WE WELCOME DRS. DENISE AMRAM AND MARTINA OCCELLI AS AFFILIATES OF THE DEPARTMENT OF EXCELLENCE

Denise Amram and Martina Occelli have become official affiliates of EMbeDS in July 2021. 

Denise Amram is currently the Coordinator of the Permanent Observatory on Personal Injury Damages and of the research line ETHOS at the LIDER Lab  – DIRPOLIS Institute, Sant’Anna School. Since 2018, she serves as the Data Protection Officer for both the Sant’Anna School and the Scuola Normale Superiore. She belongs to the steering committees of several top ranked law journals (e.g., Rivista Italiana Medicina Legale e del Diritto in Campo Sanitario, Opinio Juris in Comparatione, Diritto dell'Internet, and GenIUS). She authored and co-authored ~ 110 publications in Italian, English, French and Spanish, including a book and 2 co-editions. Her research interests include fundamental rights protection in the fields of data protection law, family law, tort and contractual liability in a national, European, and comparative perspective. In EMbeDS, she contributes to the project Predictive Justice as a member of the steering committee.

Martina Occelli is a postdoctoral research fellow in Agricultural Economics at the Institute of the Life Sciences of the Sant’ Anna School. She holds a Double Degree Master in Economic Development from the University of Pavia and Hohenheim (DE), and a Ph.D. in Economics from Sant’Anna. Her doctoral research concerned the role of local ecological knowledge in fostering the resilience of marginal rural systems. Her work, published in peer-reviewed journals like Agronomy for Sustainable Development, explores the role of local knowledge in its ecological dimension; from rainfall variability awareness, to soil management ability, she investigates the link among traditional learning, peer learning and resilience outcomes -- which can be climatic, agronomic or crop–related.  Focusing on participatory and interdisciplinary approaches, Martina's postdoctoral research aims at creating new methodologies to merge pedoclimatic and varietal data with local knowledge traits. Local knowledge is difficult to codify and thus to merge with data on climate, data from satellites, etc. Martina combines life sciences and econometric methods to successfully merge local knowledge’s dimensions with these 'hard' data.