Hua LU

Professor
Department of Computer Science
Aalborg University (Copenhagen campus)

A.C. Meyers Vænge 15, 3-2-06
2450 København SV
Denmark

Tel: +45 9940 9973
Email: LastName+FirstName "AT" cs aau dk

Photographed by Mads Folmer Jensen
Photographed by Mads Folmer Jensen
Projects Publications Services Students Teaching

I am a professor in the Department of Computer Science, Aalborg University (AAU), where I'm affiliated with the research group Data Engineer­ing, Science, and Systems (DESS). I work in AAU's Copenhagen campus, where its IT related education and research are growing. From April 2020 to January 2025, I was a professor at Roskilde University (RUC). From June 2021 to January 2025, I served as RUC's contact person at Digital Research Centre Denmark (DIREC). I also served on the Education and Networking Committee of Danish Data Science Academy (DDSA) from January 2022 to June 2024. I obtained my PhD degree from the School of Computing, National University of Singapore (NUS), and my BSc (Software/CS) and MSc (GIS) degrees from Peking University (PKU), China.

My research generally concerns data management, spanning database, data mining, big data and data science. My work has studied multiple types of data such as spatial data, outdoor GPS data, indoor positioning data (e.g., RFID, Bluetooth and Wi-Fi data), IoT/sensor data, time series, and social media data (e.g., Tweets). I have a particular research interest in data with locations, which can be static or dynamic (e.g., moving objects), and explicit (e.g., GPS coordinates) or implicit (implied by the context). A general purpose of such research is to find valuable information and knowledge efficiently from the data, which in turn can enable, improve, and enrich location based services in various scenarios (e.g., smart cities, intelligent transportation systems, and social media). Recently, I've been working on applying cutting-edge AI techniques (mainly machine learning) in designing efficient and effective solutions to data related problems. Such problems include, but are not limited to, data quality management, indexes, query processing and optimization, data analytics, and recommendation.

Currently I lead several research projects. The Villum Synergy project DiRec investigates diversity related issues in digital news recommendation. The EU MSCA postdoc project LEJO studies how to speed up spatial joins by AI based techniques. The DIREC-funded project GREENSQL focuses on building AI models to predict the energy consumption of SQL queries.

I've served as PC co-chair (or vice chair) for PAKDD 2026, SSTD 2025, IEEE BigData 2022, NDBC 2019, MDM 2012 and ISA 2011, vice PC chair for MUE 2011, PhD forum co-chair for MDM 2016 and 2022, and demo track chair for SSDBM 2014. I have also served on the program committees for conferences and workshops including SIGMOD, VLDB, ICDE, EDBT, WWW, KDD, CIKM, SSTD, MDM, ACM SIGSPATIAL GIS, DASFAA, PAKDD, SDM, APWeb, MobiDE, ISA, and others.

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 or other relevant agencies.

[Selected Recent Publications] [DBLP, Google Scholar] [Awards/Honors] [Resources]
Last modified: Jan. 2026
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