2024-2025 OCIA Research Awards
With the support of Analog Devices, Inc. (ADI), OCIA is awarding annual grants to internal WHOI investigators at two levels: Incubation Awards provide up to $100,000 in seed funding to support design, exploration, and/or early execution of new, cutting-edge scientific initiatives; and Acceleration Awards provide up to $300,000 each to expand successful or mature programs of cutting-edge scientific initiatives.
Deep Learning-Driven Downscaling: An Advanced Virtual Sensor for Coastal Resilience
Principal Investigators: Christopher Cluett (Applied Ocean Physics & Engineering)
Across the world, coastal communities face growing risks from flooding, erosion, and powerful storms. To prepare and protect people and infrastructure, local planners and industries need ocean forecasts that are not only accurate but also specific to their coastlines. The problem is that most existing forecasting tools look at the ocean on a global scale, like zooming out on a world map until small details disappear. These systems can’t tell you what’s happening at a specific harbor or beach because they average conditions over large areas. The few models that can capture those details need huge computing power and detailed maps of the seafloor, which makes them slow and expensive to use.
This project takes a different approach. Instead of relying on physical sensors scattered across the ocean, WHOI researchers are building a “virtual sensor” that is powered by artificial intelligence (AI). By teaching an AI system to recognize patterns in past ocean data, the model learns how local geography affects waves. With this knowledge, it can turn broad, global forecasts into detailed, coastline specific predictions.
The team is developing a prototype “virtual buoy” that runs on compact, energy-efficient hardware close to the coast. This virtual buoy was designed to deliver fast, high-resolution forecasts without the need for expensive and complex physical systems used today to monitor ocean conditions. For industries such as shipping, coastal engineering, insurance, and offshore energy that depend on forecasting ocean conditions, this technology offers a faster and more affordable way to stay ahead of the changing seas.
Advanced Ocean Sensing Networks Using 10BASE-T1L Single Pair Ethernet
Principal Investigators: Eric Gallimore (Applied Ocean Physics & Engineering)
Monitoring the ocean often requires complex, expensive networks of electronic sensors connected by heavy cables or batteries that need frequent replacement. These limitations make it hard for offshore energy developers and coastal industries to gather continuous, high-quality data over large areas.
This project is developing a new kind of ocean sensing network that uses an emerging technology called single-pair Ethernet. With just one thin pair of wires, this system can both power sensors and transfer data over much longer distances than today’s systems, which rely on short, multi-cable connections or battery-powered sensors that must be replaced frequently. It also allows precise timing and easier communication between devices. Sensors that are critical for monitoring ocean conditions, supporting offshore energy systems, and protecting coastal infrastructure can be installed more quickly, maintained more easily, and operated at a fraction of the cost of current systems.
This approach could transform how ocean scientists and engineers build and deploy ocean-monitoring systems while opening the door for businesses to create custom, low-cost sensor networks that reduce installation and maintenance expenses and improve the speed and reliability of ocean data collection.
AIPEX: An AI-enabled long range autonomous system for monitoring ocean ecosystem dynamics
Principal Investigators: Michael Jakuba (Applied Ocean Physics & Engineering), Heidi M. Sosik (Biology)
Understanding how ocean ecosystems are changing is critical for managing fisheries, protecting biodiversity, and planning sustainable offshore development. Yet today’s monitoring tools struggle to keep up. The ocean is vast, constantly moving, and home to life ranging in size from microscopic plankton to migrating whales. Traditional methods like research ships provide detailed information but are expensive and cover only small areas, while autonomous tools such as gliders and floats miss the fine-scale biological details that reveal how ecosystems truly function.
This project is developing a next-generation autonomous system called the Autonomous Intelligent Plankton Explorer, or AIPEX, designed to bridge that gap. AIPEX combines a long-range underwater vehicle with specialized imaging sensors and artificial intelligence to identify tiny plankton directly in the ocean and in near real time. The system’s onboard computer can process data as it’s collected, sending summaries back to shore so scientists and resource managers can respond quickly to changing ocean conditions.
By automating what once required entire ship expeditions, AIPEX is designed to dramatically reduce costs and expand the reach of ecosystem monitoring to benefit a wide range of users from scientists studying the marine food web to offshore energy and fisheries monitoring environmental impacts. AIPEX is a collaborative project between WHOI and other marine robotics engineers built upon proven commercial platforms and sensors. This work lays the foundation for future underwater systems that can make smart, autonomous decisions in the ocean.
Advanced Coastal Resilience Sensor Development: Development and Testing of a Low Cost, Single Channel HF Radar System
Principal Investigators: Anthony Kirincich (Physical Oceanography)
Coastal regions are among the most dynamic and vulnerable environments on Earth. Rapidly changing weather can threaten communities and industries that depend on safe and predictable ocean conditions. To prepare for these risks, decision-makers need detailed, real-time information about the winds, waves, and currents near the shore. Unfortunately, existing observation systems are too sparse, too expensive, or too difficult to deploy at the scale needed to fully understand these coastal hazards.
This project aims to change that by developing a new kind of high-frequency radar (HF radar) system that is smaller, more precise, and less than a third of the cost of current systems. Traditional HF radar systems require multiple large antennas and complex installations to track ocean surface movement over wide areas. The new single-antenna design being developed at WHOI integrates advanced digital signal processing with precise timing control using self-calibrating electronics that capture higher-resolution measurements of challenging coastal environments.
This research team has built upon years of successful WHOI collaborations with industry to provide better environmental monitoring hardware that helps coastal communities improve emergency responses and reduce operational risks for the shipping, offshore energy, and coastal development industries.