Jianguo Wang, Ph.D.

Biography

Jianguo Wang is currently a database engineer at Amazon Web Services (AWS), where he works on Amazon Aurora, a cloud-native distributed transactional SQL database. In particular, he is working on Aurora Globally-Distributed Database, which spans multiple AWS regions, and most importantly, horizontally scales SQL database in the cloud.

Before that, he worked as an intern at Oracle, Microsoft Research, Samsung, and Tencent.

He received his PhD degree in Computer Science from University of California, San Diego, co-supervised by Prof. Yannis Papakonstantinou and Prof. Steven Swanson; his Mphil degree in Computer Science from The Hong Kong Polytechnic University, co-advised by Prof. Eric Lo and Prof. Man Lung Yiu; and his BEng degree in Computer Science from Zhengzhou University.

Research Interests

• Database Systems
  
   
  • search/query/storage engine, indexing, transactions, distributed databases
 
• Cloud-Native Database
  
   
  • storage-compute-memory disaggregation, serverless computing
 
• Database for Modern Hardware
  
   
  • storage (NVRAM, Smart SSD), compute (SIMD, GPU), networks (RDMA, Smart NIC)
 
• Database for Emerging Applications
  
   
  • mass spectrometry, proteomics, medical/health sciences

Working Experience

• Aurora Cloud Database Team, Amazon AWS, Palo Alto, CA   03/2019 - present
  
   
  • Project: Aurora Globally-Distributed Database for the Cloud


• [PhD Research] University of California, San Diego, CA   09/2013 - 12/2018
  
   
  • Project 1: Big Data Analytics in Protein Databases (part of NSF 1759980)
   
  • Project 2: Query Processing on Compressed Data in Main Memory Databases (part of NSF 1447943)
   
  • Project 3: Re-Architecturing Search Engine Systems for New Hardware Platforms (part of NSF 1219125)
   


• [Intern] Oracle Advanced Development Group, Oracle Inc, Redwood Shores, CA   06-09/2018
  
   
  • Project: Bloom Filter Compression for In-Memory Databases
   


• [Intern] MSR Database Group, Microsoft Research, Redmond, WA   06-09/2015
  
   
  • Project: Optimizing the Bw-tree Indexing for High Performance Transactions
   


• [Intern] Samsung System Architecture Lab, Samsung Inc, San Jose, CA   06-09/2014
  
   
  • Project: SSD In-Storage Computing (a.k.a Smart SSD)
   

Awards

• Bests of the International Conference on Database Theory (ICDT) 2019

• Yuliang Li, Jianguo Wang, Benjamin Pullman, Nuno Bandeira, Yannis Papakonstantinou.
  Index-based High-dimensional Cosine Threshold Querying with Optimality Guarantees.
  Proceedings of International Conference on Database Theory (ICDT), pages 11:1-11:20, 2019.
  Bests of ICDT 2019, invited to ToCS special issue (submission).


• Yang Liu, Jianguo Wang, Steven Swanson.
  Griffin: Uniting CPU and GPU in Information Retrieval Systems for Intra-Query Parallelism.
  Proceedings of ACM Symposium on Principles and Practice of Parallel Programming (PPoPP), pages 327-337, 2018.


• Chunbin Lin, Jiaheng Lu, Zhewei Wei, Jianguo Wang, Xiaokui Xiao.
  Optimal Algorithms for Selecting Top-k Combinations of Attributes: Theory and Applications.
  Very Large Data Base Journal (VLDBJ), 27(1): 27-52, 2018.


• Jianguo Wang, Chunbin Lin, Yannis Papakonstantinou, Steven Swanson.
  An Experimental Study of Bitmap Compression vs. Inverted List Compression.
  Proceedings of ACM Conference on Management of Data (SIGMOD), pages 993-1008, 2017.


• Jianguo Wang, Chunbin Lin, Ruining He, Moojin Chae, Yannis Papakonstantinou, Steven Swanson.
  MILC: Inverted List Compression in Memory.
  Proceedings of Very Large Data Bases Conference (VLDB), pages 853-864, 2017.


• Chuitian Rong, Chunbin Lin, Yasin Silva, Jianguo Wang, Wei Lu, Xiaoyong Du.
  Fast and Scalable Distributed Set Similarity Joins for Big Data Analytics.
  Proceedings of International Conference on Data Engineering (ICDE), pages 1059-1070, 2017.


• Chunbin Lin, Jianguo Wang, Yannis Papakonstantinou.
  GQFast: Fast Graph Exploration with Context-aware Autocompletion.
  Proceedings of International Conference on Data Engineering (ICDE), pages 1389-1390, 2017.


• Chunbin Lin, Jianguo Wang, Jiaheng Lu.
  Location-sensitive Query Auto-completion.
  Proceedings of International World Wide Web Conference (WWW), pages 819-820, 2017.


• Jianguo Wang, Dongchul Park, Yang-Suk Kee, Yannis Papakonstantinou, Steven Swanson.
  SSD In-Storage Computing for List Intersection.
  Proceedings of International Workshop on Data Management on New Hardware (DaMoN), affiliated with SIGMOD, pages 4:1-4:7, 2016.


• Ruining He, Chunbin Lin, Jianguo Wang, Julian McAuley.
  Sherlock: Sparse Hierarchical Embeddings for Visually-aware One-class Collaborative Filtering.
  Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pages 3740-3746, 2016.


• Jianguo Wang, Eric Lo, Man Lung Yiu, Jiancong Tong, Gang Wang, Xiaoguang Liu.
  Cache Design of SSD-Based Search Engine Architectures: An Experimental Study.
  ACM Transactions on Information Systems (TOIS), 32(4): 1-26, 2014.


• Jianguo Wang, Eric Lo, Man Lung Yiu, Jiancong Tong, Gang Wang, Xiaoguang Liu.
  The Impact of Solid State Drive on Search Engine Cache Management.
  Proceedings of ACM Conference on Research and Development in Information Retrieval (SIGIR), pages 693-702, 2013.


• Jianguo Wang, Eric Lo, Man Lung Yiu.
  Identifying the Most Connected Vertices in Hidden Bipartite Graphs using Group Testing.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 25(10): 2245-2256, 2013.
  

Services

• AIDB@VLDB 2020, program committee
• VLDB 2020, program committee, industry track
• SIGIR 2020, program committee
• WWW 2020, program committee
• CLOUD 2020, program committee
• BigData (2020, 2019, 2018), program committee
• WSDM (2020, 2019), program committee
• TKDE (2019, 2018), reviewer
• TC (2019, 2018), reviewer
• TPDS 2019, reviewer