| Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences M Alber, A Buganza Tepole, WR Cannon, S De, S Dura-Bernal, ... NPJ digital medicine 2 (1), 115, 2019 | 710 | 2019 |
| Haptics in minimally invasive surgical simulation and training C Basdogan, S De, J Kim, M Muniyandi, H Kim, MA Srinivasan IEEE computer graphics and applications 24 (2), 56-64, 2004 | 528 | 2004 |
| Mechanical properties of the hexagonal boron nitride monolayer: Ab initio study Q Peng, W Ji, S De Computational Materials Science 56, 11-17, 2012 | 516 | 2012 |
| The method of finite spheres S De, KJ Bathe Computational Mechanics 25 (4), 329-345, 2000 | 453 | 2000 |
| New materials graphyne, graphdiyne, graphone, and graphane: review of properties, synthesis, and application in nanotechnology Q Peng, AK Dearden, J Crean, L Han, S Liu, X Wen, S De Nanotechnology, science and applications, 1-29, 2014 | 435 | 2014 |
| Effects of insertion conditions on tissue strain and vascular damage during neuroprosthetic device insertion CS Bjornsson, SJ Oh, YA Al-Kofahi, YJ Lim, KL Smith, JN Turner, S De, ... Journal of neural engineering 3 (3), 196, 2006 | 431 | 2006 |
| Multiscale modeling meets machine learning: What can we learn? GCY Peng, M Alber, AB Tepole, WR Cannon, S De, S Dura-Bernal, ... Archives of computational methods in engineering: state of the art reviews …, 2020 | 418 | 2020 |
| Outstanding mechanical properties of monolayer MoS 2 and its application in elastic energy storage Q Peng, S De Physical Chemistry Chemical Physics 15 (44), 19427-19437, 2013 | 348 | 2013 |
| Microfluidics-enabled orientation and microstructure control of macroscopic graphene fibres G Xin, W Zhu, Y Deng, J Cheng, LT Zhang, AJ Chung, S De, J Lian Nature nanotechnology 14 (2), 168-175, 2019 | 321 | 2019 |
| Mechanical properties of graphyne monolayers: a first-principles study Q Peng, W Ji, S De Physical Chemistry Chemical Physics 14 (38), 13385-13391, 2012 | 296 | 2012 |
| Achieving interface and environment fidelity in the Virtual Basic Laparoscopic Surgical Trainer A Chellali, H Mentis, A Miller, W Ahn, VS Arikatla, G Sankaranarayanan, ... International journal of human-computer studies 96, 22-37, 2016 | 286 | 2016 |
| Common uses and cited complications of energy in surgery G Sankaranarayanan, RR Resapu, DB Jones, S Schwaitzberg, S De Surgical endoscopy 27 (9), 3056-3072, 2013 | 211 | 2013 |
| Mechanical stabilities of silicene Q Peng, X Wen, S De Rsc Advances 3 (33), 13772-13781, 2013 | 205 | 2013 |
| The method of finite spheres with improved numerical integration S De, KJ Bathe Computers & Structures 79 (22-25), 2183-2196, 2001 | 191 | 2001 |
| Shockwave generates< 100> dislocation loops in bcc iron Q Peng, F Meng, Y Yang, C Lu, H Deng, L Wang, S De, F Gao Nature communications 9 (1), 1-6, 2018 | 170 | 2018 |
| Thermal injury of skin and subcutaneous tissues: A review of experimental approaches and numerical models H Ye, S De Burns 43 (5), 909-932, 2017 | 163 | 2017 |
| A theoretical analysis of the effect of the hydrogenation of graphene to graphane on its mechanical properties Q Peng, C Liang, W Ji, S De Physical Chemistry Chemical Physics 15 (6), 2003-2011, 2013 | 152 | 2013 |
| Using the PhysX engine for physics‐based virtual surgery with force feedback A Maciel, T Halic, Z Lu, LP Nedel, S De The International Journal of Medical Robotics and Computer Assisted Surgery …, 2009 | 145 | 2009 |
| In situ measurement and modeling of biomechanical response of human cadaveric soft tissues for physics-based surgical simulation YJ Lim, D Deo, TP Singh, DB Jones, S De Surgical endoscopy 23 (6), 1298-1307, 2009 | 144 | 2009 |
| Deep learning in fNIRS: a review C Eastmond, A Subedi, S De, X Intes Neurophotonics 9 (4), 041411-041411, 2022 | 129 | 2022 |
S D SchwaitzbergUniversity at BuffaloVerified email at buffalo.edu
