Rate My Professor Darwin Gouwanda

Darwin Gouwanda is an Associate Professor in the Department of Mechanical Engineering within the School of Engineering at Monash University Malaysia. He earned his Bachelor’s degree in Mechatronics Engineering and PhD in Biomedical Engineering from Monash University. His research centers on human motion analysis in sports and daily activities using wireless wearable sensors, as well as the development of rehabilitative and assistive technologies. He heads the Biomechatronics Lab, where projects include characterizing gait parameters with inertial measurement units, designing ankle rehabilitation robots, and developing hand and arm assistive devices.

Throughout his career, Gouwanda has advised the Monash University Malaysia student team at the Shell Eco-marathon Asia, leading to championship wins in the GTL Prototype category (2014), CNG Prototype (2016), and Global Autonomous Programming Challenge (2021), along with awards such as the Tribology Award (2014), Spirit of the Shell Eco-marathon Award (2025), and Data and Telemetry Award (2026). He has held leadership positions in the IEEE Engineering in Medicine and Biology Society (EMBS) Malaysia Chapter, including Vice Chair (2015), Secretary (2016), and Chapter Chair (2023–2025), and chairs the biennial IEEE International Conference on Biomedical Engineering and Sciences (IECBES). Notable awards include Best Paper Awards for "Investigating running gait using a shoe-integrated wireless inertial sensor" (2015) and "Wearable hand exoskeleton for activities of daily living" (2018), a Bronze Award at the International Invention Innovation & Technology Exhibition (2020) for "Smart instrumented shoe," and Gold Awards at the Malaysia Technology Expo for "BuoyScout" (2023) and "WindChaser" (2024). His scholarly contributions encompass 92 research outputs, including recent publications such as "A focused review on upper and lower limb joint torque estimation via neural networks" (2025, Pertanika Journal of Science and Technology), "A minimalist wireless instrumented shoe design to measure foot clearance in human gait" (2025, Measurement), and "Integrating deep learning in stride-to-stride muscle activity estimation" (2025, Scientific Reports).