Enhancing grid visibility capabilities
The development of GridScape, a geospatial tool, addressed the need for distribution system insights by providing a holistic view of the service territory, transformer triage, solar insights, and electric vehicle density. The tool leveraged specialized GIS tools such as ArcPy, and libraries like Python and R for application development.
Too Many Cooks
Ever get frustrated at the amount of extra sifting you have to do when looking for a recipe?
Harnessing OpenAI and Python to build a better Cookbook through prompt engineering. This involved using Python and an OpenAI chatbot to scrape recipes from the internet and create a user-friendly platform for finding recipes without ads.
Power BI Visualization
Enhanced EV adoption insights platform
The EV Engineering Insights Dashboard, crafted with Power BI and advanced Python scripting, showcases technical prowess in data processing, geospatial analysis, and interactive visualization. Featuring sophisticated functionalities such as Power Query, Power Pivot, and Power View, along with Python packages like pandas and GeoPandas, the dashboard provides engineers, analysts and executives a comprehensive tool for handling complex EV registration data, offering insights into spatial distribution, historical trends, and dynamic changes in the electric mobility landscape.
Oh, The Horror!
Where should you go to find a good horror movie?
I scraped two subreddits and use natural language processing to recommend a site for new horror news.
AMI Meter Rollout
Improving financial and operational insights
The creation of an SAC dashboard to monitor the transition from standard to automated meters. This transition is significant as it represents a shift from using statistical sampling to obtain estimated loads by customer type to having 100% visibility of customers and their actual usage.
Help in a SNAP
Random Forest Vote Ensemble
Which groups are vulnerable to food insecurity in America during COVID?
I perform a risk assessment on SNAP user profiles using a 10-year gap analysis process involving GIS tools as well as interpreting a prediction model.
Behind the Mask
Who wears masks? Let’s use AI to find out…
I built a neural network image classifier to predict which Twitter images, that were scraped using Tweepy, are wearing a mask. I then map the distribution of images on a GIS map.