Image of Girish Kathalagiri

Girish Kathalagiri

Data Analytics Engineer

Sr. Software Engineer, Machine Learning

San Francisco Bay Area

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Girish Kathalagiri's Email Addresses & Phone Numbers

Girish Kathalagiri's Work Experience


Data Analytics Engineer

February 2011 to June 2012

Mountain View


Senior Software Engineer, Machine Learning

Sunnyvale, California

Samsung SDS Research America

Data Scientist/ Sr. Staff Engineer

August 2014 to February 2018

San Jose, CA

Girish Kathalagiri's Education

Jawahar Novodaya Vidyalaya

Visvesvaraya Technological University

Bachelor's degree, Computer Science

2000 to 2004


Nano Degree, Self Driving Car

2016 to 2017

Girish Kathalagiri's Professional Skills Radar Chart

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Girish Kathalagiri's Estimated Salary Range

About Girish Kathalagiri's Current Company


Worked on Data Analytics Infrastructure development and Also developed Data API for the processed data.For processing of making the web data actionable to people who need it at Meebo, we use Hadoop, PIG, CouchDB, MySQL and Python glue extensively.

Frequently Asked Questions about Girish Kathalagiri

What company does Girish Kathalagiri work for?

Girish Kathalagiri works for Meebo

What is Girish Kathalagiri's role at Meebo?

Girish Kathalagiri is Data Analytics Engineer

What is Girish Kathalagiri's personal email address?

Girish Kathalagiri's personal email address is g****[email protected]

What is Girish Kathalagiri's business email address?

Girish Kathalagiri's business email addresses are not available

What is Girish Kathalagiri's Phone Number?

Girish Kathalagiri's phone (**) *** *** 154

What industry does Girish Kathalagiri work in?

Girish Kathalagiri works in the Internet industry.

Who are Girish Kathalagiri's colleagues?

Girish Kathalagiri's colleagues are Neil Pomerleau, Haoran Li, Allison Guillen-Capo, Steve Nostros, Bobby Oster, Peggy Brannigan, Chandra Yenduri, Andie Cockerill, Max Hsia, and Avishek Sharma

About Girish Kathalagiri

đź“– Summary

Data Analytics Engineer @ Meebo Worked on Data Analytics Infrastructure development and Also developed Data API for the processed data.For processing of making the web data actionable to people who need it at Meebo, we use Hadoop, PIG, CouchDB, MySQL and Python glue extensively. From February 2011 to June 2012 (1 year 5 months) Mountain ViewSenior Software Engineer, Machine Learning @ LinkedIn Working in Careers AI group, working in Job Recommendations, JYMBII ( Jobs you may be interested in module ) Sunnyvale, CaliforniaData Scientist/ Sr. Staff Engineer @ Samsung SDS Research America Working in the area of AI,reinforcement learning , Contextual bandit and Machine Learning. Building AI based solution using tensorflow, docker and Kubernetes.Implementation/experimentation using reinforcement Learning Algorithms :Policy gradient algorithms in tensorflow Worked on Spark based Scalable Decision making system. From August 2014 to February 2018 (3 years 7 months) San Jose, CAData Scientist @ AgilOne Technical Lead helping in the efforts for model building and execution platform for Machine learning and Data Flow. Work with R, PMML, Protobuf, Cascading, Regression, SVM, Random Forest.- Committer on Cascading Pattern Project. Developed GLM, Logistic Regression, RF regression, SVM scoring. Also, developed sample applications using these.- Co-authored a Paper presented at KDD PMML Workshop at Chicago, August 2013. From July 2012 to August 2014 (2 years 2 months) Mountain ViewStudent @ Stony Brook University As a Masters candidate in the department of Computer Science at SUNY Stony Brook, NewYork. I am being advised by Dr. Steven Skiena . My project topic is based on News/ Blog analysis. I worked on clustering the news entities to find patterns and similarities. Analyzing different features like, sentiment score, frequency, spikes in the news time series, polarity etc. From January 2009 to December 2010 (2 years) Stony BrookGraduate Assistant @ Stony Brook University Worked under Professor Luis Ortiz, on Boosting approach in Machine Learning.Multi-dimensional Synthetic data generator using decision stumps as true classifier.Adaptive Boosting for Classification: Boosting was used in conjunction with decisionstump as a weak learner on the UCI datasets. From May 2009 to August 2009 (4 months) Intern @ Yahoo! Worked on machine learning for Hadoop .To predict the anomalies in the Hadoop system.Worked under the guidance of Lihong Li on applying machine learning techniques todetect Hadoop system errors for Namenode and Jobtracker. Techniques that were used include One-class SVM, Hidden Markov Model improvement for One-class SVM. Investigated on newer techniques like Relative Novelty Detection. Presented a poster during Yahoo Labs Science week and was awarded the best poster. From May 2010 to August 2010 (4 months) SunnyvaleMember of Research staff @ ABB Corporate Research ABB Corporate Research; Prototyped Linux based Embedded Firewall/router as part of next generation robot system architecture. Designed and implemented boundary clock for IEEE1588. Evaluated the real-time properties and system latencies of Linux RT-PREEMPT Patch set, as a platform for paint robot controller. Also, was involved in creating the board support package for this robot controller (MPC 5200). From May 2007 to December 2008 (1 year 8 months) BangaloreSoftware Engineer @ Motorola Solutions Work involved design and implementation of two features RADIUS configuration moduleand Certificate management module for Wireless switch architecture. Designed andimplemented Guest login application for the Wireless switch.Work also involved in supporting Java Swing based Graphical user interface and CommandLine interface of Wire-less switch. Also, was involved in changing architecture of GUI toimprove the performance. From 2004 to 2007 (3 years) Intern @ Torry Harris Business Solutions Work involved implementation of communication module for Java based Backend framework for Emergency Department Clinical Support System (EDCSS) for Tan Tock From April 2004 to December 2004 (9 months) Bangalore

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Girish Kathalagiri's Personality Type

Introversion (I), Intuition (N), Thinking (T), Judging (J)

Average Tenure

1 year(s), 8 month(s)

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