Bo Tang (唐 博), PhD.

Assistant Professor, PhD Advisor (博士生导师)
Department of Computer Science and Engineering
Adjunct Assistant Professor at Department of Statistics and Data Science
Southern University of Science and Technology

Office: 317, South Tower, Faculty of Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China
Email: tangb3_AT_sustech_DOT_edu_DOT_cn

Biography

Bo Tang received the PhD Degree in the Department of Computing at Hong Kong Polytechnic University. He was a member of Database Research Group. He was supervised by Dr. Ken Yiu. He was a visiting researcher at MonetDB group (Amsterdam) and Microsoft Research Asia (Beijing). Before that, he obtained his BEng degree in computer science from Sichuan University.


Research Statement

My research interests are in the area of data management (i.e., database/big-data systems, query processing). In particular, I focus on improving query time efficiency and data analytical result accuracy. I do research because I really enjoy it. Especially, I want to do top research works which will make a difference to our life.


Adjunct Professorship

I am extremely pleased to be an adjunct assistant professor in Department of Statistics and Data Science, SUSTech. For the potential candidates (Undergraduates, Postgraduates, Postdocs, RAs and RAPs in or outside SUSTech), you are welcome to discuss the potential opportunities to work with my group via this channel.


Teaching Courses
  • CS203, Data Structure and Algorithm Analysis, Fall 2022, Fall 2021, Fall 2020, Fall 2019, Fall 2018, Spring 2018, Fall 2017
  • CS302, Operating System, Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018
  • CS217, Data Structure and Algorithm Analysisi(H), Fall 2022, Fall 2021
XCPC
    I am the coach of the SUSTech programming team since Fall 2017. Contact me if you are interested in solving challenging algorithmic problems. You can visit many wonderful cities for free :)

COVIDPat System
    Currently, our team DBGroup@SUSTech and team in UM (leading by Prof. Ryan U ) are working on large-scale COVID-19 knowledge graph analytical system . The query engine in our system outperforms the state-of-the-art solutions by 10~100 times in terms of response time. Our contribution is only to save the time, hopefully someone will use them to save our world.


Selected Publications (Full publication list, code, data and supplementary materials, e.g., slides, posters, are available via email request, * indicates the work was done under my supervision)
  1. Shiqi Zhang*, Renchi Yang, Xiaokui Xiao, Xiao Yan, Bo Tang.
    Effective and Efficient PageRank-based Positioning for Graph Visualization.
    Proceedings of the ACM Conference on Management of Data (SIGMOD) , Seattle, WA, USA, June 2023.
  2. Fang Wang*, Xiao Yan, Man Lung Yiu, Shuai Li, Zunyao Mao, Bo Tang.
    Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation.
    Proceedings of the ACM Conference on Management of Data (SIGMOD) , Seattle, WA, USA, June 2023.
  3. Bo Huang*, Victor Junqiu Wei, Raymond Chi-Wing Wong, Bo Tang.
    EAR-Oracle: On Efficient Indexing for Distance Queries between Arbitrary Points on Terrain Surface.
    Proceedings of the ACM Conference on Management of Data (SIGMOD) , Seattle, WA, USA, June 2023.
  4. Haotian Liu*, Bo Tang, Jiashu Zhang, Yangshen Deng, Xiao Yan, Xinying Zheng, Qiaomu Shen, Dan Zeng, Zunyao Mao, Chaozu Zhang, Zhengxin You, Zhihao Wang, Runzhe Jiang, Fang Wang, Man Lung Yiu, Huan Li, Mingji Han, Qian Li, Zhenghai Luo.
    GHive: Accelerating Analytical Query Processing in Apache Hive via CPU-GPU Heterogeneous Computing.
    Proceedings of the ACM Symposium on Cloud Computing (SoCC) , San Francisco, California, November 2022.
  5. Jiahao Zhang*, Bo Tang, Man Lung Yiu, Xiao Yan, Keming Li*.
    𝜏-LevelIndex: Towards Efficient Query Processing in Continuous Preference Space .
    Proceedings of the ACM Conference on Management of Data (SIGMOD), Philadelphia, PA, USA, June 2022.
  6. Huan Li, Lanjing Yi*, Bo Tang, Hua Lu, Christian Jensen.
    Efficient and Error-bounded Spatiotemporal Quantile Monitoring in Edge Computing Environments.
    48th International Conference on Very Large Data Bases (PVLDB), Sydney, Australia, September 2022.
  7. Bo Tang, Kyriakos Mouratidis, Mingji Han*.
    On m-Impact Regions and Standing Top-k Influence Problems.
    Proceedings of the ACM Conference on Management of Data (SIGMOD), Xi'an, Shannxi, China, June 2021.
  8. Kyriakos Mouratidis, Keming Li*, Bo Tang.
    Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable Size.
    Proceedings of the ACM Conference on Management of Data (SIGMOD), Xi'an, Shannxi, China, June 2021.
  9. Bo Tang, Kyriakos Mouratidis, Man Lung Yiu, Zhenyu Chen*.
    Creating Top Ranking Options in the Continuous Option and Preference Space.
    45th International Conference on Very Large Data Bases (PVLDB), Los Angeles, California, USA, August 2019.
  10. Kyriakos Mouratidis, Bo Tang.
    Exact Processing of Uncertain Top-k Queries in Multi-criteria Settings.
    44th International Conference on Very Large Data Bases (PVLDB), Rio de Janeiro, RJ, Brazil, August 2018.
  11. Bo Tang, Kyriakos Mouratidis, Man Lung Yiu.
    Determining the Impact Regions of Competing Options in Preference Space.
    Proceedings of the ACM Conference on Management of Data (SIGMOD), Chicago, Illinois, USA, May 2017.
  12. Bo Tang, Shi Han, Man Lung Yiu, Rui Ding, Dongmei Zhang.
    Extracting Top-K Insights from Multi-dimensional Data.
    Proceedings of the ACM Conference on Management of Data (SIGMOD), Chicago, Illinois, USA, May 2017.

Selected Professional Activities (Full list)
  • Reviewer for IEEE International Conference on Data Engineering (ICDE'2022 demo, '2023 industry/demo track)
  • Reviewer for ACM International Conference on Information and Knowledge Management (CIKM'2017, 2021, 2022)
  • Reviewer for The VLDB Journal (VLDBJ'2021, '2022)
  • Reviewer for IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE'2017,2018,2019,2020,2021,2022)
  • Reviewer for Thirty-Third AAAI Conference on Artificial Intelligence (AAAI'2019,2020,2021,2022)
  • Subreviewer for ACM SIGKDD 2020 (KDD'2020)

Student Supervision

Ongoing
  • Shiqi ZHANG, (PhD candidate from 2019, SUSTech-NUS joint PhD programme); Research topic: Graph management (InfoSys, CIKM, SIGMOD)
  • Wentao NING, (PhD candidate from 2020, SUSTech-HKU joint PhD programme); Research topic: Recommendation system (VLDB demo, ICDE, CIKM)
  • Haotian LIU, (PhD candidate from 2020, SUSTech); Research topic: Big data system (VLDB demo, DI2KG, SIGMOD demo, SoCC)
  • Bian Zheng, (PhD candidate from 2020, SUSTech-PolyU joint PhD programme); Research topic: Vector database
  • Runzhong Li, (PhD candidate from 2021, SUSTech-PolyU joint PhD programme); Research topic: Cloud-native database
  • Long Xiang, (PhD candidate from 2021, SUSTech); Research topic: Vector database (SIGIR*2, VLDB)
  • Jiashuo LIN, (PhD candidate from 2021, SUSTech-Pengcheng Lab joint PhD programme) Research topic: networking (IWQoS)
  • Keming LI, (Mphi from 2020, SUSTech); Research topic: Graph database (SIGMOD*2)
  • Qian LI, (Mphi from 2020, SUSTech); Research topic: VIS4DB (SoCC)
  • Chaozu ZHANG, (Mphi from 2021, SUSTech); Research topic: VIS4DB (VLDB demo)
  • Yangshen DENG, (MPhi from 2022, SUSTech); Research topic: Mordern hardware (SIGMOD demo, SoCC)
  • Qilong LI, (MPhi from 2022, SUSTech); Research topic: Query optimizer
Representive Alumni: Full list, I had the pleasure of working with you. Join us
    We always welcome brillant people to join our group. However, I have limited PhD and Master quota per year. If you want to join my research group (DBGroup@SUSTech), please fill this form and drop an email to me as soon as possible. Until now, the next positions of DBGroup members include CMU, Yale, UCSD, Gatech, UNSW, HKUST, NUS, HKPolyU, Univ. of Tokyo (academic), Tencent (industry).
For letter-of-reference requests
    I only write recommendation letters for students who had research collaboration with me, preferably for those applicants who had contributions in our research works.

Representative Awards / Honors