Dr. Chen-Kun Liaw is currently an Orthopedic Professor at Shin Kong Wu Ho Su Memorial Hospital. Since college, he has uniquely blended medicine and computer science, earning a programmer license from the Institute for Information Industry and successfully launching a commercial computer game. While serving as an orthopedic attending physician, his passion for technology led him to obtain a Ph.D. in Computer Science and Information Engineering from National Taiwan University. He later achieved the rank of Ministry-Certified Full Professor at Taipei Medical University, College of Biomedical Engineering. Dedicated to leveraging computer programming to solve complex clinical and workflow challenges, he innovated a comprehensive pooling PCR strategy during the COVID-19 pandemic to drastically enhance testing efficiency. He stands out as a rare interdisciplinary pioneer, seamlessly integrating cutting-edge engineering with advanced clinical expertise.

Defeating Resource Bottlenecks in Mass Screening: Empowering Global Pandemic Surveillance via Free Liaw Pooling Strategies As the world faces an era of continuous pandemic threats, the primary challenge for global health systems remains the initial, rapid mobilization of mass population screening. When time and testing resources are severely limited, sample pooling serves as the only mathematically viable solution to identify infectious cohorts quickly. This presentation introduces two breakthroughs in diagnostic optimization software: "Liaw Improved Hypercube Pooling" and "Liaw Multiple Pooling." Benchmarked as the most efficient pooling architectures currently available, these dual strategies drastically lower the number of test kits required to clear large populations without sacrificing diagnostic accuracy. Driven by a commitment to global health equity, these algorithms are being released entirely as freeware. We provide these accessible, high-efficiency tools to the international scientific community to ensure that no nation is left defenseless against emerging infectious diseases due to supply chain failures.