Kaylee Gad

Senior Administrative Assistant, Leadership Team

AI Forge

Machine Learning, Data Preparation, Exploratory Analysis, Forecasting and Optimization

Full Overview

Purdue University’s AI Forge initiative offers industry partners a structured pathway to collaborate with highly trained undergraduate and master’s-level talent equipped with cutting-edge generative AI skills. Through expert-led training modules and hands-on project experience, students develop applied AI capabilities aligned with real-world needs.

The program facilitates direct engagement between companies, students, and faculty, enabling organizations to advance industry-driven projects with academic support while building strong recruitment pipelines with emerging AI professionals. Students are trained in advanced AI techniques for working with textual data, retrieval-augmented generation (RAG), agentic systems, and multimodal data, enabling them to design and deploy intelligent, end-to-end AI solutions.

Example Projects

Over the past year AI-Forge students have participated-in and faculty have led multiple applied AI projects in a wide range of domains, both in academic and industry settings, including manufacturing, digital infrastructure, logistics, industrial psychology and natural resources. Capabilities include building human-in-the-loop AI training environments, developing root cause analysis frameworks for production systems, and engineering agentic AI systems for data exploration and ingestion. Recent examples include:

  • Developed an intelligent trading agent capable of analyzing large-scale trading logs to extract, interpret, and summarize actionable strategies.
  • Designed and implemented scalable data ingestion pipelines for technical and scientific documents, enabling structured extraction, organization, and storage in searchable databases.
  • Built a multimodal AI system for automated monitoring of natural environments, leveraging video data to detect, analyze, and report on dynamic ecological conditions.
  • Designed and deployed a human-in-the-loop AI training environment for workforce development in semi-conductor manufacturing at Purdue's Birck Nanotechnology Center, integrating LLMs, advanced RAG systems, with human expert feedback.
  • Developed and implemented root cause analysis tools for Ford Motor Company's manufacturing operations, creating diagnostic frameworks to identify root causes of warranty claims in production environments.
  • Engineered agentic systems for real-time root cause analysis of live streaming issues for Amazon Prime Video, building autonomous troubleshooting agents capable of diagnosing technical problems in a distributed multi-stakeholder video delivery infrastructure.
  • Architecting AI-powered root-cause diagnostic tools for semiconductor manufacturing at Seagate Technologies' global foundries, designing AI solutions to identify causal relations in manufacturing for root causing production anomalies.
  • Developped an AI-assisted traffic engineering method for large data centers (with Meta).
  • Designing integrated logistics solutions combining AI with multi-agent systems, developing optimization frameworks for supply chain forecasting (with Krenicki Center, currently exploring synergies with Penske Logistics).
  • Implemented a quality framework for retrieval-augmented generation (RAG) in a highly secure environment for U.S. government.

IP Related Considerations

Purdue University is a leader among universities in flexibility for collaborations with industry sponsors, There are several established pathways for industry collaborations, and custom solutions could be accommodated through the office of Sponsored Program Services. These policies are described in detail in the policy document on IP: https://www.purdue.edu/vpec/policies/academic-research-affairs/ia1/

Student Level

Undergraduates, Masters, PhDs

Budget

$5K-$15K, $15K-$30K, $30K+

Typical Team Size

3-5

Terms Available

Fall, Spring

Delivery Model

Faculty-Led

Interested in engaging in a project?