Phoenix Huang (PhD 2011–2014) researched multiclass object classification and hierarchical recognition systems, advancing computer vision techniques for large-scale underwater video analysis. He is now an AI Architect, designing enterprise-scale AI systems. PhD start and end years 2011 - 2014 What was your PhD research about? My PhD research focused on multiclass object classification and hierarchical recognition systems, particularly for identifying and analyzing marine species from large-scale underwater videos. I developed algorithms that improve classification accuracy and reliability under real-world, noisy conditions, work that also advanced computer vision techniques for ecological monitoring and data annotation. What motivated you to undertake doctoral study? I was motivated to pursue my PhD by a desire to deepen my understanding of computer vision and machine learning, and to contribute new methods that connect research with real-world applications. The opportunity to study at a top-tier university and work with leading experts inspired me to take on the challenge and push the boundaries of what technology can achieve. What was a highlight (one or several) of your time as a doctoral researcher? One of the highlights of my doctoral research was having my work on multiclass object classification and hierarchical recognition published at leading computer vision conferences such as ICCV. It was rewarding to see my research recognized by the community and to collaborate with talented peers on advancing large-scale visual understanding. What challenges did you face, and how did you overcome them? One of the main challenges I faced was collecting and managing large amounts of underwater image data for training and evaluation. Our team addressed these challenges by building efficient collaboration workflows, automating parts of the data acquisition process, and maintaining clear, consistent communication with international partners. What are you doing now career-wise, and how did your PhD prepare you for it? I’m currently an AI Architect, where I design large-scale AI systems that power the company's platform. My PhD work on multiclass object classification and hierarchical recognition gave me a solid foundation in building reliable, scalable machine learning models: skills that now help me architect advanced multi-agent and deep learning systems for real-world enterprise applications. What’s one key skill or mindset you developed during your PhD that you still rely on today? One key mindset I developed during my PhD is systematic problem-solving: learning to break complex challenges into smaller, testable components. That approach continues to guide my work today. What advice would you give to someone considering a PhD in Informatics? My advice would be to stay curious and patient: a PhD is less about quick results and more about developing the ability to think deeply and persist through uncertainty. Surround yourself with peers who challenge and inspire you, and remember that research is as much about collaboration and resilience as it is about innovation. Is there anything else you’d like to share with prospective students or the wider community? Enjoy the process of discovery; it’s a rare time in your life when you can explore ideas purely for the sake of learning. This article was published on 2025-12-11
