Hi, I'm Prateesh Reddy Patlolla

I Convert Coffee into Code

Data Science Grad at Indiana University Bloomington

About Me


I’m a Senior Data Scientist with over 3 years of experience in machine learning, cloud technologies, and data science. I hold a Master’s in Data Science from Indiana University Bloomington (GPA: 4.0/4.0), and my expertise spans Machine Learning, AB testing, Predictive modeling, optimization algorithms, CI/CD, and full-stack development.

I specialize in scaling up and deploying scalable machine learning models, optimizing data pipelines, and using advanced statistical techniques to solve complex infrastructure and business problems. Recently, I led a $150M optimization project at Toyota, where I applied linear constrained programming using GurobiPy, and supply chain analytics to significantly enhance operational efficiency. In addition, I developed a Generative AI tool that automated critical internal processes, contributing to large-scale cost savings.

MMy experience also includes working with cloud-based platforms such as AWS and Azure, where I designed and implemented solutions for real-time data processing, model deployment, and monitoring at scale. I have hands-on experience in data engineering and building ETL pipelines, which ensures high-quality data for machine learning models and robust production environments.

With expertise in optimization, demand forecasting, and cost-saving models, I’m passionate about using data-driven approaches to drive business value. My work reflects a deep curiosity for machine learning and cloud infrastructure, and I am always eager to continue learning and applying innovative technologies in fast-paced environments.

If you'd like to discuss work opportunities or collaborations, feel free to Email Me or Download my Resume.




Visual Studio Code Python R Java Docker AWS TensorFlow JavaScript React SQL MySQL Git GitHub



Checkout My Projects

Face Generative
Adveserial Networks (GANs)

GANs

Over the 70 years of Machine learning Research one thing we are sure about is for more effective models we need more training data especially wide variety of data. This is the inspiration around this project to generate more Face data using GANs and to use Neural Style Transfer to further broaden the scope of generated data.

Text Summarization using
Advanced NLP Methods

Text Summarization

To Provide Cognitive search capability to search against database like FDA and EMA (European medical agency) via a natural language question and return relevant results in order to help with accelerating regulatory submissions for Eli Lilly. Performed abstraction based Natural language generation methods like T5 Transformer, GPT-2 Algorithm and BART Transformer

Blockchain Financial
Transaction System

In Banking and finance sector, the term Blockchain is frequently heard. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. This project is an effort to give bank the ability to access a single source of information and also allows them to track all documentation and validate ownership of assets digitally, as an unalterable ledger in real time.

Traffic
Sign Classifier

Autonomous vehicles abide by road legislation and recognize and understand traffic signs. Traditionally, standard computer vision methods were employed to detect and classify traffic signs, but these required considerable and time-consuming manual work to handcraft important features in images. Instead by applying deep learning to this problem, we create a model that reliably classifies traffic signs, learning to identify the most appropriate features for this problem by itself.