Bredesen Center PhD Students

• Emily Herron - Graduated 2023
  • Topic: Generalized Differentiable Neural Architecture Search with Performance and Stability Improvements
  • Current: Postdoctoral Research Associate at ORNL/Analytics & AI Methods at Scale Group

PhD Summer Students

• Fan Chen - Summer 2018 - Duke University
  • Topic: Efficient Computation for Generative Adeversarial Models (Co-mentored w/ Catherine Schuman)
  • Current: Assistant Professor at Indiana University Bloomington
• Linghao Song - Summer 2018 - Duke University
  • Topic: Improved Deep Learning Architectures for Neutrino Vertex Reconstruction (Co-mentored w/ Catherine Schuman)
  • Current: Assistant Professor at Yale University
• Jeremy Liu - Summer 2017 - University of Southern California
  • Topic: Boltzmann Machines on D-Wave (Co-mentored w/ Thomas Potok)
  • Current: Senior Vice President at AlixPartners
• David Isele - Summer 2016 - University of Pennsylvania
  • Topic: Deep learning on Titan (Co-mentored w/ Robert Patton)
  • Current: Research Scientist at Honda Research Institute USA, Inc.

Undergraduate Summer Students

• Nikitha Rajagopalan - Summer 2026 - Florida State University
  • Topic: Adversarial AI Robustness
  • Current: Undergraduate at Florida State University
• Vivaan Singhvi - Summer 2025 - University of Michigan
  • Topic: Neural Rendering Techniques for Adversarial Patches
  • Current: Undergraduate at University of Michigan
• Josef Dosch - Summer 2025 - University of Tennessee
  • Topic: Improved Adversarial Detection
  • Current: Undergraduate at University of Tennessee
• Jessica Mohr - Summer 2023 - Maryville College
  • Topic: Effects of Adversarial Attacks on Deep Learning Models
  • Current: Undergraduate at Maryville College
• Emily Herron - Summer 2018 - Mercer University
  • Topic: Machine Learning for Information Extraction from Scholarly Publicaitons
  • Current: Postdoctoral Research Associate at ORNL/Analytics & AI Methods at Scale Group
• Aiden Rutter - Summer 2018 - University of Tennessee
  • Topic: Recurrent Deep Learning Models for Digital Communication
  • Current: Software Developer at Epic
• Albert Xue - Summer 2017 - Duke University
  • Topic: Generative Adversarial Networks
  • Current: PhD Student in Bioinformatics at UCLA
• Jeremy Poff - Summer 2017 - University of Tennessee
  • Topic: Recurrent Neural Networks for Text Extraction
  • Current: Software Engineer
• Parker Mitchell - Summer 2017 - University of Tennessee
  • Topic: Deep learning on FPGAs (Co-mentored w/ Catherine Schuman)
  • Current: FPGA Engineer at Optiver
• Adam Terwilliger - Summer 2016 - Grand Valley State University
  • Topic: Deep Learning Applied to Neutrino Detector Data
  • Current: Data Scientist at Rank One Computing
• Allison Cabo - Summer 2015 - Allegheny College
  • Topic: Time Similarity Metric for Cyber Data (Co-mentored with Justin Beaver)
  • Current: Data scientist at U.S. Government

High School Students

• Kieran Barr - Summer 2026 - Farragut High School (Knox County, TN)
  • Topic: Adversarial AI Robustness (Co-mentored with Jack Hutchins)
  • Current: High School Student
• Jonathan Bolme - Summer 2026 - Farragut High School (Knox County, TN)
  • Topic: Adversarial AI Robustness (Co-mentored with Jack Hutchins)
  • Current: High School Student
• Vivaan Singhvi - Summer 2024 - Farragut High School (Knox County, TN)
  • Topic: Adversarial Image Detection
  • Current: BS Student at University of Michigan
• Katie Nuchols - Summer 2018 - Clinton High School (Anderson County, TN)
  • Topic: Machine Learning Analysis of Summit Supercomputing Benchmark Data (Co-mentored with Catherine Schuman)
  • Current: BS CS Graduate from University of Tennessee