Wenjing Lu

Wenjing Lu

Ph.D. Candidate at SJTU and RIKEN AIP | Uncertainty Quantification & Medical Image Analysis

Hi, I am Wenjing Lu, a fourth-year Ph.D. student at Shanghai Jiao Tong University (SJTU), advised by Prof. Yang Yang and Prof. Yi Hong. I am currently a Student Trainee at the RIKEN Center for Advanced Intelligence Project (AIP), supervised by Dr. Qibin Zhao. Before that, I received my master’s degree from the National University of Singapore (NUS).

My research interests center on two closely connected directions: (1) principled theories and methods for uncertainty quantification, with a focus on calibration, reliability, and robust decision-making, and (2) medical image analysis, especially uncertainty-aware learning for segmentation and foundation model adaptation. Recently, I have also become interested in uncertainty modeling for agentic AI systems, where reliable uncertainty quantification is crucial for selecting actions, such as querying, orchestrating, routing, or stopping.

Please feel free to email me for research, collaborations, or a casual chat.

Email: luluerji [at] sjtu.edu.cn / wenjing.lu [at] riken.jp

I am seeking postdoctoral and industrial research opportunities and would be glad to connect.

📣 News

  • 2026.05: Our paper “Calibrating Uncertainty for Zero-Shot Adversarial CLIP” is accepted by ICML 2026.
  • 2026.02: Our paper “Harmonizing Generalization and Specialization: Uncertainty-Informed Collaborative Learning for Semi-supervised Medical Image Segmentation” is accepted by IEEE TMI.

📖 Educations

  • 2025.04 - present, Student Trainee, RIKEN AIP, advised by Dr. Qibin Zhao.
  • 2022.09 - present, Ph.D. Candidate, AGI Institute, School of Computer Science, Shanghai Jiao Tong University (SJTU), advised by Prof. Yang Yang and Prof. Yi Hong.
  • 2021.08 – 2022.06, M.S, National University of Singapore (NUS).
  • 2017.09 - 2021.06, B.Eng, University of Electronic Science and Technology of China (UESTC).

📝 Selected Publications

✉️ Corresponding author.

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Static Badge Calibrating Uncertainty for Zero-Shot Adversarial CLIP.

Wenjing Lu, Zerui Tao, Dongping Zhang, Yuning Qiu, Yang Yang✉️, Qibin Zhao✉️.

[paper] [code] [poster]

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Static Badge Harmonizing Generalization and Specialization: Uncertainty-Informed Collaborative Learning for Semi-supervised Medical Image Segmentation.

Wenjing Lu, Yi Hong✉️, Yang Yang✉️.

[paper] [code]

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Static Badge UP-SAM: Uncertainty-Informed Adaptation of Segment Anything Model for Semi-Supervised Medical Image Segmentation.

Wenjing Lu, Yi Hong✉️, Yang Yang✉️.

[paper] [slides] [code]

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Static Badge UPCoL: Uncertainty-informed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation.

Wenjing Lu, Jiahao Lei, Peng Qiu, Rui Sheng, Jinhua Zhou, Xinwu Lu, Yang Yang✉️.

[paper] [code] [poster]

🎖 Awards

  • 2026.05, Golden Reviewer Award, ICML’26, Seoul.
  • 2024.12, Student Travel Award, BIBM’24, Lisbon.
  • 2022.05, Second Prize Award for AI paper presentation, AI Research Student Conference 2022 (ARSC‘22), Singapore.
  • 2021.06, Outstanding Graduate of UESTC.

💻 Services

  • Area Chair: DeLTa @ ICLR 2026, FoGen @ ICML 2026.
  • Conference Reviewer: ICML, NeurIPS, MICCAI, AAAI.
  • Journal Reviewer: EAAI, NN.

🏫 Teaching

  • CS7336 (G) Machine Learning, Sem. 2, 2023 - 2024

🏢 Experiences

  • 2021.08 - 2022.05, Research Intern @A*STAR I²R, host by Prof. Bharadwaj Veeravalli and Dr. Zeng Zeng.