S
Suvranu De
Researcher at Rensselaer Polytechnic Institute
Publications - 383
Citations - 9378
Suvranu De is an academic researcher from Rensselaer Polytechnic Institute. The author has contributed to research in topics: Finite element method & Haptic technology. The author has an hindex of 44, co-authored 360 publications receiving 7813 citations. Previous affiliations of Suvranu De include Indian Association for the Cultivation of Science & University of Washington.
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Haptics in minimally invasive surgical simulation and training
TL;DR: This work discusses important aspects of haptics in MISST, such as haptic rendering and haptic recording and playback, and discusses the importance of net forces resulting from tool-tissue interactions in surgery.
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Mechanical properties of the hexagonal boron nitride monolayer: Ab initio study
Qing Peng,Wei Ji,Suvranu De +2 more
TL;DR: In this article, the elastic response of hexagonal boron nitride monolayer (h-BN) was studied using ab initio density functional theory and the elastic constants of the 2D hexagonal structures were obtained by expanding the elastic strain energy density in a Taylor series.
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Effects of insertion conditions on tissue strain and vascular damage during neuroprosthetic device insertion.
CS Bjornsson,Seung Jae Oh,Yousef Al-Kofahi,Y. J. Lim,Karen L. Smith,James N. Turner,Suvranu De,Badrinath Roysam,William Shain,Sung June Kim +9 more
TL;DR: An ex vivo preparation to capture real-time images of tissue deformation during device insertion using thick tissue slices from rat brains prepared with fluorescently labeled vasculature is developed.
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Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences
Mark Alber,Adrian Buganza Tepole,William R. Cannon,Suvranu De,Salvador Dura-Bernal,Krishna Garikipati,George Em Karniadakis,William W. Lytton,Paris Perdikaris,Linda R. Petzold,Ellen Kuhl +10 more
TL;DR: It is demonstrated that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces.
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The method of finite spheres
Suvranu De,Klaus-Jürgen Bathe +1 more
TL;DR: The method of finite spheres as discussed by the authors is a special case of the meshless local Petrov-Galerkin (MLPG) procedure, where the nodes are placed and the numerical integration is performed without a mesh.