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An astute, self-motivated and result oriented professional having extensive experience in research software/product development. He is  efficient in fast prototyping and production-level development using Javascript and Python.


- Scalable backend development  (Micro-service architecture) of web applications in Node.js/Express.js. 
- Design and development of REST APIs/web-services for web applications.
- Experienced in working with JSON, XML, AJAX, HTML, CSS, JQuery and Git.
- Solid experience working with various NoSQL(MongoDB, Neo4j, Redis) and SQL (PostgreSQL) databases.
- Experience with on-premises infrastructure and cloud server technologies (such as AWS, DigitalOcean, Google Cloud etc).
- Automating deployment workflows for CD/CI pipelines and NGINX (load balancing deployments).
- Experience with Node.js application development for IoT devices (such as raspberry pi etc)
- Experience with Wolfram webMathematica platform, converting mathematica programs into REST APIs. 
- Experience on writing Node.js client for TensorFlow server that uses gRPC protocol.
- Knowledge of building machine learning models using TensorFlow.
- Knowledge of scaling of scaling TensorFlow models into production using Serving API. 
- Knowledge of Apache Lucene and Hadoop.


Sep 2014Present

Full Stack Software Engineer

Solar Energy Research Institute of Singapore

I lead the software development of a variety of projects that range from simulation, machine learning, IoT and visualisation.

Jan 2014July 2014

Software Development Engineer

Pytheas Infosys Pte. Ltd.

Software development of flash sales travels portal for B2C customers of the company.

Aug 2012July 2013

Research Intern

Solar Energy Research Institute of Singapore

Prototyping a web based interface that described various standard input parameters for crystalline silicon and Amorphous silicon material model's

Dec 2011Jan 2012

Research Intern

University of Malaya - Faculty of Medicine (Tissue Engineering Group)

I worked on the analysis of data obtained from a material testing machine used to test bones used in orthopaedic practice.


XSolar-Hetero, an online web-based photovoltaic simulation platform

Research Engineer, Solar Energy Research Institute of Singapore

September 2014 - Present

Over the past few decades, various computer simulation tools have been developed, in order to predict the electrical / optical behaviour of the final solar cell device or of specifically designed test samples (Device simulations), to predict resulting electrical / optical properties due to a specific production process (Process simulations) and to predict the energy yield of the device (Yield Simulations).

"Most of the advanced device/process/yield simulation tools actually never get broadly used, as they are very specific and hard to train. These tools are written in a variety of programming languages, making it hard to collaborate. This actually hampers increasing conversion efficiency."

The Solar Energy Research Institute of Singapore (SERIS) is developing XSolar-Hetero, an online web-based photovoltaic simulation platform, that aims to make it easy for researchers to use established (and dynamically upload new) device/process/yield simulation programs for a multitude of different solar cell architectures.


mLogger , an IoT based software application to upload high-quality standard measurements with automated analysis from various photovoltaic characterisation tools

Research Engineer, Solar Energy Research Institute of Singapore

June 2016 - Present

The main motivation of building such a tool was to centralise the upload/post processing of photovoltaic characterization measurements in a standard database. Every photovoltaic characterization tool is expensive and comes with a variety of software to extract measurements in text/excel/XML etc. These tools generally lack the capability of post processing such raw measured data to provide some meaningful insights on the cells measured. Our IoT based application solves this problem by post processing the raw measurements using dynamically assigned REST APIs from XSolar-Hetero.

The application can be built/deploy on any Raspberry Pi/Intel Edison boards (>1GB RAM, ARM processor, Linux/Windows OS), supports a remote U2F based authentication with XSolar-Hetero, enables manual or automated logging of measurements from labs tools as well as field PV modules, provides post-processing of measurements using REST APIs using dynamic assignment of APIs via XSolar-Hetero. It also powers remote lock and control of Raspberry Pi via XSolar-Hetero and can be scaled using the build tool that converts any Pi into mLogger.

TruePower UI, an web application to visualisation photovoltaic module performance in real-time

Research Engineer, Solar Energy Research Institute of Singapore

May 2016 - Present

The project was to build a monitoring interface to visualise the photovoltaic modules from remote client sites. Every module has various connected sensors, that can be monitored remotely, real-time data can be stored in a centralised database and visualised on demand using this application.

Implementing various standard photovoltaic device/process/yield simulation programs as REST APIs

Research Engineer, Solar Energy Research Institute of Singapore

May 2017 - Present

Some of the standard computer simulation programs for solar cell/module research are more than a decade old and are written in a variety of programming languages. It is a very hard problem to rewrite all such programs into a preferred language and sync with developers.The simplest solution was to convert all these applications into REST API that produce standard JSON output formats.

The motivation of this project is to build a solid backend solution that not only makes it easy for "NON-PROGRAMMERS" such as physics/solar/chemical researchers to convert/manage there simulation programs as APIs but also semi-automated such code conversion process.

Using Machine Learning, Prediction of process parameters that maximise the implied open circuit voltage of a given industrial n -Type Silicon Wafer Solar Cell in BBr3 Tube Diffusion Process. 

Research Engineer, Solar Energy Research Institute of Singapore

Aug 2017 - Present

Fabrication process optimization is important in photovoltaic research as it helps to produce better solar cells and maybe reduce resources. We explore the possibility where we can use a machine learning model to optimize the BBr3 Tube Diffusion Process.

Scaling of various in-house research focused machine learning models into production using Tensorflow Serving API

Research Engineer, Solar Energy Research Institute of Singapore

July 2017 - Present

TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. TensorFlow Serving makes it easy to deploy new algorithms and experiments while keeping the same server architecture and APIs. The main aim to build CD/CI pipeline for various models that are trained/tested for specific research problems and make it available for production use.

Code samples

If you want see how i write code, i highly recommend checking the code samples below:

- mySocialNetworkAPI (Permanent Link): Node.js API backend for social network that has features -"Friend", "Unfriend", "Block", "Receive Updates"

- my npm modules (Permanent Link): mongo-morgan-ext, RunGruntTask etc


  • B. Tech (Hons) in Computer Science & Engineering from Lovely Professional University, India (2008 – 2013)


  • IEEE-LPU Student Branch (Founding Chairperson); September 2010 – September 2011