I manage the Redmond site of Gray Systems Lab (GSL) at Microsoft. GSL is an applied research lab under Azure Data that focuses on research and development for databases, big-data, and cloud systems. My research focusses on improving the performance of large-scale data-intensive systems. Earlier, I was a postdoc associate in the Database Group at MIT CSAIL, working with Professors Sam Madden and Michael Stonebraker. I received my PhD from Saarland University, working with Prof. Jens Dittrich, During my PhD, I worked on flexible and scalable data storage for traditional databases as well as for MapReduce. Before that I completed masters studies at Max Planck Institute for Informatics and received bachelor degree from IIT Kanpur.

• Machine Learning for Databases
• Workload Optimization in Cloud Data Services
• Large-scale Data-intensive Systems
• Data Preparation and Design
• Big Data Analytics

• Resource Optimization
• Peregrine
• Learning Optimizer
• CloudViews

• Cartilage
• Vertexica
• OctopusDB
• Hadoop++/HAIL

• Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
  AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft
  VLDB 2020, Tokyo, Japan. (to appear)


• Malay Bag, Alekh Jindal, Hiren Patel
  Towards Plan-aware Resource Allocation in Serverless Query Processing
  HotCloud 2020, Boston, USA. (to appear)


• Alekh Jindal
  Applied Research Lessons from CloudViews Project
  SIGMOD Record (to appear)


• Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao Le
  Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
  SIGMOD 2020, Portland, USA.arXiv


• H M Sajjad Hossain, Lucas Rosenblatt, Gilbert Antonius, Irene Shaffer, Remmelt Ammerlaan, Abhishek Roy, Markus Weimer, Hiren Patel, Marc Friedman, Shi Qiao, Peter Orenberg, Soundarajan Srinivasan, Vijay Ramani, Alekh Jindal
  PerfGuard: Deploying ML-for-Systems without Performance Regressions
  MLOps Systems 2020, Austin, USA.


• Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Gowdal, Matteo Interlandi, Alekh Jindal, Kostantinos 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, Amsterdam, Netherlands.
  


• Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Jarod Yin, Rathijit Sen, Subru Krishnan
  Peregrine: Workload Optimization for Cloud Query Engines
  SOCC 2019, Santa Cruz, California.


• Hiren Patel, Alekh Jindal, Clemens Szyperski
  Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost
  SOCC 2019, Santa Cruz, California. (poster)


• Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
  SparkCruise: Handsfree Computation Reuse in Spark
  VLDB 2019/PVLDB, Los Angeles, USA. (Demo paper)


• Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
  Towards a Learning Optimizer for Shared Clouds
  VLDB 2019/PVLDB, Los Angeles, USA.


• Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
  Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
  arXiv:1906.06590 [cs.DB], June 2019


• Alekh Jindal, Anil Shanbhag, Yi Lu
  Robust Data Partitioning
  Encyclopedia of Big Data Technologies, 2019, Springer.
  Invited Chapter


• Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
  Selecting Subexpressions to Materialize at Datacenter Scale
  VLDB 2018/PVLDB, Rio de Janeiro, Brazil.


• Alekh Jindal, Shi Qiao, Hiren Patel, Jarod Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
  Computation Reuse in Analytics Job Service at Microsoft
  SIGMOD 2018, Houston, USA.


• Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
  Query and Resource Optimization: Bridging the Gap
  ICDE 2018, Paris, France (Short paper).


• Kristin Tufte, Kushal Datta, Alekh Jindal, David Maier, Robert L Bertini
  Challenges and Opportunities in Transportation Data
  Symposium on Smart Cities and Communities 2018, Portland, USA.


• Anil Shanbhag, Alekh Jindal, Samuel Madden, Jorge Quiane, Aaron Elmore
  A Robust Partitioning Scheme for Ad-Hoc Query Workloads
  SOCC 2017, Santa Clara, USA.


• Yi Lu, Anil Shanbhag, Alekh Jindal, Samuel Madden
  AdaptDB: Adaptive Partitioning for Distributed Joins
  VLDB 2017, Munich, Germany.


• Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Samuel Madden
  IngestBase: A Declarative Data Ingestion System
  arXiv:1701.06093 [cs.DB], Jan 2017


• Anil Shanbhag, Alekh Jindal, Yi Lu, Samuel Madden
  Amoeba: A Shape changing Storage System for Big Data
  VLDB 2016, New Delhi, India. (Demo paper)


• Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia
  GraphFrames: An Integrated API for Mixing Graph and Relational Queries
  GRADES 2016, California, USA.


• Alekh Jindal, Samuel Madden, Malú Castellanos, Meichun Hsu
  Graph Analytics using Vertica Relational Database
  IEEE BigData 2015, Santa Clara, USA.


• Felix Martin Schuhknecht, Alekh Jindal, Jens Dittrich
  An Experimental Evaluation and Analysis of Database Cracking
  The VLDB Journal, August 2015
  Special Issue on best papers of VLDB 2014


• Zuhair Khayyat, Ihab F. Ilyas, Alekh Jindal, Samuel Madden, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiane-Ruiz, Nan Tang, Si Yin
  BigDansing: A System for Big Data Cleansing
  SIGMOD 2015, Melbourne, Australia.


• Alekh Jindal
  Robust Data Transformations
  CIDR 2015, Asilomar, USA. (Abstract)


• Alekh Jindal, Samuel Madden, Malu Castellanos, Meichun Hsu
  Graph Analytics using the Vertica Relational Database
  arXiv:1412.5263 [cs.DB], Dec 17, 2014


• Alekh Jindal, Samuel Madden
  GraphiQL: A Graph Intuitive Query Language for Relational Databases
  IEEE BigData 2014, Washington DC, USA. (Acceptance rate: 18.5%) [slides]


• Alekh Jindal, Praynaa Rawlani, Eugene Wu, Samuel Madden, Amol Deshpande, Mike Stonebraker
  Vertexica: Your Relational Friend for Graph Analytics!
  VLDB 2014, Hangzhou, China. (Demo paper)


• Felix Martin Schuhknecht, Alekh Jindal, Jens Dittrich
  The Uncracked Pieces in Database Cracking
  VLDB 2014/PVLDB, Hangzhou, China. [Source Code]
  Best Paper Award


• Alekh Jindal, Endre Palatinus, Vladimir Pavlov, Jens Dittrich
  A Comparison of Knives for Bread Slicing
  VLDB 2013/PVLDB, Riva, Italy.


• Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Samuel Madden
  Cartilage: Adding Flexibility to the Hadoop Skeleton
  SIGMOD 2013, New York, USA. (Demo paper) [poster]


• Barzan Mozafari, Carlo Curino, Alekh Jindal, Samuel Madden
  Performance and Resource Modeling in Highly-Concurrent OLTP Workloads
  SIGMOD 2013, New York, USA.


• Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Jens Dittrich
  WWHow! Freeing Data Storage from Cages
  CIDR 2013, Asilomar, USA.


• Alekh Jindal, Felix Martin Schuhknecht, Jens Dittrich, Karen Khachatryan, Alexander Bunte
  How Achaeans Would Construct Columns in Troy
  CIDR 2013, Asilomar, USA. [slides]


• Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz, Stefan Richter, Stefan Schuh, Alekh Jindal, Jörg Schad
  Only Aggressive Elephants are Fast Elephants
  VLDB 2012/PVLDB, Istanbul, Turkey.


• Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Jens Dittrich
  Trojan Data Layouts: Right Shoes for a Running Elephant
  ACM SOCC 2011, Cascais, Portugal. [slides] [poster]


• Alekh Jindal, Jens Dittrich
  Relax and Let the Database do the Partitioning Online
  VLDB BIRTE 2011, Seattle, USA. TR [slides]


• Jens Dittrich, Alekh Jindal
  Towards a one-size-fits-all Database Architecture
  CIDR 2011, Outrageous Ideas and Vision Track, Asilomar, USA.
  Best Outrageous Ideas and Vision Paper Award (CCC Blog)


• Jens Dittrich, Jorge-Arnulfo Quiane-Ruiz, Alekh Jindal, Yagiz Kargin, Vinay Setty, and Jörg Schad.
  Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing)
  VLDB 2010, Singapore.


• Alekh Jindal
  The Mimicking Octopus: Towards a one-size-fits-all Database Architecture
  VLDB 2010 PhD Workshop, Singapore. [slides] [poster]

• Computation Reuse in Analytics Job Service (US20190318025A1).
• Learning Optimizer for Shared Cloud (US20190303475A1).
• Selection of Subexpressions to Materialize for Datacenter Scale (US20190236189A1).
• Replicated data storage system and methods (WO2013139379).
• A method for storing and accessing data in a database system (WO2012032184, US20130226959).

• 2021: PC Member, PVLDB
• 2020: PC Member, ICDE VLDB(Demo)
• 2019: PC Member, SIGMOD ICDE EDBT SOCC CIKM VLDB(Demo)
• 2018: PC Member, CIKM DEEM DASFAA TKDE Poster
• 2017: PC Member, PVLDB SIGMOD ICDE EDBT VLDB(Demo) SIGMOD(SRC)
            Reviewer, DAPD
• 2016: Proceedings Chair, SIGMOD
            PC Member, SIGMOD SIGMOD(Demo) VLDB(Demo) ICDE(Demo) EDBT(Vision)
• 2015: PC Member, PVLDB SIGMOD EDBT(Demo)
            Reviewer, SIGMOD Record TON TKDE TODS
• 2014: PC Member, PVLDB
            Referee, SIGMOD Record
• 2013: Reviewer, PVLDB SIGMOD ICDE CIKM DAPD
• 2012: Reviewer, PVLDB ICDE
• 2011: Reviewer, EDBT
• 2010: Reviewer, VLDB

• April 2013 - August 2015:
  Postdoctoral Associate, CSAIL, Massachusetts Institute of Technology, USA.
  Focus: Big Data Analytics. Research Teaching
  Mentor: Prof. Samuel Madden


• February 2010 - August 2012:
  Ph.D. (Summa Cum Laude), Computer Science, Saarland University, Germany.
  Thesis: OctopusDB:Flexible and Scalable Storage Management for Arbitrary Database Engines. PDF
  Supervisor: Prof. Jens Dittrich


• October 2008 - January 2010:
  Master of Science (honors), Computer Science, Saarland University & Max Plank Institute for Informatics, Germany.
  Thesis: Quality in Phrase Mining. PDF
  Supervisors: Prof. Jens Dittrich, Prof. Gerhard Weikum


• July 2002 - June 2006:
  Bachelor of Technology, Electrical Engineering, Indian Institute of Technology, Kanpur, India.
  Thesis: Microcontroller Based Power Distribution Monitoring & Control. PDF
  Supervisor: Prof. S. P. Das