Scholar
Bo Zhao
Google Scholar ID: R6igYYYAAAAJ
Aalto University
Citations & Impact
Citations
163
H-index
7
i10-index
6
Publications
20
Co-authors
28
list available
Publications
Resume (English only)
Academic Achievements
- Principal investigator (PI) for several projects including AthenaRL, AthenaQEC, LARA, FlexMoE, and LashQ, funded by various organizations such as the Research Council of Finland, Finnish Quantum Flagship Exploratory Projects, Business Finland, and the Finnish Doctoral Program Network in Artificial Intelligence. Awarded Distinguished Reviewer Award for VLDB 2025.
Research Experience
- Assistant Professor at Aalto University, Finland (SEP.2023-Present); Assistant Professor at Queen Mary University of London, UK (JAN.2023-AUG.2023); Post-doctoral researcher at Imperial College London, UK (2021-2022) in the Large-Scale Data & Systems (LSDS) group, working with Prof. Peter Pietzuch; Software Development Engineer at Amazon Web Services, Redshift Team (2019-2019); Student assistant at the Parallel Programming group with Prof. Felix Wolf in RWTH-Aachen University and Technical University of Darmstadt.
Education
- PhD in Computer Science from Humboldt-Universität zu Berlin, Germany (2016-2022), supervised by Prof. Matthias Weidlich; Visiting master student in Computer Science at RWTH-Aachen University, Germany (2013-2015); Master of Science in Computer Science from Xi'an Jiaotong University, China (2012-2015); Bachelor of Science in Computer Science from Wuhan Institute of Technology, China (2008-2012).
Background
- Tenure-track Assistant Professor in the Department of Computer Science at Aalto University, leading the Aalto Data-Intensive System group (ADIS). Also affiliated with the Finnish Center for Artificial Intelligence (FCAI), the Helsinki Institute for Information Technology (HIIT), and the Quantum Doctoral Pilot Programme (QDOC). Spokesperson of the Aalto Hub in the LUMI AI Factory project. Research focuses on efficient data-intensive systems that translate data into value for decision making. The scope of research spans from scalable machine learning systems to distributed data management systems, as well as code optimization techniques.
