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Neurodiversity Inspired Science & Engineering (NISE) Graduate Trainee Fellowship Program

This 1-minute video highlighting NISE people and projects was produced by the American Society of Engineering Education and first shown at the ASEE 2022 conference. A full 6-minute version is also available at this link.


Application for NISE Fellows and Affiliates

The 2024 NISE application is open and will close on May 31. Applications will be reviewed and decisions made by July 1.

Applications may be submitted at this link:

Sponsored by a National Science Foundation Research Traineeship (NRT) grant, the NISE program takes a novel approach to the training of engineers and scientists engaged in advancing the future of work at the human technology frontier (FW-HTF), which is one of NSF’s 10 Big Ideas. NISE engages students across STEM disciplines in the development, deployment, and commercialization of FW-HTF approaches and devices that support neurodiversity individuals and/or that are inspired by their abilities. The NISE program builds on the unique strengths of the Vanderbilt School of Engineering’s Frist Center for Autism & Innovation and the Vanderbilt Graduate School.  

Eligible fields include but not limited to: School of Engineering (all graduate programs), College of Arts & Science (natural sciences graduate programs, including neuroscience and psychology), School of Medicine (basic sciences graduate programs), Graduate School (data science) 

Other eligibility requirements: PhD and master’s students from relevant fields above


The NISE training elements include:

Trainees who complete all the mandatory components of the NISE program will receive a Graduate Certificate in NISE.

Team Research Projects (mandatory): trainees pursue interdisciplinary thesis projects, co-advised by faculty from two different disciplines selected from participating departments.

NISE seminar courses (mandatory): 

  1. The Science of NISE – An overview of neurodiversity and generally autism specifically, for engineering and science students having no prior exposure.
  2. Applications of NISE – Real life applications of NISE are explored to inspire thesis projects and to gain appreciation for the connections across broad swath of STEM disciplines involved.
  3. Collaborative Approaches to NISE – In this project-based course, student pairs undertake FW-HTF design challenges directly connected to Frist Center for Autism & Innovation research; in parallel trainees are introduced to topics in robotics, psychometrics, apps development, data visualization, and others.

Summer Programs:

  • Data Science: Opportunities for training in basic and some advanced data science concepts and approaches.
  • Apps Development: Opportunities to be trained in using emerging standard tools for app development and then be introduced to design tools for creating visually effective apps.

Communication and Skills Workshop (mandatory) – training in oral & written communication skills. Trainees build skill and confidence in communication, enhancing clarity of their message, and forming connection with any audience. 

Internships – offered usually in the summer in a range of different environments relevant to NISE research and development. The NRT program helps trainees to navigate challenges of managing an internship along with their research and academic obligations.

Mini-courses Developed by NISE Fellows: 

  • Introduction to Affective Computing (developed by Miroslava Migovich – Summer 2021)
    • The use of physiological data and machine learning to determine affective states in neurotypical and neurodiverse populations, specifically autism.
    • Topics: (1) What is Affective Computing?, (2) Intro to Physiological Signals, (3) Intro to Machine Learning, (4) Applications in Autism Research, (5) What is New in the Field, (6) Application to Your Field
    • Slides, materials, and lecture recordings are available upon request to Dr. Julie Vernon (contact info below).

Other Elective Training Opportunities:


NISE Fellow Cadence Watkins awarded Best Student Paper at IEEE AIVR conference, November 2021. 

For more information, see this Vanderbilt News story.