> ## Documentation Index > Fetch the complete documentation index at: https://felimet-hub.jmcores.com/llms.txt > Use this file to discover all available pages before exploring further. # About me: researcher and developer > My background, research interests, and engineering work as a researcher and developer focused on schlieren imaging, machine learning, depth sensing, and developer tooling.

Jia-Ming Zhou 周家銘

National Chung Hsing University · Dept. of Biomechatronics Engineering · Ph.D. Student

## Welcome to Felimet Hub Here I break down setup procedures, open-source workflows and official tooling into my own SOPs, so they can actually be used correctly by an individual. I keep records of how I solve problems and work through trial and error, organizing them into a toolbox that stays useful over the long run. > A valuable technology should not stop at the model or the demo; it should run all the way from sensing and data processing through to deployment and operations. ## Research Areas & Highlights Combining electrical engineering with biomechatronics, solving complex problems through self-directed learning and driving cross-domain applications. Artificial intelligence, computer vision, multimodal sensing, image processing, schlieren optics, mechatronics integration, and visual health assessment of dairy cattle. Working on frontier applications of large language models (LLM), vision-language models (VLM) and Agentic AI, embedding autonomous reasoning, planning and tool-use agents into multimodal sensing, precision livestock and smart agriculture. Integrating visible light, infrared (thermal), depth imagery and other modalities to enhance analysis and understanding across scenes and objects. Using differences in refractive index to visualize otherwise invisible airflow, sound waves and pressure changes, enabling airflow-speed prediction and temperature monitoring. Integrating multimodal image processing with AI to build an Agentic-AI, non-contact dairy health monitoring platform for lameness, heat stress and pre-calving alerts. Combining IoT sensing, image recognition and AI decision-support to build an integrated crop-monitoring and automatic anomaly-alert system. ## Tools & Skills

## Get in Touch } href="https://github.com/felimet" /> } href="https://www.linkedin.com/in/jiamingzhoufelimet" /> } href="https://orcid.org/0009-0001-5781-0624" />