Rui Wu

(252) 328-9682 · wur18@ecu.edu

I am now an associate professor at the East Carolina University. My research interests are machine learning and data visualization.

I received my Ph.D. and Master degree from University of Nevada, Reno and my major is Computer Science and Engineering. My advisors are Dr. Sergiu Dascalu and Dr. Frederick C Harris, Jr. I received my bachelor degree from Jilin University in 2013, majoring in Computer Science.

RA positions are available. If you are interested in research and want to be my research assistant, Please email me your CV, transcripts, TOEFL, and GRE scores, and everything else that you believe will help your application.

Grants

2022/06 - 2025/05: Collaborative Research: IUSE: EHR: A Student-Centered Personalized Learning Framework to Advance Undergraduate Robotics Education, $295,916 (awarded, PI, work with University of Nevada, Reno $320,214. East Carolina University is the lead)

2021/09 - 2023/08: NIH: Characterizing Brain Activation and Postural Response During Concurrent Cognitive Tasks in the Presence of Optic Flow Stimulation: A Functional Near-Infrared Spectroscopy Study, $377,500 (awarded, CoPI)

2020/02 - 2022/01: North Carolina Sea Grant: Mitigating the Effects of Stormwater Flooding in Coastal Regions Using Machine Learning Techniques, $179,437 (awarded, CoPI)

2019/07 - 2020/06: Central Appalachian Regional Education and Research Center (CARERC) Pilot Funding Program: Occupational and Environmental Risk Factors Associated with Poor Health-Related Quality of Life in Central Appalachian Workers with COPD, $15,000 (awarded, CoPI)

2018/11 - 2022/07: NSF IUSE/PFE:RED:PPSE - From Programmers to Professional Software Engineers: Revolutionary Curricular Innovation, Inclusive Pedagogy, and Faculty Development, $2,000,000, (awarded, Senior Personnel)

2018/07 - 2021/06: NSF IUSE:HER - Assessing Virtual Reality Field Experiences for Enhanced Learning in the Geosciences, $599,950 (awarded, Senior Personnel)

Teaching

East Carolina University

2018/08 - present: Teaching CSCI 2405 Discrete Structures II, CSCI 4710/6710 Web Application, CSCI 4120/6120 Machine Learning, CSCI6840 Data Mining, SENG 1020 Data Structure, SENG 1030 Discrete Structures for Software Engineers II, CSCI 3700/SENG 3700 Database Management System, CSCI 6600 Database Management Systems, East Carolina University

University of Nevada, Reno

2018/01 - 2018/05: Co-teaching CS 791V GPU Parallel Computing, University of Nevada, Reno

Research Interests

Machine Learning
  • Data imputation
  • Forecasting
  • Model optimization
Data Visualization
  • Big data visualization and interaction
  • AR/VR data visualization

Publications

Journals (In Preparation)

  • [1] Zhang, Y., Wu, R., Dascalu, S.M. and Harris Jr, F.C., 2024. A Novel Extreme Adaptive GRU for Multivariate Time Series Forecasting, Submitted to Scientific Reports.

Journals (In Print)

  • [J13] Zhang, Y., Wu, R., Dascalu, S.M. and Harris, F.C., 2024. Multi-scale transformer pyramid networks for multivariate time series forecasting. IEEE Access.
  • [J12] Sylcottt, B., Wu, R., Guan, S. and Lin, C.C., 2023. Comparing Brain Activity Between Sitting and Standing Positions during Optic Flow with Coinciding Auditory Cognitive Tasks. Emerging Technologies in Healthcare and Medicine, 116(116).
  • [J11] Wu, R., Scully-Allison, C., Carthen, C., Garcia, A., Hoang, R., Lewis, C., Quijada, R.S., Smith, J., Dascalu, S.M. and Harris Jr, F.C., 2023. vFirelib: A GPU-based fire simulation and visualization tool. SoftwareX, 23, p.101411.
  • [J10] Wu, R., Hamshaw, S., Yang, L., Kincaid, D., Etheridge, R., Ghasemkhani, R. (2022). Data Imputation for Multivariate Time Series Sensor Data with Large Missing Data Gaps. IEEE Sensors Journal, vol. 22, no. 11, pp. 10671-10683.
  • [J09] Li, J., Ablan, C., Wu, R., Guan, S. and Yao, J., 2021. Preprocessing Method Comparisons For VGG16 Fast-RCNN Pistol Detection. EPiC Series in Computing, 76, pp.39-48.
  • [J08] Stellefson, M., Wang, M.Q., Balanay, J.A.G., Wu, R. and Paige, S.R., (2020). Latent Health Risk Classes Associated with Poor Physical and Mental Outcomes in Workers with COPD from Central Appalachian US States. International Journal of Environmental Research and Public Health, 17(18), p.6798.
  • [J07] Stellefson, M., Wang, M.Q., Balanay, J.A.G. and Wu, R., (2020). Health Risk Disparities among Employed Adults with COPD Living in Central Appalachian US States. American Journal of Health Education, pp.1-13.
  • [J06] Gregory, A., Chen, C., Wu, R., Miller, S., Ahmad, S., Anderson, J. W., Barret, H., Benedict, K., Cadol, D., Dascalu, S. M., Delparte, D., Erickson, J., Fenstermaker, L., Godsey, S. E., Harris, F. C., McNamara, J. P., Savickas, J., Sheneman, L., Stone, M., and Turner, M. A. (2020). Efficient Model-data Integration for Flexible Modeling, Parameter Analysis & Visualization, and Data Management. Frontiers in Water, 2020. doi: 10.3389/frwa.2020.00002
  • [J05] Wu, R., Yang, L., Chen, C., Ahmad, S., Dascalu, S. M., and Harris Jr., F. C. (2019). MELPF Version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement, Geoscientific Model Development Discussions, Vol 12, Issue 9, pp 4115-4131, Sept 2019. DOI: 10.5194/gmd-12-4115-2019
  • [J04] Wu, R., Scully-Allison, C., Hossain, M., Painumkal, J., Dascalu, S.M. and Harris, F.C., (2018). Virtual Watershed System: A Web-Service-Based Software Package For Environmental Modeling, Advances in Science, Technology and Engineering Systems Journal, Vol 3, Issue 5: 382-393.
  • [J03] Zhou, Y., Fu, J., Kong, Y. and Wu, R., (2018). How Foreign Direct Investment Influences Carbon Emissions, Based on the Empirical Analysis of Chinese Urban Data. Sustainability, Vol 10, No 7: 2071-1050.
  • [J02] Wu, R., Muhanna, M., Dascalu, S.M., Barford, L. and Harris Jr, F.C., (2016). Data Lossless Compression Using Improved GFC Algorithm With Multiple GPUs, International Journal of Computers and Their Applications. Vol 23, No 4: 232-241.
  • [J01] Zhang, M., Yang, T., and Wu, R. (2012). Space-efficient Multiple String Matching Automata, International Journal of Wireless and Mobile Computing, Vol. 5, No.3: 308-313.

Conferences (Full Paper Refereed)

  • [C28] Shill, P.C., Wu, R., Jamali, H., Hutchins, B., Dascalu, S., Harris, F.C. and Feil-Seifer, D., 2023, October. WIP: Development of a Student-Centered Personalized Learning Framework to Advance Undergraduate Robotics Education. In 2023 IEEE Frontiers in Education Conference (FIE) (pp. 1-5). IEEE.
  • [C27] Finlayson, A., Wu, R., Lin, C.C. and Sylcott, B., 2023, October. Development of a Virtual Reality Application for Oculomotor Examination Education Based on Student-Centered Pedagogy. In 2023 IEEE Frontiers in Education Conference (FIE) (pp. 1-5). IEEE.
  • [C26] Hall, L., Wu, R., Moore, S., Ju, A., Dalyai, R.T. and Zhu, Z., 2022, September. Localization of Human Organs with VR Tracking System and Machine Learning Techniques for Medical Purpose. In Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022) (pp. 1840-1848).
  • [C25] Gajurel, A., Louis, S.J., Wu, R., Barford, L. and Harris Jr, F.C., 2021, February. GPU acceleration of sparse neural networks. In ITNG 2021 18th International Conference on Information Technology-New Generations (pp. 323-330). Cham: Springer International Publishing.
  • [C24] Zhang, Y., Li, J., Carlo, A., Manda, A.K., Hamshaw, S., Dascalu, S.M., Harris, F.C. and Wu, R., 2021, December. Data Regression Framework for Time Series Data with Extreme Events. In Proceedings of the 2021 IEEE International Conference on Big Data (Big Data) (pp. 5327-5336). IEEE.
  • [C23] Lin, H., Wang, P., Blankenship, G.M., Lopez, E. Z., Castro, C.X., Zhu, Z., and Wu, R. (2021). Using Virtual Reality and Machine Learning Techniques to Visualize the Human Spine. In Proceedings of ISCA 30th International Confer, 77, pp.123-132, Online.
  • [C22] Wu, R., Pandurangaiah, J., Blankenship, G.M., Castro, C.X., Guan, S., Ju, A. and Zhu, Z., (2020). Evaluation of Virtual Reality Tracking Performance for Indoor Navigation. In Proceedings of the 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS). pp. 1311-1316. April 2020 Virtual Conference.
  • [C21] Janelle Blankenburg, Richard Kelley, David Feil-Seifer, Rui Wu, Lee Barford, Frederick C Harris, Jr, (2020). Towards GPU-Accelerated PRM for Autonomous Navigation Advances in Intelligent Systems and Computing, Volume 1134, Chapter 74, pp 563-569. In Proceedings of the 17th International Conference on Information Technology: New Generations (ITNG 2020) April 6-8, Las Vegas, NV.
  • [C20] Rakesh Matta, Rui Wu, and Shanyue Guan, (2019). Environmental extreme events detection: A survey. In Proceedings of the 28th International Conference on Software Engineering and Data Engineering, September 30 - October 2, San Diego, CA, USA.
  • [C19] Syed Zawad, Feng Yan, Rui Wu, Lee Barford, and Frederick C. Harris, Jr., (2019). Randomized Benchmarking of Quantum Gates on a GPU. In Advances in Intelligent Systems and Computing, Volume 800, Chapter 42, Elsevier, pp 307-316. Proceedings of the 16th International Conference on Information Technology: New Generations (ITNG 2019) April 1-3, Las Vegas, NV.
  • [C18] Scully-Allison, C., Wu, R., Dascalu, S.M., Barford, L. and Harris, F.C., 2019. Data imputation with an improved robust and sparse fuzzy k-means algorithm. In 16th International Conference on Information Technology-New Generations (ITNG 2019) (pp. 299-306). Springer, Cham.
  • [C17] Hannah Munoz, Sergiu M. Dascalu, Rui Wu, Lee Barford, and Frederick C. Harris, Jr., (2019). Image Processing Using Multiple GPUs on Webcam Image Streams. In Advances in Intelligent Systems and Computing, Volume 800, Chapter 44, Elsevier, pp 325-332. Proceedings of the 16th International Conference on Information Technology: New Generations (ITNG 2019) April 1-3, Las Vegas, NV.
  • [C15] Daniel A. Lopez, Rui Wu, Lee Barford, and Frederick C. Harris, Jr., (2019). A Memory Layout for Dynamically Routed Capsule Layers. In Advances in Intelligent Systems and Computing, Volume 800, Chapter 44, Elsevier, pp 317-324. Proceedings of the 16th International Conference on Information Technology: New Generations (ITNG 2019) April 1-3, Las Vegas, NV.
  • [C14] Wu, R., Painumkal, J., Dascalu, S.M. and Harris, F.C., (2018). Budget and User Feedback Control Strategy-Based PRMS Scenario Web Application. In Proceedings of the 15th International Conference on Information Technology-New Generation, April 16 to 18, Las Vegas, Nevada, USA, Elsevier, pp. 491-498.
  • [C13] Hossain, M., Wu, R., Painumkal, J.T., Kettouch, M., Luca, C., Dascalu, S.M. and Harris Jr, F.C., (2017). Web-Service Framework For Environmental Models. In Proceedings of IEEE Conference on Internet Technologies & Applications 2017 (ITA 2017). September 12-15, Wrexham, North Wales, UK. (6 pages).
  • [C12] Wu, R. Painumkal, J. Dascalu, S. M., and Harris Jr, F.C., (2017). Self-managed Elastic Scale Hybrid Server Using Budget Input and User Feedback. In Proceedings of the 12th Workshop on Feedback Computing, as part of the Proceedings of the 14th International Conference on Autonomous Computing, July 17-21, 2017, Columbus, Ohio. (6 pages).
  • [C11] Kettouch, M., Luca, C., Khorief, O., Wu, R. and Dascalu, S., (2017). Semantic Data Management in Smart Cities. In Proceedings of IEEE Optimization of Electrical & Electronic Equipment Aegean Conference on Electrical Machines & Power Electronics (OPTIM-ACEMP 2017), May 25-27, Brasov, Romania, pp. 1126-1131
  • [C10] Hossain, M., Munoz, H., Wu, R., Fritzinger, E., Dascalu, S.M. and Harris, F.C., (2017). Becoming DataONE Tier-4 Member Node:Steps Taken by the Nevada Research Data Center. In Proceedings of Optimization of Electrical & Electronic Equipment Aegean Conference on Electrical Machines & Power Electronics (OPTIM-ACEMP 2017). May 25-27, Brasov, Romania, pp. 1089-1094.
  • [C09] Wu, R., Painumkal, J.T., Volk, J.M., Liu, S., Louis, S.J., Tyler, S., Dascalu, S.M. and Harris, F.C., (2017). Parameter Estimation of Nonlinear Nitrate Prediction Model Using Genetic Algorithm. In Proceedings of IEEE Congress on Evolutionary Computation 2017 (CEC 2017), June 5-8, San Sebastian, Spain, pp. 1893-1899.
  • [C08] Liu, S., Louis, S.J., Jiang, T. and Wu, R., (2017). Increasing Physics Realism When Evolving Micro Behaviors for 3D RTS Games. In Proceedings of IEEE Congress on Evolutionary Computation 2017 (CEC 2017), June 5-8, San Sebastian, Spain, pp. 2465-2472.
  • [C07] Wu, R., Painumkal, J.T., Randhawa, N., Palathingal, L., Hiibel, S.R., Dascalu, S.M. and Harris, F.C., (2016). A New Workflow to Interact with and Visualize Big Data for Web Applications. In Proceedings of the 2016 International Conference on Collaboration Technologies and Systems (CTS 2016), October 31-November 4, Orlando, FL, pp. 302-309.
  • [C06] Palathingal, L., Wu, R., Belkhatir, R., Dascalu, S.M. and Harris, F.C., (2016). Data Processing Toolset for the Virtual Watershed. In Proceedings of the 2016 International Conference on Collaboration Technologies and Systems (CTS 2016), October 31-November 4, Orlando, FL, pp. 281-287.
  • [C05] Wu, R., Chen, C., Ahmad, S., Volk, J., Luca, C., Harris, F., and Dascalu, S. (2016). A Real-time Web-based Wildfire Simulation System. In Proceedings of the 2016 IEEE Industrial Electronics Conference (IECON 2016), Oct 24-27, 2016, Florence, Italy, pp. 4964-4969.
  • [C04] Wu, R., Dascalu, S., Barford, L., and Harris, F. (2016). Floating-Point Data Compression Using Improved GFC Algorithm. In Proceedings of the 25th International Conference on Software Engineering and Data Engineering (SEDE 2016), September 26-28, Denver, CO, pp. 35-40.
  • [C03] Wu, R., Dascalu, S., and Harris, F. (2015). Environment for Datasets Processing and Visualization Using SciDB. In Proceedings of the 24th International Conference on Software Engineering and Data Engineering (SEDE 2015), October 12-14, San Diego, CA, pp. 223-229.
  • [C02] Wu, R., Palathingal, L., Dascalu, S., and Harris, F. (2015). Concentration Reminder: Distraction and Drowsiness Detection for Computer Users. In Proceedings of the 2015 International Conference on Computers and Their Application (CATA 2015), March 9-11, 2015, Honolulu, HI, pp. 113-118.
  • [C01] Wu, R., Redei, A., Palathingal, L., and Dascalu, S. (2014). Waldo3D: Printing 3D models from 2D pictures. In Proceedings of the Twenty-Third International Conference on Software Engineering and Data Engineering, October 13-15, New Orleans, Louisiana, pp. 125-130.