I'm Shekhar Jadhav.

M.Sc in Physics - Photonics Lund University Electrical Engineer IIT Delhi


Let me introduce myself.

Profile Picture

Enthusiastic person who loves "Science and Nature"


Interested in Algorithmic Trading, Photonics and Machine Learning projects.

  • Fullname: Shekhar Jadhav
  • Birth Date: October 9, 1995
  • Website: www.shekharjadhav.com
  • Email: shekharjadhav1995@gmail.com sh2063ja-s@student.lu.se


These are some of the skills developed at Academics and Internship.

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More of my credentials.

A journey through timeline of my work and education.

Work Experience

Web Developer

May 2016 - July 2016

Summer Intern at ABH utbildning och rådgivning

Worked with a web-project for a Swedish company, where I got to develop a application on web platform.

The Application included knowledge about laravel, databases, php, Javascript, jquery and HTML5.

Quantitative Trading (Research & Analysis)

Aug 2018 -

Lund University Finance Society (LINC)

Developing an HFT forex trading system using both Machine Learning and fuzzy logic. Report link


Master Degree

August 2017 - Present

Lund University

Master of Science in Physics, Specialization in Photonics

Bachelor Degree

July 2013 - May 2017

Indian Institute of Technology Delhi

Bachelor of Technology in Electrical Engineering


Indian Climate Prediction from CMIP5 models by Machine Learning - ("Bachelor Thesis")

July 2016 - Nov 2016

IIT Delhi

Aim to find an optimal model for Indian Climate from 24 CMIP5 Models and compare it to the Indian Meteorological Department (IMD) data.

Implemented Multiple Linear Regression and Multiple Polynomial Regression to fit the model with appropriate degree.

Implemented Feed Forward Neural Network (FFNN) with Backpropagation and using Levenberg Marquardt Algorithm to optimise the model.

Obtained promising results to predict the climate and the error for the temperature and rainfall was very low, with a good correlation.

Face Recognition: Machine Learning

April 2016 - May 2016

IIT Delhi

Implemented Eigenfaces' PCA and Fisher's Linear Discriminant Analysis for face recognition and analysed the better performance of Fisher's method with variations in lighting and facial expressions in the image.

Handwritten Digit Recognition: Machine Learning

Mar 2016 - Apr 2016

IIT Delhi

Implemented Logistic Regression and Neural Network multi-class classifiers to recognize handwritten digits.

Examined accuracies of the two models as a function of parameters such as regularisation, learning rate, etc.

Background Subtraction: Machine Learning

Jan 2016 - Feb 2016

IIT Delhi

Implemented Stauffer Grimson Background Subtraction algorithm for segregating foreground moving objects and relatively invarying background from a video by sequentially labelling each pixel in video frames.

Algorithm exploited use of K-means for training and online Gaussian Mixture Models for prediction.


I'd Love To Hear From You.

"Dont hesitate to contact".

Where to find me

lgh 82, Spånehusvägen 62I
214 39 SWEDEN

Email Me At


Call Me At

(+46) 0735167192