微软AI首席研究员，
清华大学交叉信息研究院博士，
Lab μ 校园极客社 & Club ε 脑科学兴趣团队 创始人。
2017年至今，在微软亚洲研究院从事研究工作，现为DKI组（Data, Knowledge, Intelligance Group）的首席研究员。 主要研究方向为：数据分析、自然语言处理、人工智能和网络科学；对神经科学和心理学也略有涉猎。 负责了微软核心产品中数据分析智能的研发：Excel表格分析智能中的语义分析与推荐，以及Forms问卷回答分析智能系统的设计与搭建。
2008年至2012年在清华大学计算机科学与技术系就读本科。 2012年至2017年为清华大学交叉信息研究院(IIIS)博士研究生，及计算机科学与技术系Netman 实验室成员，导师为Thomas Moscibroda和裴丹。 博士期间主要使用数据挖掘与机器学习来刻画和优化校园生活的方方面面，包括：校园WiFi网络性能、人群移动及社交、教育教学等等。 在校期间创立了两个学生科创类社团：Lab μ 校园极客社和Club ε 脑科学兴趣团队。 在Lab μ带领着超过50人的团队，完成了3款校园产品的设计、开发和推广：TUNet自动联网助手、Tsinghua Now即刻清华，和CaμsKit校园活动套件。
Excel中的Copilot通过推荐公式、在图表和数据透视表中显示洞见，以及高亮有趣的数据，帮助您更好地处理表格中的数据。
Microsoft Excel的核心功能，包括从表格侦测解析、语义理解，到分析与洞察的自动推荐，用于支持多个Excel主界面的用户体验。
Microsoft Forms在线问卷的发放、收集，和回答数据的自动分析与推荐，用于提升问卷设计的质量，以及帮助问卷设计者分析大量的回答数据。
清华校园网工具应用，帮助师生在Android和iOS上自动登录校园网，以及管理和保护校园网账号。吸引了近20000清华用户安装使用。
清华校园生活智能助手，将网络学堂、课程表等处的信息通过卡片流展示给用户，并提供了GPA计算器、自习室座位查询等插件。
为校园大型活动（如学生节）提供的整套信息化服务。包括企业级WiFi部署、微信墙、抽奖页和弹幕系统。一年内在约20个大型活动上被使用。
PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning
Jiaru Zou, Mengyu Zhou, Tao Li, Shi Han, Dongmei Zhang
EMNLP 2024, Miami, Florida, USA, November 2024.
CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing
Xinyi He, Jiaru Zou, Yun Lin, Mengyu Zhou, Shi Han, Zejian Yuan, Dongmei Zhang
EMNLP 2024, Miami, Florida, USA, November 2024.
Encoding Spreadsheets for Large Language Models
Haoyu Dong, Yuzhang Tian, Jianbo Zhao, Junyu Xiong, Mengyu Zhou, Yun Lin, José Cambronero, Yeye He, Shi Han, Dongmei Zhang
EMNLP 2024, Miami, Florida, USA, November 2024.
TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning
Yuan Sui, Jiaru Zou, Mengyu Zhou, Xinyi He, Lun Du, Shi Han, Dongmei Zhang
EMNLP 2024, Miami, Florida, USA, November 2024.
Vision Language Models for Spreadsheet Understanding: Challenges and Opportunities
Shiyu Xia, Junyu Xiong, Haoyu Dong, Jianbo Zhao, Yuzhang Tian, Mengyu Zhou, Yeye He, Shi Han, Dongmei Zhang
ALVR 2024, Bangkok, Thailand, August 2024.
Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study
Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, Dongmei Zhang
WSDM 2024, Mérida, Yucatán, México, March 2024.
Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries
Xinyi He, Mengyu Zhou, Xinrun Xu, Xiaojun Ma, Rui Ding, Lun Du, Yan Gao, Ran Jia, Xu Chen, Shi Han, Zejian Yuan, Dongmei Zhang
AAAI 2024, Vancouver, Canada, February 2024.
AnaMeta: A Table Understanding Dataset of Field Metadata Knowledge Shared by Multi-dimensional Data Analysis Tasks
Xinyi He, Mengyu Zhou, Mingjie Zhou, Jialiang Xu, Xiao Lv, Tianle Li, Yijia Shao, Shi Han, Zejian Yuan, Dongmei Zhang
ACL 2023, Toronto, Canada, July 2023.
CASR: Generating Complex Sequences with Autoregressive Self-Boost Refinement
Hongwei Han, Mengyu Zhou, Shi Han, Xiu Li, Dongmei Zhang
ICLR 2023, Kigali, Rwanda, May 2023.
FormLM: Recommending Creation Ideas for Online Forms by Modelling Semantic and Structural Information
Yijia Shao, Mengyu Zhou, Yifan Zhong, Tao Wu, Hongwei Han, Shi Han, Gideon Huang, Dongmei Zhang
EMNLP 2022, Abu Dhabi, December 2022.
Towards Robust Numerical Question Answering: Diagnosing Numerical Capabilities of NLP Systems
Jialiang Xu, Mengyu Zhou, Xinyi He, Shi Han, Dongmei Zhang
EMNLP 2022, Abu Dhabi, December 2022.
Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks
Haoyu Dong, Zhoujun Cheng, Xinyi He, Mengyu Zhou, Anda Zhou, Fan Zhou, Ao Liu, Shi Han, Dongmei Zhang
IJCAI 2022, Messe Wien, Vienna, Austria, July 2022.
MultiVision: Designing Analytical Dashboards with Deep Learning Based Recommendation Aoyu Wu, Yun Wang, Mengyu Zhou, Xinyi He, Haidong Zhang, Huamin Qu, Dongmei Zhang VIS 2021, Virtual, October 2021.
Table2Charts: Recommending Charts by Learning Shared Table Representations Mengyu Zhou, Qingtao Li, Xinyi He, Yuejiang Li, Yibo Liu, Wei Ji, Shi Han, Yining Chen, Daxin Jiang, Dongmei Zhang KDD 2021, Virtual Event, Singapore, August 2021.
Table2Analysis: Modeling and Recommendation of Common Analysis Patterns for Multi-Dimensional Data Mengyu Zhou, Tao Wang, Pengxin Ji, Shi Han, Dongmei Zhang AAAI 2020, New York, USA, February 2020.
Collaborative Learning of Human Behavior: An Empirical Study on Location Prediction Yan Lu, Yuanchao Shu, Xu Tan, Yunxin Liu, Mengyu Zhou, Qi Chen, Dan Pei SEC 2019, Washington DC, USA, November 2019.
The Frame Latency of Personalized Livestreaming can be Significantly Slowed Down by WiFi Guoshun Nan, Xiuquan Qiao, Jiting Wang, Zeyan Li, Jiaohao Nu, Mengyu Zhou, Changhua Pei, Dan Pei IPCCC 2018, Orlando, Florida, USA, November 2018.
Mining Crowd Mobility and WiFi Hotspots on a Densely-populated Campus Mengyu Zhou, Kaixin Sui, Dan Pei, Thomas Moscibroda PURBA 2017, Maui, Hawaii, USA, September 2017.
MinHash Hierarchy for Privacy Preserving Trajectory Sensing and Query Jiaxin Ding, Chien-chun Ni, Mengyu Zhou, Jie Gao IPSN 2017, Pittsburgh, Pennsylvania, USA, April 2017.
EDUM: Classroom Education Measurements via Large-scale WiFi Networks Mengyu Zhou, Minghua Ma, Yangkun Zhang, Kaixin Sui, Dan Pei, Thomas Moscibroda UbiComp 2016, Heidelberg, Germany, September 2016.
Characterizing and Improving WiFi Latency in Large-Scale Operational Networks Kaixin Sui, Mengyu Zhou, Dapeng Liu, Minghua Ma, Dan Pei, Youjian Zhao, Zimu Li, Thomas Moscibroda MobiSys 2016, Singapore, June 2016
MobiCamp: a Campus-wide Testbed for Studying Mobile Physical Activities Mengyu Zhou, Kaixin Sui, Minghua Ma, Youjian Zhao, Dan Pei, Thomas Moscibroda WPA 2016, Singapore, June 2016