Dr. Felix Heide

Professor

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Biography

Felix Heide is a Professor of Computer Science at Princeton University, where he leads the Princeton Computational Imaging Lab. His research focuses on developing novel imaging techniques that enhance the capabilities of computers to see and understand the world, particularly in challenging conditions. With expertise in optical computing, machine learning, and computer vision, Professor Heide has produced significant work that allows for super-human capabilities in imaging applications ranging from autonomous vehicles to microscopy. He has received numerous accolades, including the Alain Fournier Ph.D. Dissertation Award and was named a Significant New Researcher by SIGGRAPH. Professor Heide’s impactful research includes contributions to the fields of deep learning, real-time imaging, and ultra-fast scene capturing. His work often lies at the intersection of optics, computer graphics, and optimization, pushing the boundaries of how we perceive and interact with the visual world. In addition to his academic roles, he has co-founded technology companies and contributed to innovations in AI-driven robotics for self-driving trucks, demonstrating a profound commitment to blending academic research with practical applications.

Research Interests

Experience

Professor

2017-06-01 — Present

Princeton University • Princeton, NJ

Professor of Computer Science, leading research in computational imaging.

Head of AI

2020-01-01 — Present

Torc Robotics • Blacksburg, VA

Leading AI research and development for autonomous vehicle technologies.

Awards

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Princeton Dean Research Distinguished Innovation Award

2025-10-01
#

Sloan Research Fellow

2023-02-01
#

Packard Fellow

2023-01-01
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Alain Fournier Ph.D. Dissertation Award

2018-06-01

Requirements for Princeton University

Doctorate Program
Requirements
GPA Requirement
Required:3
GRE General
TOEFL
Speaking
Required:27
IELTS
Speaking
Required:8
Prerequisites
Bachelor's degree in engineering or science Strong background in mathematics, materials, physics, or related engineering
Application Checklist
  • Academic Statement of Purpose
  • Personal Statement
  • Resume/CV
  • Three Letters of Recommendation
  • Transcripts
  • Application Fee
Specialization Notes

GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.