Tag: #machine-learning
Back to all newsDr Lan’s latest study collaborated with a veterinary science team to develop a machine learning method for rapid disease detection in companion animals. The research used serum biomarkers to support faster and minimally invasive screening.
For more information please refer to https://doi.org/10.1080/01652176.2026.2617470.
Dr Lan received a Meritorious Research Award in the Young Scholars Innovation Competition organised by the Taiwan Comprehensive University System (臺灣綜合大學系統). His research combined biomimetic propulsion concepts with AI techniques to improve energy efficiency across aerial and aquatic environments, demonstrating the potential of nature-inspired multifunctional propulsion systems.
A graduate student team supervised by Dr Lan, led by Yen-Cheng Chang alongside two fellow members, received a Merit Award (優等獎) in the National Intelligent Manufacturing Big Data Analytics Competition (IMBD, 全國智慧製造大數據分析競賽). Their project applied artificial intelligence and big data techniques to deliver innovative, data-driven solutions with strong analytical performance.
Dr Lan and Dr Lai’s latest study, published in Physica D: Nonlinear Phenomena, introduces a hybrid decision tree approach that reduces flapping flight analysis time by up to 75% while maintaining high accuracy. The method supports faster aerodynamic research and more efficient micro air vehicle development.
For more information please refer to https://doi.org/10.1016/j.physd.2025.134618.
Dr Lan gives a speech entitled ‘Machine Learning in Flapping Flight Transient Acceleration Modelling’ at CSME 2022.
Dr Lan and his team published a study in Drones introducing a neural network approach for estimating transient aerodynamic properties in flapping wing systems. The research supports faster and more efficient analysis of flapping flight dynamics.
For more information please refer to https://doi.org/10.3390/drones6080210.