School of Engineering
Showing 201-287 of 287 Results
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Jasmin E. Palmer
Ph.D. Student in Mechanical Engineering, admitted Autumn 2019
BioJasmin earned a Bachelor of Science in Mechanical Engineering with a concentration in Controls, Instrumentation, and Robotics at the Massachusetts Institute of Technology (MIT) and a Master of Science in Mechanical Engineering at Stanford University. Jasmin is currently pursuing her Ph.D. in Mechanical Engineering at Stanford University and conducting research with faculty supervisor Professor Allison Okamura in the Collaborative Haptics in Robotics in Medicine (CHARM) Lab. Jasmin’s Ph.D. research centers around human-computer interaction and haptics, the science of and relating to the sense of touch. Developing technology that provides beneficial haptic feedback to human operators requires a multi-pronged and interdisciplinary approach. Her work leverages concepts from psychology and neuroscience to understand human perception, experimental design, and statistical analysis, and also applies her engineering background in dynamic modeling of physical systems and mechatronic system development in order to develop novel designs for wearable devices. The goal of her thesis is to develop an adaptable simulation framework that provides realistic haptic feedback for humans to perform various dexterous manipulation tasks in dynamic virtual reality (VR) and mixed reality (MR) environments using wrist-worn tactile devices. Jasmin wants to become an inspiration for other women of color to pursue careers in STEM fields. Jasmin also enjoys composing music, playing the flute, and studying foreign languages.
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Skyler St. Pierre
Ph.D. Student in Mechanical Engineering, admitted Autumn 2020
Current Research and Scholarly Interestsbiomechanics, machine learning, computational modeling
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Peter Xie
Ph.D. Student in Mechanical Engineering, admitted Autumn 2023
BioResearch:
Engineer developing hydrogels for cancer immunotherapies -
Hanfeng Zhai
Ph.D. Student in Mechanical Engineering, admitted Autumn 2023
BioWorking on combining multiscale and multiphysics computational modeling with scientific machine learning and design optimization for mechanical and materials design in various engineering fields in biomedicine, semiconductors, and manufacturing. Previous works include Bayesian optimization for antibiofilm surfaces, porous metamaterials, physics-informed learning for bubble dynamics, molecular dynamics of graphene, etc. Have industrial experience in multiscale modeling for semiconductor manufacturing at Tokyo Electron.
