Professor of Computer Science
Department of People and Technology
Universitetsvej 1, 10.1
Tel: +45 4674 2604
Email: luhua AT rucXYZ DOT dk (XYZ to be removed)
Photographed by Mads Folmer Jensen
I am a member of the Programming, Logic and Intelligent Systems (PLIS) research group in the Department of People and Technology, Roskilde University (RUC), Denmark. Since June 2021, I have been RUC's contact person at Digital Research Centre Denmark (DIREC). I also serve on the Education and Networking Committee of Danish Data Science Academy (DDSA). From February 2007 to March 2020, I worked in the Department of Computer Science, Aalborg University. I obtained my PhD degree from the School of Computing, National University of Singapore (NUS), and my BSc (Department of Computer Science and Technology) and MSc (Institute of Remote Sensing and GIS) degrees from Peking University (PKU), China.
My research generally concerns data management, spanning database, data mining, big data and data science. My work involves different types of data such as spatial data, outdoor GPS data, indoor positioning data (e.g., RFID, Bluetooth and Wi-Fi data), and social media data (e.g., Tweets). A good deal of my research pays particular attention to locations, either explicit or implicit, in the data. A general purpose of such research is to find valuable information and knowledge efficiently from the data, which in turn are expected to enable, improve, and enrich location based services in various, especially non-conventional, scenarios. Recently, I've also been working on data cleaning, indexing, analytics and recommendation in spatial and social contexts, with a particular interest in designing effective methods applying machine learning models.
Currently I work on several research projects. An IFD-funded industrial PhD project focuses on making use of AIS data to model ship behavior. The Villum Synergy project DiRec investigates diversity related issues in digital news recommendation. The DFF-funded AI4Spatial empowers big spatial data management with machine learning techniques. The EU-funded MALOT focuses on data quality related challenges of mobility data generated in IoT contexts. The DFF-funded iLBS builds data management foundations for indoor location based services.
In 2022, I serve as a vice program chair for IEEE BigData and a PhD forum co-chair for MDM. Previously, I served as PC co-chair for NDBC 2019, MDM 2012 and ISA 2011, vice PC chair for MUE 2011, PhD forum co-chair for MDM 2016, and demo track chair for SSDBM 2014. I have also served on the program committees for conferences and workshops including VLDB, ICDE, WWW, KDD, CIKM, SSTD, MDM, ACM SIGSPATIAL GIS, DASFAA, PAKDD, SDM, APWeb, MobiDE, ISA, and others. I am a senior member of the IEEE and a member of IEEE TCDE.
To prospective students
If you're interested in working with me as a PhD student or a visiting student in my team, you're welcome to contact me via email. I will be happy to help you apply for tuition waiver from our university and financial support from Danish foundations and/or other agencies.
[Selected Recent Publications] [DBLP, Google Scholar]
- [2022-02-15]: Huan Li, Christian S. Jensen, Bo Tang, Muhammad Aamir Cheema and I will give a tutorial Spatial Data Quality in the IoT Era: Management and Exploitation at SIGMOD 2022.
- [2021-09-24]: Research project Safeguarding Diversity in News Recommendation has been approved by VILLUM FONDEN's Villum Synergy programme.
- [2021-05-10]: Research project AI-Powered Spatial Databases has been approved by Independent Research Fund Denmark.
- [2021-01-21]: Muhammad Umair, Muhammad Aamir Cheema, Omer Cheema, Huan Li and I have finished a survey paper on how COVID-19 impacts adoption of IoT in vertical sectors such as healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Check out the preprint.
- [2020-04-01]: I joined Roskilde University after working at Aalborg University for many years.
- [2020-02-04]: My postdoc Huan Li's proposal MALOT: Managing Mobility Data Quality for Location of Things got approved by EU MSCA Individual Fellowship program. Congrats to Huan!
- [2019-08-20]: Coauthored by Jianqiu Xu, Ralf Hartmut Güting and me, our vision paper won the Best Vision Paper Award at SSTD 2019.
- X. Li, H. Li, H. Lu, C. S. Jensen, V. Pandey, V. Markl: Missing Value Imputation for Multi-attribute Sensor Data Streams via Message propagation. VLDB 2024. (Data and code)
- P. Li, W. Wei, R. Zhu, B. Ding, J. Zhou, H. Lu: ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads. VLDB 2024. (Data and code)
- B. B. Magnussen, N. Bläser, H. Lu: DAISTIN: A Data-Driven AIS Trajectory Interpolation Method. SSTD 2023. (DOI)
- P. Li, H. Lu, R. Zhu, B. Ding, L. Yang, G. Pan: DILI: A Distribution-Driven Learned Index. VLDB 2023. (Data and code)
- T. Liu, H. Li, H. Lu, M. A. Cheema, H. Chan: Contact Tracing over Uncertain Indoor Positioning Data. TKDE 35(10):10324-10338, 2023. (Extended version)
- Z. Lai, D. Zhang, H. Li, C. S. Jensen, H. Lu, Y. Zhao: LightCTS: A Lightweight Framework for Correlated Time Series Forecasting. SIGMOD 2023. (Data and code)
- X. Li, H. Li, H. K.-H. Chan, H. Lu, C. S. Jensen: Data Imputation for Sparse Radio Maps in Indoor Positioning. ICDE 2023. (Data and code)
- H. Li, H. Lu, C. S. Jensen, B. Tang, M. A. Cheema: Spatial Data Quality in Internet of Things: Management, Exploitation, and Prospects. ACM Computing Surveys 55(3):57:1-57:41, 2023. (DOI)
- T. Liu, Z. Feng, H. Li, H.Lu, M. A. Cheema, H. Cheng, J. Xu: Towards Indoor Temporal-variation aware Shortest Path Query. TKDE 35(1):998-1012, 2023.
- H. Li, L. Yi, B. Tang, H. Lu, C. S. Jensen: Efficient and Error-bounded Spatiotemporal Quantile Monitoring in Edge Computing Environments. VLDB 2022. (Data and code)
- H. Chan, H. Li, X. Li, H. Lu: Continuous Social Distance Monitoring in Indoor Space. VLDB 2022. (Data and code)
- T. Liu, H. Li, H. Lu, M. A. Cheema, L. Shou: Towards Crowd-aware Indoor Path Planning. VLDB 2021. (Data and code)
- P. Li, H. Lu, Q. Zheng, L. Yang, G. Pan: LISA: A Learned Index Structure for Spatial Data. SIGMOD 2020. (Data and code)
- H. Li, H. Lu, A. Cheema, G. Chen, L. Shou: Indoor Mobility Semantics Annotation Using Coupled Conditional Markov Networks. ICDE 2020.
- F. Yu, L. Cui, W. Guo, X. Lu, Q. Li, H. Lu: A Category-Aware Deep Model for Successive POI Recommendation on Sparse Check-in Data. The Web Conference (WWW) 2020. (Data and code)
- Slides and videos of SIGMOD 2022 tutorial Spatial Data Quality in the IoT Era: Management and Exploitation (together with Huan Li, Bo Tang, Muhammad Aamir Cheema and Christian S. Jensen)
- Data and code of an indoor keyword-aware routing system.
- A benchmark (data, code and workloads) for indoor spatial queries.
- Some indoor venue keyword data used in our recent research on indoor keyword-aware routing.
- TRIPS: A System for Translating Raw Indoor Positioning Data into Visual Mobility Semantics (demonstrated at VLDB 2018). Parts of the components are open source already. See details here or watch it at YouTube.
- Indoor mobility data generator Vita (demonstrated at VLDB 2016): A joint work with the Database Lab at Zhejiang University, it is open source now. Check it out at Github or watch it at YouTube.
- Muhammad Aamir Cheema (Monash University) and I gave a tutorial Indoor Data Managmement at ICDE 2016. The slides are here.
|Last modified: Oct. 2023