Mayuresh Kunjir is a postdoctoral researcher at Qatar Center for Artificial Intelligence (QCAI), a sub-entity of QCRI. He primarily works on the problems of data discovery and data integration in modern data lake architectures.
Before joining QCRI, Mayuresh graduated with a PhD in Computer Science from Duke University, with a dissertation on memory management for data analytics systems.
Duke University; Durham, NC2019
Speeding up AutoTuning of the Memory Management Options in Data Analytics. Distributed Parallel Databases 38(4): 841-863 (2020)2020
Black or White? How to Develop an AutoTuner for Memory-based Analytics. SIGMOD Conference 2020: 1667-16832020
Black or White? How to Develop an AutoTuner for Memory-based Analytics [Extended Version]. CoRR abs/2002.117802020
Automating Memory Management in Data Analytics. Duke University, Durham, NC, USA,2019
Guided Bayesian Optimization to AutoTune Memory-Based Analytics. ICDE Workshops 2019: 125-1322019
Thoth in Action: Memory Management in Modern Data Analytics. Proc. VLDB Endow. 10(12): 1917-19202017
ROBUS: Fair Cache Allocation for Data-parallel Workloads. SIGMOD Conference 2017: 219-2342017
ROBUS: Fair Cache Allocation for Multi-tenant Data-parallel Workloads. CoRR abs/1504.067362015
Thoth: Towards Managing a Multi-System Cluster. Proc. VLDB Endow. 7(13): 1689-16922014
Peak power plays in database engines. EDBT 2012: 444-4552012