Advanced Photonics Congress

26 July 2021 – 30 July 2021
Optica Virtual Event - Eastern Daylight/Summer Time (UTC - 04:00)

Special Programming
IPR Debate - Integrated Photonics: What Didn't Work Quite as Expected
Quantum Networks Panel Discussion: The Future of Quantum Networks

Bioinspired Optics: From Fundamental Biology to Tools and Applications
Forty Years of Light Management
 Machine Learning for Photonics


Symposium: Bioinspired Optics: From Fundamental Biology to Tools and Applications

The thematic focus of this symposium will be on the interdisciplinary area of bioinspired optics: specifically, understanding nature’s optical design principles and leveraging them for the development of novel optical tools. The talks will cover various approaches in biomolecular engineering and nanofabrication methodologies, which strive to emulate some of the unique light-manipulating capabilities of living systems, as well as the implementation of new optical characterization strategies. The symposium aims to encourage interdisciplinary discussion, with the simultaneous hope of identifying new research opportunities in bioinspired optics and photonics, advancing fundamental biological understanding, and accelerating next-generation optical tool development. Through our cross-disciplinary focus, we are striving to cultivate a cohesive and inclusive community of scientists at all career stages and from across all demographic groups.

Organizers: Woei Ming "Steve" Lee, Australian National University, USA; Alon Gorodetsky, University of California Irvine, USA

Roger Hanlon, Marine Biological Laboratory at Woods Hole, USA
The Octopus as Tech: Exploring the Biology and Technological Potential of Nature’s Master of Color Change

Session 1 – Bio-inspired Systems

Sonke Johnsen, Duke University, USA
The Diverse Structures Underlying Ultrablack Coloration in Tropical Butterflies and Deep-sea Fish

Dan Morse, University of California, Santa Barbara, USA
Bioinspired Biophotonics

Silvia Vignolini, University of Cambridge, UK
Biomimetic Colour Engineering from Nature to Applications

Thomas Cronin, University of Maryland, Baltimore County, USA
Biological Optics:  Evolutionary Inventiveness in Light Control

Session 2 – Bio-inspired Tools

Viktor Gruev, University of Illinois at Urbana Champaign, USA
Bioinspired Polarization and Multispectral Imagers for Image Guided Cancer Surgery and Underwater Geolocalization

Francesca Palombo, University of Exeter, UK
Optical Measurement of Mechanical and Chemical Properties of Biomaterials and Tissues

Mathias Kolle, Massachusetts Institute of Technology, USA
Biological Growth and Optical Manufacture of Structurally-colored Materials

Sedat Nizamoglu, Koc University, Turkey
Optoelectronic Neural Interfaces - Fundamentals and Applications


Symposium: Forty Years of Light Management

Forty years ago, in December 1981, Eli Yablonovitch submitted his seminal paper on “Statistical Ray Optics,” which was one of the first papers investigating light management for solar cells from a fundamental physics perspective.

Light management has mainly been performed with antireflective coatings and textures, which enhance the average light path and hence, absorption in the solar cells. In the last twenty years highly innovative concepts were also investigated, such as (quasi)periodic structures, plasmonic nanostructures, Bragg reflectors, and photonic up- and downconversion. On the other hand, state-of-the-art silicon solar cells have almost perfect light trapping with external quantum efficiencies close to 100% for a broad wavelength range using only conventional light trapping techniques.

With this symposium, we aim to bring together leading experts in the field representing all the light management concepts investigated during the past forty years. We will critically review different light trapping techniques developed in the past decades and discuss, how the field may and should develop further.

Keynote: Eli Yablonovitch, University of California, Berkeley, USA

Harry Atwater, Caltech, USA
New Directions for Fuels from Sunlight

Benedikt Bläsi, Franuhofer ISE, Germany
The MorphoColor Concept for Colored Photovoltaic Modules and Solar Thermal Collectors

Bruno Ehrler, AMOLF, Netherlands
Carrier Multiplication to Enhance Solar Cell Efficiency

Paul Fassl, Karlsuhe Inst. of Technology, Germany
Revealing the Internal Luminescence Quantum Efficiency of Perovskite Films via Accurate Quantification of Photon Recycling

Olindo Isabella, TU Delft, Netherlands
Light Trapping in Si-based Optical Systems for PV Applications

Janez Krc, University of Ljubljana, Slovenia
Modelling-assisted Optimization of Light In-coupling, Out-coupling and Waveguiding in Photonic Devices


IPR Debate - Integrated Photonics: What Didn't Work Quite as Expected

Take a break from IPR bleeding-edge research with a session welcoming a reflection on the path that brought photonics to where it is now. Three distinguished panelists will share their view on well-established research topics that have not yet ived up to expectations. Join and defend your beloved study or support our speakers’ view.

Panelists include:
Roel Baets, Ghent University, INTEC, Belgium
Light Sources on Silicon: Nothing Beats III-V

Jacob Khurgin, Johns Hopkins University, USA
Why LiNBO3 is Still the King of Modulators?

Thomas Krauss, University of York, UK
Resonant Biosensors: High Q is a Bad Idea


Symposium: Machine Learning for Photonics

The connection between optics and computing has been a persistent research theme over the last century and has been made even stronger with the artificial intelligence revolution of the last decade.  This symposium will focus on the latest emergent research topics at the intersection of machine learning and optics.  The first is on the use of machine learning to accelerate the simulation and design of optical materials and devices.  The second is on the use of integrated optical hardware to perform computing tasks, including the training of neural networks, with unprecedented speed and energy efficiency. 

Ali Adibi, Georgia Inst. of Technology, USA
Manifold Learning for Knowledge Discovery in Optical Metamaterials

Hairsh Bhaskaran, University of Oxford, UK
Photonic Computing Using Functional Accumulative Materials

Alexander Boltesseva, Purdue University, USA
Advancing Photonic Design and Quantum Measurements with Machine Learning

Daniel Brunner, CNRSFrance
3D Photonic Integration Making Parallel Neural Networks Scalable

Darius Bunandar, University of Texas at Austin, USA
Accelerating AI with Photonics

Toshihazu Hasimoto, NTT Device Technology Lab, Japan
Optical Circuit Design with Large Degrees of Freedom for Scalable Optical Neural Networks

Tengfei Luo, University of Notre Dame, USA
Thin-Film Metamaterial Optical Diode Designed Using Machine Learning

Evan Reed, Stanford University, USA
New Photocathode Materials Identified by Data Driven Discovery

Junsok Rho, Pohang Univ of Science & TechnologyRepublic Of Korea
Inverse Design and Forward Modeling in Nanophotonics Using Deep Learning

Peter Wiecha, LAAS CNRS, France
Generalized Nano-optics Fields Predictions and Inverse Design of Complex Transmission Matrices Enabled by Deep Learning

Darko Zibar, Danmarks Tekniske UniversitetDenmark, Tutorial
Building the Next Generation of Photonic Systems Using Machine Learning


Quantum Networks Panel Discussion: The Future of Quantum Networks

Jan Huwer, Toshiba, UK
Prem Kumar, Northwestern University, USA
Anil Prabhakar, IIT Madras, India