Yiming LI

Ph.D in Robotics

Idiap Research Institute

About me

Hello, welcome to my website! I am currently a research assistant in the Robot Learning & Interaction group at Idiap Research Institute and a PhD student at Ecole Polytechnique Federale de Lausanne (EPFL), supervised by Dr. Sylvain Calinon. My current research interests mainly focus on robot manipulation, perception, motion planning and machine learning.

In my daily life, I like playing games (like Zelda, LoL…) and traveling.


  • Robot Manipulation
  • Motion Planning
  • Machine Learning
  • Robot Perception


  • MSc in Control Theory and Control Engineering, Jun, 2022

    Institute of Automation, Chinese Academy of Sciences

  • BSc in Mechanical Engineering, Jun, 2019

    Tongji University


[10/2022] I start my PhD in the Robot Learning & Interaction group at Idiap Research Institute.

[08/2022] One paper accpeted by IEEE Transactions on Cognitive and Developmental Systems (T-CDS).

[02/2022] One paper accpeted by ICRA’22.

[12/2021] One paper accpeted by IEEE Robotics and Automation Letters (RA-L).

[07/2021] One paper accpeted by IROS’21.

[02/2020] I joined ByteDance AI Lab as a research intern.


Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation

Grasping in cluttered scenes has always been a great challenge for robots, due to the requirement of the ability to well understand the …

DVGG: Deep Variational Grasp Generation for Dextrous Manipulation

This work presents DVGG, an efficient grasp generation network that takes single-view observation as input and predicts high-quality …

HGC-Net: Deep Anthropomorphic Hand Grasping in Clutter

Grasping in cluttered environments is one of the most fundamental skills in robotic manipulation. Most of the current works focus on …



6-DoF Robotic Grasp Pose Estimation

We proposed a simultaneous network to jointly learn instance-level, collision-free 6-DoF grasp poses in cluttered.

FightingICE Game AI Competition

We developed several RL-based AIs to fight against existing opponents, and defeated MctsAi (baseline) with a win rate of over 90%.

HIT DLR hand teleoperation

We developed a real-time hand-arm teleoperation system based on ROS for imitation learning on dextrous manipulation (UR5 with HIT-DLR Hand)

Personal Urban Mobility Access (PUMA)

PACE Vehicle Engineering Center, Tongji University.

RoboMaster Competition

Super Power Robot Team, Tongji University.


[2022] Outstanding students of the Institute of Automation, Chinese Academy and Sciences

[2019] Excellent Graduates of Shanghai

[2018] First Prize in RoboMaster National College Student Robot Contest

[2018] First Prize in PACE Global Project Competition

[2018] Meritorious Winner in Mathematical Contest In Modeling

[2018] Tongji Scholarship of Excellence

[2017] Second Prize of Mathematics Competition of Chinese College Students

[2016] Tongji Scholarship of Excellence


  • ymli.cn@gmail.com
  • (+41) 77 278 38 48 & (+86) 155 5656 1628
  • 7 Rue Pre-Borvey, Martigny, 1920