CV

I am Jiawei Fu, an interdisciplinary student researcher on computer vision and robotics.

Table of contents

Basics

Name Jiawei Fu
Position Research Intern
Email jiawfu@student.ethz.ch
Url https://jayefu.github.io/
Summary An interdisciplinary student researcher on computer vision and robotics
Status I am actively searching for Ph.D. positions in the field of computer vision and robotics

Research

  • 2023.01 - now
    Differentiable Morphology for Visual Sensors
    Worked with Andrei Atanov, Andrew Spielberg ,and Amir Zamir
    Visual Intelligence and Learning Lab, EPFL, Lausanne, Switzerland
    • Working on differentiable morphology for visual sensors
  • 2022.04 - 2022.09
    Multi-modal Dataset Collection for Autonomous Driving
    Worked with Dengxin Dai
    Vision for Autonomous Systems, Max Planck Institute for Informatics, Saarbrucken, Germany
    • Collected multi-modal datasets with 2 RGB cameras, 2 event cameras, 2 LiDARs, 1 GNSS+INS System, and 1 Jetson Xavier
    • Implemented the algorithms for calibration, synchronization, data collection, and post-processing
    • Designed the electrical and mechanical structure for binding the sensors
  • 2021.09 - 2022.03
    Learning Deep Sensorimotor Policies for Vision-based Drone Racing
    Worked with Yunlong Song, Yan Wu, Fisher Yu, Davide Scaramuzza
    Robotics and Perception Group, University of Zurich, Zurich, Switzerland
    • Developed a deep sensorimotor policy with Learning-by-Cheating for vision-based drone racing
    • Enhanced the robustness of the vision-based policy with contrastive learning and data augmentation
    • Conducted flight experiments in a realistic simulator and achieved state-of-the-art performance
  • 2021.03 - 2021.07
    Computational Morphology for ANYmal-on-Wheels
    Worked with Marko Bjelonic, Joonho Lee, Marco Hutter
    Robotic Systems Lab, ETH Zurich, Zurich, Switzerland
    • Developed the joint optimization framework for both morphology and control of ANYmal-on-Wheels
    • Used Bayesian Optimization to learn morphology and Reinforcement Learning to optimize control
    • Conducted experiments in a realistic simulator and reduced the energy consumption during locomotion on rough terrains

Work

  • 2022.04 - 2022.09
    Research Intern
    Advised by Prof. Dengxin Dai
    Topic: Multi-modal Dataset Collection for Autonomous Driving
    Vision for Autonomous Systems, Max Planck Institute for Informatics, Saarbrucken, Germany
    • Collected multi-modal datasets with 2 RGB cameras, 2 event cameras, 2 LiDARs, 1 GNSS+INS System, and 1 Jetson Xavier
    • Implemented the algorithms for calibration, synchronization, data collection, and post-processing
    • Designed the electrical and mechanical structure for binding the sensors
  • 2021.09 - 2022.03
    Student Intern
    Advised by Prof. Davide Scaramuzza
    Topic: Learning Deep Sensorimotor Policies for Vision-based Drone Racing
    Robotics and Perception Group, University of Zurich, Zurich, Switzerland
    • Developed a deep sensorimotor policy with Learning-by-Cheating for vision-based drone racing
    • Enhanced the robustness of the vision-based policy with contrastive learning and data augmentation
    • Conducted flight experiments in a realistic simulator and achieved state-of-the-art performance

Education

Awards

Skills

Programming Language
Python
C++
C
MATLAB
Framework
PyTorch
TensorFlow
ROS
CMake
Developer Tool
Docker
Singularity
Git
Hardware
Jetson
RGBD Camera
LiDAR
GPS

Languages

Chinese
Native speaker
English
Fluent
German
Basic