As we celebrate 100 years of the department of electrical and computer engineering at UNB, we are proud to recognize the alumni who built its legacy. Throughout 2026, we will share profiles and stories highlighting the milestones and people who have shaped the department's history.

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Before AI scams and deepfakes became part of everyday conversation, Catherine Huang (MScE’05) was already exploring how to navigate a world where technology doesn’t always tell the truth.   

That belief has guided her across continents and career shifts in one of the fastest‑moving fields in the world — adversarial machine learning, trustworthy AI and AI safety.  

Catherine’s journey began in southern China, where she studied electrical engineering and built an early career in banking. By her late twenties, she was already a manager. But she wanted more. “I wanted to challenge myself… go to a new country and explore.”   

In 2000, she immigrated to Canada with her husband and young son, arriving in Toronto just as the job market collapsed after 9/11. “There [were] no jobs. So, then I decided, okay, I need to go back to school.”   

A phone call that changed everything   

That decision led her to apply to UNB in 2002 to complete her MScE — but not without hiccups. After realizing her application was missing a TOEFL score, Catherine picked up the phone. “I made a very important phone call.” Soon after, she was accepted.    

“We were the first team to deliver the safety features… on mobile devices like Pixel and Samsung.”

At UNB, Catherine started studying biomedical engineering, a field she hadn’t originally planned to pursue. “I didn’t even know what that was, but I got funding to support my family.”   

She leaned into the challenge. After years away from technical studies and adjusting to a new language, country and a totally new research field, she excelled — earning all A-pluses and eventually a three-year fellowship from Natural Sciences and Engineering Research Council of Canada. She quickly built confidence in her abilities.    

Catherine’s research focussed on myoelectric signal processing, helping classify limb movements for prosthetic use. The work would later be widely cited as robotics gained popularity. “We were pioneers in that research.”   

Encouraged by her supervisor, Dr. Kevin Englehart (BScE’89, MScE’92, PhD’99), she transferred directly from her master’s into a PhD in 2003 and received her NSERC funding in 2004.     

Through this work, she began exploring machine learning in ways that would later define her career. “The UNB program actually started my career journey into machine learning and AI… that’s the most inspiring part.”   

A turning point — and starting again   

As her research progressed, Catherine’s life outside the lab was evolving as well. When her husband accepted a job in Portland, Oregon, in 2005, she made the decision to move with her family.   

At the time, she had just welcomed her second child. She transferred her doctoral studies to Oregon Graduate Institute —  which would later merge with Oregon Health & Science University — where she would earn her PhD in biomedical engineering in 2010.   

Before fully transitioning to her new institution, she chose to formally complete her master’s degree at UNB. “I remotely defended my master’s thesis from Portland,” she recalls.  

In Portland, Catherine continued her research in a new environment while raising a young family. Her work expanded into brain-computer interfaces, building directly on the foundation she had established at UNB.   

A different kind of choice   

After completing her PhD , Catherine was offered a postdoctoral position at Harvard Medical School, an opportunity many would consider a defining career step. “I got accepted… the professor assigned my desk and told me, ‘After this, you can be a professor anywhere.’”   

But the reality was more complicated. The position would require her to relocate to Boston while her family remained in Portland. “They said maybe I could take one son… and leave the other with my husband.”    

It was in that moment that the weight of the decision became clear. “On the way in a taxi, I was crying. I had to decline it because of my personal situation.” Instead, she chose to stay in Portland and build her career there. “I said, I’m not going to academia… my family is my top priority.”   

It was a decision that changed her trajectory — but not her impact. “I never regretted [my decision]. It’s just different paths.”    

From research to real-world risk   

Catherine began her industry career at Intel Labs in Portland, where her work shifted from academic research into applied machine learning research to solve real-world problems.    

It was there that she championed an adversarial machine learning program at the Intel Science & Technology Center for Security Computing at UC Berkeley. As she explains, “If I change a couple of pixels… the algorithm will predict if this is a penguin picture… as a frying pan.”   

At the time, this kind of work, now associated with deep fakes, adversarial AI and misinformation, was still emerging.   

At Intel and later McAfee, she worked on problems like detecting malicious websites, identifying scams and strengthening systems against attack. According to Catherine, attackers can manipulate machine learning. “They can poison your training data so that your algorithm will bias to the attacker's interest.”   

What began as a technical challenge quickly revealed broader implications. “These are very dangerous… disinformation can hurt society.” That work would become the foundation for her career in AI safety.    

Protecting people in the age of AI    

Today, Catherine works at Google Safeworks — helping protect users from increasingly sophisticated threats, including deepfakes and AI-powered scams. 

As an area tech lead, she oversees a team to develop on-device safety features for generative AI, designed to prevent harmful or inappropriate content from being generated in the first place. “We were the first team to deliver the safety features… on mobile devices like Pixel and Samsung.” The work brought responsible AI protections directly to millions of users.    

“They can poison your training data so that your algorithm will bias to the attacker's interest.”   

In 2025, Catherine and her team received a Google Tech Impact Award, one of the company’s highest internal awards. She also received two Google Core Tech Impact Awards for content safety in 2024 and 2025. For Catherine, the recognition reinforced something she had long believed. “It showed me… you can still do meaningful, high-impact work.”    

Choosing her own path   

Looking back, Catherine sees her journey not as a straight line, but as a series of choices shaped by curiosity, challenge and responsibility. “I always believed… it’s never too late to learn.”   

From arriving in Canada and starting over, to reshaping her academic path, to stepping away from academia and into industry, each decision required clarity and courage. “I didn’t follow what people expect. I followed what I want[ed].” 

Today, she sees that same spirit reflected in her sons. Her oldest is completing a PhD in computational neuroscience at NYU and moving into a postdoctoral role at Columbia University, while her younger son is studying animation at the California Institute of the Arts.   

For Catherine, it’s a reminder that the path forward isn’t always linear — but it can lead exactly where it needs to. And in doing so, she has helped shape the future of AI — not just by advancing technology, but by helping ensure it is used safely, responsibly and for the benefit of others.