| ALEX: an updatable adaptive learned index J Ding, UF Minhas, J Yu, C Wang, J Do, Y Li, H Zhang, B Chandramouli, ... Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 318 | 2020 |
| Trill: A high-performance incremental query processor for diverse analytics B Chandramouli, J Goldstein, M Barnett, R DeLine, D Fisher, JC Platt, ... Proceedings of the VLDB Endowment 8 (4), 401-412, 2014 | 254 | 2014 |
| Faster: A concurrent key-value store with in-place updates B Chandramouli, G Prasaad, D Kossmann, J Levandoski, J Hunter, ... Proceedings of the 2018 International Conference on Management of Data, 275-290, 2018 | 186 | 2018 |
| Temporal analytics on big data for web advertising B Chandramouli, J Goldstein, S Duan 2012 IEEE 28th international conference on data engineering, 90-101, 2012 | 137 | 2012 |
| Real-time-ready behavioral targeting in a large-scale advertisement system B Chandramouli, J Goldstein, X Jin, BS Raman, S Duan US Patent 8,442,863, 2013 | 129 | 2013 |
| Microsoft CEP server and online behavioral targeting MH Ali, C Gerea, BS Raman, B Sezgin, T Tarnavski, T Verona, P Wang, ... Proceedings of the VLDB Endowment 2 (2), 1558-1561, 2009 | 128 | 2009 |
| Streamrec: a real-time recommender system B Chandramouli, JJ Levandoski, A Eldawy, MF Mokbel Proceedings of the 2011 ACM SIGMOD International Conference on Management of …, 2011 | 122 | 2011 |
| Asynchronous transfer of state information between continuous query plans B Chandramouli, JD Goldstein, PA Zabback, DE Maier, D Wang US Patent 8,478,743, 2013 | 114 | 2013 |
| Complex event processor for historic/live/replayed data L Bussard, IJG dos Santos, O Nano, T Tarnavski, J Goldstein, ... US Patent 9,632,846, 2017 | 108 | 2017 |
| Mison: a fast JSON parser for data analytics Y Li, NR Katsipoulakis, B Chandramouli, J Goldstein, D Kossmann Proceedings of the VLDB Endowment 10 (10), 1118-1129, 2017 | 106 | 2017 |
| Qd-tree: Learning data layouts for big data analytics Z Yang, B Chandramouli, C Wang, J Gehrke, Y Li, UF Minhas, PÅ Larson, ... Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 103 | 2020 |
| Efficient logical merging over physically divergent streams B Chandramouli, DE Maier, JD Goldstein, PA Zabback US Patent 9,965,520, 2018 | 78 | 2018 |
| High-performance dynamic pattern matching over disordered streams B Chandramouli, J Goldstein, D Maier Proceedings of the VLDB Endowment 3 (1-2), 220-231, 2010 | 78 | 2010 |
| Estimating latencies for query optimization in distributed stream processing B Chandramouli, J Goldstein US Patent App. 12/573,108, 2010 | 74 | 2010 |
| The extensibility framework in Microsoft StreamInsight M Ali, B Chandramouli, J Goldstein, R Schindlauer 2011 IEEE 27th International Conference on Data Engineering, 1242-1253, 2011 | 70 | 2011 |
| Dynamic pattern matching over ordered and disordered data streams B Chandramouli, JD Goldstein, D Maier, MH Ali, R Schindlauer US Patent 8,762,297, 2014 | 65 | 2014 |
| Scalable progressive analytics on big data in the cloud B Chandramouli, J Goldstein, A Quamar Proceedings of the VLDB Endowment 6 (14), 1726-1737, 2013 | 63 | 2013 |
| Accurate latency estimation in a distributed event processing system B Chandramouli, J Goldstein, R Barga, M Riedewald, I Santos 2011 IEEE 27th International Conference on Data Engineering, 255-266, 2011 | 63 | 2011 |
| Spatio-temporal stream processing in microsoft streaminsight MABCB Sethu, RE Katibah Data Engineering 69, 2010 | 60 | 2010 |
| Cloud-edge topologies B Chandramouli, SK Nath, W Zhou US Patent 9,098,344, 2015 | 58 | 2015 |
Yinan LiMicrosoft ResearchVerified email at microsoft.com
