Yanming Xiu (修彦名)

Greetings! I am currently a 2nd year Ph.D. at Intelligent Interactive Internet of Things (I^3T) Lab , Department of Electrical and Computer Engineering, Duke University in Durham, NC, where I work on computer vision, deep learning and medical imaging. My Advisor is Dr. Maria Gorlatova.

Prior to coming to Duke, I earned my B.Eng. in Automation and a honor undergraduate degree at Zhejiang University in 2022. I also worked as a research assistant at the University of Hong Kong in 2021.

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Research Interests

I'm interested in machine learning and its application in computer vision, especially Augmented Reality (AR) and Virtual Reality (VR). I also have some background in robotics and control theory.

My current research is mainly focused on object detection and re-arrangement in AR scenraios through deep learning methods.

Experiences

Education

  • Aug. 2022 - Now: Ph.D. Student, Department of Electrical and Computer Engineering, Duke University

    Core Courses: CS527: Computer Vision; ECE 661: Deep Neural Networks; ECE 684: NLP; ECE 685: Intro to Deep Learning; ECE 687: Advanced Machine Learning

    GPA: 3.88/4.00


  • Aug. 2018 - Jun. 2022: B.Eng in Automation, College of Control Science and Engineering, Zhejiang University

    Core Courses: Computer Vision and Machine Learning; Robotics; Embedded Systems; Control Theory; Big-data Analysis

    GPA: 3.85/4.00


  • Aug. 2018 - Jun. 2022: Honors Degree, Chu-Kochen Honors College, Zhejiang University

    Core Courses: Mathematical Analysis; Linear Algebra; Probability and Statistics; General Physics; Programming in C


Honors

  • Jun. 2022: Outstanding Undergraduate Graduates, Zhejiang University (Top 10%)

  • Oct. 2021: First Tier Scholaship for Academic Excellence, Zhejiang University (Top 5%)

Projects

Some of my previous projects are listed here to show my comprehensive engineering ability:

Clothes Folding Robot
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This is a joint project co-advised by Prof. Wenping Wang from HKU and Prof. Yiping Feng from ZJU. The project include 3 parts: 1) clothes landmark detection through HRNet, 2) Robotic arm path planning and 3) Overall system construction. The camera takes an image of clothes and pass it to my fork version of HRNet . Then the HRNet predict the key points of the clothes and pass them to robot control script. Finally, the arm execute the folding process.

Bell Hitting Robot
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This is a competition held by ZJU CSE. The participants are required to control the robot arm and hit the bells for as much times as possible within 1 minute, while obstacle avoidance is also required. I loaded the robot model in Gazebo, implemented the torque control algorithm and tested it in real-world robot.

Chipless RFID Tag Detection
/ video / Demostration

This is a training program in 2020, in which I designed a new type of chipless RFID tag so that the production cost of tags can be reduced. The tag can be correctly detected by the RFID reader at around 5-80 cm, which are common detection distances for warehouse logistics tasks.