李宏智 教授

李宏智 教授

长聘特聘教授

同济大学

最新动态

2026 三篇论文被 ACL 2026 录用:
  • Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
  • Lost in Stories: Consistency Bugs in Long Story Generation by LLMs
  • Beyond Rejection Sampling: Trajectory Fusion for Scaling Mathematical Reasoning
2026 一篇论文被 ICLR 2026 录用:"Do LLMs Forget What They Should? Evaluating In-Context Forgetting in Large Language Models"。
2026年5月 加入同济大学,担任长聘特聘教授。
2026 招贤纳士!课题组招收两名博士后研究员,研究方向为大规模AI系统、生成式人工智能及多模态分析。欢迎联系我们

个人简介

同济大学工程智能研究院长聘特聘教授、博士生导师。于哥伦比亚大学计算机科学专业获得博士学位。

研究方向涵盖机器智能领域,包括多模态内容分析知识抽取与表示模式识别以及云计算。目前主要研究方向为大规模人工智能算法和系统领域,包括生成式人工智能大规模推荐系统大规模GPU集群管理和优化

曾任微软研究院、微软搜索与人工智能事业部(美国总部)首席研究员和首席架构师微软人工智能亚太区首席应用科学家,生成式人工智能部门负责人

教育背景

计算机科学 博士
哥伦比亚大学(Columbia University),美国
计算机科学 硕士
哥伦比亚大学(Columbia University),美国
计算机科学 学士
浙江大学(Zhejiang University),中国

研究方向

面向视觉智能的深度学习

研发先进的深度神经网络模型,用于视觉理解,包括目标检测、模式挖掘和多媒体数据中的场景分析。

多模态内容分析

整合并分析文本、图像、视频和音频等多种模态的信息,实现全面的内容理解。

知识抽取与表示

构建能够从异构多媒体数据源中自动抽取、结构化和表示知识的系统。

模式识别

设计大规模视觉模式发现与识别算法,实现大规模图像和视频数据集的高效挖掘。

云计算

利用云计算平台部署可扩展的人工智能解决方案,实现实时视觉智能和多媒体处理。

多媒体新闻探索

开发面向异构多媒体新闻源的结构化探索与偶然发现系统。

代表性学术论文

完整论文列表请访问 Google Scholar 主页。

2025
Towards Web-scale Recommendations with LLMs: From Quality-aware Ranking to Candidate Generation
Jay Shah, Iman Barjasteh, Ankur Barapatre, Rana Forsati, Gang Luo, Fei Wu, Yuchen Fang, Xia Deng, Hongzhi Li, et al.
ACM SIGKDD (KDD), 2025
2024
Analyzing User Preferences and Quality Improvement on Bing's WebPage Recommendation Experience with Large Language Models
Jay Shah, Gang Luo, Jing Liu, Ankur Barapatre, Fei Wu, Changhe Wang, Hongzhi Li
ACM Conference on Recommender Systems (RecSys), pp. 751–754, 2024
WebReco: A Comprehensive Overview of an Industrial-Scale Webpage Recommendation System at Bing
Jay Shah, Iman Barjasteh, Ankur Barapatre, Changhe Wang, Gang Luo, Rana Forsati, Jay Chu, Hongzhi Li, et al.
2024
Leveraging LLMs to Enhance a Web-Scale Webpage Recommendation System
Iman Barjasteh, Jay Shah, Ankur Barapatre, Rana Forsati, Gang Luo, Fei Wu, Hongzhi Li, et al.
2024
2020
Rethinking Classification and Localization for Object Detection
Yue Wu, Yinpeng Chen, Lu Yuan, Zicheng Liu, Lijuan Wang, Hongzhi Li, Yun Fu
IEEE/CVF CVPR, 2020
MEmoR: A Dataset for Multimodal Emotion Reasoning in Videos
Guangyao Shen, Xin Wang, Xuguang Duan, Hongzhi Li, Wenwu Zhu
ACM MM, 2020
2019
Multi-Modal Deep Analysis for Multimedia
Wenwu Zhu, Xin Wang, Hongzhi Li
IEEE TCSVT, 2019
2018
PatternNet: Visual Pattern Mining with Deep Neural Network
Hongzhi Li, Joseph G. Ellis, Lei Zhang, Shih-Fu Chang
ACM ICMR, 2018 最佳海报奖
Automatic Visual Pattern Mining from Categorical Image Dataset
Hongzhi Li, Joseph G. Ellis, Lei Zhang, Shih-Fu Chang
IJMIR, 2018
2017
Improving Event Extraction via Multimodal Integration
Tongtao Zhang, Spencer Whitehead, Hanwang Zhang, Hongzhi Li, Joseph G. Ellis, Lifu Huang, Wei Liu, Heng Ji, Shih-Fu Chang
ACM MM, 2017
2016
Event Specific Multimodal Pattern Mining for Knowledge Base Construction
Hongzhi Li, Joseph G. Ellis, Heng Ji, Shih-Fu Chang
ACM MM, 2016
Placing Broadcast News Videos in their Social Media Context Using Hashtags
Joseph G. Ellis, Svebor Karaman, Hongzhi Li, Hong Bin Shim, Shih-Fu Chang
ACM MM, 2016
Cross-media Event Extraction and Recommendation
Di Lu, Clare R. Voss, Fangbo Tao, Xiang Ren, Rachel Guan, Rostyslav Korolov, Tongtao Zhang, Dongang Wang, Hongzhi Li, et al.
NAACL, 2016
Watching What and How Politicians Discuss Various Topics: A Large-Scale Video Analytics UI
Emily Song, Joseph G. Ellis, Hongzhi Li, Shih-Fu Chang
ACM ICMR, 2016
2015
Cross-document Event Coreference Resolution based on Cross-media Features
Tongtao Zhang, Hongzhi Li, Heng Ji, Shih-Fu Chang
EMNLP, 2015
2014
Scalable Visual Instance Mining with Threads of Features
Wei Zhang, Hongzhi Li, Chong-Wah Ngo, Shih-Fu Chang
ACM MM, 2014
2013
News Rover: Exploring Topical Structures and Serendipity in Heterogeneous Multimedia News Sources
Hongzhi Li*, Brendan Jou*, Joseph G. Ellis*, Daniel Morozoff*, Shih-Fu Chang
ACM MM, 2013
Structured Exploration of Who, What, When, and Where in Heterogeneous Multimedia News Sources
Brendan Jou*, Hongzhi Li*, Joseph G. Ellis*, Daniel Morozoff*, Shih-Fu Chang
ACM MM, 2013
mPano: Cloud-Based Mobile Panorama View from Single Picture
Hongzhi Li, Wenwu Zhu
SPIE Optics & Photonics, 2013
News Rover
Brendan Jou*, Hongzhi Li*, Joseph G. Ellis*, Daniel Morozoff*, Shih-Fu Chang
GNYMV Workshop, 2013 最佳演示奖
Joint Social and Content Recommendation for User-Generated Videos in Online Social Network
Zhi Wang, Lifeng Sun, Wenwu Zhu, Shiqiang Yang, Hongzhi Li, Dapeng Oliver Wu
IEEE TMM, 2013
2012
A Novel Large-Scale Digital Forensics Service Platform for Internet Videos
Hao Yin, Wen Hui, Hongzhi Li, Chuang Lin, Wenwu Zhu
IEEE TMM, vol. 14, no. 1, pp. 178–186, 2012
2011
Real-time 3D Applications on Handheld Devices: Challenges and Trend
Wenwu Zhu, Dan Miao, Hongzhi Li
IEEE COMSOC MMTC E-Letter, Vol. 6, No. 6, 2011
2010
Melog
Hongzhi Li, Xian-Sheng Hua, Xijia Liu
ACM MM, 2010
Melog: Mobile Experience Sharing through Automatic Multimedia Blogging
Hongzhi Li, Xian-Sheng Hua
ACM Multimedia Workshop, 2010

荣誉奖项

Grand Challenge 冠军(第一名)
ACM Multimedia 2012
最佳演示奖(Best Demo Award)
Greater New York Multimedia & Vision (GNYMV) Workshop, 2013
最佳海报奖(Best Poster Award)
ACM International Conference on Multimedia Retrieval (ICMR), 2018

学术服务

程序委员会委员

  • ACM International Conference on Multimedia (ACM MM)
  • IEEE International Conference on Multimedia and Expo (ICME)
  • International Joint Conference on Artificial Intelligence (IJCAI)

期刊审稿人

  • IEEE Transactions on Multimedia (TMM)
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • Journal of Visual Communication and Image Representation (JVCI)
  • Journal of Visualization (JVIS)

联系方式

电子邮件

所属单位

同济大学

Google Scholar

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