Aalto University, Finland
Queen Mary University of London, UK
Imperial College London, UK
Software Development Engineer
Amazon Web Services, Redshift Team
PhD in Computer Science
Humboldt-Universität zu Berlin, Germany
Visiting PhD student in Computer Science
University of Queensland, Australia
Visiting master student in Computer Science
RWTH-Aachen University, Germany
Master of Science in Computer Science
Xi'an Jiaotong University, China
Bachelor of Science in Computer Science
Wuhan Istitute of Technology, China
Huanzhou Zhu*, Bo Zhao*, Gang Chen, Weifeng Chen, Yijie Chen, Liang Shi, Yaodong Yang, Peter Pietzuch, Lei Chen (*equal contribution)
MSRL: Distributed Reinforcement Learning with Dataflow Fragments
In the USENIX Annual Technical Conference (ATC), Boston, MA, USA, 2023.
Song Liu, Xinhe Wan, Zengyuan Zhang, Bo Zhao, Weiguo Wu
TurboStencil: You Only Compute Once for Stencil Computation
In (Future Generation Computer Systems), 2023.
Gururaghav Raman, Bo Zhao, Jimmy Chih-Hsien Peng, Matthias Weidlich
Adaptive incentive-based demand response with distributed non-compliance assessment
In (Applied Energy), Volume 326, 2022.
State Management for Efficient Event Pattern Detection
(Dissertation), Humboldt-Universität zu Berlin, 2022.
Bo Zhao, Han van der Aa, Nguyen Thanh Tam, Nguyen Quoc Viet Hung, Matthias Weidlich
EIRES: Efficient Integration of Remote Data in Event Stream Processing
In Proc. of the 47th ACM SIGMOD International Conference on Management of Data (SIGMOD), Xi'an, China, ACM, June 2021.
Bo Zhao, Nguyen Quoc Viet Hung, Matthias Weidlich
Load Shedding for Complex Event Processing: Input-based and State-based Techniques
In Proc. of the 36th IEEE International Conference on Data Engineering (ICDE), Dallas, TX, USA, IEEE, April 2020.
Gururaghav Raman, Jimmy Chih-Hsien Peng, Bo Zhao, Matthias Weidlich
Dynamic Decision Making for Demand Response through Adaptive Event Stream Monitoring
In Proc. of 2019 IEEE Power & Energy Society General Meeting (PESGM), Atlanta, GA, USA. IEEE, August 2019.
Complex Event Processing under Constrained Resources by State-based Load Shedding
In Proc. of the 34th IEEE International Conference on Data Engineering (ICDE), Paris, France, IEEE, April 2018.
Song Liu, Bo Zhao, Qing Jiang, Weiguo Wu
A Semi-Automatic Coarse-Grained Parallelization Approach for Loop Optimization And Irregular Code Sections
In Chinese Journal of Computers, 2017, 40(9): 2127-2147.
Bo Zhao, Zhen Li, Ali Jannesari, Felix Wolf, Weiguo Wu
Dependence-Based Code Transformation for Coarse-Grained Parallelism
In Proc. of the International Workshop on Code Optimisation for Multi and Many Cores (COSMIC) held in conjunction with CGO, San Francisco, CA, USA, ACM, February 2015.
Zhen Li, Bo Zhao, Ali Jannesari, Felix Wolf
Beyond Data Parallelism: Identifying Parallel Tasks in Sequential Programs
In Proc. of 15th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP), Zhangjiajie, China, Lecture Notes in Computer Science, Springer, November 2015.
Song Liu, Weiguo Wu, Bo Zhao, Qing Jiang
Loop Tiling for Optimization of Locality and Parallelism
In Journal of Computer Research and Development, 2015, 52(5): 1160-1176.
Tel. : +358 503227953
Tietotekniikan laitos, P.O.Box 15400, FI-00076 Aalto
B128, Department of Computer Science, Aalto University
Konemiehentie 2, 02150 Espoo, Finland
Programme Committee: CIKM'21,22,23
Availability Committee: SIGMOD'22,23
Demonstration Track Committee: ICDE'23,24
Journal Reviewer: TPDS'23
The Data-Intensive System group at Aalto University is seeking full-time doctoral researchers (PhD candidates) in data-intensive computing systems.
We conduct research on efficient data-intensive systems that translate data into value for decision making. The scope of our research spans across multiple subfields, from scalable data-centric machine learning systems to distributed data stream management systems, as well as code optimization techniques. That is to answer the question “how to co-design multiple layers of the software stack to improve scalability, performance, and energy efficiency of ML systems”. Our long-term goal is to explore and understand the fundamental connections between data management and modern ML systems to make decision-making more transparent, robust and efficient. Please find more details in our research statement.
Successful applicants will conduct impactful research in the field of data-intensive systems and their applications, publish research results in top-tier conferences, and collaborate with other researchers and visit world-leading research groups and industry labs within our international network (e.g., Imperial College, TUM, MPI-SWS, HU Berlin, NUS, Uni Edinburgh, AWS, Huawei, etc).
The position is available from September 2023 with a flexible starting date as mutually agreed. To apply and for further information, please contact Prof. Bo Zhao. Applications shall include at least the following information in a single PDF document:
The Department of Computer Science is the largest department at Aalto and one of the leading computer science research units in northern Europe. It is routinely ranked among the top 10 in Europe and in the top 100 globally (Shanghai ranking 51-75, USNews 71, Times 73, QS 84). The CS Department is located at the Otaniemi campus in Espoo – one of the most important north-european technology hubs, with a high concentration of companies, startups and research institutes from the high-tech sector, and with a thriving culture of entrepreneurship. It is less than a 15 minutes metro ride away from the center of Helsinki, capital of Finland. The campus is designed by the renowned architect and designer, Alvar Aalto. Please check out our virtual campus experience.
Aalto University is located in Finland which is among the best countries in the world according to many quality of life indicators. For the sixth year in a row (including 2023), Finland is listed as the world's happiest country, according to the World Happiness Report. Please find more information about living in Finland and the Aalto inforamtion package. Want to know more about us and your future colleagues? You can watch these videos: Aalto University – Towards a better world, Aalto People, Shaping a Sustainable Future. Read more about working at Aalto.