Biography

Dr. Li Bai is the Chair and Professor in the Electrical and Computer Engineering Department at Temple University. He has extensive research experience and expertise in distributed software computing, wireless sensor networks, system and software integration using commercial-off-the-shelf products and computer network security. He published over 60 peer-reviewed international journals and conference papers in the related areas. He has been involved in several sponsored research projects using portable devices with 802.11 wireless communication protocols. In addition, he was a core organizer in the 8th International Conference on Information Fusion held in Philadelphia in July 2005.

Research Interests

  • Robotic Operating System (ROS), Drone, Multi-Agent System, Distributed Software Computing
  • Wireless Sensor Networks
  • System and Software Integration Using Commercial-Off-the-Shelf Products and Computer Network Security.

Courses Taught

Number

Name

Level

ECE 2612

Digital Circuit Design

Undergraduate

ECE 3432

Robotic Control using Robotic Operating System (ROS)

Undergraduate

ECE 3613

Processor Systems Laboratory

Undergraduate

ECE 4532

Computer Network Communication

Undergraduate

Selected Publications

  • Li, Y., Xie, D., Cember, A., Nanga, R.P.R., Yang, H., Kumar, D., Hariharan, H., Bai, L.i., Detre, J.A., Reddy, R., & Wang, Z.e. (2020). Accelerating GluCEST imaging using deep learning for B0 correction. Magn Reson Med, 84(4), pp. 1724-1733. United States. doi: 10.1002/mrm.28289

  • Xie, D., Li, Y., Yang, H., Bai, L.i., Wang, T., Zhou, F., Zhang, L., & Wang, Z.e. (2020). Denoising arterial spin labeling perfusion MRI with deep machine learning. Magn Reson Imaging, 68, pp. 95-105. Netherlands. doi: 10.1016/j.mri.2020.01.005

  • Xie, D., Li, Y., Yang, H.L., Song, D., Shang, Y., Ge, Q., Bai, L., & Wang, Z. (2019). BOLD fMRI-Based Brain Perfusion Prediction Using Deep Dilated Wide Activation Networks. Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11861 LNCS, pp. 373-381. doi: 10.1007/978-3-030-32692-0_43