Imperial College London

Dr. Bo Zhao

Faculty of EngineeringDepartment of Computing

Research Associate in Cloud Computing
 
 
 
//

Contact

 

bo.zhao Website CV

 
 
//

Location

 

346Huxley BuildingSouth Kensington Campus

//

Summary

 

Summary

I am a post-doctoral researcher in the Department of Computing at Imperial College London, working in the Large-Scale Data & Systems (LSDS) group with Prof. Peter PietzuchI conduct research of efficient data-intensive systems at the intersection of scalable reinforcement learning systems and distributed data management systems, as well as compilation-based optimisation techniques. 

My long-term goal is to explore and understand the fundamental connections between data management and modern machine learning systems to make decision-making transparent, robust and efficient.

Before joining Imperial, I was a research assistant (link) and obtained my PhD in the Databases and Information Systems Group at Humboldt-Universit├Ąt zu Berlin, supervised by Prof. Matthias Weidlich.



Publications

DBLP    Google Scholar

  1. 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, Preprint, ArXiv, 2022
  2. Gururaghav Raman, Bo Zhao, Jimmy Chih-Hsien Peng, Matthias Weidlich
    Adaptive incentive-based demand response with distributed non-compliance assessment, Applied Energy (IF=11.446), Volume 326, 2022
  3. Bo Zhao
    State Management for Efficient Event Pattern Detection
    Dissertation, Humboldt-Universit├Ąt zu Berlin, 2022.
  4. 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.
  5. 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.
  6. 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.
  7. Bo Zhao
    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.


    Before PhD
  8. 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.
  9. 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.
  10. 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.
  11. 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.

Academic Services

PC MemberCIKM 2021, CIKM 2022

Availability Committee: SIGMOD 2022

Demonstration Track Committee: ICDE 2023

Publications

Journals

Raman G, Zhao B, Peng JCH, et al., 2022, Adaptive incentive-based demand response with distributed non-compliance assessment, Applied Energy, Vol:326, ISSN:0306-2619

Conference

Zhao B, van der Aa H, Thanh TN, et al., 2021, EIRES: Efficient Integration of Remote Data in Event Stream Processing, ACM SIGMOD International Conference on Management of Data (SIGMOD), ASSOC COMPUTING MACHINERY, Pages:2128-2141, ISSN:0730-8078

Zhao B, Nguyen QVH, Weidlich M, 2020, Load Shedding for Complex Event Processing: Input-based and State-based Techniques, IEEE 36th International Conference on Data Engineering (ICDE), IEEE COMPUTER SOC, Pages:1093-1104, ISSN:1084-4627

Raman G, Peng JCH, Zhao B, et al., 2019, Dynamic Decision Making for Demand Response through Adaptive Event Stream Monitoring, ISSN:1944-9925

Zhao B, 2018, Complex Event Processing under Constrained Resources by State-Based Load Shedding, 34th IEEE International Conference on Data Engineering Workshops (ICDEW), IEEE, Pages:1699-1703, ISSN:1084-4627

More Publications