Fiona Hua, PhD

Director of Perception, aka: Mega marine data set builder

As a child, Fiona Hua’s parents had hopes that she would one day become a professional violinist. But after watching her mechanical engineer father advance in his career, she yearned to follow for a job that gave her more variety and challenge. Upon graduating high school, Fiona studied automation at a major university, earning academic placement in the top three percent of her class. The designation allowed her to join a team representing her school during a high-profile robotics competition. While the event was successful in that the team worked together to build robots for specific tasks, what Fiona got out of it was so much more: She realized her professional interests lied on the programming side of the industry.

The discovery of her passion for software development drove her to pursue her Masters’ of Science in Control Theory and Engineering, followed by a Ph.D. in electrical and computer engineering – studies that focused on programming and visual recognition technology. Before she had even graduated from with her Ph.D, however, Fiona was offered a position at Aware, Inc., in Boston, as a research scientist. The job specialized in facial recognition software in support of security and banking technologies. She accepted in 2013 and finished her doctoral program while working full time.

After five years, a recruiter contacted her to gauge her interest in a perception and data lead with Sea Machines in Boston. It was 2018 and Sea Machines had just completed its Series A funding round successfully. A follower of autonomous vehicle technology, Fiona was shocked to learn how advanced Sea Machines’ autonomous systems were. Despite having no background in the marine industry, Fiona realized the job was within her reach.

“Though the data identifying facial and marine targets was fundamentally different, the AI powering the process is the same,” Fiona said.

Fiona accepted the job and started her position building the company’s advanced perception technology and data library of marine targets to support the SM300 and SM400 systems. During her first week on the job, Fiona took a ride aboard Sea Machines’ autonomous boat. An infrequent boater, Fiona was amazed by the technology.

“It was – and is – amazing to witness,” she said. “If I ever own a boat, I want a Sea Machines system for it. It gave me such a level of comfort and trust on the water and I want to build the smart perception to empower this autonomy vessel.”

Fiona, who embraces new experiences, was overjoyed in her new role. Her first challenge involved improving the quality of the company’s situational awareness data to meaningfully annotate it with tracking identifiers. Under her leadership, she formed a process to ensure data integrity as it was transferred from Europe to the team in Boston, and been effectively used to develop the AI-powered perception system. With her system in place, Sea Machines has identified more than 86 million targets – one of the largest marine data sets in the industry. She has also given Sea Machines’ advanced perception system the ability “see” 20km into the maritime domain to identify even very small objects, a capability that offers safer and more reliable vessel operations.

“I think the work we are doing is harder than that of self-driving cars. The scale of marine targets adds complexity. We see very large, tall vessels right next to tiny buoys, and we are training our system to recognize both in the same frame. And the diversity of the boat types is so much greater than vehicles on the roadway. But it helps to keep it interesting,” Fiona explained. “The current challenge is to continually develop our advanced situational awareness system with the greatest possible accuracy for vessels operating in diverse locations.”

Notably, Fiona recently enrolled in Boston University’s MBA program, a course of study that she hopes will enrich her career and help her overcome common business challenges in the future.

“Whatever I can do to positively contribute to my team, I want to do it,” said Fiona. “We are a motivated group that feels like family. We all work towards the same goals and I really enjoy working alongside my teammates.”