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Hi, I’m Shekhar 👋

I work on data-heavy projects in Python, focusing on preprocessing, structuring datasets, and organizing experiments into clean, reproducible code.

Below are some examples of my work:


Time-Series & Sensor Data

  • EDA & ECG ML pipeline [Tilburg Uni] [Ongoing]
    Developing structured preprocessing and machine learning/analysis pipelines for physiological time-series data (skin conductance and ecg), including cleaning, validation, and feature preparation. Currently looking into feature importance using recursive feature elimination. https://gitlab.uvt.nl/tsb-rst/eda_ecg_preprocessing

  • EEG / Brain-Computer Interface (Motor Imagery) [Independent] [Ongoing]: Reproducing the motor imagery BCI pipeline developed by Tibrewal et al. 2022 from scratch with modifications. Preprocessing, epoching, artifact rejection (ICA), and using models like CSP and LDA for classification. Repository link here.

  • ECG Arrhythmia Classification [Independent] [Finished]
    Built an end-to-end ML pipeline for classifying clinical ECG data, including preprocessing, feature extraction, model training, and evaluation. Read the indepth article about the project and its limitations here.

  • EEG / Brain-Computer Interface (code modulated VEP) [AI Dept, Radboud Uni][DataDrivenNeurotechLab] [Finished]
    Developed and evaluated signal-processing + ML methods (CCA, LDA) for classification in a BCI experiment.


Data Processing & Utility Projects


Currently Learning

  • Advanced SQL (DataLemur) – practicing industry-style query problems

📫 LinkedIn: https://www.linkedin.com/in/shekharnarayanan

Languages and Tools

Languages:

Python
Python3
Matlab
Matlab
R
R
R
SQL

Main libraries for Python3:

Pytorch
Pytorch
Numpy
Numpy
Pandas
Pandas
Sklearn
Sklearn
Matplotlib
Matplotlib
Keras
Keras

My tools for Data Manipulation:

Anaconda
Conda
Jupyter
Jupyter
AWS
AWS

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