I am currently a masterโ€™s student in Data Science at New York University.

I am interested in Multimodal Representation Learning, Continual Learning, Embodied AI and Robot Learning (Reinforcement & Imitation Learning).

I like gaming ๐ŸŽฎ, badminton ๐Ÿธ, and rock climbing ๐Ÿง—โ€โ™‚๏ธ.

And I have Frosty โ€” the cutest little cat ever :33333333




๐Ÿšง Ongoing Projects

CMCL: Continual Multimodal Contrastive Learning

Implicit Task Affordance Prediction in 3D Space

Hierarchical Classification of Near-Death Experience Narratives

๐Ÿ“ Publications

ICASSP 2025
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Fully Spiking Neural Network for Legged Robots

Xiaoyang Jiang, Qiang Zhang, Jingkai Sun, Jiahang Cao, Jingtong Ma, Renjing Xu

Project

  • In this paper, we successfully apply a lightweight population coded Spiking Neural Network (SNN) to process legged robots, achieving outstanding results across a range of simulated terrains. This study presents a highly efficient SNN for legged robots that can be seamless integrated into other learning models.
  • Paper accepted for oral presentation at ICASSP 2025.
ICRA 2024
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Prompt, Plan, Perform: LLM-based Humanoid Control via Quantized Imitation Learning

Jingkai Sun, Qiang Zhang, Yiqun Duan, Xiaoyang Jiang, Chong Cheng, Renjing Xu

  • We present a novel approach that combines adversarial imitation learning with large language models (LLMs). This innovative method enables the agent to learn reusable skills with a single policy and solve zero-shot tasks under the guidance of LLMs. To the best of our knowledge, this is the first framework that controls humanoid robots using a single learning policy network and LLM as a planner.
  • Accepted at ICRA 2024.
NeurIPS 2023 Workshops
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Saliency-Guided Hidden Associative Replay for Continual Learning

Guangji Bai, Qilong Zhao, Xiaoyang Jiang, Yifei Zhang, Liang Zhao

  • This paper presents the Saliency Guided Hidden Associative Replay for Continual Learning. SHARC primarily archives salient data segments via sparse memory encoding. Importantly, by harnessing associative memory paradigms, it introduces a content focused memory retrieval mechanism, promising swift and near-perfect recall, bringing CL a step closer to authentic human memory processes.
  • Accepted at NeurIPS 2023 Workshops.

๐ŸŽ– Honors and Awards

  • 2020 - 2024 Excellent Student Scholarship granted by Northeastern University
  • 2022.06 Silver Prize in Liaoning in China College Studentsโ€™ Internet Plus Innovation and Entrepreneurship Competition held by the Ministry of Education
  • 2022.04 National Third Prize in the Underwater Operations Program in China Robot Contest co-held by China Association of Automation and Chinese RoboCup Committee
  • 2020.08 First Prize in the RoboMaster University Championship and First Prize in the RoboMaster Infantry Racing and Intelligent Shooting programs, funded and organized by DJI

๐Ÿ“– Educations

  • 2024.09 - 2026.05 (now), M.S. in Data Science, Center for Data Science, New York University.
  • 2020.09 - 2024.07, B.Eng. in Robotics Engineering, Faculty of Robot Science and Engineering, Northeastern University.

๐Ÿ’ป Professional Experience

  • 2024.09 - now, CILVR Lab, NYU
  • 2022.09 - 2024.07, Microelectronics Thrust, Function Hub, HKUST
  • 2023.04 - 2023.11, Incremental Learning Group, Emory University
  • 2020.08 - 2021.08, T-DT Innovation Laboratory, Northeastern University

๐Ÿˆ Frosty