This summer has been exciting and productive here at deFacto, in-part, from the hard work from our first group of interns that we had the pleasure of working with. Hailing from RPI (Rensselaer Polytechnic Institute) and SUNY Geneseo, these students worked on developing everything from coursework revolving around deFacto software for the Fall semester at RPI, creating predictive forecasting models that are applicable across various industries, and the creation and implementation of our new virtual assistant – deFactoid.
Below is a short bio of the students we worked with and how they contributed to making deFacto planning the smartest, fastest thinking corporate planning product.
- Sarah Hanlon
- Junior (RPI)
- Business and Management Major
- Concentrations: Supply Chain and Finance
- Role
- deFacto Planning will be used in the curriculum in the fall at RPI and Sarah assisted in the designing of coursework that revolves around the software. Sarah also assisted in the creation of a Supply Chain planning model that will be showcased in deFacto.
- James Stark
- Junior (RPI)
- Business and Management Major
- Role
- James assisted in the implementation of deFacto into RPI curriclium as well. James was directly involved in creating coursework where he learned deFacto Planning software and applied that knowledge.
- Brandon Rao
- Junior (RPI)
- Computer Science Major
- Cognitive Science Minor
- Jim Hines
- Quantitative Finance and Risk Analytics – Masters
- Computer Science – Bachelors
- Role
- Brandon and Jim were part of the team that brought a virtual assistant, named deFactoid, to life for deFacto. The assistant will have many uses for deFacto, and Brandon and Jim worked hard on each step throughout the creation process.
- Nishant Zope
- Information Technology – Data Science – Masters (RPI)
- Computer Engineering – B.E.
- Mohit Parkhi
- Information Technology – Masters
- Information Technology – B.E.
- Role
- Nishant and Mohit brought their Data Science skills to assist in creating predictive forecasting models for deFacto. This project was designed to create a robust machine learning model that can provide accurate predictions for any industry.
- Andrea Bedard
- Math Major (SUNY Geneseo)
- Role
- Andrea was directly involved in the visualization side of the of predictive modeling. Andrea learned visualization skills quickly and applied those each section of the project. The end result was a thorough display of data that could be easily understood by end users.