu/kb621cw6967.
He claims he is now retired, but apparently, he is still working. -
Scott L. Delp, Ph.D.
Director, Wu Tsai Human Performance Alliance at Stanford, James H. Clark Professor in the School of Engineering, Professor of Bioengineering and of Mechanical Engineering
Current Research and Scholarly InterestsExperimental and computational approaches to study human movement. Development of biomechanical models to analyze muscle function, study movement abnormalities, design medical products, and guide surgery. Imaging and health technology development. Discovering the principles of peak performance to advance human health. Human performance research. Wearable technologies, video motion capture, and machine learning to enable large-scale analysis.
