Develop data intensive backend services using Java and Scala for clients.   Develop search APIs using Elasticsearch and Apache Solr. Further, I do CI/CD using Jenkins, Docker, Vagrant Maven, SBT, CMake and Linux . Also, I do mentoring at https://www.codementor.io/@hariharansrc.

Software Engineer

Project Description:
Crawl, perform static code analysis and create automated software benchmarks of open source projects.

My Contribution:
1. Developed Maven actor to fetch open source java projects from maven central.  
2. Developed Elasticsearch actor to feed the software metrics  that are analyzed by other actors. 
3. Created continuous integration using Jenkins.
4. Developed REST APIs. 
5. Redesigned command line client  for  REST APIs that replaces  reflection based http client library. 

Research Assistant

Project Description:
Development of a product named BIMAssure to perform rule checking on Building Information Modeling (BIM) models.

My Contribution:
1. Developed search services using Elasticsearch. 
2. Developed rule API and rule plugins using Java. 
3. Created custom java classloader to run rules in a sandboxed environment. 
4. Developed testing environment for performing integration testing of rules using Junit and embedded Elasticsearch. 
5. Extended Maven plugins for Continuous Integration.  

Project Description:  
Collaboration and knowledge discovery platform for use within the organization.

My Contribution: 
1. Developed search services using Apache Solr. 
2. Developed REST APIs using Spring MVC. 
3. Created Continuous Integration pipeline using Jenkins. 
4. Optimized performance of services using Redis. 

I use Elasticsearch mainly to develop search services for applications. In general, Elasticsearch provides excellent full text search, complex boolean queries  or aggregation queries performed across multiple nodes in distributed manner.

Also I have used Logstash, Beats and Kibana with Elasticsearch as part of ELK stack to index logs and other metrics and analyze it in Elasticsearch.

Software Engineer with expertise in Java, Scala, Go and Elasticsearch

Hariharan Ramanathan

Social collaboration tool to increase interaction within a team. Helps to identify talents within a team.

Prime

Digital Twin of commercial building to run rules on models before executing it on actual buildings.

BIM Assure

CustoNN (Customized Neural Networks) is about performing object recognition on FPGA devices. In general, Convolution Neural Networks(CNN) are used to for object recognition of entities in image datasets. Traditionally, training and inference of the machine learning models are performed on GPU devices since the GPUs architecture are  optimized for parallel numerical operations esp. matrix computations.  Though FPGA devices do not have fixed computer architecture like CPU or GPU devices they can be tuned to get high performance inference for the machine learning model. To validate the idea the project implemented inference model in FPGAs and compared the various design trade-offs of using customized hardware architecture of FPGA devices over GPU devices.

CustoNN

Perform static code analysis on open source projects and extract software metrics and feed it into Elasticsearch.

Personal details

Hariharan R.

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