My name is Yan Zhuang. I am a Research Engineer at Tencent, where I work on Large Multimodal Models (LMMs) for Healthcare Intelligence and Neural Search. Previously, I received my Ph.D. in Computer Science and Technology from University of Electronic Science and Technology of China (UESTC), advised by Prof. Fuji Ren. Before that, I obtained my M.S. in Computer Technology from UESTC, under the supervision of Prof. Yanru Zhang, and my B.S. in Information and Computing Science from Anhui Science and Technology University.
Multimodal Affective Intelligence
- Multimodal sentiment and emotion understanding
- Robust multimodal learning under missing, noisy, and incomplete modalities
- Representation learning, multimodal alignment, and efficient fusion
Multimodal Reasoning & Foundation Models
- Large multimodal models (LMMs)
- Multimodal mathematical reasoning and self-verifiable inference
- Reasoning, planning, and reinforcement learning for multimodal agents
Healthcare Intelligence
- Medical multimodal intelligence
- Clinical decision support and healthcare applications with LMMs
Recent News
Recent research updates, publications, awards, and professional activities.
- May 2026 · 🎉 ReNoRD has been accepted to ACM International Conference on Multimedia Retrieval (ICMR 2026).
- Apr. 2026 · 🎉 DEJA has been accepted to ACL Main 2026, marking our recent work on trustworthy reasoning for retrieval-augmented generation.
- Mar. 2026 · 🎉 Our work DHM has been accepted by Neurocomputing.
- Jan. 2026 · 🎉 TMDC has been accepted to AAAI 2026.
- Sep. 2025 · 🎉 HME has been accepted to NeurIPS 2025.
- Jul. 2025 · 🎉 CMAD has been accepted to ICCV 2025.
- Apr. 2025 · 🎉 FAME has been accepted to ACM Multimedia 2025.
- Mar. 2025 · 🎉 IIE has been accepted by IEEE Transactions on Multimedia (TMM).
Featured Publications
(*denotes joint first-authors. Representative publications on multimodal representation learning, robust multimodal intelligence, large multimodal models, and trustworthy reasoning. Full publication list is available on Google Scholar.)
Beyond Explicit Refusals: Soft-Failure Attacks on Retrieval-Augmented Generation
TMDC: A Two-Stage Modality Denoising and Complementation Framework for Multimodal Sentiment Analysis with Missing and Noisy Modalities
Hyper-Modality Enhancement for Multimodal Sentiment Analysis with Missing Modalities
CMAD: Correlation-Aware and Modalities-Aware Distillation for Multimodal Sentiment Analysis with Missing Modalities
Intra-sample and Intra-modal Enhancement for Multimodal Sentiment Analysis with Missing Modalities
- ICMR 2026 ReNoRD: Learning from Relations under Noisy Pseudo Labels via Relational Distillation for Multimodal Sentiment. Tiantai Zhai, Yan Zhuang, Fuji Ren, Jiawen Deng, Liang Luo.
- Neurocomputing 2026 Decoupled Hypergraph Modeling for Multimodal Sentiment Analysis. Yanping Huang, Jiawen Deng, Yan Zhuang, Jiali You, Qian Liu, Fuji Ren.
- ACM MM 2025 FAME: Fusion-Aware Multi-modal Ensemble for Social Media Popularity Prediction. Yan Zhuang, Wei Bai, Yanru Zhang, Minhao Liu, Jiawen Deng, Fuji Ren.
- IEEE TAFFC 2025 Enhanced Emotion Recognition in Conversations through Hybrid Context Encoding and Latent Dependency Mining. Zheng Hu, Jiawen Deng, Satoshi Nakagawa, Yan Zhuang, Xiaoyue Zhang, Shimin Cai, Fuji Ren.
- IEEE TMM 2025 Multi-Level Contrastive Learning for Multimodal Sentiment Analysis. Yan Zhuang, Wei Bai, Yanru Zhang, Jiawen Deng, Zheng Hu, Xiaoyue Zhang, Fuji Ren.
- Research 2025 R3DG: Retrieve, Rank and Reconstruction with Different Granularities for Multimodal Sentiment Analysis. Yan Zhuang, Yanru Zhang, Jiawen Deng, Fuji Ren.
- WWW 2025 ETS-MM: A Multi-Modal Social Bot Detection Model Based on Enhanced Textual Semantic Representation. Wei Li, Jiawen Deng, Jiali You, Yuanyuan He, Yan Zhuang, Fuji Ren.
- ACM MM 2024 GLoMo: Global-local modal fusion for multimodal sentiment analysis. Yan Zhuang, Yanru Zhang, Zheng Hu, Xiaoyue Zhang, Jiawen Deng, Fuji Ren.
- IEEE TKDE 2024 Hierarchical denoising for robust social recommendation. Zheng Hu, Satoshi Nakagawa, Yan Zhuang, Jiawen Deng, Shimin Cai, Tao Zhou, Fuji Ren.
Research Projects
My research has evolved around three interconnected directions: multimodal representation learning, robust multimodal intelligence, and large multimodal models for reasoning and real-world applications.
Robust Multimodal Intelligence
Building robust multimodal learning frameworks capable of handling missing modalities, noisy observations, and incomplete multimodal information. This research line focuses on modality denoising, adaptive fusion, representation enhancement, and knowledge distillation.
Representative works: TMDC (AAAI 2026), HME (NeurIPS 2025), CMAD (ICCV 2025)
Multimodal Representation Learning
Developing effective multimodal representation learning methods through contrastive learning, cross-modal alignment, global-local interaction, and relational modeling to improve multimodal understanding.
Representative works: GLoMo (ACM MM 2024), MLCL (TMM 2025), IIE (TMM 2025), ReNoRD (ICMR 2026)
Large Multimodal Models
Exploring reasoning, verification, and practical deployment of large multimodal models, with applications to mathematical reasoning, healthcare intelligence, and trustworthy AI systems.
Current topics include: RLVR, Medical LMMs, Trustworthy Reasoning
Professional Experience
My research experience spans both academia and industry, with a primary focus on multimodal intelligence, large multimodal models, and real-world AI systems.
Jul. 2026 – Present Research Engineer: Tencent
Working on large multimodal models for healthcare intelligence and next-generation AI search systems. My current research focuses on multimodal reasoning, trustworthy AI, reinforcement learning for reasoning, and practical deployment of multimodal foundation models in real-world applications.
Jan. 2026 – Jun. 2026 Research Intern: Tencent
Conducted research on reinforcement learning for multimodal mathematical reasoning and trustworthy large multimodal models, with applications to healthcare intelligence.
Jan. 2022 – Jun. 2022 Research Intern: NetEase FUXI Laboratory
Conducted research on large language model pre-training and efficient language representation learning, laying the foundation for subsequent research on multimodal foundation models.
Education
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Sep. 2022 – Jun. 2026 Ph.D. in Computer Science and Technology
University of Electronic Science and Technology of China (UESTC), Advisor: Prof. Fuji Ren -
Sep. 2019 – Jun. 2022 M.S. in Computer Technology
University of Electronic Science and Technology of China (UESTC),Advisor: Prof. Yanru Zhang -
Sep. 2015 – Jun. 2019 B.S. in Information and Computing Science
Anhui Science and Technology University
Honors and Awards
Academic Honors
- UESTC Outstanding Graduate, 2026
- UESTC Academic Newcomer Award, 2026
- National Scholarship (Ph.D.), 2025
- National Scholarship (B.S.), 2017
Competition Awards
- Best Performance Award, ACM Multimedia 2025 Social Media Prediction Challenge (Image Track)
- Silver Award, China International College Students’ “Internet+” Innovation and Entrepreneurship Competition, 2021
- Second Prize, China Postgraduate Mathematical Contest in Modeling (Huawei Cup), 2020
Professional Activities
Journal Reviewing
- IEEE Transactions on Multimedia (TMM 2025-2026)
- IEEE Transactions on Affective Computing (TAFFC 2026)
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT 2026)
- Transactions on Machine Learning Research (TMLR 2026)
- Knowledge-Based Systems (KBS 2026)
- IEEE Transactions on Vehicular Technology (TVT 2023-2024)
Conference Reviewing
- CVPR 2026
- ICML 2026 (Gold Reviewer Award, Top 25%)
- NeurIPS 2026