CV

Experience

  • 2025 – Present

    Singapore

    Research Fellow

    Hyundai–NTU–A*STAR Corporate Lab, NTU

    Foundation models for industrial inspection and robotic part picking.

    • Developed DriftAD for few-shot anomaly detection with CLIP, achieving up to 1.5-point gains in 1-shot AUROC and PRO. First-author paper at ACM Multimedia 2026.
    • Extended to zero-shot anomaly detection with TRACE, using CLIP and DINOv3; submitted to AAAI 2027.
    • Built an open-vocabulary perception and grasping pipeline for unfamiliar object categories. Validated on industrial parts and demonstrated in on-site robotic grasping; filed a related patent.
  • 2021 – 2025

    Singapore

    Research Associate

    School of EEE, Nanyang Technological University

    Image and video restoration, efficient super-resolution, and multimedia data understanding.

    • Developed a two-stage method to restore damaged JPEG images, reaching 38.92 dB PSNR on 2K images (+5.52 dB over EPDN). First-author CVPR 2023 paper; contributed to a related video-recovery study at NeurIPS 2023.
    • Designed PromptSR, a 0.78M-parameter super-resolution model with gains of up to 0.48 dB over baselines (IEEE TMM 2026). Extended this work to adaptive superpixel token aggregation in AsTaSR.
    • Built Byte2Image and ByteNet to classify raw file fragments without file extensions or metadata. Fused byte and image representations, improving accuracy by up to 12.2% across two benchmarks (IEEE TMM 2024).
  • 2017 – 2020

    Chongqing, China

    Graduate Researcher

    College of Computer Science, Chongqing University

    Energy-efficient video decoding and deep learning hardware.

    • Parallelized H.264 decoding with dynamic voltage and frequency scaling: 27–32% faster decoding and 23–25% lower energy use across 720p–2160p video (ICPADS 2018).
    • Contributed to HolyLight, a nanophotonic CNN accelerator achieving 13× higher throughput per watt than a ReRAM baseline (DATE 2019).

Education

  • 2022 – 2025

    Singapore

    Ph.D. in Electrical and Electronic Engineering

    Nanyang Technological University

  • 2017 – 2020

    Chongqing, China

    M.Eng. in Computer Science

    Chongqing University

  • 2013 – 2017

    Chongqing, China

    B.Eng. in Internet of Things Engineering

    Chongqing University

Selected Publications

Skills

Foundation & Multimodal Models: CLIP, DINOv3, SigLIP, ImageBind, SAM, Grounding DINO, LLaVA, Qwen
Vision & Content Understanding: Object detection, Instance segmentation, Object tracking, Anomaly detection, Open-vocabulary perception, Image/video understanding
Learning Methods: Few-/zero-shot learning, Multimodal learning, Self-supervised learning, Prompt learning, Distillation, PEFT
Programming & Tools: Python, C/C++, PyTorch, TensorFlow, Hugging Face, NumPy, OpenCV, Git

Languages

Chinese : Native
English : Professional working proficiency