In an era of rapid technological advancement, Artificial Intelligence (AI) has permeated every facet of our lives. Professor Chun-Rong Huang, the current Director of the Institute of Multimedia Engineering at National Yang Ming Chiao Tung University (NYCU), has long dedicated himself to medical imaging and AI research. His career is a testament to the power of interdisciplinary collaboration and a relentless academic spirit.

Finding Direction Amidst Uncertainty: From Electrical Engineering to Computer Science

Reflecting on his student days, Professor Huang admits to experiencing a period of "existential fog" common to many high schoolers. In an age before the internet and university expos, he chose Electrical Engineering based on a senior's simple pitch: "You'll learn things completely different from high school."

While studying at National Cheng Kung University (NCKU), he explored electronics and IC design but discovered a deeper passion for Computer Science and software development. This curiosity led him to join Professor Pau-Choo Chung's lab, focusing on AI in medical imaging. He realized then that this technology wasn't just intellectually stimulating—it had the tangible power to save lives.

An Engineer in the Medical School: A Year of "Clinical Hardship"

Professor Huang's research is defined by its refusal to stay confined to the lab. During his graduate studies, a bout with H. pylori led him to meet Dr. Bor-Shyang Sheu at NCKU Hospital. The doctor issued a visionary challenge: Could AI identify H. pylori in endoscopic images?

Dr. Hsu's advice was blunt: "To teach the AI to see, you must first learn to see it yourself." For two years, Professor Huang stepped out of his comfort zone as an engineer, spending every Monday in the endoscopy suite learning to diagnose gastric diseases alongside clinicians. This immersion allowed him to speak the "language of medicine," eventually leading to publications in top-tier medical journals and earning the respect of the healthcare community.

Strengthening the Core: Refining AI Algorithms at Academia Sinica

Seeking to broaden his horizons beyond NCKU, Professor Huang moved to Taipei to work under Professor Chu-Song Chen at Academia Sinica. During his eight years there, he shifted his focus from specific applications to the fundamental logic of Computer Vision and Machine Learning.

His academic prowess is reflected in his record: 21 projects for the Ministry of Science and Technology and the Ministry of Education, along with prestigious honors like the Future Tech Award. Yet, despite these accolades, he felt a calling toward a different mission: the transmission of knowledge.

Education First: Combatting Anxiety in the AI Era

Professor Huang eventually transitioned to a faculty position, driven by a desire to interact with students. Citing Han Yu's On Teaching, he believes a teacher's primary role is "transmitting the Way" (Chuandao)—guiding students toward their life's purpose.

To students anxious about AI's ability to write code, he offers a grounded perspective. He personally mentors his students through the logic of their theses, word by word. "AI can produce flashy text, but it is often contradictory and lacks depth," he explains. "Human value lies in logical thinking and the power of explanation." He trains students not just to use AI, but to master it as a logical tool.

The Challenge of "Black Box" AI in Medicine

In clinical settings, the "unexplainability" of AI is a major hurdle. Professor Huang shares an example of a model diagnosing gallstones from CT scans. While the model was accurate, further investigation revealed it was focusing on areas outside the human body or unrelated organs to reach its conclusion.

"That is terrifying for a doctor," he notes. Consequently, his team focuses on Reliable and Explainable AI that can pinpoint exactly why a diagnosis was made. He maintains that true interdisciplinary research requires "learning the other's language" to design task-specific models that solve real-world clinical problems.

Beyond Brilliance: A Call for Empathy

In his lab, Professor Huang keeps a 16-character motto gifted by Researcher Mark Liao: " Every job is a self portrait of those who did it. Autograph your work with quality."

While he praises the brilliance of the students at NYCU, he offers a gentle reminder: Empathy is as important as excellence. "Because these students are so gifted, their actions have a significant impact on others," he says. "If they can practice more empathy and think about the collective good, they will be a far greater asset to the nation and society."

This commitment to social responsibility is perhaps what keeps Professor Huang's research warm, even in the cold, analytical world of AI development.