Postdoc Spotlight: For the Love of Robots

As a postdoctoral fellow at FAU Harbor Branch Oceanographic Institute, Alisa Kunapinun, EngD, said she hopes to improve the efficiency and performance of aquaculture systems through advanced machine-learning techniques.

Kunapinun works with Bing Ouyang, Ph.D., associate research professor in ocean engineering and applied technology, to research how artificial intelligence (AI) might better compress and send data underwater with wireless communication systems, without losing important information during that compression. “In this case, I use AI deep learning in the compression and decompression process because specifically trained AI can know the details and do loss-less compression in the focus area more than other compressors,” she said.

Prior to her work at FAU Harbor Branch, which began in May 2023, Kunapinun earned a master of engineering in mechatronics from the Asian Institute of Technology in Thailand, where she was born and raised. Mechatronics is an interdisciplinary branch of engineering that focuses on the integration of mechanical, electrical and electronic engineering systems.

After earning her degree in 2010, she spent the last decade working in a range of countries, including Thailand, Japan and Taiwan, where she specialized in robotics and vision-guided technology. One of her positions as vice director for Cal-Comp Automation and Industrial 4.0 (Thailand) Co., Ltd., provides robots or software tools to help businesses automate manual processes.

Kunapinun said she realized that she had a knowledge gap when it came to AI and machine learning, so she decided to continue her education. “I love robots and I know that robots need vision and artificial intelligence (AI), so I work hard to let robots be more intelligent,” she said.

In September 2022, she earned a doctorate in engineering in mechatronics also from the Asian Institute of Technology. While there, she worked in the biomedical field, studying ways to better distinguish thyroid lumps from the thyroid gland in the base of the necks in ultrasound images using new algorithms based on a specific type of machine-learning, called generative adversarial network. Creating better tools for detecting and segmenting these lumps can help physicians determine if they are cancerous or not and then follow-up, she said, to track them over time.

For Kunapunin, working with technology and machine-learning at FAU Harbor Branch is the perfect fit to expand her skill set in biomedical engineering.

“Through my varied expertise,” she said, “I hope to help advance the medical world by helping solve world issues like hunger and health concerns, like a cure for cancer.”