Shashankk Shekar Chaturvedi

Shashankk Shekar Chaturvedi

I am currently pursuing a graduate degree in Applied AI at Stevens Tech, USA, where I have gained a strong foundation in advanced AI techniques and their practical applications. My previous experience at UBS Group and Accenture, along with my prior Master's degree, has equipped me with skills in developing VR/AR applications, data analysis, software engineering, software quality assurance, and web project management. My current interests include:

> Astronomical data analysis: Applying machine learning to uncover insights from celestial data.
> Machine learning and deep learning: Developing innovative algorithms to solve complex problems.
> Full stack software development: Creating dynamic, client-focused solutions using technologies like React, Node.js, Docker, and serverless architectures such as AWS Lambda and JAMstack.
> VR/AR App Development: Designing immersive and interactive VR/AR applications using cutting-edge technologies like Unity, Unreal Engine, and Python.

My current projects include recommendation systems, LLM chatbots using LLAMA 2, fine-tuning with custom data, and vector embedding. Additionally, I created the brand Neuradent, a smart toothbrush focused on leveraging AI and data-driven insights for personalized oral care, real-time feedback, and effective marketing channels. With a background that spans data and software engineering as well as innovative marketing skills, I thrive on exploring areas such as distributed systems, formal methods, and networks, bringing a creative and analytical approach to each challenge.

Recent Projects

Machine Learning / Modeling and Optimization

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Stellar Classification - A Particle Swarm Optimization Approach

This project employs Particle Swarm Optimization (PSO) to automate and optimize the spectral classification of celestial bodies, enhancing our understanding of the universe's composition and evolution.

Libraries used:- Matplotlib, Pandas, Seaborn, Pyswarms

Github link:- https://github.com/Shashankk99/Stellar-Classification/

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Credit Card Fraud Detection Using Machine Learning Algorithms

Our project explores optimal Machine Learning algorithms like Logistic Regression, Decision Trees, and XGBoost to tackle credit card fraud in online transactions. Through techniques like Random Oversampling and SMOTE, we aim to enhance ML-based solutions for more secure online transactions.

Libraries used: Scikit-Learn, XGBoost.

Project Paper:- Fraud-Detection_ML.pdf

Marketing Management

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Neuradent - Smart Toothbrush

Developed a comprehensive marketing strategy for Neuradent, a smart toothbrush brand. The project focused on leveraging AI and data-driven insights for personalized oral care, real-time feedback, and effective marketing channels.

Key components: Data-driven oral care, personalized coaching, integration with the NeuraDent app, AI in marketing and product development.

Project link: View Project

Software Development @ A Glance

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Stock Market Prediction Tool

This project involves developing a stock market prediction tool utilizing machine learning algorithms such as ARIMA, LSTM, and Linear Regression to forecast stock prices and analyze sentiment from tweets.

Libraries used:- TensorFlow, Keras, Scikit-Learn

Github link:- GitHub

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NutriScan - Personal Health and Dietary Assistant

NutriScan is a mobile app designed to help users make informed decisions about their health and dietary needs while shopping. Users can register, input health details, and scan product labels to check suitability.

Libraries used: Expo, React Navigation, Firebase (Auth, Firestore)

Github link: GitHub

Network Analysis & Monitoring

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Automated Network Traffic Analysis and Monitoring System

Developed a system for automated network traffic analysis to detect anomalies and ensure optimal performance. The project involved capturing network traffic data, performing real-time analysis, and visualizing the results on a monitoring dashboard. This system enhances network security and performance by identifying potential threats and inefficiencies.

Skills Used: Programming Languages: Python, C++, Networking: TCP/IP, OSI Model, Tools: Wireshark, Nagios, Grafana, DevOps: Jenkins, Git, Data Visualization: Real-time monitoring dashboards

Project link: View Project

Computer Vision

AI Object Drag

This is an AI Virtual Drag project where we can drag objects virtually through hand movement. This project was created using Python Open-CV.

Libraries used:- Open CV, CV Zone, Media Pipe, Hand Detector

Github link:- https://github.com/Shashankk99/AI-Virtual-Drag

AI Virtual Keyboard

The AI Virtual is one of the best application of Computer Vision. Using the Open CV library, a virtual keyboard lets us type words virtually.

Libraries used:- Open CV, CV Zone, Hand Detector

Github link:- https://github.com/Shashankk99/AI-Virtual-Keyboard

UI/UX Design

Travellzy App

This is a protytpe design of a Travel app designed to give the glimpse of the actual app. This App was designed using Adobe XD.

Harmony - The Music App

This is the prototype design of Harmony, which is a music app. This design gives a good glance over the App UI and was made using Adobe XD.

 

Poster Designing

Nature Workshop

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Hour of Code

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