Rate My Professor Geetha Mohan

Dr Geetha Mohan serves as a Lecturer at Curtin University Dubai Campus within the Faculty of Science and Engineering and the Global Curtin portfolio. She earned her PhD in Computer Science and Engineering from VIT University, Chennai, India, with doctoral research centered on enhancing reliability and energy efficiency in wireless sensor networks. In her teaching role, she delivers key undergraduate courses such as Unix and C Programming (COMP1000), Computer Systems (COMP2000), Cloud Computing (CNCO3003), and Capstone Computing Projects, equipping students with foundational and advanced computing skills essential for industry applications.

Dr Mohan's research specializations include artificial intelligence, Internet of Things (IoT), wireless sensor networks, machine learning applications, and computer networking protocols. Her scholarly contributions are evidenced in several peer-reviewed publications. A prominent work is 'CEPRAN: cooperative energy efficient and priority based reliable routing protocol with network coding for WBAN,' published in Wireless Personal Communications in 2021, which has received 40 citations. Other significant papers encompass 'Enhanced Cuckoo Search Algorithm for Energy Efficient Cooperative Communication in Wireless Body Area Networks' (Journal of Advanced Research in Dynamical and Control Systems, 2019), 'Research on the Machine Learning Algorithms on Heart Condition Predictions' (International Journal of Innovative Technology and Exploring Engineering, 2019), 'IoT-Enabled Efficient Solid Waste Management System Towards Building Smart City' (International Journal of Civil Engineering and Technology, 2018), 'Water Borne Diseases Detection Using Biosensor' (International Journal of Advances in Computer and Electronics Engineering, 2017), and 'Towards an Enhanced Efficient Cross Layer Protocol (EECLAP) for Wireless Sensor Networks' (International Journal of Mechanical Engineering & Technology, 2017). Additional research includes 'Dental Caries Segmentation from Orthopantomograms using Optimized DeepLabV3+' (5th International Symposium on Intelligent Computing Systems, 2024) and 'Understanding students’ learning experiences by mining social media data' (IJRET, 2019). These works underscore her impact in developing energy-efficient routing, health monitoring via WBAN, smart city IoT solutions, and AI-driven diagnostics, aligning with contemporary challenges in computing and engineering.