Research Areas
Wright is interested in physical computation, control, and complexity, mostly with photons.
Current research directions include:
- Physical and quantum neural networks: Using physical systems with many controllable parameters for analog computing, and for computational imaging and sensing.
- Automated experimental science and engineering: Computer-driven discovery, design, and control of complex physical systems, usually with physics-informed machine learning.
- Multimode quantum and nonlinear photonics: The physics and applications of nonlinear and quantum optical wave propagation and oscillators, usually involving many degrees of freedom.
Research on these topics includes experimental, theoretical, and computational components, with an emphasis on experiments and prototypes based on, or enabled by, photonics. Where feasible, he is interested in developing and applying broad, system-level concepts and algorithms. Accordingly, he also welcome diverse ideas and applications from adjacent fields, such as robotics, applied mathematics, fluids, biology, and materials science.
Selected Awards & Honors
- Cornell William Nichols Findley Award, 2018
- Tingye Li Innovation Prize, 2018
- Optica Outstanding Reviewer Recognition, 2017
- Cornell William Nichols Findley Award, 2015