Pao Tai Lin, Ph.D., began his academic journey pursuing dual undergraduate studies in chemistry and electrical engineering, before discovering his true calling in using optical sciences for water quality monitoring.
After earning his master’s degrees in chemistry and optics, Lin went to Northwestern University in Evanston, Illinois, to pursue his Ph.D. in materials science. During his time at Northwestern, Lin began to focus on device design, fabrication and application.
“This initial emphasis was what connected and sparked my research in optical science,” Lin said.
Knowing that optical sensors are an effective measurement tool but usually quite large, he began researching miniaturizing and optimizing these instruments.
“With my training in device fabrication, this was a new opportunity for me to use those skills and that knowledge,” Lin said.
In 2015, after his postdoctoral studies at Harvard and MIT, Lin joined Texas A&M University and today is an associate professor in both the Department of Electrical and Computer Engineering and the Department of Materials Science and Engineering. His research lab studies mid-infrared integrated photonics and remote Sensing (MiPRoS), and applications of those technologies in environmental and health fields.
Lin has used his background in chemistry throughout his research and development of optical sensors that can achieve real-time environmental detection when performing measurements.
“Being able to understand the biochemical processes occurring while the sensors are operating is why my framework in chemistry proves incredibly useful in my research,” Lin said.
Present research
Currently, Lin is working with his research lab of graduate and undergraduate students to create a chip-scale optical sensor for in-field detection in water monitoring.
In 2023 he was named a Texas Water Resources Institute Faculty Fellow, receiving federal funding to support his research.
“My vision in creating next-generation optical sensors for water pollution detection is creating devices that are both tiny and smart, designs that utilize machine learning and artificial intelligence,” Lin said.
Through this, his research group is using machine learning to aid the design of the water quality optical sensor device.
“The goal is to create a more efficient and accurate way to monitor water and machine learning is allowing us to quickly analyze this data,” Lin said.
Steering the future of research
Lin enjoys helping graduate engineering students use both their existing skills and new ones.
“I initially give them two research areas: one that is in their background already, and then another that is more challenging or stretching for their current skills,” Lin said.
He noted that it is important for these students to explore beyond basic steps, into more advanced research. Lin also encourages teamwork with his students and emphasizes that everyone has their unique capability and expertise to contribute.
“Every student has their strengths," he said. "For example, some students are highly thoughtful in organizing research plans, some students are very innovative, and some are skilled in engineering materials and devices. So, our lab group is like a small community, where each can collaborate and contribute to the team."
Above all, Lin urges his students to have the mindset that they have great potential to make contributions to science, engineering, society and humanity.
