Qiqi Dai

Qiqi Dai

Since July 2023, I have been a research fellow at the Departmnet of Electrical and Computer Engineering (ECE) in National University of Singapore (NUS). Prior to that, I received the PhD degree from Nanyang Technological University (NTU) in 2023, Master’s Degree from NUS in 2019, and Bachelor’s Degree from Soochow University in 2018.

🏫 Education

  • 2019.08 - 2023.06, Ph.D. in Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore.
  • 2018.08 - 2019.06, M.Sc. in Electrical and Computer Engineering, National University of Singapore (NUS), Singapore.
  • 2014.09 - 2018.06, B.Eng. in Communication Engineering, Soochow University, Suzhou, China.

📝 Publication

2024

  • Q. Dai, Y. H. Lee, H.-H. Sun, J. Qian, M. L. M. Yusof, D. Lee, and A. C. Yucel, “Learning from Clutter: An Unsupervised Learning-Based Clutter Removal Scheme for GPR B-Scans,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 19668-19681, 2024.
  • J. Qian, Y. H. Lee, K. Cheng, Q. Dai, M. L. M. Yusof, D. Lee, and A. C. Yucel, “A Deep Learning-Augmented Stand-Off Radar Scheme for Rapidly Detecting Tree Defects,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-15, 2024.

2023

  • Q. Dai, Y. H. Lee, M. L. M. Yusof, D. Lee, and A. C. Yucel, “Learning from noise: An unsupervised GPR data denoising scheme based on generative adversarial networks,” in Proc CNC-USNC/URSI National Radio Sci. Meet., Portland, OR, 2023.
  • Q. Dai, Y. H. Lee, J. Qian, M. L. M. Yusof, D. Lee, and A. C. Yucel, “A signal processing algorithms-assisted deep learning scheme for ground-penetrating radar imaging,” in Proc CNC-USNC/URSI National Radio Sci. Meet., Portland, OR, 2023.
  • Q. Dai, Y. H. Lee, H.-H. Sun, G. Ow, M. L. M. Yusof, and A. C. Yucel, “3DInvNet: A deep learning scheme for 3D ground-penetrating radar data inversion,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-16, 2023.

2022

  • Q. Dai, Y. H. Lee, H.-H. Sun, G. Ow, M. L. M. Yusof, and A. C. Yucel, “DMRF-UNet: A two-stage deep learning scheme for GPR data inversion under heterogeneous soil conditions,” IEEE Transactions on Antennas and Propagation, vol. 70, no. 8, pp. 6313-6328, 2022.
  • Q. Dai, Y. H. Lee, H.-H. Sun, J. Qian, G. Ow, M. L. M. Yusof, and A. C. Yucel, “A deep learning-based GPR forward solver for predicting B-scans of subsurface objects,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022.
  • H.-H. Sun, Y. H. Lee, Q. Dai, C. Li, G. Ow, M. L. M. Yusof, and A. C. Yucel, “Estimating parameters of the tree root in heterogeneous soil environments via mask-guided multi-polarimetric integration neural network,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.
  • Q. Dai, Y. H. Lee, H.-H. Sun, G. Ow, M. L. M. Yusof, and A. C. Yucel, “S2M-Net: A deep learning-based scheme for GPR image translation from simulation to measurement via a conditional generative adversarial network,” in Proc CNC-USNC/URSI National Radio Sci. Meet., Denver, Colorado, USA, 2022.
  • J. Qian, Y. H. Lee, Q. Dai, K. Cheng, L. He, D. Lee, and A. C. Yucel, “Rapid health assessment of trees via deep learning-augmented radar,” in Proc CNC-USNC/URSI National Radio Sci. Meet., Denver, Colorado, USA, 2022.

2021

  • Q. Dai, Y. H. Lee, H.-H. Sun, G. Ow, M. L. M. Yusof, and A. C. Yucel, “A deep learning scheme for rapidly reconstructing 3D permittivity maps from GPR C-scans,” in Proc IEEE Int. Symp. Antennas Propagat., Singapore, 2021.
  • Q. Dai, Y. H. Lee, H.-H. Sun, G. Ow, M. L. M. Yusof, and A. C. Yucel, “A two-stage deep neural network for ground-penetrating radar data inversion under heterogeneous soil conditions,” in Proc CNC-USNC/URSI National Radio Sci. Meet, Singapore, 2021.
  • Q. Dai, Y. H. Lee, H.-H. Sun, G. Ow, M. L. M. Yusof, and A. C. Yucel, “A fast 2D GPR forward solver for convex objects based on a deep learning technique,” in Proc CNC-USNC/URSI National Radio Sci. Meet, Singapore, 2021.

2020

  • Q. Dai, B. Wen, G. Ow, M. L. M. Yusof, Y. H. Lee, and A. C. Yucel, “A deep learning-based methodology for rapidly detecting the defects inside tree trunks via GPR,” in Proc IEEE Int. Symp. Antennas Propagat., Montreal, Canada, 2020.

2019

  • G. Shao, Y. Tang, L. Tang, Q. Dai, and Y.-X. Guo, “A novel passive magnetic localization wearable system for wireless capsule endoscopy,” IEEE Sensors Journal, vol. 19, no. 9, pp. 3462-3472, 2019.

🎖 Awards

  • 2022-IEEE Antennas and Propagation Society (AP-S) Fellowship
  • 2018-Outstanding Graduate in Soochow University