Yiqing's resume

Education

  • 2020-Present
    Ph.D. in Computer Science
    National University of Singapore
  • 2016-2020
    B.A. in Computer Science and B.A. in Applied Mathematics
    National University of Singapore

Research Experience

  • 2023-2024
    Visiting PhD student
    CSAIL, MIT
    • Advised by Prof. Prof. Leslie Kaelbling and Prof. Tomás Lozano-Pérez
    • Developed "Set It Up!", a neuro-symbolic system that interprets and optimizes under-specified instructions for tabletop arrangements. Published at RSS 2024.
  • 2020-Present
    PhD student
    School of Computing, National Univeristy of Singapore
    • Advised by Prof. David Hsu
    • Designed IRL methods to scale up reward learning (Inverse RL) to long-horizon, high-dimensional tasks.
    • Developed methods to learn human objectives from diverse sources—demonstrations, language instructions, pre-trained models, and synthetic data—and translated these signals into optimization.
    • Built a simulator and benchmark for the Differentiable Deformable Object Manipulation methods.

Professional Services

  • 2024, July
    Task Specification Workshop at RSS 2024
    Delft, Netherlands
    • Main organizer for the Workshop on Task Specification at RSS 2024.
  • 2024, Nov
    2nd LEAP Workshop at CoRL 2024
    Munich, Germany
    • Co-organizer for the 2nd Workshop on Learning Effective Abstraction for Planning (LEAP) at Conference on Robot Learning (CoRL) 2024.
  • 2021 - Present
    Conference Reviewer
    NeurIPS, ICML, ICLR, RSS, ICRA, AAAI, AAMAS

Teaching

  • 2021-2022, SEM2
    CS4278/CS5478 Intelligent Robots, Algorithms and Systems
    National University of Singapore
    • Teaching Assistant
    • Conducted tutorials, graded assignments, and provided feedback to students.

Skills

  • Python, Jax, Java, PyTorch, TensorFlow, Mujoco, IssacSim