Technology Domains: Software Development, Data Science, Machine Learning, Deep Learning, Blockchain, Web Development

Disciplines:  Healthcare, Society, Supply Chain and Logistics, Crime, Nature, Differently Abled, Cosmetics

Tech Stack: HTML, JavaScript, CSS, Boostrap, Materialize CSS, Python, Flask, Numpy, Pandas, Seaborn, Matplotlib, MySQL, MongoDB,  DynamoDB, SQLite, Angular JS, Solidity, Web3, Sklearn, Keras, Tensorflow, Sensors, Arduino, IBM Cloud, Google Cloud Vision, Spacy,

fastai, Plotly, Chart.js


Mentor: Mr Karan Kamdar, CEO 1MW, Stanford

Nov 19' - May 20'

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Detection and Calculation of Cement Bags in a Warehouse with Object Detection

Extracting frames from video as .jpeg images by adjusting the fps.

Adjusting the image resolution as a part of data cleaning and data preprocessing

Labeling all the images for cement bag detection using the LabelImg tool
Converting the input images in the dataset to appropriate PASCAL/VOC

Format for object detection.An XML parser script was written for verification
Generating .tiff records and splitting the data into training set and testing set

Using Faster_RCNN_Inception_V2 model for configuring the hyperparameters during model training
Achieved an accuracy of over 98%
Deployed the model on Flask and tested the model using Tensorflow
Hyperparameter tuning for optimized results

The model was tested over a private network and the User Interface was designed using Materialize CSS


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Mentors: Dr. Manoj Sharma, PhD IIT, Dr Madhushi Verma, PhD IIT

May 20' - Jul 20'

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Lung disease Classification, Segmentation and Quantification with Explainable AI

Synthetic Image Generation using DGCANs whilst improving its quality with Image Super-Resolution with RRDN

Multiclass Image Classifier for classifying Chest X-Ray Images into Normal, COVID-19, and PNEUMONIA with an accuracy of 98.2% with DenseNet121, achieving a 3% increase in accuracy after data augmentation.

Implemented Cyclic learning Rate for optimization and GradCAMs for visualization of the affected area

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Technojack Infosolutons

Mentor: Mr Yogesh Jadhav, Professor Amity University

Medication Adherence Monitoring with Tracking Automation and Emergency Assistance

 Implemented OCR System for detection of drugs and it’s dosing from doctor’s handwritten prescriptions

 Detection of text in images using OpenCV and EAST Text Detector.

Worked on Google Cloud Vision API for text recognition and detection

Web Scraping the drug names of over 60,000 medicines from and

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TakenMind's Global Internship Programme ( Recognized by United Nations )

Sept 19' - Oct 19'



Employee Attrition Problem 

Conducted various statistical tests like correlation, covariance,p-test,z-test, etc

Data Visualization through Bar Graphs, Heatmaps, Scatter Plots, Histograms, Pie Charts

Data profiling and Implemented data cleaning techniques for filling missing values and removing redundant data

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