Winners

2018 Results

The 2018 Nittany AI Challenge included representation, participation, and support from:

  • 10 Campuses
  • 16 Colleges
  • 35+ Departments
  • 58 Faculty/Staff
  • 196 Students
  • 8 AI/EdTech Companies

Phase One Winners

Ten projects were awarded $2,500 in seed money for the development of a prototype.

  • Aspire
  • Course Recommendation System Using Historical Student Course Enrollment and Performance
  • FeelLike
  • From Micro to Macro: Applying Machine Learning to Scale up Competency Based Learning at PSU
  • Intelligent Prediction System using Emotion Classification
  • LionPlanner
  • Nittany AI Challenge (Mock Interview)
  • Pathfinder: Recommending Course Pathways via Supervised Learning and Text Mining
  • ProFound, A Professor Search Engine
  • ResOpp: Research Opportunities for University Students

Phase Two Winners

Five prototypes were selected to receive $5,000 for further development of a minimum viable product.

Aspire
An application to help students map out their college careers by providing recommendations on experiences and skills needed to achieve their dream jobs post-graduation. Team members: Tyler Spagnolo (team lead), Shane Hepner, Isabelle Biase, and Dr. Montgomery Alger

From Micro to Macro: Applying Machine Learning to Scale up Competency Based Learning at PSU
A tool that integrates human and algorithmic (AI) grading capabilities to provide instant student feedback and reduce grader workload with an emphasis on evaluating digital badges. Team members: Emily Rimland (team lead), Victoria Raish, Jeff Rimland, Angela Demarco, and Arianna Scheidell

LionPlanner
A web application that simplifies academic planning by providing students with full, modifiable plans for all their semesters and consolidating all the resources and requirements they need for the process. Team members: Michael Roos (team lead), Quinn Verbeke, Thanh Tran, Matthew Mancini, Dylan Shoemaker, Christina Warren, Benjamin Proto, and Dr. Wang-Chien Lee

Pathfinder: Recommending Course Pathways
An application that uses machine learning algorithms to recommend effective course pathways, learning from past course enrollment and the performance data of other students. Team members: Dr. Dongwon Lee (team lead), Thai Le, Yiming Liao, and Jason Zhang

ProFound, A Professor Search Engine
A solution that retrieves all of the information publicly available about a professor and intelligently categorizes and populates it into a portal that students can access to search for a professor by name and/or research area. Team members: Shaurya Rohatgi (team lead), Neisarg Dave, Mukund Srinath, and Dr. C Lee Giles

Phase Three Winners

The final phase of the Challenge concluded on September 5, 2018, when the final five teams presented their minimum viable products (MVPs) to a panel of judges. Three teams were chosen to receive funding from the remaining $50,000 pool of funds.

  • LionPlanner – $30,000
  • ProFound, A Professor Search Engine – $10,000
  • Aspire – $10,000

Learn more about the 2018 Challenge finalists.

Past Results

Learn about the 2017 winners.