Prof. Mohammad Belal
Biography
I am an atomic, molecular, and optical (AMO) physicist with broad research experience in experimental soft condensed matter, optoelectronics, high-power fiber lasers, optical-atomic-molecular spectroscopy, coherent atomic control, and quantum technologies. At NOC, I apply this expertise to develop next-generation intelligent monitoring systems for complex environments, including oceans, glaciers, cities, and terrestrial landscapes. Ocean Fibre Sensing (OFS), is one such initiative that I lead. OFS exploits optical-fibres within legacy submarine cables of energy and telecommunications, and transforms them into dense arrays of sensors with unprecedented (dense space-time) ambient environmental observations, alongside enabling cirtical insights into cable-health. Advanced signal processing/analytics combined with bespoke machine learning and artifical intelligence algorithms, not only bakes intelligence into OFS but also preserves efficient analysis of large, multi-dimensional datasets, on high-performance compute architectures. On-the-fly analytics to data-streams (>10 GiB/s) has enabled exploration of alternative compute architectures (e.g., Quantum-based) to overcome classical compute bottlenecks.
My work combines physics, engineering, advanced signals-analysis and data science to provide high-resolution, wide-area insights, transforming complex measurements into clear visualizations and actionable information. Ultimately, these efforts aim to understand, manage, and respond to changes in marine, maritime, glacial, and urban environments, helping to quantify and protect our planet’s critical natural assets.
Projects
Ongoing PhD project:
- https://www.mindscdt.southampton.ac.uk/Project23
- https://www.mindscdt.southampton.ac.uk/Project%2029
- Physical sciences PhD projects | The University of Edinburgh
Funded (ongoing and upcoming) projects:
- SBRI-2020 (PI): Submarine High-fidelity Active-monitoring of Renewable energy Cables (SHARC)
- Trans National Access' 2021-A (PI): Fibre-optic Intelligent Submarine High-fidelity Environmental Sensing (FISHES)
- Trans National Access' 2021-B(PI): Sea-floor High-fidelity Optic-fibre-based Renewables-infrastructure Sensing and Evaluation (SeaHORSE)
- Progeny-Phase1 2022 (PI): Next Generation Underwater Sensing
- PycnoGen 2022-2027 (EP/X025136/1; Co-I): Generation of the global ocean internal pycnocline in the ice-covered Southern Ocean
- Progeny-Phase2 2023 (Co-I): Next Generation Underwater Communications
- NSF-NERC 2024-2027 (NE/Z000408/1; UK-PI): Collaborative Research: Direct comparison of ocean temperature and velocity structure from in-situ measurements and distributed optical fiber sensing
- GSRF 2024 - 2026 (NE/Y003365/1; PI)& Wide-area low-cost sustainable ocean temperature and velocity structure extraction using distributed fibre optic sensing within legacy seafloor cables
- Emso-Eric 2024 - 2026 (PI): Submarine noise-Evaluation and Analytics using Low-cost Sustainable -sensing (SEALS)
- MoD/QQ 2024 (4 months; PI): Geospatial Acoustic Underwater Smart Sensing (GAUSS)
- Xlinks 2024 (PI): Monitoring system evaluation
- SOUNDSCALE 2025 - 2027 (MR/Z505845/1; Co-I): Sensing On Urban Noise: Distributed Sensing For Collaborative And Sustainable Cityscapes And Living Environments
- FULL-OCEAN-FIBRE 2025 - 2028 (ARIA: Forecasting Tipping Points)
Roles Provided
I lead Ocean Fibre Sensing (OFS) research at NOC. It comprises optoelectronic interrogation of optical fibres within submarine cables of energy and telecommmunications combined with advanced signal processing/analytics to enable intelligent, sustainable, wide-area, real-time monitoring of diverse and complex environments, e.g., oceans, glaciers, cities, and terrestrial landscapes whilst also monitoring cable-health. The intelligence layer is anchored in custom signal processing pipelines built in combination with machine learning and AI algorithms, allowing efficient analysis of large, complex, multi-parameter datasets. Compute enabling these advancements comprises advanced GPU-CPU architectures besides quantum compute exploration which is also underway to overcome classical-compute bottlenecks.
