Synthetic data AI/ML App

Our company is interested in researching the different options for synthetic data generation, with Python libraries as a starting point. Applications of this work span the variety of services we provide in data creation, management, and analysis to potential clients in the social impact sector. We would like to collaborate with students to research how best to compare the available Python packages for synthetic data generation, which typically involves use of statistical methods alongside generative models (i.e. generative adversarial networks, variational autoencoders) and sometimes conditional generative models. Students will create a summative white paper style document as well as use that as a basis for a Jupyter notebook that rigorously and holistically demonstrates the findings. This will involve several different steps for the students, including: Conducting background research on how existing Python synthetic data libraries were created and set up. Analyzing our current services offerings in data creation, management, and analysis. Researching how existing Python synthetic data libraries could be applied for potential clients. Developing a summative white paper that provides unique outcomes or insights into our application for potential clients. Providing a Jupyter notebook that can be used to guide our exploration of next steps for potential clients.

Interactive Map: Search & View

The main objective of the Interactive Location Explorer project is to create a user-friendly, visually intuitive map-based platform that allows users to: Search and Discover Locations : Enable users to explore locations based on specific search criteria, such as availability, type, or features. Display Key Information : Present detailed information about locations directly on the map via interactive markers or pop-ups. Improve Navigation : Allow seamless navigation across geographic areas with zooming and panning features. Enhance User Engagement : Provide a visually appealing and engaging interface to improve the overall user experience. Facilitate Decision-Making : Help users make informed decisions quickly by integrating search results with map visuals for easy comparison. This project aims to combine functionality with design to make searching for locations more intuitive and efficient.

Synthetic data AI/ML App

Our company is interested in building upon our synthetic data application. Impact of this work spans the variety of services we provide in data creation, management, and analysis to potential clients in the social impact sector. We would like to collaborate with students to simulate different tabular data scenarios by needs specific to each sub-sector we serve, i.e. philanthropy, impact investing, think tank, advocacy, higher education. Students will write code and documentations to explore 2-3 common, tabular dataset scenarios per sub-sector that our company can use as reference points for our application's back-end processing tasks. This will involve several different steps for the students, including: Developing familiarity with Python synthetic data libraries Building intuition on dataset structures typical in social impact sub-sectors Evaluating then prioritizing options for building the app back-end with a zero-trust architecture model Writing clean code and requisite technical documentations