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Chen-yi Lu

Ph.D. Student
Purdue University
lu842 (at) purdue.edu


About Me

I am a 2nd-year Ph.D. student at Purdue University, advised by Prof. Somali Chaterji.

My research focuses on data-efficient learning algorithms and deep representation learning for computer vision tasks, such as image semantic segmentation, video classification, and image generation. Additionally, my research interests include multimodal learning, particularly text-to-image diffusion models and video grounding.

Prior to joining Purdue, I was a research assistant at National Taiwan University (NTU), working with Prof. Ta-Te Lin. At NTU, I focused on developing embedded devices and machine learning algorithms for precision agriculture. This work involved addressing real-life challenges such as developing interpretable algorithms to assist decision-making, designing user-friendly interfaces for decision support systems, and creating robust machine learning algorithms and edge devices capable of handling outliers and withstanding harsh environments.

In the summers of 2023 and 2024, I interned at Adobe Research, working with Mehrab Tanjim. We focused on improving the inference efficiency of text-to-image diffusion models through concept trajectory retrieval.

Selected Publications (Full list on Google Scholar)

  1. CVPR
    Improving Semi-supervised Semantic Segmentation with Sliced-Wasserstein Feature Alignment and Uniformity
    Chen-yi Lu, Kasra Derakhshandeh, Somali Chaterji
    The IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025.
  2. ECCV
    ReCon: Training-Free Acceleration for Text-to-Image Synthesis with Retrieval of Concept Prompt Trajectories
    Chen-yi Lu, Shubham Agarwal, Md Mehrab Tanjim, Kanak Mahadik, Anup Rao, Subrata Mitra, Shiv Kumar Saini, Saurabh Bagchi, Somali Chaterji
    European Conference on Computer Vision (ECCV), 2024.
  3. Biosystems Engineering
    Online semi-supervised learning applied to an automated insect pest monitoring system
    DJA Rustia, CY Lu, JJ Chao, YF Wu, JY Chung, JC Hsu, TT Lin
    Biosystems Engineering, 2021, 208, 28-44
  4. Pest Management Science
    Towards intelligent and integrated pest management through an AIoT‐based monitoring system
    DJA Rustia, LY Chiu, CY Lu, YF Wu, SK Chen, JY Chung, JC Hsu, TT Lin
    Pest Management Science, 2022, 78 (10), 4288-4302
  5. Computers & Electronics in Ag.
    Edge-based wireless imaging system for continuous monitoring of insect pests in a remote outdoor mango orchard
    DJA Rustia, WC Lee, CY Lu, YF Wu, PY Shih, SK Chen, JY Chung, TT Lin
    Computers and Electronics in Agriculture, 2023, 211, 108019
  6. IFAC-PapersOnLine
    Generative adversarial network based image augmentation for insect pest classification enhancement
    CY Lu, DJA Rustia, TT Lin
    IFAC-PapersOnLine, 2019, 52 (30), 1-5

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