Alekh Jindal

Alekh Jindal


Founding Chief Architect
Keebo

Greater Seattle Area, USA
e-mail: alekh@keebo.ai

Microsoft Research
LinkedIn
Twitter


I am the Chief Architect at Keebo, an early stage startup that is looking to reshape enterprise analytics with data learning. Before this, I managed the Redmond site of Gray Systems Lab (GSL), under Azure Data at Microsoft, that focused on research and development for databases, big-data, and cloud systems. My research interests lie in 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.



News
  • 12/21: PyScope goes into production!
  • 11/21: Steering query optimizer deployed in production for Cosmos!
  • 08/21: AutoExecutor wins the Best Demo Award at VLDB'21!
  • 08/21: PerfGuard paper for avoiding performance regression accepted to VLDB'22.
  • 08/21: Invited talk at LADSIOS and panel discussion in Poly panel at VLDB'21.
  • 07/21: Learning-based checkpoint optimizer paper accepted to VLDB'21.
  • 06/21: Steering query optimizer paper received Industry: Honorable Mention at SIGMOD'21!
  • 06/21: Paper on history and future of Cosmos big data platform accepted to VLDB'21 Ind.
  • 05/21: Tutorial on machine learning for cloud data systems accepted to VLDB'21.
  • 05/21: AutoExecutor demo accepted to VLDB'21.
  • 04/21: SparkCruise industry paper accepted to VLDB'21.
  • 01/21: Steering query optimizers paper accepted to SIGMOD'21 Ind.
  • 12/20: Learning optimizer paper accepted to ICDE'21 Ind.
  • 12/20: Experiences from shipping compute reuse accepted to EDBT'21 Ind. Teaser Talk
  • 10/20: Python at Cloud scale paper accepted to CIDR'21. Video Blog NWDS Talk
  • 10/20: Learned cardinality models deployed in Cosmos production!
  • 09/20: Seagull paper for load prediction accepted to PVLDB
  • 09/20: Applied research experiences appear in SIGMOD Record
  • 08/20: Dataset simulator from ~10K production pipelines released
  • 08/20: SparkCruise ships in Microsoft's own Apache distro!
  • 07/20: SparkCruise demoed on Synapse Spark @ Spark + AI Summit
  • 04/20: Plan-aware resource allocation paper accepted to HotCloud
  • 04/20: AutoToken paper for predicting resource allocation accepted to VLDB Ind. Blog
  • 03/20: CloudViews enabled for automatic reuse by default in Cosmos customers!
  • 01/20: Learned cost models paper accepted to SIGMOD

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

Current Projects
Past Projects
Publications
DBLP, Google Scholar, Microsoft Academic
Patents
  • System and method for machine learning for system deployments without performance regressions (US20210263932A1)
  • Cloud based query workload optimization (US20210089532A1)
  • Learned resource consumption model for optimizing big data queries (US20200349161A1)
  • Computation Reuse in Analytics Job Service (US Patent 11,068,482).
  • Learning Optimizer for Shared Cloud (US Patent 11,074,256).
  • Selection of Subexpressions to Materialize for Datacenter Scale (US Patent 10,726,014).
  • Replicated data storage system and methods (WO2013139379).
  • A method for storing and accessing data in a database system (WO2012032184, US20130226959).

Professional Activities
Short CV
Experience
  • 2021-Present
    Founding Chief Architect, Keebo, Greater Seattle Area, USA.

  • 2015-2021
    Principal Scientist Manager, Microsoft, Redmond, USA.

  • 2007-2008
    Senior Software Engineer, Ibibo Web, Gurgaon, India.

  • 2006-2007
    Associate Consultant, British Telecom, Bangalore, India.

  • 2005-2006
    Project Research Associate, National Program on Technology Enhanced Education, IIT Kanpur, India.

  • 2005
    Intern, IBM Software Lab, Pune, India.

Education
  • 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