Spatial Ecology course trainers
Giuseppe Amatulli, PhD
Geo-data Scientist, Spatial Ecology; g.amatulli at spatial-ecology.net
Giuseppe is the lead scientist at Spatial-Ecology for data analysis and product development. He is an accredited GIS data expert with deep expertise in spatial modelling and coding with open source software for environmental applications. His current focus is on hydrological modelling at a global scale, in addition to researching species distribution under climate change scenarios.
Giuseppe has a breadth of experience in GIS technologies, remote sensing, informatics, cluster and parallel computing, and statistics. He is proficient in applying complex modelling techniques to automate the analysis of high-resolution data under Linux-based platforms.
Giuseppe holds a research scientist position at Yale University in the US, and has previously worked at the European Commission Joint Research Centre, and at the University of Zaragoza. His coverage of the forestry and environmental sectors entails wildfire occurrence risk and pattern recognition, ecological shifts under climate geo-engineering scenarios. Notably, he runs geocomputation training courses worldwide on the latest data programming techniques.
Giuseppe has a PhD from the University of Basilicata in Italy, an MSc in Geo-Information Science from Wageningen University, and MSc in Forestry from Bari University. His time away from coding is spent leading adventure trips in remote locations, which involve canyoning, caving, rafting and hiking.
Longzhu Shen, PhD
Scientific Advisor, Spatial Ecology; l.shen at spatial-ecology.net
Longzhu is a mathematical modeller with a specialisation in quantum mechanics and statistical learning algorithms. At Spatial Ecology, he is leading the development of water chemistry analytics by integrating water quality assessment into a global hydrological model using machine learning techniques.
Longzhu’s breadth of experience ranges from spatial modelling for charting nutrient distribution in freshwater to the development of algorithms to engineer chemicals with a lower toxicity potential. He is proficient in electronic structure calculations, chemical reaction mechanism investigations, and multiscale modeling for complex biological systems.
Longzhu has previously worked as research scientist position at Cambridge University in the UK, where he was developing mathematical models to predict the molecular evolution of prominent viruses, which can be used to advance vaccine design.
Longzhu has a PhD in Chemistry from Carnegie Mellon University, and did his post-doctoral research in toxicology and molecular design at Yale University. In his spare time, he enjoys hiking, skateboarding and traveling.
** Antonio Fonseca, M.Sc. **
Antonio is a machine learning researcher working at the intersection between Computational Neuroscience and Deep Learning. He is currently interested in using Deep Learning to model brain dynamics and what it can tell us about cognition and behavior.
Antonio’s expertise includes robotics (software and hardware development), signal processing, computational vision, behavioral neuroscience and deep learning algorithms. More specifically, he is an expert in applying and developing machine learning frameworks to complex problems.
Antonio worked on software development for mining robots and solutions for banking companies. Most recently, he worked on applying machine learning and signal processing techniques to investigate behavior in developing animals, which has important implications for studies involving genetic disorders and how to treat them.
Antonio is a Neuroscience Ph.D student at Yale University, obtained a bachelor’s degree in robotics engineering and a master’s in microelectronics. When he is not thinking about biological or artificial neuronal networks, Antonio enjoys rock climbing and hiking (most often doing both on the same trip).