Dr. Shunqiao Sun

  • Assistant Professor

Contact Information

  • Office: 3009 NERC
  • Phone: (205) 348-0508

Areas of Research

  • Statistical Signal Processing
  • Millimeter Wave Automotive Radar
  • Remote Sensing
  • Machine Learning
  • Connected and Autonomous Vehicles


  • Ph.D., Electrical and Computer Engineering, Rutgers University, 2016
  • M.S., Electrical Engineering, Fudan University, 2011
  • B.S., Electrical Engineering, Southern Yangtze University, 2004


Dr. Shunqiao Sun joined The University of Alabama in August 2019 as a tenure-track assistant professor. From 2016 to 2019, he was with the radar core team of Aptiv, Technical Center, Malibu, California, where he worked on advanced radar signal processing and machine learning algorithms for self-driving cars. At Aptiv, he had opportunity to lead the angle finding research and development efforts of Aptiv’s next generation short range radar, or SRR, sensor to provide 360 degree sensing, which has won booking of more than 120 million units.

His research interests lie at the interface of statistical and sparse signal processing with mathematical optimizations, automotive radar, MIMO radar, remote sensing, machine learning, connected and autonomous vehicles. Sun was awarded the 2015-2016 Rutgers University ECE Department Graduate Program Academic Achievement Award. He is also the winner of the 2016 IEEE Aerospace and Electronic Systems Society Robert T. Hill Best Dissertation Award for his dissertation “MIMO Radars with Sparse Sensing.” Sun is a senior member of the Institute of Electrical and Electronics Engineers, or IEEE.

At UA, Sun and his students are conducting research on state-of-the-art radar technologies and applying them to emerging challenges including autonomous driving, global climate change, digital health and smart home. Examples of on-going projects include:

  1. High Resolution Imaging Radar System for Level 4 and Level 5 Autonomous Driving
  2. NOAA/UCAR: Radar Remote Sensing for Snow and Soil Moisture in Greenland and Antarctica
  3. Deep Neural Networks Based Environment Perception Using Radar Low Level Data

Publications and Patents:

  • S. Sun, K. V. Mishra and A. P. Petropulu, ‘‘Target estimation by exploiting low rank structure in widely separated MIMO radar,’’ in Proc. IEEE Radar Conference, Boston, MA, April 22-26, 2019.
  • S. Sun and A. P. Petropulu, ‘‘Waveform design for MIMO radars with matrix completion,’’ IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 8, pp. 1400-1414, 2015.
  • S. Sun, W. U. Bajwa, and A. P. Petropulu, ‘‘MIMO-MC radar: A MIMO radar approach based on matrix completion,’’ IEEE Trans. on Aerospace and Electronic Systems, vol. 51, no. 3, pp. 1839-1852, 2015.
  • S. Sun and A. P. Petropulu, ‘‘On waveform conditions in MIMO radars using matrix completion,’’ in Proc. 49th Annual Asilomar Conference on Signals, Systems, and Computers (Asilomar), Pacific Grove, CA, Nov. 8-11, 2015. (Invited)
  • S. Sun and A. P. Petropulu, ‘‘On transmit beamforming in MIMO radar with matrix completion,’’ in Proc. IEEE 40th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, April 2015.

Honors and Awards:

  • IEEE Aerospace and Electronic Systems Society Robert T. Hill Best Dissertation Award (2016)
  • Rutgers University ECE Department Graduate Program Academic Achievement Award (2015-2016)