RESEARCH SPOTLIGHT
Hi, I am
MUHAMMAD RIAZ
HOST INSTITUTE
(CSIC-IFISC)
PROJECT TITLE
New architectures of photonic time-delay reservoir computing
KEY WORDS
Photonic Computing, Reservoir Computing, Semiconductor Lasers, Nonlinear Dynamics, Temporal Information Processing
RESEARCH AIM
My research aims to develop energy-efficient photonic computing systems so that time-dependent information can be processed faster with low energy consumption.
RESEARCH OVERVIEW
My research explores how light can be used to perform computing tasks faster and with much lower energy consumption than conventional electronic systems. Instead of relying only on traditional computer chips, I use tiny semiconductor lasers whose natural dynamics can process time-dependent information, such as communication signals and sensor data. By understanding and optimizing how these lasers interact, I aim to develop new photonic computing technologies that are both fast and energy efficient. In the long term, this research could support next-generation artificial intelligence, high-speed communications, and real-time data processing while reducing the energy required by future computing systems.
RESEARCH CHALLENGE
Modern artificial intelligence and data processing systems require increasing computational power, leading to high energy consumption and limited processing speed when handling rapidly changing data. My research aims to address this challenge by developing energy-efficient photonic computing systems that use the natural dynamics of semiconductor lasers to process temporal information directly in the optical domain. The goal is to reduce computational complexity while maintaining high-speed performance, enabling faster and lower-power processing of time-dependent data for applications such as optical communications, sensor technologies, and future neuromorphic computing systems.
RESEARCH INNOVATION
My approach combines photonic reservoir computing with ultra-low-threshold semiconductor lasers, exploiting their intrinsic nonlinear dynamics and memory to process temporal information directly in the optical domain. Unlike conventional AI systems that rely on computationally intensive training of large neural networks, reservoir computing requires training only the output layer, significantly reducing computational complexity. In addition, my research systematically investigates how optical injection, frequency detuning, and delayed feedback influence reservoir performance, providing insights into optimizing photonic computing systems.
RESEARCH IMPACT
What excites me most is the opportunity to use the natural dynamics of light to perform computation in ways that are fundamentally different from conventional electronics. I find it fascinating that a semiconductor laser can act not only as a light source but also as a computing element capable of processing temporal information. The possibility of combining photonics, nonlinear dynamics, and artificial intelligence to develop faster and more energy-efficient computing systems motivates me to explore this field and contribute to future photonic AI technologies.
RESEARCH SUMMARY
My research focuses on time delay reservoir computing (TDRC) with optically injected low threshold semiconductor lasers for fast and energy-efficient temporal information processing. I investigate how ultra-low-threshold semiconductor lasers with optical feedback and optical injection can serve as physical reservoirs for processing complex time-dependent signals. The current work explores the influence of key dynamical parameters, including frequency detuning, injection strength, and feedback conditions, on reservoir performance in tasks such as one-step-ahead prediction of the Santa Fe laser time series. The long-term objective is to develop advanced photonic reservoir architectures incorporating multiple delay loops and amplification-assisted topologies to improve computational capability, scalability, and robustness. This research aims to contribute to low-power photonic artificial intelligence hardware for high-speed signal processing and next-generation neuromorphic computing applications.
RESEARCH VISUAL
RESEARCH JOURNEY
RESEARCH SECONDMENT
The host organization is Aston University, United Kingdom (England), the duration of each secondment is three months. The main objectives of the secondments are to gain expertise in channel equalization for optical communication systems and characterize semiconductor optical amplifier (SOA) devices. The secondment will strengthen the application of photonic reservoir computing to high-speed optical communication systems. My expectation is to get hand-on experience in Optical communication system analysis, channel equalization techniques, SOA characterization and operation, experimental photonics, data analysis.
LEARNING GOALS
I am excited to gain hands-on experience in channel equalization techniques and the characterization of semiconductor optical amplifiers (SOAs), as these are directly relevant to my research. I also look forward to working with experts in the field, learning new experimental methodologies, and broadening my understanding of how advanced photonic technologies can be translated into practical, high-speed, and energy-efficient communication systems.
RESEARCH BENEFITS
The secondment at Aston University will strengthen my research by connecting my photonic reservoir computing work with practical optical communication applications. Training in channel equalization will help me understand how reservoir computing can compensate signal distortions in high-speed optical links. In addition, hands-on experience in SOA device characterization will support the development of amplification-assisted photonic reservoir architectures.
CAREER DEVELOPMENT
The secondment will provide valuable expertise in optical communication systems and photonic device characterization, broadening both my scientific knowledge and experimental skills. It will enable me to apply photonic reservoir computing to practical communication challenges while gaining experience with state-of-the-art photonic technologies. Working in a different research environment and collaborating with leading researchers will also strengthen my international research network. These experiences will support my long-term goal of becoming an independent researcher developing energy-efficient photonic computing technologies for artificial intelligence and next-generation communication systems.
MORE THAN PHD
Why did you decide to join POSTDIGITAL+ ?
I chose POSTDIGITAL+ because it provides an exceptional opportunity to work in an international and interdisciplinary research environment while addressing challenging problems in next-generation digital technologies. The combination of excellent supervision, specialized training, international secondments, and collaboration with both academic and industrial partners makes it an ideal platform for my professional development. It also aligns perfectly with my research interests in photonic computing and artificial intelligence, allowing me to develop the expertise and international perspective needed to become an independent researcher.
What do you think is the biggest advantage of being part of the International Doctoral Network?
I believe the biggest advantage of being part of an international doctoral network is the opportunity to collaborate with researchers from diverse scientific backgrounds and institutions. It provides access to complementary expertise, advanced research facilities, and interdisciplinary training that would be difficult to obtain within a single institution. The network also promotes knowledge exchange, international collaboration, and professional development through secondments, workshops, and joint research activities. It helps me in order to strengthen my research as well as build a global professional network and develop the skills needed for a successful researcher.
What skill have you developed the most so far?
I believe the skill I have developed the most is research problem-solving. during my PhD, I have learned how to design experiments systematically, analyze complex datasets, and interpret results by combining theoretical understanding with experimental observations. I have also significantly improved my programming and automation skills, particularly for controlling laboratory instruments and processing experimental data. These experiences have strengthened my ability to approach research challenges independently and develop efficient solutions.
What are your career ambitions after completing your doctorate?
After completing my PhD, I aim to continue my career as a researcher in the field of photonic computing and artificial intelligence. In the short term, I hope to further strengthen my research expertise, expand my technical skills, and gain experience through collaborative international research projects. In the long term, I aspire to become part of a leading international research team, contributing to scientific innovation and advancing technologies that address real-world challenges for the benefit of society.
What inspired you to pursue this research Area?
What inspired me most is the idea that light can do much more than transmit information—it can also perform computation. I was fascinated by the possibility of using the natural behavior of semiconductor lasers to solve complex computing problems in a faster and more energy-efficient way. This unique combination of photonics, nonlinear dynamics, and artificial intelligence motivated me to pursue research that has the potential to contribute to future computing and communication technologies.
What surprised you most since starting your PhD?
What surprised me most was how collaborative and interdisciplinary the research environment is. Since joining POSTDIGITAL+, I have had the opportunity to interact with researchers from different fields, which has broadened my perspective beyond my own area of expertise. I was also impressed by the strong support for professional development through training events, secondments, and networking opportunities.