Fanyou Wu | 吴凡优

Applied Scientist II
PXT Central Science (PXTCS)

I am Fanyou Wu, and I am an Applied Scientist at Amazon PXT Central Science (PXTCS). I received my Ph.D. degree in Forestry from Department of Forestry and Natural Resources, Purdue University(2021). Before attending Purdue, I received my master’s degree from University of Eastern Finland (2018) and bachelor’s degree from Nanjing Forestry University (2015) both in Wood Material Science. I was also an exchange student at the University of British Columbia (2013).

My research focuses on applying machine learning to human resource area. Attending machine learning related competitions is my side interests, and I have won many championships and runners-up in machine learning related competitions and top conference competitions at KDD, IJCAI, NeurIPS, and CVPR.


Sep 14, 2022 Our tree diameter measurement and species identification App is under under testing [update].
Jul 22, 2022 I received 2nd place for KDD CUP 2022 Amazon in Task 2 and Task 3.

Selected publications

  1. 🚥
    Can language models be used for real-world urban-delivery route optimization?
    Yang Liu, Fanyou Wu, Zhiyuan Liu, Kai Wang, Feiyue Wang, Xiaobo Qu
    The Innovation 2023
  2. 🌳
    Data Collection and Deep Learning-Based Detection of Wood Growth Rings
    Fanyou Wu, Yunmei Huang, Bedrich Benes, Charles Warner, Rado Gazo
    Information Processing in Agriculture (in press) 2023
  3. 🚥
    Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform
    Yang Liu, Fanyou Wu, Cheng Lyu, Shen Li, Jiepin Ye, Xiaobo Qu
    Transportation Research Part E 2022
  4. 🌳
    Deep BarkID: A Portable Tree Bark Identification System by Knowledge Distillation
    Fanyou Wu, Rado Gazo, Bedrich Benes, Eva Haviarova
    European Journal of Forest Research 2021
  5. 🌳
    Wood Identification Based on Longitudinal Section Images by Using Deep Learning
    Fanyou Wu, Rado Gazo, Eva Haviarova, Bedrich Benes
    Wood Science and Technology 2021
  6. 📷
    Efficient Project Gradient Descent for Ensemble Adversarial Attack
    Fanyou Wu, Rado Gazo, Eva Haviarova, Bedrich Benes
    arXiv preprint arXiv:1906.03333 2019