Background

Dr. Wang’s research interests include Computational and data-enabled science and engineering (CDS&E) and its applications in multiphysics and multiscale systems engineering, including fluid structural interaction, microfluidics/nanofluidics, thermal and energy management, additive manufacturing, among others. The specific focuses are (1) physics-based adaptive modeling, from high-fidelity multiphysics CFD/FEM analysis to reduced order modeling and closed-form modeling for real-time simulation, trade space exploration, and process control; (2) data-driven multi-fidelity surrogate modeling for multidisciplinary analysis and optimization, large-scale system-level simulation, and adaptive model integration; (3) massive and real-time data analytics, discovery, and management, including engineering data mining, parameter estimation, uncertainty quantification, machine learning, and green computing & visualization; and (4) systems engineering of microfluidics/nanofluidics, including model development, system design, control synthesis, hardware development, and experimentation, with the long-term goal towards engineering intelligence

Education

• Ph.D., Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 2005
• M.S., Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 2000
• B.S., Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 1998

Experience 

• Professor, Mechanical Engineering, University of South Carolina, 2024 - Present
• Associate Professor, Mechanical Engineering, University of South Carolina, 2017-2023
• Director, Biomedical and Energy Technologies, CFD Research Corporation, 2014-2017
• Manager, Biomedical and Energy Technologies, CFD Research Corporation, 2011-2014
• Group Leader, Biomedical and Energy Technologies, CFD Research Corporation, 2009-2011
• Senior Engineer, Biomedical and Energy Technologies, CFD Research Corporation, 2007-2009
• Engineer, Biomedical and Energy Technologies, CFD Research Corporation, 2005-2007

Selected Publications

• L. M. Lee, J. M. Rosanoa, Y. Wang*, C. J. Garsona, B. Prabhakarpandiana, K. Pant* G. J. Klarmannc, L. M. Alvarez, and E. Lai, Label-Free Mesenchymal Stem Cells Enrichment from Bone Marrow by Spiral Inertial Microfluidics, Analytical Methods, 10, 713-721, 2018 

• H. Song, J.M.Rosano, Y.Wang*, C.J. Garson, B. Prabhakarpandian, K. Pant, G.J. Klarmann, L.M.Alvarez, E. Lai, Spiral-shaped inertial stem cell device for high-throughput enrichment of iPSC-derived neural stem cells, Microfluid Nanofluid, Vol. 21: 64. DOI:10.1007/s10404-017-1896-5, 2017

• H. Song, J. Rosano, Y. Wang*, C.J. Garson, B. Prabhakarpandian, K. Pant, G.J. Klarmann, A. Perantoni, L.M. Alvarez, and E. Lai, "Identification of Mesenchymal Stem Cell Differentiation State Using Dual-micropore Microfluidic Impedance Flow Cytometry", Analytical Methods, Vol. 8, pp. 7437-7444, 2016. (Cover Story)

• H. Song, J. Rosano, Yi Wang*, et al., “Continuous-Flow Sorting of Stem Cells and Differentiation Products based on Dielectrophoresis", Lab on Chip, 15, Vol. 5, pp. 1320-1328, 2015.

• H. Song, Y. Wang*, C. Garson, K. Pant, "Concurrent DNA Preconcentration and Separation in Bipolar Electrode-Based Microfluidic Device", Analytical Methods, Vol. 7, 1273-1279, 2015. (Cover Story)

• Y. Wang*, H. Song, K. Pant, "A reduced-order model for whole-chip thermal analysis of microfluidic lab-on-a-chip systems", Microfluidics and Nanofluidics, Vol. 16, pp. 369-380, 2014.

•  H. Song, Y. Wang*, J. M. Rosano, B Prabhakarpandian, C. Garson, K. Pant, and E. Lai, "A microfluidic impedance flow cytometer for identification of differentiation state of stem cells", Lab on Chip, Vol. 13, pp. 2300-2310, 2013.