Summit Venture Studios - Machine Learning for Grant-to-Patent-to-Company Analysis

Company Overview

Summit Venture Studios (SVS) is a venture investment firm that works with universities and their technology transfer offices.  SVS is focused on discovering technologies with a promising business case from inventors at universities, develop a business around the technology, and deploy a go-to-market strategy with a target to exit the company through a buyout acquisition.

Project Description

Students on this project will use machine learning to analyze data from NSF and USPTO databases. The goal is to identify patents resulting from NSF grants and track how grant topics lead to the founding of companies using PitchBook. Students will develop a machine learning model, validate results, and present a comprehensive report on grant-patent-company connections, aiding investment decisions. This project equips students with data science and machine learning skills while providing valuable insights for strategic investment decisions.

Outcomes:

• Machine Learning Model: Develop and test a model to match NSF grants with USPTO patents.

• Data Analysis & Validation: Ensure accurate identification of NSF grant-related patents.

• Market Database Filtering: Establish filters in PitchBook to link grant topics to company formation.

• Grant-Patent-Company Nexus Report: Compile findings to illustrate relationships between grants, patents, and companies.

Project Stages:

•Data Acquisition and Model Development: Gather data and create the machine learning model.

•Model Implementation & Data Analysis: Apply the model, validate patent origins, and analyze results.

•Market Database Filtering: Use PitchBook to trace grant-related company creations.

•4. Final Report: Present a detailed report on grant-patent-company connections.