Ram Sriharsha
Committer And PMC Member, Apache Spark at The Apache Software Foundation
Burlington, Vermont, United States
Summary
🤩
Rockstar🎓
Top SchoolRam Sriharsha is a seasoned technology leader and long-time Apache Spark committer with 13+ years building scalable data and ML platforms. He has led engineering and research teams at Pinecone, Splunk, Databricks and Yahoo, most recently serving in executive R&D and CTO roles focused on production-grade vector search and analytics. His work spans product, engineering and open-source contributions—most notably performance and GeoJSON/WKT parser improvements for the magellan geospatial project on Spark. Comfortable at the intersection of systems, machine learning and big data, he repeatedly moves research into robust, distributed production systems. Based in Burlington, VT, he combines a strong academic foundation (PhD physics, IIT Madras BTech electronics) with a track record of shipping high-performance data infrastructure. An uncommon strength is his hands-on optimization of core parsing and data-format logic that materially speeds real-world geospatial workflows.
14 years of coding experience
18 years of employment as a software developer
Indian Institute of Technology MadrasPhD, Physics, PhD, Physics at University of Maryland
Stackoverflow
31reputation
361reached
2answers
1question
Github Skills (13)
scala10
spatial10
geo10
geospatial10
geojson10
spatial-data10
data-analysis9
java6
bytecode6
jvm6
profiling6
javac6
jaxb6
Programming languages (5)
Github contributions (5)
harsha2010/magellan
Jun 2015 - Sep 2017
Geo Spatial Data Analytics on Spark
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 91 commits, 97 PRs in 2 years 3 months
Contributions summary:Ram focused on improving the performance and functionality of the WKT parser, likely for use in geospatial data analysis. They implemented a faster parser for WKT strings, improving its speed. Furthermore, the user's commits include modifications to support GeoJSON data, which is a standard for representing geographic data. These changes demonstrate contributions related to parsing, data formats, and potentially the core logic for geospatial data processing.
data-analyticsgeospatialsparkgeospatial-analyticssparksql
harsha2010/spark
Apr 2015 - Nov 2015
Contributions:4 PRs, 98 pushes, 70 branches in 6 months
apachebig-datasparkscalaapache-spark
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