Kusuma | Portfolio

About Me

I’m Kusuma Satya Sreeja Chalasani — a passionate Data Science graduate student with a strong background in cloud infrastructure, automation, and machine learning. I thrive at the intersection of structured data and creative solutions. With hands-on experience in platforms like Azure and GCP, I’ve built scalable data pipelines, automated systems with Python, and used predictive models to drive smarter decisions.

Beyond my technical work, I’m an artist at heart. Whether I’m visualizing data or sketching portraits, I find joy in creating meaningful expressions. I believe that great data science combines logic and creativity — and that’s exactly how I approach my work.

I'm currently exploring opportunities to blend my love for data, AI, and design into impactful real-world projects. Let’s build something amazing together!

Community

I'm also an active member of the ISA Cultural Team at the University of North Texas, where I contribute to organizing campus events and creative cultural activities that promote collaboration, diversity, and engagement.

Skills

Programming & Data Analysis

Python, SQL, Pandas, NumPy

Data Visualization

Matplotlib, Seaborn, Plotly, Tableau, Time Series Charts

Machine Learning

Regression, Classification, Clustering, Scikit-learn, CNN (Emotion Detection)

Cloud & Automation

Azure (VMs, Storage), GCP (BigQuery, Dataproc), Splunk, PowerShell

Big Data & Streaming

PySpark, Hive, Spark Structured Streaming, OpenRefine, ETL Pipelines

Web Development

Flask, HTML5, CSS3, JavaScript, Responsive Design, API Integration

AI Integration

OpenAI GPT API, Prompt Engineering (DishGenie Project)

Tools & Platforms

Jupyter Notebook, Google Colab, VS Code, GitHub, Render, Google Sheets, Excel

Experience

Professional Experience

Cloud Support Engineer – Data Operations

DHL Project, Cloud4C | Jun 2022 – Jul 2024

Implemented data pipelines and analysis procedures, improving resource usage by 10%.
Managed Azure VMs, cloud storage, and workflow monitoring.
Automated log analytics with Splunk and PowerShell.
Prepared datasets and deployed ML models for predictive analytics.
Generated insights from infrastructure using storage trends.

Student Assistant – Technical Support

UNT College of Merchandising, Hospitality & Tourism | Jul 2024 – Present

Provided tech support for faculty/students by resolving software, hardware, and network issues.
Managed 240+ student loaner laptops, including imaging, software installation, and security updates.
Assisted with IT desk operations—answering queries and guiding students through the borrowing process.
Maintained organized workspace and ensured timely updates for system integrity and performance.
Supported faculty IT needs and promoted secure computing practices.

Academic & Project Experience

Data Engineer – Crime Rate Prediction

Academic Project | Spring 2025

Built pipelines with GCP: BigQuery, Hive, and PySpark on Dataproc.
Cleaned large datasets using OpenRefine and Python.
Enabled real-time data analysis via Spark Structured Streaming.
Created crime trend dashboards using heatmaps and time-series plots.

AI Developer – DishGenie Recipe App

Group Project | 2025

Built a full-stack recipe generator using Flask, HTML/CSS, and GPT API.
Enabled user input control for cuisine, ingredients, and difficulty.
Integrated OpenAI API and deployed responsive UI via Render.
Managed UI feedback, error handling, and API performance logging.

Projects

DishGenie – AI Recipe Generator

A Flask-based web app that generates creative recipes using OpenAI’s GPT model. Users can input ingredients and cuisine preferences to receive personalized recipe ideas.

Developed a full-stack web application with Flask, HTML, and CSS.
Integrated OpenAI’s GPT API to generate recipe content based on user input.
Designed a user-friendly interface for real-time interaction and feedback.
Deployed the app using Render for public access.

Visit Project

Crime Rate Prediction – GCP Project

A cloud-native pipeline built to analyze and visualize crime trends using scalable tools on Google Cloud Platform.

Used BigQuery for SQL-based analysis and data warehousing.
Performed ETL and transformations with Hive and PySpark on Dataproc.
Cleaned raw datasets using Python and OpenRefine.
Implemented Spark Structured Streaming for live data handling and dashboard creation.

Emotion-Based Music Recommendation System

A smart system that detects a user’s emotion using facial expressions and recommends music based on their mood.

Used CNN to classify emotions from facial images captured via webcam.
Mapped detected emotions to relevant music playlists using Spotify’s API.
Built a Python-based interface for real-time emotion recognition and response.
Improved UX with seamless transitions between mood detection and music output.

Energy Consumption Forecasting

A predictive analytics project focused on forecasting household electricity usage using time-series models.

Utilized historical consumption datasets for training models in Python.
Applied statistical and machine learning techniques like ARIMA and LSTM.
Visualized trends using Matplotlib and Seaborn.
Reduced prediction error by 20% through hyperparameter tuning and normalization.

Certificates

Microsoft Certified: Azure Fundamentals (AZ-900) – Earned in February 2023.
Gained foundational understanding of Azure services, core cloud concepts, pricing models, governance, and compliance in cloud environments.
View Certificate

AI For Everyone – DeepLearning.AI – Completed in June 2021.
Learned AI strategy, key use cases, limitations of AI, workflow basics, and how to navigate AI adoption in business environments responsibly.
View Certificate

My Creative Space

Outside of my professional work in data science and cloud engineering, I pursue pencil sketching and digital illustration as a personal hobby.

This gallery features a few of my favorite works — blending emotion, culture, and character through art.

Explore more of my work on Instagram:

@pencilart_love

Kusuma Satya Sreeja Chalasani