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Arun Kejariwal

Arun Kejariwal

142 Followers
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Personal Information
Organization / Workplace
San Francisco Bay Area United States
Occupation
Statistical Learning Principal at Machine Zone, Inc.
About
I have diverse experience in statistical and machine learning, time series analysis, data-driven mobile marketing, software development, and hardware design. I have a strong publication record and am a strong advocate of open source. Have built a team of exceptional researchers from the ground-up. An effective communicator and deft at working with cross-functional teams in different geographies. Seasoned architect with exceptional deep dive analysis skills in both hardware & software and with extensive experience in R&D of novel techniques, based on statistical learning and time series analysis, to address end-user experience/revenue impacting problems. Highly passionate about building...
Contact Details
Tags
anomaly detection deep learning time series statistical learning algorithms live data data sketches streaming systems scalability stream processing sequence learning correlation low latency machine learning statistics real-time big data forecasting cloud computing attention-based models apache pulsar streaming applications lstm satori robust performance twitter capacity planning space-time tradeoff battery-constrained healthcare ai speed-accuracy tradeoff edge computing stateful computation serverless performance accuracy trade-off jiffy durability model serving real time analytics neural networks common representation learning multimodal smart cities computer vision decision making pulsar bookeeper heron storage messaging missing data analytics clustering statistical leaning breakouts anomalies papacity planning #velocityconf #capacityplanning #performance #fore statistical analysis fail whale qcon elasticity monitoring garbage collection
See more
Presentations (23)
See all
A Tool for Practical Garbage Collection Analysis In the Cloud
9 years ago • 3405 Views
Techniques for Minimizing Cloud Footprint
9 years ago • 1349 Views
Isolating Events from the Fail Whale
9 years ago • 1956 Views
A Systematic Approach to Capacity Planning in the Real World
9 years ago • 5516 Views
Gimme More! Supporting User Growth in a Performant and Efficient Fashion
9 years ago • 2299 Views
Days In Green (DIG): Forecasting the life of a healthy service
8 years ago • 789 Views
Statistical Learning Based Anomaly Detection @ Twitter
8 years ago • 5103 Views
Velocity 2015-final
7 years ago • 2097 Views
Finding bad apples early: Minimizing performance impact
7 years ago • 1069 Views
Real Time Analytics: Algorithms and Systems
6 years ago • 22863 Views
Data Data Everywhere: Not An Insight to Take Action Upon
6 years ago • 1540 Views
Anomaly detection in real-time data streams using Heron
5 years ago • 4654 Views
Modern real-time streaming architectures
5 years ago • 7169 Views
Live Anomaly Detection
5 years ago • 2967 Views
Correlation Analysis on Live Data Streams
4 years ago • 1999 Views
Deep Learning for Time Series Data
4 years ago • 1589 Views
Correlation Analysis on Live Data Streams
4 years ago • 320 Views
Designing Modern Streaming Data Applications
4 years ago • 2621 Views
Model Serving via Pulsar Functions
3 years ago • 1651 Views
Sequence-to-Sequence Modeling for Time Series
3 years ago • 1916 Views
Sequence-to-Sequence Modeling for Time Series
3 years ago • 3138 Views
Serverless Streaming Architectures and Algorithms for the Enterprise
3 years ago • 2820 Views
Anomaly Detection At The Edge
2 years ago • 558 Views
Likes (1)
Hadoop, Pig, and Twitter (NoSQL East 2009)
Kevin Weil • 13 years ago
  • Activity
  • About

Presentations (23)
See all
A Tool for Practical Garbage Collection Analysis In the Cloud
9 years ago • 3405 Views
Techniques for Minimizing Cloud Footprint
9 years ago • 1349 Views
Isolating Events from the Fail Whale
9 years ago • 1956 Views
A Systematic Approach to Capacity Planning in the Real World
9 years ago • 5516 Views
Gimme More! Supporting User Growth in a Performant and Efficient Fashion
9 years ago • 2299 Views
Days In Green (DIG): Forecasting the life of a healthy service
8 years ago • 789 Views
Statistical Learning Based Anomaly Detection @ Twitter
8 years ago • 5103 Views
Velocity 2015-final
7 years ago • 2097 Views
Finding bad apples early: Minimizing performance impact
7 years ago • 1069 Views
Real Time Analytics: Algorithms and Systems
6 years ago • 22863 Views
Data Data Everywhere: Not An Insight to Take Action Upon
6 years ago • 1540 Views
Anomaly detection in real-time data streams using Heron
5 years ago • 4654 Views
Modern real-time streaming architectures
5 years ago • 7169 Views
Live Anomaly Detection
5 years ago • 2967 Views
Correlation Analysis on Live Data Streams
4 years ago • 1999 Views
Deep Learning for Time Series Data
4 years ago • 1589 Views
Correlation Analysis on Live Data Streams
4 years ago • 320 Views
Designing Modern Streaming Data Applications
4 years ago • 2621 Views
Model Serving via Pulsar Functions
3 years ago • 1651 Views
Sequence-to-Sequence Modeling for Time Series
3 years ago • 1916 Views
Sequence-to-Sequence Modeling for Time Series
3 years ago • 3138 Views
Serverless Streaming Architectures and Algorithms for the Enterprise
3 years ago • 2820 Views
Anomaly Detection At The Edge
2 years ago • 558 Views
Likes (1)
Hadoop, Pig, and Twitter (NoSQL East 2009)
Kevin Weil • 13 years ago
Personal Information
Organization / Workplace
San Francisco Bay Area United States
Occupation
Statistical Learning Principal at Machine Zone, Inc.
About
I have diverse experience in statistical and machine learning, time series analysis, data-driven mobile marketing, software development, and hardware design. I have a strong publication record and am a strong advocate of open source. Have built a team of exceptional researchers from the ground-up. An effective communicator and deft at working with cross-functional teams in different geographies. Seasoned architect with exceptional deep dive analysis skills in both hardware & software and with extensive experience in R&D of novel techniques, based on statistical learning and time series analysis, to address end-user experience/revenue impacting problems. Highly passionate about building...
Contact Details
Tags
anomaly detection deep learning time series statistical learning algorithms live data data sketches streaming systems scalability stream processing sequence learning correlation low latency machine learning statistics real-time big data forecasting cloud computing attention-based models apache pulsar streaming applications lstm satori robust performance twitter capacity planning space-time tradeoff battery-constrained healthcare ai speed-accuracy tradeoff edge computing stateful computation serverless performance accuracy trade-off jiffy durability model serving real time analytics neural networks common representation learning multimodal smart cities computer vision decision making pulsar bookeeper heron storage messaging missing data analytics clustering statistical leaning breakouts anomalies papacity planning #velocityconf #capacityplanning #performance #fore statistical analysis fail whale qcon elasticity monitoring garbage collection
See more

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