I am currently a Postdoctoral Research Fellow at the NExT++ Lab, National University of Singapore, working with Prof. Tat-Seng Chua. I first joined NExT++ as a visiting Ph.D. student from December 2022 to September 2024. In 2025, I completed my Ph.D. in Computer Science and Technology at Hunan University under the supervision of Assoc. Prof. Da Cao. My research focuses on enabling trustworthy multimodal learning by ensuring interpretablity and causality in AI models, integrating techniques for knowledge retrieval and reasoning, and developing self-correction mechanisms to enhance self-improvement capabilities, with human-in-the-loop frameworks to support reliable human-AI interaction. Based on these methods, I aim to build intelligent multimodal reasoning systems that can understand the world beyond human perception.

I have authored over 10 publications in top-tier venues—including ICLR, ACMMM, EMNLP, BIBM, TNNLS, KBS, ESWA, and regularly review for ICLR, ACMMM, ACL and Neural Networks.

🔥 News

• 2025.04: One paper is accepted by ICLR 2025.

📝 Publications

• ICLR 2025 Neural Causal Graph for Interpretable and Intervenable Classification, Jiawei Wang, Shaofei Lu, Da Cao, Dongyu Wang, Yuquan Le, Zhe Quan, Tat-Seng Chua.

• ESWA 2025 Spatial–Temporal Video Grounding with Cross-Modal Understanding and Enhancement, Shu Luo, Jingyu Pan, Da Cao, Jiawei Wang, Yuquan Le, Meng Liu.

• KBS 2025 Weakly-supervised Spatial-Temporal Video Grounding via Spatial-Temporal Annotation on a Single Frame, Shu Luo, Shijie Jiang, Da Cao, Huangxiao Deng, Jiawei Wang, Zheng Qin.

• TNNLS 2024 Graph Reasoning With Supervised Contrastive Learning for Legal Judgment Prediction, Jiawei Wang, Yuquan Le, Da Cao, Shaofei Lu, Zhe Quan, Meng Wang.

• TASLP 2024 R²: A Novel Recall & Ranking Framework for Legal Judgment Prediction, Yuquan Le, Zhe Quan, Jiawei Wang, Da Cao, Kenli Li.

• ACMMM 2024 Causal-driven Large Language Models with Faithful Reasoning for Knowledge Question Answering, Jiawei Wang, Da Cao, Shaofei Lu, Zhanchang Ma, Junbin Xiao, Tat-Seng Chua.

• BIBM 2024 TranSVPath: A TabTransformer-Based Model for Predicting the Pathogenicity of Structural Variants, Yaning Yang, Jiawei Wang, Xiaoqi Wang, Liwen Xu, Liangrui Pan, Shaoliang Peng.

• ACMMM 2023 Deconfounded Multimodal Learning for Spatio-temporal Video Grounding, Jiawei Wang, Zhanchang Ma, Da Cao, Yuquan Le, Junbin Xiao, Tat-Seng Chua.

• NeurIPS 2021 (MATHAI4ED) REAL2: An End-to-end Memory-augmented Solver for Math Word Problems, Shifeng Huang, Jiawei Wang, Jiao Xu, Da Cao, Ming Yang.

• EMNLP Findings 2021 Recall and Learn: A Memory-augmented Solver for Math Word Problems, Shifeng Huang, Jiawei Wang, Jiao Xu, Da Cao, Ming Yang.

• Neurocomputing 2020 Domain Adaptation with SBADA-GAN and Mean Teacher, Chengjian Feng, Zhaoshui He, Jiawei Wang, Qinzhuang Lin, Zhouping Zhu, Jun Lu, Shengli Xie.

• ACMMM 2019 MOC: Measuring the Originality of Courseware in Online Education Systems, Jiawei Wang, Jiansheng Fang, Jiao Xu, Shifeng Huang, Da Cao, Ming Yang.

• ACMMM 2019 The Retrieval of the Beautiful: Self-Supervised Salient Object Detection for Beauty Product Retrieval, Jiawei Wang, Shuai Zhu, Jiao Xu, Da Cao.

🥇 Honors and Awards

• 2024.11: China National Scholarship
• 2022.09 - 2024.09: China Scholarship Council (CSC) Scholarship

🎉 Prospective Interns

I welcome applications from self-motivated students interested in exploring:

• Data Synthesis: Active-learning MLLMs with explainable reinforcement learning pipelines.
• Visual Reasoning: Tool-augmented MLLMs with external visual capabilities and knowledge.
• Human-AI Interaction: Human-in-the-loop frameworks for interactive, responsible AI.

If you are passionate about advancing multimodal reasoning and AI trustworthiness, please send your CV, academic transcripts, and a brief research statement to wangjiawei0531@gmail.com. I look forward to collaborating with you at NExT++! (2 positions available)