Hanqi Zhuang

Hanqi Zhuang

Associate Dean and Professor

Department of Electrical Engineering and Computer Science

777 Glades Road, EE 403A

Boca Raton, FL 33431-0991

p: 561.297.3413

zhuang@fau.edu

Education

  • Ph.D., Electrical Engineering, Florida Atlantic University, 1989
  • M.S., Electrical Engineering, Florida Atlantic University, 1986
  • B.S., Electrical Engineering, Shanghai University, 1982

Research Interests

  • Signal Processing and Machine Learning
  • Robotics and Computer Vision
  • Biomedical Applications: Cancer Diagnosis, Seizure Detection, Emotion Detection and Classification
  • Marine Animal Sound Detection and Classification

Current Sponsored Research

  1. Cherubin, L., H. Zhuang and J. VanZwieten, “Loop Current System SSH and subsurface current prediction with a transfer learning approach,” $350,000, Gulf Research Programs, National Academies of Science, Engineering and Medicine, January 1, 2020 to June 30, 2021.
  2. Cherubin, L., M. Ajemian, H. Zhuang and N. Erdol, “Unveiling the ‘grouper guard’ - the first line of subtropical coastal defense to UUVs via integrated acoustic smart-sensing.” DARPA, $6,000,000, Ref #:HR001118S0027-PA-016, Nov. 2018-Nov. 2023.
  3. Zhu, H., H. Zhuang, T. Khoshgaftaar, D. Pados, and L. Cherubin, “MRI: Acquisition of Artificial Intelligence & Deep Learning (AIDL) Training and Research Laboratory,” NSF #1828181, $652,850, 10/1/2018-9/30/2023.
  4. Ali Zilouchian, Nancy Romance, Nurgun Erdol, and Hanqi Zhuang, “HSI‐ STEM & Articulation Program: An Articulated State College‐University Framework for Increasing Graduation Rates of Hispanic and Low‐income Students in Computer Science,” Department of Education. Total award: $4,456,707, 10/01/2016‐09/30/2021.

previous sponsored research

Refereed Journal Articles1

  1. Gorday, P., N. Erdol, and H. Zhuang, "Complex-Valued Neural Networks for Noncoherent Demodulation," IEEE Access, to appear.
  2. Wang, J., H. Zhuang, L.M. Cherubin, A. Ali, and A. Muhamed-Ali, “Medium-Term Forecasting of the LCS and its Eddy Formations in GoM with a Divide-and-Conquer Machine Learning Approach,” J. Geophysical Research, 124(8), 5586-5606, July 2019.
  3. Muhamed Ali, A., H. Zhuang, A. K. Ibrahim, “Multi-pose facial expression recognition using Rectangular HOG feature extractor and Label-Consistent KSVD classifier”. IJBM, in press, 2019.
  4. Ibrahim, A., H Zhuang, L.M. Chérubin, M.T. Schärer Umpierre, A.M. Ali, R. S Nemeth, and N. Erdol. “Classification of Red Hind Grouper Call Types using Random Ensemble of Stacked Autoencoders”. J. Acoustical Society of America, 146 (4), 2155-2162, 2019
  5. Rehman, O., H. Zhuang, A. Ibram, A. Muhamed Ali, and Z. Li, “Validation of miRNAs as Breast Cancer Biomarkers with a Machine Learning Approach.” Cancers, 11(3), 431, 2019.
  6. Muhamed Ali, A., H. Zhuang, A. Ibrahim, O. Rehman, M. Huang, and A. Wu, “A Machine Learning Approach for the Classification of Kidney Cancer Subtypes Using miRNA Genome Data,” Applied Science, 8(12), 2018.
  7. Ibrahim, A., H. Zhuang, L.M. Cherubin, and N. Erdol, “Automatic Classification of Grouper Species by Their Sounds using Deep Neural Networks,” J. Acoustical Society of America - EL, Vol. 144, No. 3, 2018.
  8. Ibrahim, A., L.M. Cherubin, H. Zhuang, M.T. S. Umpierre, F. Dalgleish, N. Erdol, B. Ouyang, and A. Dalgleish, “An Approach for Automatic Classification of Grouper Vocalizations with Passive Acoustic Monitoring,” J. Acoustical Society of America, Vol. 143, No. 2, February 2018.
  9. Vegad, S., H. Patel, H. Zhuang, and M. Naik, “Audio-Visual Person Recognition Using Deep Convolutional Neural Networks,” (Undergraduate Student Paper), J Biostatics and Biometrics, Vol. 8, No. 5, Oct. 2017, pp. 1-7, 2017.
  10. Muhamed A., H. Zhuang, and A. Ali, “An Approach for Facial Expression Recognition,” Int Journal of Biometrics, 2017 Online.
  11. Esfahanian, M., H. Zhuang, N. Erdol, and E. Gerstein, “Two-stage Detection of North Atlantic Right Whale Upcalls using Local Binary Patterns and Machine Learning Algorithms,” J. Applied Acoustics, v 120, May 2017, pp 158-166.
  12. Esfahanian, M., H. Zhuang, and N. Erdol, “Sparse Representation for Classification of Dolphin Whistles by Type,” J. Acoustical Society of America – EL, Vol. 136 (1), July, 2014.
  13. Esfahanian, M., H. Zhuang, and N. Erdol, “On Contour-based Classification of Dolphin Whistles by Type,” J. Applied Acoustics, Vol. 76, pp. 274-279, Feb 2014.

1 All the Journals listed are international journals and papers published are reviewed by anonymous reviewers.

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