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ORCIDAbhishek Roy 0008
Person information
- affiliation: Snowflake Inc.
- affiliation (former): Keebo Inc., Ann Arbor, MI, USA
- affiliation (former): Microsoft, Gray Systems Lab, Azure Data
- affiliation (former): University of Massachusetts Amherst, MA, USA
- affiliation (former): Indian Institute of Technology Guwahati, India
Other persons with the same name
- Abhishek Roy — disambiguation page
- Abhishek Roy 0001
![[0000-0002-9272-6778]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-9272-6778")
— Samsung Electronics, Suwon, South Korea (and 1 more) - Abhishek Roy 0002 — University of Virginia, Charlottesville, VA, USA
- Abhishek Roy 0003 — Texas A&M University, Department of Computer Science, College Station, TX, USA (and 1 more)
- Abhishek Roy 0004 — Temple University, School of Business and Management, Philadelphia, PA, USA (and 1 more)
- Abhishek Roy 0005 — University of California, Davis, Department of Electrical and Computer Engineering, CA, USA
- Abhishek Roy 0006 — Indian Institute of Technology Patna, India
- Abhishek Roy 0007 — George Mason University, Department of Computer Science, Fairfax, VA, USA
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2020 – today
- 2023
[c8]Rathijit Sen, Abhishek Roy, Alekh Jindal:
Predictive Price-Performance Optimization for Serverless Query Processing. EDBT 2023: 118-130- [c7]Barzan Mozafari, Radu Alexandru Burcuta, Alan Cabrera, Andrei Constantin, Derek Francis, David Grömling, Alekh Jindal, Maciej Konkolowicz, Valentin Marian Spac, Yongjoo Park, Russell Razo Carranzo, Nicholas Richardson, Abhishek Roy, Aayushi Srivastava, Isha Tarte, Brian Westphal, Chi Zhang:
Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning. SIGMOD Conference Companion 2023: 239-251 - 2021
- [j6]Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal:
Phoebe: A Learning-based Checkpoint Optimizer. Proc. VLDB Endow. 14(11): 2505-2518 (2021) - [j5]Rathijit Sen, Abhishek Roy, Alekh Jindal, Rui Fang, Jeff Zheng, Xiaolei Liu, Ruiping Li:
AutoExecutor: Predictive Parallelism for Spark SQL Queries. Proc. VLDB Endow. 14(12): 2855-2858 (2021) - [j4]Abhishek Roy, Alekh Jindal, Priyanka Gomatam, Xiating Ouyang, Ashit Gosalia, Nishkam Ravi, Swinky Mann, Prakhar Jain:
SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft. Proc. VLDB Endow. 14(12): 3122-3134 (2021) - [j3]H. M. Sajjad Hossain, Marc T. Friedman, Hiren Patel, Shi Qiao, Soundar Srinivasan, Markus Weimer, Remmelt Ammerlaan, Lucas Rosenblatt, Gilbert Antonius, Peter Orenberg, Vijay Ramani, Abhishek Roy, Irene Shaffer, Alekh Jindal:
PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! Proc. VLDB Endow. 14(13): 3362-3375 (2021) - [c6]Alekh Jindal, Shi Qiao, Hiren Patel, Abhishek Roy, Jyoti Leeka, Brandon Haynes:
Production Experiences from Computation Reuse at Microsoft. EDBT 2021: 623-634 - [i3]Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal:
Phoebe: A Learning-based Checkpoint Optimizer. CoRR abs/2110.02313 (2021) - [i2]Rathijit Sen, Abhishek Roy, Alekh Jindal:
Predictive Price-Performance Optimization for Serverless Query Processing. CoRR abs/2112.08572 (2021) - 2020
- [c5]Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu:
Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. CIDR 2020
2010 – 2019
- 2019
- [j2]Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino:
SparkCruise: Handsfree Computation Reuse in Spark. Proc. VLDB Endow. 12(12): 1850-1853 (2019) - [c4]Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan:
Peregrine: Workload Optimization for Cloud Query Engines. SoCC 2019: 416-427 - [i1]Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu:
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. CoRR abs/1909.00084 (2019) - 2017
- [c3]Abhishek Roy, Yanlei Diao, Uday Evani, Avinash Abhyankar, Clinton Howarth, Rémi Le Priol, Toby Bloom:
Massively Parallel Processing of Whole Genome Sequence Data: An In-Depth Performance Study. SIGMOD Conference 2017: 187-202 - 2015
- [c2]Yanlei Diao, Abhishek Roy, Toby Bloom:
Building Highly-Optimized, Low-Latency Pipelines for Genomic Data Analysis. CIDR 2015 - 2012
- [j1]Abhishek Roy, Yanlei Diao, Evan Mauceli, Yiping Shen, Bai-Lin Wu:
Massive Genomic Data Processing and Deep Analysis. Proc. VLDB Endow. 5(12): 1906-1909 (2012)
2000 – 2009
Coauthor Index
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