Inma Tomeo-Reyes

Dr. Inma Tomeo-Reyes is a Senior Lecturer at the School of Electrical Engineering and Telecommunications, University of New South Wales (UNSW), Sydney, Australia. With extensive expertise in signal and image processing, pattern recognition, and machine learning, she contributes significantly to both research and teaching in electrical engineering and biometrics.

Dr. Tomeo-Reyes received her B.E. and M.E. degrees in Telecommunications Engineering from Universidad Carlos III de Madrid (UC3M), Spain, in 2006 and 2008, respectively. In 2010, she earned an M.E. degree in Multimedia and Communications from UC3M, where she also worked as an R&D Engineer for over three years. She completed her Ph.D. in Electrical Engineering at Queensland University of Technology (QUT), Australia, in 2015, followed by a Graduate Certificate in Academic Practice at QUT in 2017.

Her research spans signal and image processing, pattern recognition, and machine learning, with a particular focus on biometrics. Dr. Tomeo-Reyes's doctoral work concentrated on developing techniques to enhance the robustness of biometric systems against security threats. She has made significant contributions to medical image analysis, particularly in white blood cell classification and segmentation, as well as in engineering education research. Her recent publications demonstrate a strong trend toward integrating emerging technologies into engineering curricula and developing effective assessment methods for engineering education, with notable work on online laboratories and the application of AI in engineering education.

• Senior Fellow of The Higher Education Academy (SFHEA), 2020
• Student's Choice Teaching Award (UNSW), 2019
• Vice-Chancellor's Performance Award - Best Learning Experiences (QUT), 2017
• Science and Engineering Faculty PhD Scholarship on Academic Merit (QUT), 2013
• Predoctoral Fellowship for Excellence in Research (Ibercaja Foundation, Spain), 2011

Dr. Tomeo-Reyes is passionate about teaching and supporting students, implementing strategies to improve student engagement and active learning, especially in large first-year courses. Her research in engineering education focuses on applying educational research findings to course design and delivery. She has led projects on online laboratories, teamwork evaluation, and curriculum development that align with industry needs, demonstrating her commitment to preparing engineering students for real-world challenges.

Her work spans multiple research collaborations focusing on biometrics, medical image analysis, and engineering education. She actively contributes to projects related to white blood cell analysis, biometric security, and innovative teaching methods in engineering education, bridging the gap between theoretical knowledge and practical application.