The workshop aims to raise awareness about the importance of human-centric complex systems science and digital humanism and promote their adoption in technology and system design.
We hope to achieve that by highlighting the works of complex system scientists, who focus on analyzing and designing complex systems in a way that considers their impact on people and communities. Together with our industry partner Leiwand AI, we will highlight local Austrian companies that ensure their technology and digital systems align with human values, such as well-being, dignity, and autonomy.
We hope to attract passionate early-stage postdocs, Ph.D. students, and master students in the fields of Complex systems, Computer science, Data Science, Computational Social Science, and Humanities and Social sciences.
Join us in our mission to create a human-centric future and develop a roadmap providing strategic guidelines on how to realize digital humanism's vision and integrate its ideals into society.
Fariba Karimi is the organizer of the “Complexity Science meets Digital Humanism campaign” and will be the host of this spring workshop at CSH.
Fariba leads the Complexity Science Hub’s computational social science team. In addition, she has been an assistant professor at TU Wien since January 2023.
Fariba’s research focuses on computational social science, the emergence of biases and inequality in networks and algorithms, and modeling human behavior. Her recent research revolves around the topics of the visibility of minorities in social networks, the impact of network structure on ranking and recommender algorithms, and disparities in academia and its impact on under-represented groups. She combines statistical analyses of large datasets of online interactions with computational models, agent-based modeling, and network analysis.
Fariba received a PhD in physics and computational science from Umea University, in Sweden, in 2015 and was a PostDoc at GESIS – Leibniz Institute for Social Sciences, in Germany. In 2023, she received the Young Scientist Award from the German Physical Society for her research on inequality in complex networks.
Anirban Chakraborti is currently the Dean of Research & Development at BML Munjal University, and a professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University. He graduated with a master's in physics from the University of Calcutta, obtained his PhD in physics from Jadavpur University, and completed a Habilitation à Diriger des Recherches (HDR) in physics at the Université Pierre et Marie Curie. He was registrar at Jawaharlal Nehru University, New Delhi; associate professor at the Chair of Quantitative Finance at Ecole Centrale Paris; and lecturer in theoretical physics at Banaras Hindu University, Varanasi. His postdoctoral tenures were at Brookhaven National Laboratory, USA, and Helsinki University of Technology, Finland (now known as Aalto University). For his pioneering work in econophysics, he was awarded the Young Scientist Medal by the Indian National Science Academy in 2009. Recently, he was elected a Fellow of The World Academy of Sciences (TWAS-UNESCO).
Márton Karsai is an associate professor at the Department of Network and Data Science at the Central European University (CEU). He is the director of the Social Data Science MS program at CEU, and he leads the Computational Human Dynamics team. He is a network scientist with research interest in human dynamics, computational social science, and data science, especially focusing on heterogeneous temporal dynamics, spatial and temporal networks, socioeconomic systems and social contagion phenomena. He is an expert in analysing large human behavioural datasets and in developing data-driven models of social phenomena.
Matteo Marsili is a theoretical physicist with research interests ranging from non-equilibrium statistical physics and critical phenomena to quantitative economics and finance, high dimensional (featureless) statistical inference and learning, systems biology and neuroscience. He earned his PhD from the Scuola Internazionale Superiore di Studi Avanzati (SISSA) of Trieste in 1994. After postdoctoral positions in Manchester University, Fribourg University and SISSA, he first joined the Istituto nazionale per la fisica della materia (INFM) as a researcher and later the Abdus Salam International Centre for Theoretical Physics (ICTP). He is interested in understanding how collective behaviour results from the interaction of simple units, be them particles in physics, neurons in a brain tissue or traders in financial markets. He exploits techniques that have been developed in statistical physics to unveil the "un-intended consequences" of interdependencies in other domains of life sciences.
Elisa Omodei is an assistant professor at the Department of Network and Data Science at the Central European University (CEU). She holds a BSc and a MSc in physics from the University of Padua and Bologna, respectively, and a PhD in applied mathematics for the social sciences from the École Normale Supérieure of Paris. She carried out her postdoctoral training at the Rovira and Virgili University in Tarragona, Spain. She then spent over four years at the United Nations, first at UNICEF's Office of Innovation in New York and then at the UN World Food Programme in Rome. In her research, she explores how complexity and data science can help us address the needs of the most vulnerable populations and monitor the UN Sustainable Development Goals. She also served as Vice-President Secretary of the Complex Systems Society from 2018 to 2021.
Erich Prem is a researcher at the Institute of Philosophy, University of Vienna. He is also chief RTI strategy advisor and CEO of eutema GmbH. He is an internationally renowned expert in research and innovation strategy with more than two decades of work experience in research and innovation management and Research, Technology Development and Innovation (RTDI) policy. Prem is a certified managerial economist and works in AI ethics, research politics, and innovation research and strategy. He was a guest researcher at the Massachusetts Institute of Technology (MIT). He received his Dr. phil. (epistemology) from the University of Vienna, his Dr. tech. from TU Vienna where he also completed his master's in computer science (Dipl. Ing). He is a lecturer in Digital Humanism at TU Wien and in Data Ethics at the University of Vienna. He received his MBA in general management from Donau University.
Gertraud Leimüller is Co-founder and CEO of leiwand.ai and CEO of winnovation, one of the first open innovation consultancies in Europe, which she founded after her studies at Harvard University and the Massachusetts Institute of Technology. As a leading open innovation expert and graduate of Vienna University (Dr.rer.nat.) she has been successfully transforming national and international organizations from the private and public sectors for more than 15 years. Gertraud serves as an evaluator in European innovation programs and shares her knowledge as a book author, columnist, and university lecturer.
Ivona Krchova is a senior AI researcher at MOSTLY AI, a startup focused on building the synthetic data generator engine. In addition to developing an internal model, she explores new ideas to improve products. Krchova has also gained valuable experience working as a consultant at Ernst & Young and as an analyst at an international analytical hub in the energy industry. She earned her degree in Probability, Mathematical Statistics, and Econometrics from Charles University in Prague.
Lluís Danús is a researcher at the Science and Engineering of Emergent Systems laboratory (SEES:lab) at Universitat Rovira i Virgili (URV). A physicist by training, his research interests lie in applying network science, information theoretical approaches, and large-scale data analysis to the study of complex social dynamics driving science production. His primary research focus is to investigate how different research environments influence science production. Specifically, he has conducted research on how gender influences the way early-career faculty adjust their research portfolio in new research departments. Additionally, he has also studied how developing science in different sociocultural settings results in distinct collaboration structures among prominent scientists, which ultimately affects their scientific output. His research findings have provided valuable insights into science production dynamics and have implications for science policy and management.
Maria del Rio-Chanona has been a James S. McDonnell Foundation postdoctoral fellow at the Complexity Science Hub since June 2021. Maria has a PhD in mathematics from Oxford University, where she was part of the complexity economics group of the Institute for New Economic Thinking, Oxford Martin School. She has worked alongside international policy organizations, including the International Monetary Fund and the International Labour Organisation. Maria’s research draws from network science, natural language processing, as well as agent-based modeling and focuses on labor economics, the future of work, green transition, and the economic impact of the Covid-19 pandemic. Since December 2021, she has been a JSMF postdoctoral fellow at Harvard Growth Lab as well.
Peter Klimek is faculty member of the Complexity Science Hub. Drawing from his expertise in complexity science, data science, statistics and physics, his research aims to improve our understanding and ability to predict complex socio-economic systems, ranging from human disease over healthcare systems to economic and financial systems. Peter and his research team developed prediction and stress-test models for how people acquire more and more chronic disorders as they age, how healthcare systems cope with changes in their workforce, and how shocks disrupt economic and financial markets. He invented a novel statistical test to detect signs of electoral fraud and was the first to mathematically prove that governments are bound to become ineffective over time. He authored a textbook on the Theory of Complex Systems (together with Stefan Thurner and Rudolf Hanel) and operated a model used by the Austrian government to forecast the Covid-19 epidemics in Austria. Peter is also director of the Supply Chain Intelligence Institute Austria (ASCII) and holds an associate professorship at the Medical University of Vienna.
Dániel Kondor joined the Complexity Science Hub as a PostDoc in May 2021. Before that, he worked at the Senseable City Lab at MIT and SMART FM in Singapore. He earned a PhD in physics with a focus on network and data science from the Eötvös Loránd University in Budapest in 2015. Dániel has worked with diverse topics that focus on the analysis of large-scale geographically embedded phenomena, including the study of human mobility in various contexts. His current research focuses on large-scale, agent-based models of interactions among historical societies. His research interests include data-driven and agent-based modeling of complex social, economical, and technological phenomena.
Rafael Prieto-Curiel has been a postdoctoral research fellow at the Complexity Science Hub since May 2022. Before that he was at the Mathematical Institute of the University of Oxford/Centre for Advanced Spatial Analysis at University College London, working on urban dynamics at the Peak Urban project. He has a master’s degree in statistics and a PhD degree from University College London UCL in maths and security and crime. Rafael was director of strategic analysis at the Emergency Attention Centre of Mexico City where he worked on crime forecasting and police and resources allocation. At CSH, he works on mobility, migration, urban dynamics, and a demographic analysis of African cities.
Alexandra Ciarnau joined DORDA law firm in 2016 and co-heads the Digital Industries Group. She is specialized in IT, IP and data protection. In this context she advises national and international clients on innovative digitalization projects in the areas of artificial intelligence, virtual reality, blockchain and web3. Alexandra is further a board member of Women in AI Austria, where she focuses on policy work shaping the regulatory landscape to enable trustworthy AI business models and products. In addition, she is the author of numerous articles, co-author of books and lecture at universities.