Dr. Feng Gu is currently a Professor of Computer Science at College of Staten Island, The City University of New York. He received his B.S. degree in mechanical engineering from China University of Mining and Technology and M.S. degree in information systems from Beijing Institute of Machinery. He obtained his M.S. and Ph.D. degrees in computer science from Georgia State University. His research interests include modeling and simulation, complex systems, and high performance computing. His research has been supported by National Scinece Foundation and National Institute of Justice. He was an assistant professor of computer science from 2010 to 2013 and the chair of department of computer science and mathematics from 2012 to 2013 at Voorhees College, Denmark, South Carolina.
Degrees
Ph.D., Georgia State University
M.S., Georgia State University
M.S., Beijing Institute of Machinery
B.S., China University of Mining and Technology
[1] Zhong, Wei, and Gu, F. A multi-level deep learning system for malware detection. Expert Systems with Applications, 133: 151-162, 2019.
[2] Zhang, X., and Gu, F. Adaptive particle sampling and resampling parallel/distributed particle filters, HPC 2019, 2019 Spring Simulation Multi-Conference, 2019.
[3] Zhang, X., Xiao, J., and Gu, F. Applying support vector machine to electronic health records for cancer classification, MSM 2019, 2019 Spring Simulation Multi-Conference, 2019.
[4] Zhang, X., Mohamed, A., Nguyen, L, and Gu, F. Performance analysis of parallel/distributed particle filters, 2018 Spring Simulation Multi-Conference, 761-771, 2018. (TMS/DEVS 2018 best paper award)
[5] Gu, F. On-demand data assimilation of large-scale spatial temporal systems using sequential Monte Carlo methods. Simulation Modelling Practice and Theory, 85: 1-14, 2018.
[6] Dai, M., He, W., Tian, X., Giraldi, A., and Gu, F. Working with communities on social media varieties in the use of Facebook and Twitter by local police. Online Information Review, 41(6): 782-796, 2017. (Outstanding Paper in the 2018 Emerald Literati Awards)
[7] Yu, N., Yu, Z., Gu, F., and Pan, Y. Evaluating the impact of encoding schemes on deep auto-encoders for DNA annotation, 13th International Symposium on Bioinformatics Research and Applications, 390-395, 2017.
[8] Gu, F. Localized recursive spatial-temporal state quantification method for data assimilation of wildfire spread simulation. Simulation: Transactions of the Society for Modeling and Simulation International, 93(4): 343-360, 2017.
[9] Yu, N., Yu, Z., Gu, F., Li, T., Tian, X., and Pan, Y. Deep learning in genomic and medical image data analysis: challenges and approaches. J Inf Process Syst, 13(2): 204-214, 2017.
[10] Zhang, X., Huang, L., Ferguson-Hull, E., and Gu, F. Adaptive particle routing in parallel/distributed particle filters, 2017 Spring Simulation Multi-Conference, 580-589, 2017.
[11] Liao, S., Xiao, J., Xie, Y., and Gu, F. Towards use of electronic health records: Cancer classification, 2017 Spring Simulation Multi-Conference, 845-854,2017.
[12] Yu, N., Guo, X., Gu, F., and Pan, Y. Signalign: An ontology of DNA as signal for comparative gene structure prediction using information-coding-and-processing techniques. IEEE Transactions on NanoBioScience, 15(2): 119-130, 2016.
[13] Bai, F., Gu, F., Hu, X., and Guo, S. Particle routing in distributed particle filters for large-scale spatial temporal systems. IEEE Transactions on Parallel and Distributed Systems, 27(2): 483-491, 2016.
[14] Gu, F., Syeda, R., and Ai, C. Geo-reference image data assimilation for wildfire spread simulation, 2016 Spring Simulation Multi-Conference, 78-85.
[15] Xie, X., Verbraeck, A., and Gu, F. Data assimilation in discrete event simulations: a rollback based Sequential Monte Carlo approach, 2016 Spring Simulation Multi-Conference, 522-529, 2016.
[16] Yu, N., Yu, Z., Li, B., Gu, F., and Pan, Y. A comprehensive review of emerging computational methods for gene identification. Journal of Information Processing Systems, 21 (1): 1-34, 2016.
[17] Wu, S., Zhang, P., Li, F., Gu, F., and Pan, Y. A hybrid discrete particle swarm optimization-genetic algorithm for multi-task scheduling problem in service oriented manufacturing systems. Journal of Central South University, 23(2): 421-429, 2016.
[18] Gu, F., and Wang, X. Analysis of allele specific expression -- A Survey. Tsinghua Science and Technology, 20(5): 513-529, 2015.
[19] Gu, F., Butt, M., Ai, C., Shen, X., and Xiao, J. Adaptive particle filtering in data assimilation of wildfire spread simulation, 2015 Summer Simulation Multi-Conference, 159-168, 2015.
[20] Yu, N., Guo, X., and Gu, F., and Pan, Y. DNA AS X: An information-coding-based model to improve the sensitivity in comparative gene analysis, 11th International Symposium on Bioinformatics Research and Applications, 366-377, 2015.
[21] Yu, N., Gu, F., Guo, X., and He, Z. A fine-grained flow control model for cloud-assisted data broadcasting, CNS 2015, 2015 Spring Simulation Multi-Conference, 324-331, 2015.
[22] Gu, F. Adaptively perturbing localized state space in data assimilation of wildfire spread simulation. ANSS 2015, 2015 Spring Simulation Multi-Conference, 254-263, 2015. (Runner-up of the best paper award for ANSS 2015)
[23] Ai, C., Zhong, W., Yan, M., and Gu, F. A partner-matching framework for social activity communities. Computational Social Networks, 1:5, 2014.
[24] Guo, X., Yu, N., Gu, F., Ding, X., Wang, J., and Pan, Y. Genome-wide interaction-based association of human Diseases-a survey. Tsinghua Science and Technology, Tsinghua Science and Technology, 9(16), 596-616, 2014.
[25] Ai, C., Zhong, W., Yan, M., and Gu, F. Partner matching applications of social networks. COCOON 2014: 647-656, 2014.
[26] Zheng, X., and Gu, F. Fast Fourier transform on FCC and BCC lattices with outputs on FCC and BCC lattices respectively, Journal of Mathematical Imaging and Vision, 49(3): 530-550, 2014.
[27] Yan, X., Gu, F., Hu, X., and Pan, Y. Dynamic formation control for autonomous underwater vehicles, Journal of Central South University, 2014(21):113-123, 2014.
[28] Yan, X., Gu, F., Hu, X., and Engstrom, C. Dynamic data driven event reconstruction for traffic system using sequential Monte Carlo methods, 2013 Winter Simulation Conference, 2042-2053, 2013.
[29] Xue, H., Gu, F., Hu, X. Data assimilation using sequential Monte Carlo methods in wildfire spread simulation, ACM Transaction on Modeling and Computer Simulation, 22(4):23:1-25, 2012.
[30] Gu, F., Hu, X. Analysis and quantification of data assimilation based on sequential Monte Carlo methods for wildfire spread simulation, International Journal of Modeling, Simulation, and Scientific Computing, 4, 445-468, 2010.
[31] Yan, X., Gu, F., Hu, X., Guo, S. A dynamic data driven application system for wildfire spread simulation, Proc. 2009 Winter Simulation Conference (WSC'09), 2009.
[32] Yan, X., Chen, B., Qian, H., Gu, F., Hu, X. A handover scheme for subnet mobility in heterogeneous networks. World Conference on Engineering, 2009.
[33] Gu, F., Yan, X., Hu, X. State estimation using particle filters in wildfire spread simulation. Proc. 42nd Annual Simulation Symposium (ANSS), 2009 .
[34] Gu, F., Hu, X. Towards applications of particle filter in wildfire spread simulation. Proc. 2008 Winter Simulation Conference (WSC'08), 2008.
[35] Gu, F., Hu, X., Ntaimo, L. Towards validation of DEVS-FIRE wildfire simulation model. Proc. High Performance Computing and Simulation Symposium (HPCS08), part of SpringSim'08, 2008.
[36] Liu, C., Xie, T., Bi, H., and Gu, F. Analysis of MBO in Chinese corporations. Journals of Beijing Institute of Machinery, 17(3): 83-87, 2002.
[37] Gu, F., Lu, T. The study and implementation of web-based office automation. Journals of Beijing Institute of Machinery, 17(3): 40-45, 2002.
Contact Information
Mon. and Wed. 3:00-4:40pm