Computational optics for MIR sensing

Computational optics for MIR sensing

Research Challenge

Thermal cameras are rapidly becoming essential in industrial inspection, autonomous systems, environmental monitoring, security, and healthcare. However, conventional thermal imagers only provide intensity information, limiting their ability to distinguish materials, identify chemical compositions, or extract detailed physical properties of a scene.

At the same time, many materials exhibit unique spectral and polarization signatures in the mid-wave infrared (MWIR) and long-wave infrared (LWIR) wavelength ranges. Capturing this information could dramatically improve object recognition, defect detection, process monitoring, and environmental sensing. Yet current systems capable of measuring thermal, spectral, and polarimetric information simultaneously are often bulky, expensive, and require complex optical assemblies.

Recent advances in computational imaging and meta-optics provide a radically different approach. Engineered metasurfaces can encode multiple dimensions of information directly onto an image sensor, while advanced algorithms reconstruct the full thermal, spectral, and polarization content of the scene. This paradigm enables compact, low-cost imaging systems capable of extracting significantly more information than conventional cameras.

The challenge of this PhD is to develop computational meta-optical imaging systems that combine thermal imaging with spectral and polarimetric sensing, enabling a new generation of intelligent infrared cameras.

Research Objectives

The goal of this PhD is to establish a complete computational sensing framework that combines advanced infrared meta-optics with image reconstruction algorithms.

Specific objectives include:

• Design metasurface-based imaging architectures for thermal, spectral, and polarimetric sensing.
• Develop inverse-design methodologies for engineered disordered metasurfaces operating in the MWIR or LWIR spectral ranges.
• Create computational reconstruction algorithms capable of recovering temperature distributions, spectral signatures, and polarization information from compressed measurements.
• Develop low-loss metasurface components compatible with scalable semiconductor manufacturing processes.
• Demonstrate compact infrared imaging systems that outperform conventional thermal cameras in information content and functionality.

Expected Impact

The developed technology could enable a new generation of compact infrared cameras capable of simultaneously measuring:

• Temperature distributions
• Material composition
• Chemical signatures
• Surface properties
• Polarization information

Potential application fields include:

• Environmental monitoring
• Gas and chemical sensing
• Security and Aerospace
• Robotics and autonomous systems

By merging meta-optics, computational imaging, and artificial intelligence, this research aims to redefine what an infrared camera can measure and interpret.

Candidate Profile

We are looking for highly motivated candidates with a background in:

• Photonics
• Optics
• Physics
• Electrical engineering

Experience with electromagnetic simulations, nanofabrication, optical design, or semiconductor technologies is considered an advantage.