Dr Qichen Wang wins ACM SIGMOD Research Highlight Award for groundbreaking data science research

Dr Qichen Wang, a Research Assistant Professor at the Department of Computer Science in Hong Kong Baptist University, has received the esteemed Association for Computing Machinery (ACM) Special Interest Group on Management of Data (SIGMOD) Research Highlight Award for his paper titled "Conjunctive Queries with Comparisons," originally published in SIGMOD 2022. This recognition is the result of his fruitful collaboration with Professor Ke Yi from the Hong Kong University of Science and Technology.

The award-winning paper illustrates a remarkable breakthrough in processing queries for conjunctive queries with comparisons, which is an essential area for online analytical processing (OLAP) and spatio-temporal queries, as well as in machine learning over relational data. Dr Wang and Professor Yi's research achieved an unprecedented running time and theoretical optimality, making it a significant contribution to the field of data science research.

Dr Wang is dedicated to developing novel algorithms for query processing with nice theoretical guarantees that also work well in practice. His research spans various areas of database query optimisation, including dynamic query processing, distributed query processing, and more. He believed that the finding of a new and asymptotically optimal algorithm for a large class of conjunctive queries with comparisons is able to demonstrate order-of-magnitude speedup over SparkSQL on a variety of graph patterns and analytical queries.

The SIGMOD Research Highlight Award is a highly selective and prestigious accolade in the database community, recognising research projects that exemplify core database research. The award aims to bring greater visibility to the selected works within the database community, industry partners, and the broader ACM community. This year, twelve articles were chosen from various conferences and community nominations.

The ACM SIGMOD focuses on the principles, techniques, and applications of database management systems and data management technology. Its members include software developers, academic and industrial researchers, practitioners, users, and students.