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𝑳𝒂 π‘½π’Šπ’† 𝑬𝒏 𝑹𝒐𝒔𝒆

About Me

Hello! I am Tianjie Dai, an Algorithm Engineer at ByteDance, focusing on overseas advertising technology. I am passionate about leveraging cutting-edge technology to create seamless and meaningful experiences for global users.

Before that, I am fortunate to be advised by Prof. Jiangchao Yao and Prof. Ya Zhang (Vice Dean of School of Artificial Intelligence, SJTU) at Shanghai Jiao Tong University, where I gained solid foundations in deep learning and its applications in real-world systems.

Education

Shanghai Jiao Tong University

Master of Science, Information and Communication Engineering

2023.09 - 2026.03

Shanghai Jiao Tong University

Major: Bachelor of Engineering, Information Engineering

Minor: Bachelor of Economics, Finance

2019.09 - 2023.06

Jiangsu Yancheng Middle School

Science Track, Elective: Biology

2016.09 - 2019.06

Experience

Algorithm Engineer @ ByteDance

Search Advertising Technology, TikTok GMPT

Focus: AI Search, Generative Recommendation

2026.05 - Present

Research Intern @ Taobao & Tmall Group

Pailitao Team, Future Living Laboratory

Focus: Sequential Recommendation, MLLM Inference Acceleration

2025.01 - 2025.12

Algorithm Intern @ REDnote

Security & Risk Control Platform, Tech Platform

Focus: Optimization and Deployment of Face Detection Service

2024.11 - 2025.01

Research Intern @ Shanghai AI Laboratory

Smart Healthcare Center, Applied Research Department

Focus: Multimodal Medical Pretrained Model

2024.03 - 2024.09

Publications

  1. UniChest: Conquer-and-Divide Pre-training for Multi-Source Chest X-Ray Classification
    Tianjie Dai, Ruipeng Zhang, Feng Hong, Jiangchao Yao, Ya Zhang, Yanfeng Wang
    IEEE Transactions on Medical Imaging, Volume 43, August 2024
    Paper / Code
  2. RAD: Towards Trustworthy Retrieval-Augmented Multi-modal Clinical Diagnosis
    Haolin Li*, Tianjie Dai*, Zhe Chen, Siyuan Du, Jiangchao Yao, Ya Zhang, Yanfeng Wang
    NeurIPS 2025
    Paper / Code
  3. Bag of Tricks for Long-Tailed Multi-Label Classification on Chest X-Rays
    Feng Hong*, Tianjie Dai*, Jiangchao Yao, Ya Zhang, Yanfeng Wang
    ICCV 2023 Workshop
    Paper
  4. Privileged Information Assisted Learning from Noisy Correspondence
    Zihua Zhao, Tianjie Dai, Mengxi Chen, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
    Neurocomputing, Volume 672, April 2026
    Paper
  5. Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning
    Zihua Zhao, Mengxi Chen, Tianjie Dai, Jiangchao Yao, Bo Han, Ya Zhang, Yanfeng Wang
    CVPR 2024
    Paper / Code
  6. CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray
    Mingquan Lin, Gregory Holste, Song Wang, Yiliang Zhou, Yishu Wei, Imon Banerjee, Pengyi Chen, Tianjie Dai, Yuexi Du, Nicha C Dvornek, Yuyan Ge, Zuwei Guo, Shouhei Hanaoka, Dongkyun Kim, Pablo Messina, Yang Lu, Denis Parra, Donghyun Son, Álvaro Soto, Aisha Urooj, René Vidal, Yosuke Yamagishi, Zefan Yang, Ruichi Zhang, Yang Zhou, Leo Anthony Celi, Ronald M Summers, Zhiyong Lu, Hao Chen, Adam Flanders, George Shih, Zhangyang Wang, Yifan Peng
    Medical Image Analysis, Volume 106, December 2025
    Paper

Selected Awards

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2024 National Scholarship
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2022 National Scholarship
πŸ₯ˆ
Runner-up of CXR-LT Challenge 2024
πŸ₯ˆ
Finalist of MCM/ICM 2021