Tuesday, 16 December Speakers
TU1 – 13:00 (Keynote)
Advances in Hollow Cores Fibers – from Lab to Field, David Richardson, Microsoft, UK. Astounding progress has been made in recent years in the development of hollow core fibers (HCF). Key developments include the realization of optical attenuation levels substantially below those possible in solid fibers, an emerging HCF ecosystem, and a steadily increasing number of field deployments. This presentation will highlight key developments, showcase recent system demonstrations, and address emerging opportunities and ongoing challenges.
TU2 – 13:30 (Keynote)
Graphene and layered materials for photonics and optoelectronics, Andrea C. Ferrari, Cambridge Graphene Centre, University of Cambridge, UK.
TU3 – 14:00 (Invited)
High-Speed EML Technology for Large-Scale Machine Learning Applications, Nobuo Ohata, Mitsubishi Electric Corporation, Information Technology R&D Center, Photonics Technology Department, Advanced Photonics Group, Japan. In rapidly expanding AI data centers, thousands of GPUs are interconnected via optical communication to perform large-scale parallel computation for training machine learning models. As the computational scale grows, the total power consumption of AI data centers is also increasing explosively, making the balance between computing performance and energy efficiency an urgent challenge. This presentation will discuss trends in backend network architectures for AI data centers and introduce Electro-Absorption Modulated Laser (EML) technology, which is well-suited for machine learning applications because of its low-power operation and high-speed performance.
TU4 – 14:20 (Invited)
Towards high-density programmable photonic circuits: scalability of their key building blocks, Cristina Gómez-Hidalgo, iPRONICS, Spain. Programmable photonic processors are rapidly advancing in circuit density, and their scalability is under study. In this work, we provide wafer-level validation of the fundamental photonic building blocks towards large-scale integration of photonic circuits.
TU5 – 14:40 (Contributed)
Overview of advanced optical interconnect technologies, processes, and equipment in co-packaged optics, Matthew L Hall*, Das Kumar, Xiuyun He, Kevin Shortiss, Sharon Butler, Kamil Gradkowski, Padraic E Morrissey, and Peter O’Brien, Photonics Packaging Group, Tyndall National Institute, Lee Maltings Complex Dyke Parade, T12 R5CP, Cork, Ireland. An overview of advanced optical interconnects is presented in the context of co-packaged optics, including high-density optical interconnects, 3D printed micro-optics, and novel glass interposer technologies, which are key to overcoming key photonics packaging challenges.
TU6 – 15:30 (Keynote)
Trends in New Optical Fibers: Opportunities and Challenges, Ming-Jun Li, Corning Inc, USA. This talk explores recent advancements in optical fiber technology for enhancing fiber transmission capacity and optical interconnect density. It will examine opportunities of these new optical fibers as well as challenges for practical applications.
TU7 – 16:00 (Invited)
Advancing Connectivity and Sensing with Chip-Scale VCSEL Array Technology, Iman Tavakkolnia, University of Cambridge, UK. We present a chip-scale optical wireless system integrating a custom 5×5 VCSEL array with beam-shaping micro-optics, achieving over 360 Gbps data rate and uniform multi-beam coverage. Fabricated in the UK, these arrays enable scalable and energy-efficient communication and sensing, opening new opportunities in photonic wireless technologies.
TU8 – 16:20 (Invited)
Sub-nanosecond Light-by-light Reconfiguration in Optical Fibres, Kunhao Ji1, David J. Richardson1,2, Stefan Wabnitz3, and Massimiliano Guasoni1*, 1Optoelectronics Research Centre, University of Southampton, Southampton SO17 1BJ, UK; 2Microsoft (Lumenisity Limited), Unit 7, The Quadrangle, Abbey Park Industrial Estate, Romsey, SO51 9DL, UK; 3Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, 00184 Rome, Italy. We demonstrate sub-nanosecond light-by-light reconfiguration of a probe in multimode and multicore fibres, enabled by dispersionless multi-phase-matching for programmable mode control, core-to-core routing, and remote characterisation within a unified platform.
TU9 – 16:40 (Contributed)
Optimising Photonic Inverse Design via Interpretable Machine Learning, Lirandë Pira1, Airin Antony 2,3*, Nayanthara Prathap1, Jamika Ann Roque3, Daniel Peace2,3, Jacquiline Romero2,3, 1Centre for Quantum Technologies, National University of Singapore, Singapore; 2Australian Research Council Centre of Excellence for Engineered Quantum Systems, University of Queensland, St Lucia, 4072, Australia; 3School of Mathematics and Physics, University of Queensland, St Lucia, 4072, Australia; 4National Institute of Physics, College of Science, University of the Philippines, Diliman, Quezon City, 1101, Philippines. The black-box nature of topological inverse design makes intuitive optimisation of device performance challenging. Our local interpretable model identifies patterns underlying inverse-designed broadband multiplexers and helps increase the 0.5-dB bandwidth beyond 200 nm.
