Miami Herbert's ICSRI Fellows Program

Miami Herbert's ICSRI Fellows Program is designed to inspire the next generation of leaders to explore the frontiers of artificial intelligence, ethics, and innovation. Fellows learn to apply AI responsibly across disciplines—bridging business, technology, and society—while gaining hands-on experience with the University’s research resources.

  1. ICSRI
  2. ICSRI Fellows Program

Throughout the year, Fellows will present their work at open symposia, showcasing projects that combine technical expertise with ethical leadership and organizational impact. Although the program does not offer a stipend, an award of financial support will be granted to one or more Fellows to attend and present their work at a professional conference in recognition of outstanding contributions.

Each Fellow benefits from dual mentorship

  • A faculty research advisor who guides academic and technical development
  • An ICSRI-appointed industry mentor who provides expertise in AI applications, responsible design, and computational research

This prestigious designation is awarded annually to six undergraduate students (sophomore level or above) from any School or College at the University of Miami who are in good standing.

Application Requirements

  • One-page research proposal
  • Transcript or CV

Important Dates

  • Application Deadline: Coming soon!
  • Fellows Announced: Coming soon!

Submit your application to: icsri@miami.edu

2026 Fellows Award Winners

  • Savannah Fletcher
    Research Topic: Bridging the Language Barrier in Miami-Dade’s Healthcare System Through Productive AI
    Description: Researching responsible LLM integration in Miami-Dade healthcare to improve Spanish-English communication, reduce provider-to-patient friction, and ensure ethical, accurate, privacy-conscious patient translation support.
  • Nikhil Sunder
    Research Topic: Non-Stationary Spectral Decomposition Network (NS-SDN) for Econometric Forecasting
    Description: NS-SDN is a neural architecture for forecasting non-stationary periodic time series, learning latent frequency-modulating functions via spectral decomposition inspired by Hilbert-Huang methods, transformers, sinusoidal modeling, and Fourier networks.
  • Kyle Pasion
    Research Topic: Generative AI and Blockchain Technology
    Description: Exploring blockchain applications for content provenance and authenticity to combat the spread of AI-generated misinformation on social media.
  • Lucas Yeykelis
    Research Topic: Reasoning and General-Purpose LLMs: Cognitive Trade-offs and System Efficiency
    Description: Analyzing performance differences between reasoning and general-purpose LLMs across inference tasks, comparing model responses to human debate behavior for synthetic AI persona applications.