Our Team
Lecturer and Co-organizer: Santo Fortunato
Santo Fortunato is a Professor at the Luddy School of Informatics, Computing, and Engineering at Indiana University. Previously, he was a professor of complex systems at the Department of Computer Science at Aalto University, Finland. Prof. Fortunato got his Ph.D. in Theoretical Particle Physics at the University of Bielefeld In Germany. His focus areas are network science, especially community detection in graphs, computational social science, and the science of science. His research has been published in leading journals, including Nature, Science, Nature Physics, PNAS, Physical Review Letters, Physical Review X, Reviews of Modern Physics, and Physics Reports, and has collected around 50,000 citations (Google Scholar). His single-author article “Community Detection in Graphs” (Physics Reports 486, 75-174, 2010) is one of the best-known and most cited papers in network science. Fortunato received the Young Scientist Award for Socio- and Econophysics 2011, a prize given by the German Physical Society, for his outstanding contributions to the physics of social systems. He is a Fellow of the Network Science Society (2022) and the American Physical Society (2022). He was the Founding Chair of the International Conference of Computational Social Science (IC2S2), which he first organized in Helsinki in June 2015. He was the Chair of Networks 2021, the largest-ever event on network science, a historic merger of the NetSci and Sunbelt conferences. He is the author of the book “A First Course in Network Science” by Cambridge University Press (2020), the most accessible textbook on the new science of networks.
Co-organizer: Michelle Girvan
Michelle Girvan is a Professor of Physics at UMD and also serves as Vice President of the Network Science Society. Girvan’s primary expertise involves applying techniques from dynamical systems and statistical physics toward the study of complex networks, with application to biological and technological systems. Girvan’s seminal research papers on detecting and evaluating modularity in networks include the third most cited paper ever published in PNAS and the most cited paper ever published in Physical Review E. Girvan’s recent work explores how the dynamical and connectivity features of artificial neural networks influence their ability to process information, especially in the context of reservoir computing. Girvan is also a member of the External Faculty at the Santa Fe Institute, as well as a Fellow of the American Physical Society and the Network Science Society.
Hands-on Session Instructor: Satyaki Sikdar
Satyaki Sikdar is an incoming Assistant Professor of Computer Science at Loyola University Chicago. He is a postdoctoral fellow at the Luddy School of Informatics, Computing, and Engineering at Indiana University, where he works with Santo Fortunato. He holds a Ph.D. in Computer Science from the University of Notre Dame. His research is at the confluence of network science, machine learning, and computational social science. His work has been published in leading venues such as IEEE TKDE, Scientific Reports, IEEE ICDM, and ACM WSDM.
TA: Ana Elisa Dellamatrice Barioni
Ana is a Ph.D. student at the Physics and Astronomy department of Northwestern University and a member of the Center of Network Dynamics, working with prof. Adilson Motter. Her research focuses on studying the stability of synchronized states of coupled second-order systems and the role of diversity in enhancing stability. Systems of interest for her projects are coupled autonomous vehicles, coupled lasers, and brain networks.
TA: Daniel Kaiser
Daniel is a Ph.D. candidate at the Luddy School of Informatics, Computing, and Engineering at Indiana University with Filippo Radicchi. His research focuses on the reconstruction of multiplex networks from monoplex, aggregated observations. Other projects include community detection and walk dynamics on hypergraphs, ranking algorithms, and uses of information theory in network clustering.
TA: Fatemeh Sadat Fatemi Nasrollahi
Fatemeh is a postdoctoral fellow at the Luddy School of Informatics, Computing, and Engineering at Indiana University, currently working with Professor Santo Fortunato. She received her Ph.D. in Physics from Pennsylvania State University. Her interdisciplinary research involves the use of network science in biology and ecology; specifically, she implements network science methods to recover meaningful biological implications from data. Her work has been published in well-known physics and multidisciplinary journals, such as Physical Review and Scientific Reports.
Alessandra is a postdoctoral researcher in the MOBS Lab at the Network Science Institute (Northeastern University). Her current research mainly focuses on the analysis of socio-technical systems by means of network models and machine learning, from human mobility to online debate. She received her Ph.D. in Computer Science from the University of Turin, during that period she was also a fellow of the Accelnet Multinet Program.
TA: Sara Venturini
Sara Venturini is a postdoctoral fellow at the MIT Senseable City Lab at the Massachusetts Institute of Technology. Sara earned a Ph.D. in Computational Mathematics in 2023 from the University of Padova, where she started her academic career with a Bachelor’s and Master’s in Mathematics. She won a fellowship within the AccelNet-MultiNet program, which allowed her to visit Indiana University in Bloomington in 2022. Currently, she is interested in combining her computational and applied mathematics background with her passion for complex networks in real-world social science applications. Sara’s research interests include higher-order networks, optimization methods, machine learning, and the science of science.