王骏超博士，副研究员，硕导。研究方向包括设计自动化，机器学习，医学检测等。2017年毕业于美国加州大学河滨分校获生物工程博士学位，2018年以第六层次人才入职杭州电子科技大学射频电路与系统教育部重点实验室任教至今。已发表13篇学术论文，3篇发表于微流控行业顶级期刊Lab on a Chip，其中2篇被选为封面文章。他也是Phi Beta Kappa国际奖学金获得者。
联系方式：junchao@hdu.edu.cn
学术成果：
20211.Zhang N, Zha K,Wang J*. Exploring the Design Efficiency of Random Microfluidic Mixers. IEEE Access, 2021.
2.Wang, J.*, Zhang, N., Chen, J., Su, G., Yao, H., Ho, T. Y., & Sun, L. (2021). Predicting the fluid behavior of random microfluidic mixers using convolutional neural networks. Lab on a Chip, 21(2), 296-309. (Cover)
20201.Wang, J.*, Su, G., Wan, C., Huang, X., & Sun, L. (2020). A Keyword-Based Literature Review Data Generating Algorithm—Analyzing a Field from Scientific Publications. Symmetry, 12(6), 903.
2.Chen, J.,Wang, J., Xuan, W., Dong, S., & Luo, J. (2020). Universal Triboelectric Nanogenerator Simulation Based on Dynamic Finite Element Method Model. Sensors, 20(17), 4838.
20191.Ma, K., Sun, L., Wang, Y., &Wang, J.(2019, August). Classification of blood cancer images using a convolutional neural networks ensemble. In Eleventh International Conference on Digital Image Processing (ICDIP 2019) (Vol. 11179, p. **). International Society for Optics and Photonics.
2.Wang, J.*, Zhang, N., Chen, J., Rodgers, V. G., Brisk, P., & Grover, W. H. (2019). Finding the optimal design of a passive microfluidic mixer. Lab on a Chip, 19(21), 3618-3627. (Cover)
3.Ji, W., Ho, T. Y.,Wang, J., & Yao, H. (2019). Microfluidic design for concentration gradient generation using artificial neural network. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(10), 2544-2557.
20181.Huang, X., Chen, J., Liu, J., Li, Y.,Wang, J., Xuan, W., & Guo, J. (2018, November). Lensfree Microfluidic On-chip Flowing Cell Imaging with Integrated Surface Acoustic Wave Pumping. In 2018 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA) (pp. 172-173). IEEE.
2.Wang, J.*, Fu, L., Yu, L., Huang, X., Brisk, P., & Grover, W. H. (2018, July). Accelerating Simulation of Particle Trajectories in Microfluidic Devices by Constructing a Cloud Database. In 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) (pp. 666-671). IEEE.
Before 20181.Wang, J., Rodgers, V. G., Brisk, P., & Grover, W. H. (2017). Instantaneous simulation of fluids and particles in complex microfluidic devices. PloS one, 12(12), e**.
2.Wang, J., Rodgers, V. G., Brisk, P., & Grover, W. H. (2017). MOPSA: A microfluidics-optimized particle simulation algorithm. Biomicrofluidics, 11(3), 034121.
3.Wang, J., Brisk, P., & Grover, W. H. (2016). Random design of microfluidics. Lab on a Chip, 16(21), 4212-4219.
4.Yuning, S. U., Ye, N. I.,Junchao, W. A. N. G., Zhihao, X. U., & Zhihao, S. U. N. (2012). Two-enzyme coexpressed recombinant strain for asymmetric synthesis of ethyl (R)-2-hydroxy-4-phenylbutyrate. Chinese Journal of Catalysis, 33(9-10), 1650-1660.