Luca Giancardo

Dr. Luca Giancardo is an Associate Professor at the Center for Precision Health, School of Biomedical Informatics (SBMI), University of Texas Health Science Center at Houston (UTHealth) with co-appointments at the McGovern Medical School and the Institute for Stroke and Cerebrovascular Diseases, UTHealth. He is a computer scientist by training with extensive experience in image/signal analysis and machine learning applied to biomedical sciences. Before arriving at SBMI, he was a research fellow at the Massachusetts Institute of Technology, leading the technology development of a research endeavor to detect early signs of Parkinson's via the daily interaction with electronic devices. This work allowed him to be the recipient of funding from Michael J. Fox Foundation and win the 2015 Singapore Challenge. Between 2011 and 2013, he was a Postdoctoral Fellow at the Italian Institute of Technology where he worked on new tools for analyzing mice behaviors as well as analysis methodologies for highly-dimensional diffusion tensor imaging data. During his PhD at the Oak Ridge National Laboratory and Université de Bourgogne he worked on many different retina analysis algorithms to automatically screen diabetic patients for retinopathy and macular edema. The result of his work is currently been translated to industry and various prizes were awarded to his research team; the R&D Award by R&D Magazine, ORNL Award Excellence in Technology Transfer, ORNL Significant Event Team Award and FLC South-east Regional Award Excellence in Technology Transfer. Luca Giancardo received his BSc from the Southampton Solent University where he was awarded the British Computer Society prize for Best Student in his final year and the David Nicholas Award for Innovation for his computer vision based computer interface in 2005. After working in R&D for a year for Real Time Tracking ltd., an English company developing vision-based systems for sporting events he was selected for the first VIBOT Erasmus Mundus program. The VIBOT is research oriented Computer Vision and Robotics MSc delivered by three different European institutions: Heriot-Watt University Edinburgh (UK), Universitat de Girona (Spain) and Université de Bourgogne (France). For his master's thesis he started to work with the Oak Ridge National Laboratory (USA) where he developed an algorithm to detect the quality of retina images acquired by fundus cameras (an invention disclosure was obtained). During his PhD at the Oak Ridge National Laboratory and Université de Bourgogne he worked on many different retina analysis algorithms to automatically screen diabetic patients for retinopathy and macular edema. In 2011, he started a postdoctoral fellowship with the Istituto Italiano di Tecnologia (Italy) where he worked on automated analysis of the brain connections in diffusion MRI and on vision-based systems to track and classify small animal behaviors. In 2013, he was appointed as a research fellow at the Massachusetts Institute of Technology, acting as co-PI on three biomedical engineering projects: early detection of Parkinson's Disease in the general population, wearable scoliosis monitoring devices and hydration monitoring in the elderly.