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"Knowledge, smart work and integrity have no substitute."

Career Plan

I look forward for opportunities to serve in a professionally driven business or research environment where I can explore true potential of my capabilities and contribute lucid and smart solutions to challenging real world problems, thereby, expand my professional expertise. 

Work History

15 May 201721 July 2017

Summer Research Intern

Data Science Lab, School of Computer and Communication Sciences, École polytechnique fédérale de Lausanne (EPFL), Switzerland

I worked on a project titled - "Supervised Q-walk for Learning Vector Representation of Nodes in Networks" in the realm of network analysis which involved developing a method for learning vector representation of nodes in a network. The method was inspired by a recently proposed node2vec framework. The latter framework is unsupervised, whereas my approach was a supervised adaptation leveraging label information for improving upon the quality of the learned representation of nodes. The project was developed using Python 3.5,  NetworkX, Numpy, Matplotlib, Scikit-learn, Gensim on Intel Xeon powered Ubuntu 16.04. 

This project was done individually as part of  [email protected]EPFL 2017 programme.

"...Throughout his internship, Naimish put an extraordinary amount of passion and hard work
into his project. He ran extensive experiments and regularly provided detailed updates to
me. Finally, he compiled his findings in a thorough report. In the process, Naimish has
broadened his machine learning expertise significantly through self-directed study.

I am confident Naimish will fare very well in the remainder of his Master’s degree and wish
him the very best for his future career. "

- Prof Robert West, Assistant Professor, Data Science Lab, School of Computer and Communication Sciences, EPFL

Letter of Appraisal can be seen at

22 May 201620 July 2016

Studentische Hilfskräfte

Department of Analytical Information Systems and Business Intelligence, Universität Paderborn, Germany

I worked on a Kaggle project titled - "Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet".  With my deep learning model, I could secure 18th rank on Kaggle leaderboard in Facial Key Points Detection Challenge.  The project deployed scientific python with deep learning libraries like keras with theano backend.

The project report can be seen at

"...To best of my knowledge and judgement, Mr. Agarwal's work not only constitutes not only a mere implementation but original research advancing the state of the art.

I'd wholeheartedly like to thank Mr. Agarwal for his dedication, skill and hard work. Given the results of his work, I have offered Mr. Agarwal a full semester internship in my lab."

- Jun. Prof Dr Artus Krohn-Grimberghe, Assistant Professor, AIS/BI, University of  Paderborn

Certificate of Completion can be seen at


August 2017Present

Robot Manipulator Trajectory Planning using Machine Learning Techniques

I am planning to give a novel approach to perform trajectory planning for robot manipulators using machine learning such that the joints configuration of the robot arm which corresponds to a given end effector location can be estimated without first performing inverse kinematics. 

March 2017April 2017

Graph Analysis of Countries and their Official Languages

The project was done as part of the course on Graph Theory in 7th Semester of IIIT-Allahabad. The project used Python 3.5, NetworkX, Gephi, Neo4j and Bash Script on Ubuntu 16.04. 

The project report can be seen at

December 2016December 2016

Signatures Features Visualisation using Deep Convolutional Autoencoder

The project was done as a skill assessment test for selection at EPFL Switzerland for Summer Internship in 2017. Based on my work, I have been selected at EPFL for the duration of 15th May 2017 to 22nd July 2017.

The code repository is located at

February 2016May 2016

Face Recognition using Eigenfaces, Fisherfaces and Support Vector Machines

This project was developed, with 5 team members, as part of Image and Vision Processing course in 6th semester of IIIT-Allahabad. The project deployed R programming language and scientific python with the usage of scikit-learn library for machine learning.

February 2016May 2016

Speaker Recognition using Convolutional Deep Belief Networks

The project was developed, with 5 team members, as a semester project in 6th semester of IIIT-Allahabad. The project deployed the following technologies:

  • Scientific Python stack like Python 2.7, Theano, Numpy, Matplotlib, etc
  • CUDA with CuDNNv4
August 2015December 2015

Static Hand Gesture Recognition using Reinforcement Learning

The project was developed, with 5 team members, as a semester project in 5th semester of IIIT-Allahabad. The project was deployed in pure python.

March 2015April 2015

Tender Management System

The project was developed, with 4 team members, as part of Database Systems Course in 4th Semester of IIIT-Allahabad. The project featured a TMS system similar to present-day Public Works Department TMS. The project deployed the following technologies:

  • Web Development Languages - HTML, CSS, Javascript, JQuery, PHP
  • MySQL Database
November 2014December 2014

Operating System Scheduling Algorithms Simulator

The project was developed, with 5 team members, as part of Operating Systems Course in 3rd Semester of IIIT-Allahabad. The project simulated various OS Scheduling Algorithms like Round Robin, SJF, etc. The project deployed following technologies:

  • Java SE - mainly Java Swing
  • Text to Speech Synthesis Library - provided better Human-Computer Interaction
May 2014June 2014

Airlines Reservation System

The project was developed at HP Educational Services, Kanpur, India as part of the course Java 2 Enterprise Edition Struts with Hibernate Framework. It featured a simpler version of modern-day Airline Reservation Systems. The project deployed the following technologies: 

  • Java 2 Enterprise Edition - Java Server Pages and Servlets
  • MySQL Database
  • Glassfish Server
  • Adobe Dreamweaver 30 days Trial Software


Machine Learning and Data Science

I have been working in the field of Machine Learning and Data Science since June 2015. Since then I have engaged myself in various projects involving it. I also work with Deep Learning  techniques like Feed Forward Neural Networks, Convolutional Neural Networks, Auto-encoders, etc. 


I have been using Python since October 2015. Since then I have taken online training on various python related topics and also have put it into use in many course assignments and projects. I mainly work with Scientific Python stack comprising Python 3.6, Numpy, Matplotlib, Scipy, Pandas, Scikit-learn, Keras, Pandas, NetworkX, etc.

R Programming

I have used R extensively from June 2015 to May 2016. I have also taken various online courses on Data Camp.


I have used Java extensively from 2009 to 2014 in various course assignments and projects.


I have worked with C# in 2015 since it has a beautiful syntax and at the same time the Visual Studio IDE made it a painless experience to work with C#.

Transact SQL

I have worked extensively with Transact SQL in 2014 only.


I have been using Docker since July 2017.


I have worked with Gephi in March - April 2017.


I have worked with Neo4j in March - April 2017.

Web Design

Basic web development skills - HTML and CSS



July 2016December 2016

Member of Dean's Merit List

IIIT-Allahabad has listed me in Dean's Merit List for extraordinary performance in 7th Semester.

January 2016June 2016

Institute Performance Award

Received a cash prize of INR 36,000 for excellent performance in 6th semester of IIIT-Allahabad. 

January 2014June 2014

Merit Incentive Award

Received a cash prize of INR 36,000 for excellent performance in 2nd semester of IIIT-Allahabad. 

April 2011April 2013

School Scholarships

Based on excellent performance in classes 11th and 12th, I got 100% free education in school.

Online Courses Certifications

Jan 2016Present

Database Fundamentals

Microsoft Virtual Academy
Jan 2016Present

Visual Studio Code


Dec 2015Present

Intro to Statistics with R: Introduction


Dec 2015Present

Importing Data into R

Dec 2015Present

C# Fundamentals with Visual Studio 2015


Aug 2015Present


Stanford Online
Aug 2015Present

Intermediate R


Aug 2015Present

Big Data - Fundamentals

Big Data University 

Jul 2015Present

Introduction to R


Jul 2015Present

How to work with Quandl in R


Jul 2015Present

Reporting with R Markdown


Jul 2015Present

Data Visualization in R with ggvis


Jul 2015Present

Kaggle R Tutorial on Machine Learning


Jul 2015Present

Data Manipulation in R with dplyr


March 2015Present

Programming in C# - Jump Start

Microsoft Virtual Academy
Jan 2015Present

Quick Start Challenge - Universal App

Microsoft Virtual Academy

Online Courses Certificates Portfolio