Hi, I am Howard (Jingbiao) Mei, a PhD student at the Machine Intelligence Laboratory (MIL), University of Cambridge, supervised by Prof. Bill Byrne. I am a member of Peterhouse.
My research focuses on multimodal retrieval, hateful meme detection, and vision-language models. My work spans retrieval-augmented generation for visual question answering, content moderation with multimodal reasoning, and long-term personalized memory systems. I have published at top venues including NeurIPS, ACL, EMNLP, ICLR, and NAACL.
For a full list of publications, talks, and portfolio, see my academic page: meijingbiao.github.io.
Research Interests
- Multimodal Retrieval and Retrieval-Augmented Generation
- Hateful Meme Detection and Content Moderation
- Vision-Language Models
- Reinforcement Learning and Preference Optimization
- Personalized AI and Long-Term Memory
Education
- Ph.D. in Engineering, University of Cambridge, Oct 2022 – Jun 2026
- Machine Intelligence Laboratory, Peterhouse
- Supervisor: Prof. Bill Byrne
- Research interests: Vision-Language models, Information retrieval, RL and reasoning models
- M.Eng & B.A. in Information and Computer Engineering, University of Cambridge, Oct 2018 – Jun 2022
Work Experience
- Multimodal LLM Research Intern, RedNote (Xiaohongshu), Mar 2025 – Present
- Harmful content detection, RLHF/GRPO for MLLMs, curriculum learning for content moderation
- AI Strategy Research Intern, Huawei Cambridge Research Centre (ISR), May 2024 – Present
- Strategic AI research, co-organising workshops at ECCV/WWW/BMVC/ECAI/Eurographics
- AI Research Intern, Huawei Cambridge Research Centre (Kirin AI Solution), Jul 2022 – Jan 2023
- On-device streaming ASR, model compression, patent EP4404187A1
- Deep Learning Research Intern, University of Cambridge, Jun 2021 – Sep 2021
- Multimodal hateful speech detection with pretrained vision-language models
- Deep Learning Research Intern, Shanghai Jiao Tong University, Sep 2020 – Dec 2020
- Fault-tolerant neural network architectures, published at DAC 2021, patent CN113570056A
- Web Programmer, Jieqi Edge Computing, Jul 2019 – Sep 2019
News
- [Mar 2026] Paper accepted at ACL 2026: Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models.
- [Mar 2026] New preprints: According to Me: Long-Term Personalized Referential Memory QA and Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization.
- [Jan 2026] Paper accepted at ICLR 2026: ExPO-HM: Learning to Explain-then-Detect for Hateful Meme Detection.
- [Sep 2025] Paper accepted at EMNLP 2025 Main as Oral: Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection.
- [Sep 2025] Paper accepted at NeurIPS 2025: On Extending Direct Preference Optimization to Accommodate Ties.
- [May 2024] Two papers accepted at ACL 2024 Main: PreFLMR and RGCL.
- [Mar 2024] Paper accepted at NAACL 2024 Main: Control-DAG.
Academic Service
Supervision: Co-supervision of Cambridge Engineering MPhil (MLMI), UROP, and MEng student projects (2022–2026).
Teaching: Demonstrator and supervisor for MLMI 8 on Machine Translation and Visual Question Answering (2022–2025) and Large Language Model Applications (2025–2026).
Workshop Organising: Multimodal Information Retrieval Challenge at WWW 2025; UK and Ireland Speech Workshop 2024.
Reviewing: ACL ARR (Feb/May/Jul 2025, Jan 2026), NeurIPS 2025, ICLR 2025/2026, ICML 2026.
嗨,我是 Howard(梅竞标),目前是剑桥大学机器智能实验室 (MIL)的博士生,导师为 Bill Byrne 教授。我是Peterhouse 学院的成员。
我的研究方向包括多模态检索、仇恨 Meme 检测以及视觉-语言模型。研究工作涵盖视觉问答的检索增强生成、基于多模态推理的内容审核,以及长期个性化记忆系统。相关成果发表于 NeurIPS、ACL、EMNLP、ICLR、NAACL 等顶级会议。
完整的论文列表、学术报告与作品集,请访问我的学术主页:meijingbiao.github.io。
研究兴趣
- 多模态检索与检索增强生成
- 仇恨 Meme 检测与内容审核
- 视觉-语言模型
- 强化学习与偏好优化
- 个性化 AI 与长期记忆
教育背景
- 博士,工程学,剑桥大学,2022 年 10 月 – 2026 年 6 月
- 机器智能实验室,Peterhouse 学院
- 导师:Bill Byrne 教授
- 研究方向:视觉-语言模型、信息检索、强化学习与推理模型
- 工程硕士 & 学士,信息与计算机工程,剑桥大学,2018 年 10 月 – 2022 年 6 月
工作经历
- 多模态大模型研究实习生,小红书 (RedNote),2025 年 3 月 – 至今
- 有害内容检测、面向 MLLM 的 RLHF/GRPO、内容审核的课程学习
- AI 战略研究实习生,华为剑桥研究中心 (ISR),2024 年 5 月 – 至今
- 战略性 AI 研究,联合组织 ECCV/WWW/BMVC/ECAI/Eurographics 研讨会
- AI 研究实习生,华为剑桥研究中心(麒麟 AI 解决方案),2022 年 7 月 – 2023 年 1 月
- 深度学习研究实习生,剑桥大学,2021 年 6 月 – 2021 年 9 月
- 深度学习研究实习生,上海交通大学,2020 年 9 月 – 2020 年 12 月
- 网页程序员,捷奇边缘计算,2019 年 7 月 – 2019 年 9 月
近期动态
- [2026 年 3 月] 论文被 ACL 2026 接收:Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models。
- [2026 年 3 月] 新预印本:According to Me: Long-Term Personalized Referential Memory QA 和 Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization。
- [2026 年 1 月] 论文被 ICLR 2026 接收:ExPO-HM: Learning to Explain-then-Detect for Hateful Meme Detection。
- [2025 年 9 月] 论文被 EMNLP 2025 Main 接收(Oral):Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection。
- [2025 年 9 月] 论文被 NeurIPS 2025 接收:On Extending Direct Preference Optimization to Accommodate Ties。
- [2024 年 5 月] 两篇论文被 ACL 2024 Main 接收:PreFLMR 与 RGCL。
- [2024 年 3 月] 论文被 NAACL 2024 Main 接收:Control-DAG。
学术服务
指导学生: 联合指导剑桥工程系 MPhil (MLMI)、UROP 及 MEng 学生课题(2022–2026)。
教学: 担任 MLMI 8 课程 Machine Translation and Visual Question Answering(2022–2025)与 Large Language Model Applications(2025–2026)的助教与 Supervisor。
研讨会组织: WWW 2025 多模态信息检索挑战赛;UK and Ireland Speech Workshop 2024。
论文评审: ACL ARR(2025 年 2/5/7 月、2026 年 1 月)、NeurIPS 2025、ICLR 2025/2026、ICML 2026。