Dezhen Song

Deputy Department Chair of Robotics, and Professor of Robotics

Research interests

Song’s research focuses on robot spatial intelligence, which requires perceiving spatial information from multimodal sensory data and making decisions based upon it. Spatial intelligence is a fundamental ability for robots to perceive their environment and make motion plans to physically interact with it. His research focus includes algorithms for cross-modality perception and learning, robust navigation, scene representation and understanding, and tightly coupled perception and planning. All of the above are built on spatial and motion uncertainty analyses drawn from either explicit geometric/stochastic model-based approaches or data-driven machine learning (ML)-based approaches.

Email

Prior to joining MBZUAI, Song was a professor and associate department head for academics in the Department of Computer Science and Engineering at Texas A&M University. From 2008 to 2012, Song was an associate editor of IEEE Transactions on Robotics (T-RO). From 2010 to 2014, he was an associate editor of IEEE Transactions on Automation Science and Engineering (T-ASE). Song was a senior editor for IEEE Robotics and Automation Letters (RA-L) from 2017 to 2021 and currently is a senior editor for IEEE Transactions on Automation Science and Engineering (T-ASE). He is also a multimedia editor and chapter author for Springer Handbook of Robotics. His research has resulted in one monograph and more than 130 refereed conference and journal publications.
  • Ph.D. in Operations Research from University of California, Berkeley
  • Master’s in Industrial Automation from Zhejiang University
  • Bachelor of Science in Process Control from Zhejiang University
  • The 1st place overall, 1st place in Dynamic event, GM/SAE Autodrive Challenge II, year 2, The 12th Unmanned Team, TAMU, June 2023
  • TEES Engineering Genesis Award, 2022
  • The Best Paper Award of the LCT 2022 Affiliated Conference, HCII 2022, (with Zohreh Shaghaghian, Heather Burte, and Wei Yan), for paper entitled “Learning Spatial Transformations and their Math Representations through Embodied Learning in Augmented Reality"
  • Amazon Research Award (ARA) 2020, robotics track,
  • Dean of Engineering Excellence Award, College of Engineering, Texas A&M University, 2016
  • Award for Excellence in Physical Sciences & Mathematics, 2009, for contribution to Springer Handbook of Robotics, Association of American Publishers, Inc.
  • TEES Select Young Faculty, 2007
  • Faculty Early Career Development (CAREER) Award, National Science Foundation, 2007-2012
  • Kayamori Best Paper Award, (with Dr. Jingang Yi and Dr. Shengwei Ding), IEEE International Conference on Robotics and Automation, 2005.

  • Gaofeng Li, Shan Xu, Dezhen Song, Fernando Caponetto, Ioannis Sarakoglou, Jingtai Liu, and Nikos Tsagarakis, On Perpendicular Curve-based Task Space Trajectory Tracking Control with Incomplete Orientation Constraint, IEEE Transactions on Automation Science and Engineering (T-ASE), vol. 20, no. 2, April 2023, pp. 1244 - 1261
  • Kuo Chen, Jingang Yi, and Dezhen Song, Gaussian Processes-based Control of Underactuated Balance Robots with Guaranteed Performance, IEEE Transactions on Robotics (T-RO), vol. 39, no. 1, Feb. 2023, pp. 572 - 589
  • Chengsong Hu, Shuanyu Xie, Dezhen Song, Alex J. Thomasson, Robert Hardin IV, and Muthukumar Bagavathiannan, Algorithm and System for Robotic Micro-dose Herbicide Spray for Precision Weed Management, IEEE Robotics and Automation Letters (RA-L), vol. 7, no. 4, Oct. 2022, pp. 11633 – 11640
  • Aaron Kingery and Dezhen Song, Improving Ego-Velocity Estimation of a Low-cost Doppler Radar for Vehicles by Recognizing Background and Elevation Effects, IEEE Robotics and Automation Letters (RA-L), vol. 7, no. 4, October 2022, pp. 9445 - 9452
  • Hsin-Min Cheng and Dezhen Song, Graph-based Proprioceptive Localization Using a Discrete Heading-Length Feature Sequence Matching Approach, IEEE Transactions on Robotics (T-RO), vol. 37, no. 4, August 2021, pp. 1268-1281
  • Shuangyu Xie, Chengsong Hu, Muthukumar Bagavathiannan, and Dezhen Song, Toward Robotic Weed Control: Detection of Nutsedge Weed in Bermudagrass Turf Using Inaccurate and Insufficient Training Data, IEEE Robotics and Automation Letters (RA-L), vol 6, no. 4, Oct. 2021, pp. 7365-7372.
  • Gaofeng Li, Dezhen Song, Shan Xu, Lei Sun, and Jingtai Liu, On Perpendicular Curve-based Model-less Control Considering Incomplete Orientation Constraint, IEEE/ASME Transactions on Mechatronics (T-MECH), vol. 26, no. 3, June 2021, pp. 1479-1489
  • Chieh Chou, Dezhen Song, and Haifeng Li, Encoder-Camera-Ground Penetrating Radar Sensor Fusion: Bimodal Calibration and Subsurface Mapping, IEEE Transactions on Robotics (T-RO), Vol. 37, No. 1, Feb. 2021, pp. 67-81.
  • Haifeng Li, Chieh Chou, Longfei Fan, Binbin Li, Di Wang, and Dezhen Song, Toward Automatic Subsurface Pipeline Mapping by Fusing a Ground-Penetrating Radar and a Camera, IEEE Transactions on Automation Science and Engineering (T-ASE), Vol. 17, No. 2, April 2020, pp 722-734.
  • Haifeng Li, Dezhen Song, Yong Liu and Binbin Li, Automatic Pavement Crack Detection by Multi-Scale Image Fusion, IEEE Transactions on Intelligent Transportation Systems (T-ITS), vol. 20, no. 6, June 2019, pp. 2025 - 2036.

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