Haonan Peng
Assistant Professor, Mechanical and Mechatronics Engineering Tech
Haonan Peng
Assistant Professor, Mechanical and Mechatronics Engineering Tech
Bio
Ph.D. in Electrical and Computer Engineering, University of Washington, Seattle, WA
M.S. in Mechanical Engineering, University of Washington, Seattle, WA
B.S. in Mechanical Engineering, Central South University, Changsha, China
Haonan Peng is an Assistant Professor in the Department of Manufacturing and Mechanical Engineering Technology at Rochester Institute of Technology (RIT). He received his Ph.D. in Electrical and Computer Engineering (2026) and M.S. in Mechanical Engineering (2019) from the University of Washington, where he worked in the BioRobotics Lab under the supervision of Prof. Blake Hannaford.
His research focuses on robotic sensing, control, and manipulation, with a particular emphasis on surgical robotics. He is interested in integrating model-based methods and artificial intelligence to improve the accuracy, efficiency, and autonomy of robotic systems. His work includes learning-based calibration, sensorless force estimation, motion planning, and closed-loop control for cable-driven surgical robots. He has also worked on medical image analysis and non-invasive blood pressure sensing.
His research has been published in journals including Medical Image Analysis, npj Robotics, and IEEE Transactions on Automation Science and Engineering. He received the UW ECE Yang Award for Outstanding Doctoral Student in 2026.
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Peng H, Lewis A, Su YH, Lin S, Chiang DT, Jiang W, Lai H, Hannaford B. Efficient data-driven joint-level calibration of cable-driven surgical robots. npj Robotics. 2024 Dec 2;2(1):9.
Peng H, Lewis A, Su YH, Hannaford B. Ablation study on features in learning-based joint calibration of cable-driven surgical robots. IEEE Transactions on Automation Science and Engineering. 2025 Jul 1;22:17680-95.
Peng H, Lin S, King D, Su YH, Abuzeid WM, Bly RA, Moe KS, Hannaford B. Reducing annotating load: Active learning with synthetic images in surgical instrument segmentation. Medical Image Analysis. 2024 Oct 1;97:103246.
Peng H, Yang X, Su YH, Hannaford B. Real-time data driven precision estimator for raven-ii surgical robot end effector position. In2020 IEEE International Conference on Robotics and Automation (ICRA) 2020 May 31 (pp. 350-356). IEEE.
Lin S, Qin F, Peng H, Bly RA, Moe KS, Hannaford B. Multi-frame feature aggregation for real-time instrument segmentation in endoscopic video. IEEE Robotics and Automation Letters. 2021 Jul 9;6(4):6773-80.
King D, Adidharma L, Peng H, Moe K, Li Y, Yang Z, Young C, Ferreria M, Humphreys I, Abuzeid WM, Hannaford B. Automatic summarization of endoscopic skull base surgical videos through object detection and hidden Markov modeling. Computerized Medical Imaging and Graphics. 2023 Sep 1;108:102248.
Su YH, Jiang W, Chitrakar D, Huang K, Peng H, Hannaford B. Local style preservation in improved gan-driven synthetic image generation for endoscopic tool segmentation. Sensors. 2021 Jul 30;21(15):5163.