My name is Poojitha Kale and I have a master's degree in Electrical Engineering from Penn State University. My thesis was based on studying EEG signals for patients with Epilepsy. It focused on using non-linear information transfer techniques to identity seizure hotspots in the brain that are not realized through regular diagnostic tests. It was the first study to be done on human patients. During my master's, I had the opportunity to showcase my understanding of signals and my analytics capabilities through two conference publications.
Due to my interest in data science, I moved to San Francisco for a fellowship. During which I improved my skills in python and SQL. I can execute machine learning concepts to perform data analysis, predictions, forecasting, and visualizations. I also have some experience working with PySpark and Tensorflow.
In short, I am an aspiring Data Scientist with a background in Electrical Engineering. And I would love to use my skills in data science, machine learning, and technology for social good.
-
Experience
I am currently working as an intern at Zedbee Technologies where I work on forecasting the energy consumption of HVAC systems by modeling tonnage, water flow, the temperature of water in and out as well as the frequency of operation of the machine to attain zero energy buildings by providing holistic- monitoring and energy conservation solutions.
-
Projects
As a fellow at The Data Incubator, I worked on the following projects:
• Forecast a country’s progress to achieve 100% access to electricity by 2030 by modeling the trend of investments in renewable energy, population growth and technological expansion using ARIMA
• Developed a web-scraper to crawl through the captions of photos from the NYC Social Diary and build a complex network graph showcasing social interactions for the NY Elite
• Predict ratings of restaurants in NYC planning to open new branches with an accuracy of 97% using custom-built estimators, workflow pipelines and natural language processing
• Compile a violation record-keeping database of restaurants in the NYC area for the past 10 years in SQL
• Predict accurate tags for user posts in stack overflow with an accuracy of 96% using Spark distributed computing