- Data scientist and machine learning developer with over 10 years of experience in data science.
- Expert in Python, C++, with a solid foundation in physics, mathematics, and statistics.
- Expert in developing XAI modules to enhance decision-making transparency of black-box models for images and timeseries.
- Developer of the Open-Source Python Package (TelescopeML).
- Lead developer of XAI module for TelescopeML (PyPI).
- Developer of end-to-end AI/ML/DL projects, collaborating with cross-functional teams.
- Developer of a novel suppression model and particle-in-cell simulation module for emission flux.
| Projects | Techniques | Data Types | Poster |
|---|---|---|---|
|
TelescopeML Open-Source Python Package Deep Convolutional Neural Networks and Machine Learning Models for Analyzing Stellar and Exoplanetary Telescope Spectra |
Deep CNN, Machine Learning, XAI, Bayesian optimization, Feature Engineering | Timeseries, Tabular |  |
|
Malaria Cell Classifier Deep Convolutional Neural Networks and Machine Learning Models for Anomaly Detection in Microscopic Malaria cells. |
Deep CNN, Data Augmentation, Feature Engineering, Image Processing, Optimization | Image |  |
|
BloodPy-Automated Blood Cell Classifier Multi-Classification of Peripheral Blood Cells using Deep Convolutional Neural Networks and Machine Learning Models. |
Deep CNN, Data Augmentation, Transfer Learning, U-Net, Image Processing, Statistical Analysis, OpenCV, Fine-tuning | Image, Metadata |  |
|
Dataset: Segmented Peripheral Blood Cells Using OpenCV A Dataset of Segmented White Blood Cell Images Using Advanced Image Processing Techniques. |
GrabCut, Morphological Operations, OpenCV | Image, Binary Masks, Dataset |  |
|
LIME for Macroscopic Medical Images A Surrogate Model (Local Interpretable Model-agnostic Explanations) for Enhancing Transparency of Medical Diagnostics. |
Deep CNN, LIME, XAI, Computer Vision, Optimization | Image |  |
|
CAM for Macroscopic Medical Images Class Activation Mapping (CAM) Technique for Anomaly Localization Interpretability. |
Deep CNN, CAM, XAI, Computer Vision, Data Analysis, Optimization | Image |  |
|
Automated Nucleus Detector A Semantic Segmentation Solution for Automating Nucleus Detection of Microscopic Biomedical Images. |
U-Net, Keras-tunner, Semantic Segmentation | Image |  |
|
FastAPI Questionnaire API A FastAPI application to manage and retrieve questionnaire data with user authentication and custom error handling. |
FastAPI, Authentication, Data Management, Error Handling, Shell | API, CSV |  |
|
Neural Compression Advanced Autoencoder Architecture for Efficient Data Compression Losslessly. |
Autoencoder, GenAI, SSIM, PSNR | Image |  |
|
LIME for ECG Classification A Surrogate Model (Local Interpretable Model-agnostic Explanations) for Enhancing Transparency of TimeSeries. |
CNN, LIME, Time Series Analysis | Timeseries |  |
|
Beta-Variational Autoencoders Generative Learning (GenAI) with Beta-Variational Autoencoders. |
Beta-VAEs, Latent Space Analysis | Image |  |
|
Movie Recommendation Systems A comprehensive collection of movie recommendation systems, implementing collaborative filtering, content-based filtering, and Bayesian average techniques. |
Collaborative Filtering, Content-Based Filtering, Bayesian Average | Metadata, User Ratings, CSV |  |
|
Falcon 9 rocket Predictor A Data-Driven Project to Predict the Success of Falcon 9 Rocket Landings. |
Data Wrangling, Feature Engineering, Web-Scraping, JSON Data Processing, SQL, Hadoop, Folium, Decision Tree Classification | Unstructured Data, Tabular, Database |  |
|
Variational AutoEncoders A collection of Variational AutoEncoder (VAE) architectures developed by Keras deep learning framework. |
Variational AutoEncoders, Exploratory Data Analysis (EDA) | Image |  |
|
Netflix Content Analysis An Exploratory Analysis of Netflix's Vast Catalog to Uncover Trends and Insights into Content Distribution, Popularity, Quality, and Key Contributors. |
Exploratory Data Analysis (EDA), Data Visualization, Statistical Analysis | Metadata |  |
|
Air Passenger Timeseries Analysis An Exploratory Analysis of the Air Passengers Timeseries dataset, Uncovering Trends and Patterns in Air Travel Over the Years. |
Timeseries Analysis, Log Transformation, Moving Averages, Seasonal Decomposition, Seasonal Adjustment | Timeseries |  |