About Rosario Lombardo
Rosario received cum laude his BSc and MSc in Computer Science from the University of Pisa and earned his PhD in Bioinformatics from the University of Verona. He holds a Global MBA in Consulting Management from SP Jain School of Global Management.
He is currently Head of Bioinformatics at The Microsoft Research - University of Trento. There he supervises several research projects in collaboration with pharma and nutrition companies, driving the innovation towards industrial scientific research. Among his research interests are Deep Learning and Text mining, enabling technologies for complex Quantitative Systems Pharmacology mathematical models such as Visual modeling, and High-Performance Simulations. Rosario mentored several intern/BSc/MSc/PhD students and was coach to a number of colleagues. With over 15 years' experience in business, scientific and technological consulting, he has managed cross-functional, international projects in Pharma, Nutrition and Bank industries.
Hunting for foods that can help infants build strong immune systems would traditionally have researchers trial potential foods with infants, then do blood analysis to see if there were positive benefits. We describe a technique that dramatically narrowed the efforts required in identifying potential weaning foods to test a boost of infant immunity in clinical trials.