Research goal: Improving the performance and usability of databases systems
Jiaheng Lu is a computer scientist and a teacher, with a broad interest in databases and data management. His recent interests include multi-model database management systems, semantic string processing and job optimization for big data platform.
Jiaheng was awarded a Ph.D. degree in 2007 from the National University of Singapore. His Ph.D. topic was about XML query processing. He was at the University of California, Irvine for two-year Postdoc research. Then he joined the Renmin University of China in 2008, where he has worked for seven years. Jiaheng now works at the University of Helsinki, Finland. He has broad research and teaching experiences in four countries (China, Singapore, USA, and Finland).
Qingsong is a postdoc at UDBMS group. His research focuses are developing systems and designing efficient algorithms to enhance data analytics. In specific he interests in a broad of topics such as autonomous database system, event stream mining, probabilistic database, scalable stream processing, temporal analytics of dynamic graph, database query optimization, etc. They can be subsumed into an intersecting discipline "Data Science".
Qingsong was awarded Ph.D. degree in 2016 from University of Southern Denmark, where he had spent 5 years on his doctoral dissertation for addressing the challenges of scalable stream processing under the supervision of Prof. Yongluan Zhou. Thereafter, he joined North University of China and served as an assistant professor at School of Computer Science and Technology for about two years. Now he is working on some very interesting topics in Database with Prof. Jiaheng Lu at University of Helsinki.
Pengfei Xu is a doctoral student at the University of Helsinki since 2016. He received his Master's (mgr inż.) degree in Politechnika Wrocławska, Poland, and Bachelor's (B.Eng.) degree in Zhengzhou University, China.
Pengfei’s current research topic is string processing and DBMS query optimisation. Aside from Computer Science, he is also a skilled software developer, reverse engineer, and server administrator. He is always curious about how things work at low-level.
Chao Zhang is a Ph.D. candidate at the Department of Computer Science, University of Helsinki. His supervisor is Jiaheng Lu. Prior to joining UH, Chao spent one year at Renmin University of China (RUC) for Ph.D. studies.
Chao's current research topic focuses on performance evaluation and optimization for multi-model databases. In addition, He has many other research interests in the field of database including automatic DBMS tuning, polystore system benchmarking, and optimization of big data systems such as Hadoop and Spark.
Yuxing obtained his BSc in Computing Information Science from the Guangdong University of Technology, China, in 2014 and MSc in Computer Science and Engineering from Politecnico di Milano, Italy, in 2016, respectively. After his masters, he joined UDBMS group in the Department of Computer Science at the University of Helsinki as a doctoral student.
Currently, he's pursuing the Ph.D. degree in the field of Multi-model data management and Big data management. He likes problem modeling, programming, and music. He is also enthusiastic for out-door activities, such as hiking, football, etc.
Gongsheng has been pursuing his doctoral studies in the Doctoral Programme of Computer Science, University of Helsinki since 2017.
His current research topics are Quantum & Databases, and AI & Databases.
I am a MSc student and I work as a research assistant in UDBMS research group. My major is mathematics. Currently my main research topics are applications of category theory to multi-model databases and study of certain convex structures defined by submodular functions for obtaining better size bounds for conjunctive queries.
Zhengtong Yan is a Ph.D. student at the UDBMS research group of the University of Helsinki since October of 2020. He received his Bachelor’s degree in Engineering (B.Eng.) from Northwestern Polytechnical University, China, and his Master’s degree in Science (M.Sc) from China Ship Research & Development Academy, China.
His current research topic is autonomous multi-model databases. He is passionate about utilizing deep reinforcement learning and quantum computing techniques to enhance the capabilities of databases.
We are looking for highly motivated, independent, and organized individual students/researchers to join our research group. Do not hesitate to contact us.
Jyrki Heinonen, Master thesis "From Classical DW to Cloud Data Warehouse", December 2020.
Nygren, Saara, Master thesis "A Survey of Machine Learning Methods for Relational Database Tuning ", December 2020.
Dawei Wang, Visting Ph.D. student from Renmin University, China, May 2019 - Nov 2019.
Lizhen Fu, Postdoctoral researcher in our group, Nov 2018 - Nov 2019.
Tri Nguyen, Master thesis "Towards A Unified Indexing Structure for Multi-Model Databases", June 2019, Grade: 5.
Ziye Zhou, Master thesis "Worst-case optimal join algorithms for multi-model databases", September 2018.
Shewangizaw Sore, Master thesis "Benchmarking multi-model databases with MongoDB and AgensGraph", June 2018.
Peter Goetsch, Master thesis "Geometric Approaches to Big Data Modeling and Performance Prediction", June 2018.
Shiva Ram Shrestha, Master thesis "Parameter tuning and performance evaluation with HiBench on Hive and Spark SQL", January 2018.
Meiling Li, Master thesis "Benchmarking Multi-model Databases with ArangoDB and OrientDB", August 2017.
Shuqing Fang, Master thesis "Sampling-based Frequency Estimation on Massive Wikipedia JSON Documents", April 2017.
Jun Chen, Visting Ph.D. student from Renmin University, China, Sep 2016 - May 2017.