Organizers
Yuanxi Fu is a PhD student in the School of Information Sciences at the University of Illinois at Urbana-Champaign. She received her MS in bioinformatics (2021) and PhD in chemistry (2015) from the University of Illinois at Urbana-Champaign and BS in chemistry from Nanjing University in China (2008). Her area of research is argumentation in science with an emphasis on theoretical and conceptual innovations.
Dr. Sarah Bratt is an Assistant Professor at the University of Arizona School of Information (iSchool). She holds a B.S. in Philosophy from Ithaca College and M.S. in Library and Information Science with a Data Science certificate from Syracuse University. Her research lies at the intersection of scholarly communication, research data management, and science of science. The overarching goal of her research is to understand and design for long-term research data sustainability and actionable science policy. Her research has been published in Quantitative Science Studies (QSS), Journal of Informetrics, and Scientometrics. She was a Research Fellow at the Laboratory of Innovation Science at Harvard (LISH), a Teaching Fellow at the iSchool Inclusion Institute (i3), and has received several awards including the PhD prize in Information Science & Technology from Syracuse University and honorable mention as a 2022 Better Scientific Software (BSSw) Fellow.
Harlin Lee is an Assistant Professor at the School of Data Science and Society (SDSS) at University of North Carolina, Chapel Hill with secondary appointments in the departments of mathematics and computer science. Previously, she was a postdoc at UCLA Applied Math, and received her PhD in Electrical and Computer Engineering and MS in Machine Learning from Carnegie Mellon University in 2021. She got her BS and MEng in Electrical Engineering and Computer Science from MIT in 2016 and 2017, respectively.
Her research focuses on learning from high-dimensional data supported on structures such as graphs, networks or low-dimensional subspaces, motivated by applications in health care and social science. She has been recognized with Rising Stars in Data Science (2022), Rising Stars in Computational and Data Sciences (2022) and Carnegie Mellon University Electrical and Computer Engineering Outstanding Woman in Engineering (2021).
Satyaki Sikdar is an Assistant Professor at the Department of Computer Science at Loyola University Chicago. Previously, he was a postdoc at Indiana University, and received his PhD in Computer Science from the University of Notre Dame in 2022.
His research interest is understanding the fundamental mechanisms that drive complex, interconnected systems using tools at the confluence of AI, network science, and computational social science. His current research is focused on analyzing large-scale bibliometric data from scientific publications using generative models and embeddings. His work has been published in Nature Human Behaviour, IEEE Transactions on Knowledge and Data Engineering, and Scientific Reports.
Liubov Tupikina Dr. Liubov Tupikina, a research scientist at Bell Labs, combines expertise in mathematics and theoretical physics to study network dynamics, time series analysis, and AI. Following her PhD from Humboldt University of Berlin and research positions across European and South American universities, she now focuses on network robustness, stochastic processes, and embedding techniques. As a principal organizer of Embed-Days and leader of its mathematics track, she champions mathematical excellence in the field. Her current work spans from survivability theory to applications of collective intelligence in responsible AI development.
Dongyi Wang is a PhD candidate in CWTS at Leiden University. He received his bachelor’s(2021) and master’s degrees(2023) in Information Management from Sun Yat-sen University. Wang’s research interests include quantitative science studies as well as science communication with a focus on science communication among occupations.
Akrati Saxena Akrati Saxena is an Assistant Professor at the Computer Science and AI department of the Faculty of Science at Leiden University. Her research interests include Social Network Analysis, Complex Networks, Computational Social Science, Data Science, and Fairness. Her current research is focused on understanding inequalities in complex networks and algorithmic fairness in network and data science. She is interested in understanding and modeling the impact of affirmative actions and international policies on the collaboration network.
Program Committee
Jian Du, Peking University
Charles Gomez, University of Arizona
Vincent Traag, Leiden University
Lucila Gisele Alvarez Zuzek, Bruno Kessler Foundation