| Free dolly: Introducing the world’s first truly open instruction-tuned llm M Conover, M Hayes, A Mathur, J Xie, J Wan, S Shah, A Ghodsi, ... Company Blog of Databricks, 2023 | 335 | 2023 |
| Personalized delivery time optimization RKH Vijay, B Arai, M Hull, U Irmak, P Khincha, SM Shah, J Yan, L Yuan US Patent 9,473,446, 2016 | 300 | 2016 |
| Serving large-scale batch computed data with project Voldemort. R Sumbaly, J Kreps, L Gao, A Feinberg, C Soman, S Shah FAST 12, 18-18, 2012 | 264 | 2012 |
| Systems and methods for email response prediction SM Shah, U Irmak, F Jumah, B Arai US Patent 9,344,297, 2016 | 243 | 2016 |
| Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022 | 231 | 2022 |
| Root cause detection in a service-oriented architecture M Kim, R Sumbaly, S Shah ACM SIGMETRICS Performance Evaluation Review 41 (1), 93-104, 2013 | 203 | 2013 |
| The big data ecosystem at linkedin R Sumbaly, J Kreps, S Shah Proceedings of the 2013 ACM SIGMOD International Conference on Management of …, 2013 | 197 | 2013 |
| LinkedIn skills: large-scale topic extraction and inference M Bastian, M Hayes, W Vaughan, S Shah, P Skomoroch, H Kim, ... Proceedings of the 8th ACM Conference on Recommender systems, 1-8, 2014 | 118 | 2014 |
| Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Medrxiv, 2021.02. 03.21250974, 2021 | 91 | 2021 |
| Using Provenance to Aid in Personal File Search. S Shah, CAN Soules, GR Ganger, BD Noble USENIX Annual Technical Conference, 171-184, 2007 | 77 | 2007 |
| The browsemaps: Collaborative filtering at LinkedIn. L Wu, S Shah, S Choi, M Tiwari, C Posse RSWeb@ RecSys 1271, 2014 | 65 | 2014 |
| A scenario modeling pipeline for COVID-19 emergency planning JC Lemaitre, KH Grantz, J Kaminsky, HR Meredith, SA Truelove, ... Scientific reports 11 (1), 7534, 2021 | 63 | 2021 |
| Modeling impression discounting in large-scale recommender systems P Lee, LVS Lakshmanan, M Tiwari, S Shah Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 41 | 2014 |
| Avatara: OLAP for web-scale analytics products L Wu, R Sumbaly, C Riccomini, G Koo, HJ Kim, J Kreps, S Shah Proceedings of the VLDB Endowment 5 (12), 1874-1877, 2012 | 35 | 2012 |
| Incremental processing on data intensive distributed applications SM Shah, MT Hayes US Patent App. 14/337,841, 2015 | 31 | 2015 |
| A study of e‐mail patterns S Shah, BD Noble Software: Practice and Experience 37 (14), 1515-1538, 2007 | 29 | 2007 |
| Hourglass: A library for incremental processing on Hadoop M Hayes, S Shah 2013 IEEE International Conference on Big Data, 742-752, 2013 | 27 | 2013 |
| Metaphor: a system for related search recommendations A Reda, Y Park, M Tiwari, C Posse, S Shah Proceedings of the 21st ACM international conference on Information and …, 2012 | 24 | 2012 |
| Connection invitation ordering SM Shah, M Tiwari, RR Sumbaly, C Wang US Patent 8,825,785, 2014 | 23 | 2014 |
| Generating member profile recommendations based on community overlap data in a social graph SM Shsh US Patent App. 14/192,010, 2015 | 20 | 2015 |
