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Bio

Dr. Bingsheng He is currently a Professor and Vice Dean (Research), School of Computing, National University of Singapore. Before joining NUS in May 2016, he held a research position in the System Research group of Microsoft Research Asia (2008-2010) and a faculty position in Nanyang Technological University, Singapore.

He got the Bachelor degree in Shanghai Jiao Tong University (1999-2003), and the Ph.D. degree in Hong Kong University of Science & Technology (2003-2008).
Bingsheng has served as a PC member for international conferences in databases (e.g.,ACM SIGMOD, VLDB, IEEE ICDE), cloud computing (e.g., ACM SoCC) and parallel and distributed systems (e.g., SC, HPDC and IPDPS), and as a demo co-Chair in VLDB 2017, PC co-Chair in IEEE CloudCom 2014/2015 , HardBD2016, IEEE BigData Congress 2018 and ICDCS 2020. He has served in editor board of international journals, including IEEE Transactions on Cloud Computing (IEEE TCC), IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), Springer Journal of Distributed and Parallel Databases (DAPD), and ACM Computing Surveys (CSUR). He has got editorial excellence awards for his service in IEEE TCC and IEEE TPDS in 2019.

His current research interests include Big data management systems (with special interests in cloud computing and emerging hardware systems), Parallel and distributed systems and Cloud Computing. His papers are published in prestigious international journals (such as ACM TODS and IEEE TKDE/TPDS/TC) and proceedings (such as ACM SIGMOD, VLDB/PVLDB, ACM/IEEE SuperComputing, ACM HPDC, and ACM SoCC). He is affiliated with both the Systems and Networking group and the Database group at NUS.

He has got a number of awards including IBM Ph.D. fellowship (2007-2008), NVIDIA Academic Partnership (2010-2011) and Nanyang Education Award (School) 2014. He has got a number of paper awards and honorable mentions in international prestigious conferences and journals including VLDB 2023 (industry track), IEEE TPDS 2019 best paper award, ACM SIGMOD 2008, VLDB 2013 (demo), IEEE IC2E 2016, 2017 IEEE/ACM William J. McCalla ICCAD Best Paper Award, and PACT 2018 (see Awards).

He is an ACM Distinguished Member (2020).

Recent Updates

• We are hiring! Several positions including Ph.D. students, Research Fellow, and Research Assistant are available. Research areas: 1) Large Language Model (LLM): fine-tuning, inference, systems and applications, 2) graph mining and learning systems for fraud detection, and 3) Federated learning systems.
• We periodically update this survey on federated machine learning systems (Survey).
• Call for contributions. Xtra members are building various data systems. See Repositories for Xtra Computing Group. For example, ThunderSVM and ThunderGBM has got 1.1K and over 500 stars in GitHub. We still have quite some issues to make the libraries more usable and functional. Please let me know if you want to join this journey.
• ThundeRiNG can generate 655 billion random numbers per second on a single FPGA!
• July 2023:
  • VLDB 2023 Industry Track Best Paper Runner-up Award (for the work "Xuanhe Zhou, Cheng Chen, Kunyi Li, Bingsheng He, Mian Lu, Qiaosheng Liu, Wei Huang, Guoliang Li, Zhao Zheng, Yuqiang Chen. FEBench: A Benchmark for Real-Time Relational Data Feature Extraction. VLDB: International Conference on Very Large Data Bases (VLDB) 2023.")
• July 2022:
  • Open-source: NIID-Bench: a benchmark for federated learning algorithms under non-IID data distribution scenarios. By Qinbin Li and Yiqun Diao.
  • Open-source: FedTree: a federated learning system for tree-based models. By Qinbin Li etc.
• Oct 2021:
  • Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Xu Liu, Bingsheng He. A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. Accepted by IEEE Transactions on Knowledge and Data Engineering.
  • Our demo paper "From Community Search to Community Understanding: A Multimodal Community Query Engine" received the Best Demo Paper Runner-up Award at CIKM 2021 (Queensland).
• Sept 2021:
  • Mr. Qinbin Li got Google PhD Fellowship 2021.
  • My Google citation has reached five digits :)
  • Zeyi Wen, Zhishang Zhou, Hanfeng Liu, Bingsheng He, Xia Li, Jian Chen. Enhancing SVMs with Problem Context Aware Pipeline. ACM KDD: In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21)
  • Jin Zhao, Yu Zhang, Xiaofei Liao, Ligang He, Bingsheng He, Hai Jin, Haikun Liu. LCCG: A Locality-Centric Hardware Accelerator for High Throughput of Concurrent Graph Processing. IEEE/ACM SC: International Conference for High Performance Computing, Networking, Storage and Analysis 2021.
  • Shixuan Sun^, Yuhang Chen*, Shengliang Lu*, Bingsheng He, Yuchen Li: ThunderRW: An In-Memory Graph Random Walk Engine. VLDB: International Conference on Very Large Data Bases (VLDB) 2021. (also published in Proc. VLDB Endow. 14(11): 1992-2005 (2021)).
  • [Book] Johns Paul*, Shengliang Lu* and Binsheng He. Database Systems on GPUs. Foundations and Trends in Databases (Now Publisher) 2021.
• July 2021:
  • Mr. Shengliang Lu, Mr. Qinbin Li and Mr. Xinyu Chen got Research Achievement Award of SoC, 2021.
  • Hongshi Tan*, Xinyu Chen*, Yao Chen, Bingsheng He, Weng-Fai Wong. ThundeRiNG: Generating Multiple Independent Random Number Sequences on FPGAs. ACM ICS: International Conference on Supercomputing 2021.
  • Qinbin Li*, Bingsheng He, Dawn Song. Practical One-Shot Federated Learning for Cross-Silo Setting. IJCAI: 30th International Joint Conference on Artificial Intelligence, 2021.
  • [Survey] Zeyi Wen^, Qinbin Li*, Bingsheng He, Bin Cui. Challenges and Opportunities of Building Fast GBDT Systems. IJCAI: 30th International Joint Conference on Artificial Intelligence - Survey Track, 2021.
• May 2021:
  • Our ThunderGP paper was selected as one of the top papers at FPGA 2021, invited to submit to FPGA 2021 Special Issue in ACM TRETS.
  • PREMIA Best Student Paper Gold Award 2021 (for the work "Qinbin Li*, Zeyi Wen^, Bingsheng He. Practical Federated Gradient Boosting Decision Trees. AAAI: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2020)").
• March 2021:
  • Johns Paul*, Bingsheng He, Shengliang Lu*, Chiew Tong Lau. MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures. ACM SIGMOD: ACM SIGMOD International Conference on Management of Data 2021.
  • Shengliang Lu*, Shixuan Sun^, Johns Paul*, Yuchen Li, Bingsheng He. Cache-Efficient Fork-Processing Patterns on Large Graphs. ACM SIGMOD: ACM SIGMOD International Conference on Management of Data 2021.
  • Shixuan Sun^, Yuhang Chen*, Bingsheng He, Bryan Hooi. PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration. ACM SIGMOD: ACM SIGMOD International Conference on Management of Data 2021.
  • Zhi Kang Johan Kok*, Gaurav, Sien Yi Tan, Feng Cheng, Shixuan Sun^, Bingsheng He. Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload. ACM SIGMOD: ACM SIGMOD International Conference on Management of Data 2021.
  • Chang Ye, Yuchen Li, Bingsheng He, Zhao Li, Jianling Sun. GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection. ACM SIGMOD: ACM SIGMOD International Conference on Management of Data 2021.
  • Shuhao Zhang*, Yancan Mao, Jiong He, Philipp Marian Grulich, Steffen Zeuch, Bingsheng He, Richard Ma, Volker Markl. Parallelizing Intra-Window Join on Multicores: An Experimental Study. ACM SIGMOD: ACM SIGMOD International Conference on Management of Data 2021.
  • Cheng Chen, Jun Yang, Mian Lu, Taize Wang, Zhao Zheng, Yuqiang Chen, Wenyuan Dai, Bingsheng He, Weng-Fai Wong, Guoan Wu, Yuping Zhao, Andy Rudoff. Optimizing In-memory Database Engine For AI-powered On-line Decision Augmentation Using Persistent Memory. VLDB: International Conference on Very Large Data Bases (VLDB) 2021. (also published in Proceedings of the VLDB Endowment, Volume 14 Issue 5, 2020)
• Jan 2021: I am extremely honored...
  • I am appointed as NUS Dean's Chair Associate Professor, Jan 2021-Dec 2023.
  • New: ACM Distinguished Member Award 2020.
• Dec 2020: Great thanks to Xilinx donating Xilinx Adaptive Compute Clusters (XACC) program 2020 (one of the four awarded projects worldwide from Xilinx).
• Nov 2020:
  • Xinyu Chen*, Hongshi Tan*, Yao Chen, Bingsheng He, Weng-Fai Wong and Deming Chen. ThunderGP: HLS-based Graph Processing Framework on FPGAs. FPGA 2021: ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2021).
  • Shengliang Lu*, Bingsheng He, Yuchen Li, Hao Fu*. Accelerating Exact Constrained Shortest Paths on GPUs. International Conference on Very Large Data Bases (VLDB) 2021.
  • New! 2019 Best Paper Award from IEEE Transactions on Parallel and Distributed Systems by the IEEE Computer Society Publications Board (1 out of 987 submissions, for the work "Zeyi Wen^, Jiashuai Shi*, Bingsheng He, Jian Chen, Kotagiri Ramamohanarao, and Qinbin Li*, Exploiting GPUs for Efficient Gradient Boosting Decision Tree Training , IEEE Transactions on Parallel and Distributed Systems, vol. 30, no. 12, 2019, pp. 2706-2717.")
• Oct 2020:
  • Shixuan Sun^, Xibo Sun, Yulin Che, Qiong Luo, Bingsheng He. RapidMatch: A Holistic Approach to Subgraph Query Processing. International Conference on Very Large Data Bases (VLDB) 2021.
  • Johns Paul*, Bingsheng He, Shengliang Lu*, Chiew Tong Lau. Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs. International Conference on Very Large Data Bases (VLDB) 2021.
  • Johns Paul*, Jie Liang Ang*, Tianyuan Fu*, Bingsheng He, Shengliang Lu*, Sien Yi Tan and Feng Cheng. Poet: an Interactive Spatial Query Processing System in Grab. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (Industrial Paper).
• July 2020: we have made the following open-sourced systems:
  • ThunderGP: Fast Graph Processing for HLS-based FPGAs. ThunderGP is featured at Xilinx Apps and Libraries.
  • G3: a programming framework for Graph Neural Network (GNN) applications on GPUs.
• July 2020: I was appointed as Vice Dean (Research), NUS School of Computing.
• July 2020: Invited plenary speech at NPC 2020 (17th IFIP International Conference on Network and Parallel Computing), Sept.28-30, 2020 (expected).
• June 2020: Invited keynote speech at ISPA 2020 (18th IEEE International Symposium on Parallel and Distributed Processing with Applications), Oct 15-27 2020 (expected).
• June 2020: Wentian Guo, Yuchen Li, Mo Sha, Bingsheng He, Xiaokui Xiao, Kian-Lee Tan. Accelerated Subgraph Enumeration on Partitioned Graphs. SIGMOD 2020: ACM SIGMOD International Conference on Management of data, 2020.
• June 2020: Internships are filled (May 2020-Oct 2020): we have four internships available for NUS students to fulfill their internship requirement (under special arrangement of COVID-19). see "Software Developer Interns for Graph Neural Network Project".
• April 2020: our system paper for ThunderGBM has been accepted in JMLR Machine Learning Open Source Software. Cheers! Details: Zeyi Wen, Jiashuai Shi, Hanfeng Liu, Bingsheng He, Qinbin Li, Jian Chen. ThunderGBM: Fast GBDTs and Random Forests on GPUs. JMLR: Journal of Machine Learning Research (2020).
• April 2020:
  • Feng Zhang, Ningxuan Feng, Yani Liu, Cheng Yang, Jidong Zhai, Shuhao Zhang, Bingsheng He, Jiazao Lin, Xiaoyong Du. PewLSTM: Periodic LSTM with Weather-Aware Gating Mechanism for Parking Behavior Prediction. IJCAI-PRICAI 2020 (610/4806=12.7%).
  • Feng Zhang, Lin Yang, Shuhao Zhang, Bingsheng He, Wei Lu, Xiaoyong Du. FineStream: Fine-Grained Window-Based Stream Processing on CPU-GPU Integrated Architectures. USENIX ATC: USENIX Annual Technical Conference 2020 (65/348=18.7%).
• Feb 2020: three papers are accepted in ICDE 2020.
  • Li Wang, Zining Zhang*, Zhenjie Zhang, Bingsheng He. PA-Tree: Polled-Mode Asynchronous B+-Tree for NVMe. ICDE 2020: IEEE International Conference on Data Engineering 2020.
  • Shuhao Zhang*, Yingjun Wu, Feng Zhang, Bingsheng He. Towards Concurrent Stateful Stream Processing on Multicore Processors. ICDE 2020: IEEE International Conference on Data Engineering 2020.
  • Hong Huang, Xuanhua Shi, Yipeng Zhang, Zhenyu Hu, Hai Jin, Huan Shen, Yongluan Zhou, Bingsheng He, Ruibo Li, Keyong Zhou. Maxson: Reduce duplicate Parsing Overhead on Raw Data. ICDE 2020: IEEE International Conference on Data Engineering 2020 (Industry and Application track, acceptance rate: 26%).
• Jan 2020: Xtra's member Mr. Qinbin Li and Mr. Xinyu Chen got Research Achievement Award of SoC, 2020.
• Nov 2019: one paper is accepted in CIDR 2020. Details: Xinyu Chen*, Ronak Bajaj^, Yao Chen, Jiong He, Bingsheng He, Weng-Fai Wong and Deming Chen. Is FPGA useful for hash joins. CIDR 2020: Conference on Innovative Data Systems Research.
• Nov 2019: two papers are accepted in AAAI 2020.
  • Qinbin Li*, Zeyi Wen^, Bingsheng He. Practical Federated Gradient Boosting Decision Trees. AAAI: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) (1,591/7,737=20.6%).
  • Qinbin Li*, Zhaomin Wu*, Zeyi Wen^, Bingsheng He. Privacy-Preserving Gradient Boosting Decision Trees. AAAI: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) (1,591/7,737=20.6%).
• Oct 2019: two papers are accepted in IEEE TPDS.
  • Qiumin Lu, Zheng Xiao, Jiacheng Ma, Yaozu Dong, Zhengwei Qi, Jianguo Yao, Bingsheng He, Haibing Guan. gMig: Efficient vGPU Live Migration with Overlapped Software-based Dirty Page Verification. TPDS: IEEE Transactions on Parallel and Distributed Systems 2019
  • Amelie Chi Zhou, Bingkun Shen, Yao Xiao, Shadi Ibrahim, Bingsheng He. Cost-Aware Partitioning for Efficient Large Graph Processing in Geo-Distributed Datacenters. TPDS: IEEE Transactions on Parallel and Distributed Systems 2019.
• Oct 2019: Qinbin's undergraduate project has been published in IEEE TNNLS. Details: Qinbin Li*, Zeyi Wen^, Bingsheng He. Adaptive Kernel Value Caching for SVM Training. IEEE TNNLS: IEEE Transactions on Neural Networks and Learning Systems.
• Sept 2019: Xtra's member Mr. Shuhao Zhang has successfully done his Ph.D. defense. Congratulations, Dr. Zhang.
• Sept 2019: one paper is accepted in IEEE TKDE. Details: Feng Zhang, Jidong Zhai, Bo Wu, Bingsheng He, Wenguang Chen, Xiaoyong Du. Automatic Irregularity-Aware Fine-Grained Workload Partitioning on Integrated