School of Engineering
Showing 1-10 of 21 Results
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Punnag Padhy
Postdoctoral Scholar, Materials Science and Engineering
Current Research and Scholarly InterestsCurrently, I am working on an on-chip platform to simultaneously trap and manipulate micron scale beads and droplets with an intention to implement chemical reactions on a chip at ultrasmall volumes.
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Feng Pan
Postdoctoral Scholar, Materials Science and Engineering
BioFeng Pan is a postdoctoral scholar with Prof. Jennifer A. Dionne in the Department of Materials Science and Engineering at Stanford. He received his Ph.D. in Physical Chemistry at the University of Wisconsin Madison, advised by Prof. Randall H. Goldsmith, and M.S. in Physical Chemistry at Texas A&M University, advised by Prof. Simon W. North, and B.S. in Chemistry at Jilin University (China). His research expertise spans several aspects, including plasmonics, nanophotonics, and single-particle microresonator microscopy and spectroscopy, planar laser-induced fluorescence for molecular tagging velocimetry and thermometry in gaseous flows.
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Aakash Patil
Postdoctoral Scholar, Mechanical Engineering
BioDr. Aakash Patil is a postdoctoral researcher at Stanford University working on deep Learning-assisted predictive modeling for high-dimensional spatio-temporal problems, particularly for turbulence in fluids. At the Center for Turbulence Research he works with Prof. Beverley McKeon as a part of a grant funded by the US Office of Naval Research. His Ph.D. in Computational Mathematics from Mines ParisTech - Paris Sciences et Lettres University led to the development of innovative deep learning methods for nonlinear dynamical systems and the creation of high-performance CPU-GPU frameworks for deep learning-assisted simulations. He was a co-founder of GreenPanda in 2014, a webtech startup catering SMBs, and exited in 2019 after 5 years of successful inclusion of SMBs in India's digital ecosystem.
His expertise includes building deep learning foundation models for high-dimensional spatio-temporal problems, scientific computing, machine learning operations, and quantitative analysis for complex scientific and engineering challenges. Interested in consultations or collaborations? Connect on LinkedIn at https://linkedin.com/in/aakash-patil
