activity
20202025
collaborators

5 papers

physics.optics2025

MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design

S. Rodionov, A. Burguete-Lopez, M. Makarenko +3

Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains for a broad range of applications. Howe…

physics.ins-det2025

Towards real-time additive-free dopamine detection at mM with hardware accelerated platform integrated on camera

Ning Li, Qizhou Wang, Zhao He +3

Tracing physiological neurotransmitters such as dopamine (DA) with detection limits down to mM is a critical goal in neuroscience for studying brain funct…

cs.CV2022

Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders

Maksim Makarenko, Arturo Burguete-Lopez, Qizhou Wang +4

Hyperspectral imaging has attracted significant attention to identify spectral signatures for image classification and automated pattern recognition in computer vision. State-of-th…

physics.optics2020

Broadband vectorial ultra-flat optics with experimental efficiency up to 99% in the visible via universal approximators

Fedor Getman, Maksim Makarenko, Arturo Burguete-Lopez +1

Integrating conventional optics into compact nanostructured surfaces is the goal of flat optics. Despite the enormous progress of this technology, there are still critical challeng…

physics.optics2020

Generalized Maxwell projections for multi-mode network Photonics

M. Makarenko, A. Burguete-Lopez, F. Getman +1

The design of optical resonant systems for controlling light at the nanoscale is an exciting field of research in nanophotonics. While describing the dynamics of systems with few r…