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
Simulator
Habitat
Flightmare
RaiSim
Isaac Sim
Developer Tool
Docker
Singularity
Git
Hardware
Jetson
RGBD Camera
LiDAR
GPS

Languages

Chinese
Native speaker
English
Fluent
German
Basic