1. Prateep Kumar Sengupta
M.Tech in Communication Engg.
B Tech in Electronics & Instrumentation Engg Mobile: +91-9836364622
77/3, Purba Sinthee Road, Dum Dum, Kolkata-30 Email: kumarsen.88@gmail.com
Seeking a position as an Engineer with an organization where I can contribute my skills for organization’s success and
synchronize with new technology. I would like to assist to the organization’s R&D related to data science and machine
learning.
Preferred languages: UNIX Shell Scripts, Python
Others: Perl, Excel VBA, Java
Web Scraping Tools: import.io, BeautifulSoup (Python), Selenium (Python), iMacros
Data Science & Machine Learning Tools: SPSS, Pandas (Python), Excel Analytics Toolpak, ALIZE Toolkit
Email Marketing Tools: Mailchimp, Agile CRM, Zoho, GetResponse
Research Databases: Zoominfo, CB Insights, Pitchbook, Hoovers, Data.com
Operating Systems: Windows 7, Ubuntu, Fedora
Degree University Year CGPA
M.Tech [Communication
Engineering]
WBUT 2013 - 2015 8.71/10
B.E [EIE] WBUT 2006 - 2010 7.25/10
*Working as a Technology Associate at IBC Consultants, Kolkata. (Sept 2015 to Present)
*Worked as a Trainee (AS3.0 and Android Development) at Virtual Infocom, Kolkata. (July 2012 to Dec 2012)
*Worked as a Junior Project Assistant (JPA) in IIT Kharagpur. (Nov 2010 to August 2011)
Self-learner of coding languages / softwares / applications
Research background in Machine Learning and Optimization
People management skills
I hereby declare that the information furnished above is true to the best of my knowledge.
Date: Signature of the Candidate:
Soft Skills
Academic Background
Work Experience
Skill set for Industry
Declaration

2. Appendix
M.Tech Thesis
“Study, Design and Optimization of Rectangular Patch Antennas usable in L-band and S-band”
The project has 3 distinct parts, which are-
Study of characteristics of Probe-Fed patch antennas usable in L-Band: We intend to study the VSWR and
return loss characteristics of probe fed patch antennas (rectangular as well as circular) usable in L-band.
Dimension Estimation of a Rectangular Patch Antenna using ANN: We intend to estimate the dimensions
of edge-fed patch antennas along with the substrate dimensions, using Artificial Neural Networks as the training
tool and Levenberg Marquardt Least Squares as training algorithm.
Optimization of a Rectangular Patch Antenna using Gradient free Algorithms: We intend to carry out a
length as well as width parameters optimization of an inset-fed as well as probe-fed patch antenna using Pattern
Search Optimization (Gradient-Free Direct Search for global optima) for minimized VSWR and Return Loss.
We also intend to study the effect of adding the inset dimensions as optimizing parameters along with patch and
substrate dimensions in a modified version of the scheme.
Softwares used: Ansoft HFSS, Zeland IE3D, Matlab (Neural Network Toolbox)
B.Tech Project
“Software and Hardware Realization of a FM Transmitting System”
This project mainly deals with a radio frequency FM transmission and reception system. The software realization as well
as hardware implementation of the system was done in the process.
Softwares used: Matlab (Simulink, Communication Toolbox), EWB Multisim 10, Circuit Maker
 Prateep Kumar Sengupta, Anirban Neogi, “Pattern Search based Dimension Optimization of a Rectangular
Inset-Fed Patch antenna for Minimized VSWR and Return Loss”, IJARCCE, Volume 4, Issue 4, April 2015.
 Prateep Kumar Sengupta, Anirban Neogi, “Effect of Inset Dimensions on a Modified Pattern Search based
Optimization Scheme for a Rectangular Inset-Fed Microstrip Antenna with Minimized Return Loss” (In
review).
*Worked as a Junior Project Assistant (JPA) in IIT Kharagpur, from Nov 2010 to August 2011, in the project
entitled “Automatic Speaker Recognition on VoIP” sponsored by Vodafone Essar Ltd.
Here, we have developed a real-time ASR system, tested in Ubuntu 10.0, working over Skype. We have used GMM-
UBM as the training algorithm for the ASR, with the POLYCOST database for the background modeling. The ASR
system basically does the following-
Records a conversation from a Skype conversation.
Converts the .mp3 recorded file into a 2-channel .wav file.
Converts the 2-channel speech into a 1-channel .wav file, containing only the voice sample of the claimed speaker
id.
Trims a 30 seconds speech sample from the 1-channel speech.
Tests it against the voice sample of the claimed speaker id.
Generate the threshold, compare it with the test threshold and upload the score on the Mysql database. (contd.)
We have used following languages/toolkits/softwares for the development of the system mentioned-
 ALIZ-E toolkit for speaker recognition module using GMM-UBM
 Skype Call Recorder (open source) for recording the conversation.
 Bash shells for audio processing as well as executables configuration.
 Perl to connect to Mysql server for database manipulation.
Project / Thesis
Publications
Detailed Work Experience

3. *Worked as a Trainee (AS3.0 and Android Development) from July 2012 to September 2012 at Virtual Infocom,
Kolkata.
We have developed an online test module for Computer Training India. The tests were for various subjects such as the
languages C, C# and Java, and were developed using Eclipse IDE, Android SDK and some knowledge on JSON
Parsing for Android.
*Worked as a Tech Freelance (From September 2015 to December 2015) at IBC Consultants, Kolkata.
Worked in Web Content mining for lead generation and market research.
* Working as a Technology Associate (From January 2015 to Current) at IBC Consultants, Kolkata.
Following are my current responsibilities-
Web data mining and Web Content Mining
Macro development using Excel VBA
Email Marketing