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Jaydeep Belapure, PhD

Physicist | Data Scientist

Based in Halle (Saale), Germany

Hi, I am a physicist by education and physicist/data scientist by profession, having 6+ years of experience as a Sr. Scientist at a leading technology company.

A short introdution to myself

What excites me

I love solving data driven problems using modern Machine learning algorithms, with a strong inclination towards problems in medical and healthcare domain.

At BrainLicht, I am posting some of the interesting problems that I have worked on. Along this path I have developed strong expertise in various machine learning methods as well as handling variety of data types, such as 1D signals, 2D/3D images, text-data, or multi-dimensional data sets.

In my spare time I love running and cycling in the woods along the country side roads.

Work Experience

My professional background

n Sr. Scientist

Advanced technology group, R&D, Thermofisher Scientific, Eindhoven, Netherlands | 2014-2020.

n-1 Postdoctoral researcher

Max Planck Institute for Plasma Physics, Munich, Germany | 2013

n-2 Doctoral student

Technical University of Munich, Munich, Germany,

International Max Planck Reseach School, Munich, Germany | 2009 - 2013.

n-3 Research Assistant

Inter University Center for Astronomy and Astrophysics (IUCAA), Pune &

National Center for Radio Astrophysics, Pune, India | 2008.


Something that is never over...


Selected problems I enjoyed working on...

Convolutional neural network

Image classification using deep learning.

CNN based model to classify images as cats or dogs. Without transfer learning techniques. Validation accuracy of ~95% is achieved.

View here » Github »
CNN visualization

Deep learning: Visualize filters and feature maps

Inside CNN: how the filters look like? what does the output at different layers look like? Visualize the feature maps and filters.

View here » Github »

CNN model to identify if a patient has Pneumonia

A CNN based model is developed to identify if a patient is suffering from Pneumonia or not. Model developed from scratch i.e. without transfer learning, show 91% test accuracy.

View here » Github »

Book recommender system using description of books.

Recommend books, using Co-similarity as well as user-book matrix factorization approach. Plus a quick search engine to find a book given some keywords.

View here » Github »

Clustering Covid-19 research articles

By using Natural Language Processing (NLP) techniques and matrix factorization (PCA/LDA), thousands of text articles are processed to identify different clusters.

View here » Github »


Call me, maybe.