Knowledge Lab

Alexander Belikov

Postdoctoral Scholar, University of Chicago

Alexander Belikov is interested in applications of machine learning and natural language processing to social phenomena and texts. Of particular interest to him are the relation extraction and the convergence of social consensus, which can be studied in conjunction. 
Alexander received his B.S. and M.S. from the Moscow Institute of Physics and Technology and his PhD in physics from the University of Chicago.
Prior to joining the Knowledge Lab, he held a two-year postdoc at the Institut d'Astrophysique de Paris. He also worked as a quantitative researcher in wholesale risk modeling at JP Morgan Chase and later at the exotic equity derivatives desk at Barclays Capital in New York.
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Valentin Danchev

Postdoctoral Scholar, University of Chicago

Valentin Danchev is a computational sociologist. He uses network analysis, computational models, text analysis, and large-scale databases to study how patterns of connectivity in social, spatial, and semantic networks influence differences in outcomes, such as replicable discoveries, innovation, mobility opportunities, and inequality.

At Knowledge Lab, Valentin conducts a large-scale evaluation of the robustness and replicability of tens of thousands of research results published in the biomedical literature and examines what network structures of scientific communities contribute to robust, replicable discoveries. He also examines the interplay of social, biological, and organizational mechanisms inducing robust innovations in oncology research.

Valentin holds a DPhil (PhD) in Development Studies from the University of Oxford, where he was also affiliated with the networks research group at the Mathematical Institute. Prior to that, he received his MA from the University of Essex and his BA from the University of Sofia, both in Sociology.

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Eamon Duede

Special Advisor, Knowledge Lab, University of Chicago

Eamon served as the Executive Director of Knowledge Lab from 2013 - 2017. He held a key leadership role in strategic and operational planning and management. He was responsible for coordinating day-to-day research activities, asset allocation and distribution (including a major regranting program), supporting and driving key negotiations, as well as acting as a high-level interface between the Center, its partners, and industry.

Eamon holds a B.A. and M.A. in philosophy and has served as an instructor of various logics, and a lecturer in philosophy (ethics, epistemology, and the history of philosophy) and is currently persuing a Ph.D in the Philosophy and Sociology of Science from the University of Chicago's Committee on the Conceptual and Historical Studies of Science.

His academic interests are focused on the constellation of problems fixed around the concepts ‘perception’, ‘belief’, and ‘knowledge’. Philosophy and Sociology of Science; Bayesian Epistemology; the Science of Data; the Role of Mathematical and Statistical Models in Knowledge Creation, Ratification, Propagation, and Rejection; Statistical Inference (Deduction, Induction, and Abduction).

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James A. Evans

Director, Knowledge Lab; Professor, Sociology, University of Chicago; Faculty Director, Masters Program in Computational Social Sciences; External Professor, Santa Fe Institute

I am Director of Knowledge Lab, Professor of Sociology, Faculty Director of the Computational Social Science program, and member of the Committee on Conceptual and Historical Studies of Science at the University of Chicago. I am also an External Professor at the Santa Fe Institute. My research focuses on the collective system of thinking and knowing, ranging from the distribution of attention and intuition, the origin of ideas and shared habits of reasoning to processes of agreement (and dispute), accumulation of certainty (and doubt), and the texture--novelty, ambiguity, topology--of human understanding. I am especially interested in innovation--how new ideas and technologies emerge--and the role that social and technical institutions (e.g., the Internet, markets, collaborations) play in collective cognition and discovery. Much of my work has focused on areas of modern science and technology, but I am also interested in other domains of knowledge--news, law, religion, gossip, hunches and historical modes of thinking and knowing. I support the creation of novel observatories for human understanding and action through crowd sourcing, information extraction from text and images, and the use of distributed sensors (e.g., RFID tags, cell phones). I use machine learning, generative modeling, social and semantic network representations to explore knowledge processes, scale up interpretive and field-methods, and create alternatives to current discovery regimes. My research is funded by the National Science Foundation, the National Institutes of Health, DARPA, Facebook, IBM, the Sloan Foundation, Jump! Trading and other sources, and has been published in Science, PNAS, Nature Human Behavior, Nature Biotech, American Journal of Sociology, American Sociological Review, Social Studies of Science, Administrative Science Quarterly, PLoS Computational Biology and other journals. My work has been featured in Nature, the Economist, Atlantic Monthly, Wired, NPR, BBC, El País, CNN and many other outlets. 
At Chicago, I sponsor the Computational Social Science workshop. I teach courses on augmented intelligence, computational content analysis, the history of modern science, science studies, and Internet and Society. Before Chicago, I received my doctorate in sociology from Stanford University, served as a research associate in the Negotiation, Organizations, and Markets group at Harvard Business School, started a private high school focused on project-based arts education, and completed a B. A. in Anthropology and Economics at Brigham Young University. In the course of these events, I married Jeannie Evans and we now have four (fabulous) children, Noah, Ruth, Anna and Kate.
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Austin Kozlowski

Graduate RA, University of Chicago

I am a doctoral student in the Chicago sociology department. My research focuses on the questions of how belief systems are structured and why certain ideas seem to “go together.” By applying state-of-the-art computational methods, I attempt to shed new light on these age-old questions from the sociology of knowledge and culture.
At Knowledge Lab, I am currently engaged in a project utilizing word embeddings to discover cultural associations and categories in text. This project aims to advance an analytical and relational approach to the study culture, building-up our understanding of how meanings are situated with respect to one another in a cultural system.
Before coming to the University of Chicago, I earned my BA in Sociology at the University of Michigan and worked as a research associate with the Chitwan Valley Family Study at the UM Institute for Social Research. During my time at Michigan, I conducted research on the effects of agricultural technology adoption among subsistence farm households in Nepal.
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Molly Lewis

Postdoctoral Scholar, UChicago

My research focuses on understanding how linguistic meaning--semantic space--is acquired in cognitive development, changes over historical time, and varies cross-linguistically. I am also interested in issues related to scientific replicability and reproducibility. I received my PhD in Developmental Psychology from Stanford University, where I worked with Michael Frank. Before that, I received a BA in Linguistics from Reed College.
At the Knowledge Lab, my work examines cross-linguistic variability in the alignment of linguistic meaning using large scale corpora. I am co-advised by James Evans at the Knowledge Lab and Gary Lupyan in the Psychology Department at the University of Wisconsin-Madison.
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Lingfei Wu

Postdoctoral Scholar, University of Chicago

My research interest is the sciences of collaboration and innovation. I apply mathematical models and machine learning techniques to analyze collective knowledge production systems, including Web of Science, U.S. patents, Stack Exchange, GitHub. My works were published on journals including Physical Review E, Scientific Reports, PloS ONE, and also generated broad interested among diverse audience in New Scientists and Science Daily. I got my PhD in Communication from the City University of Hong Kong in 2013. Overlapping with the PhD program I spent a year in Baidu as an algorithm engineer (internship). I joined Knowledge Lab in 2016 after working two years in the Center for Behavior, Institutions and the Environment at Arizona State University as a post-doc researcher. I am a core member of Swarma Club, a research network in Beijing with a vision to bridge academic, industry, and government. I love dogs but never got a chance to keep one. I am hosting Lu Gu (meaning yesterday once more in Chinese), a Podcast to encourage guests (mostly junior scientists) to share awkward moments and tough times of life. Find me at lingfeiw AT if you are not a robot and got real questions to ask.

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Shahab Asoodeh

Postdoctoral Scholar, University of Chicago

I am interested in the applications of discrete (differential) geometry and information theory in machine learning and network science. In particular, my main research at the Knowledge Lab focuses on the following two broad questions:  1) How to quantify geometry of graphs, simplicial complexes, and more generally, hypergraphs and to interpret them in real-world networks? And 2) How to use geometry and information theory to define and quantify fairness and privacy in machine learning and data mining?

I am fortunate to work with James Evans at the Knowledge Lab and Ishanu Chattopadhyay at the Institute of Genomics and System Biology (IGSB).

I received my PhD and MSc both in applied mathematics from Queen’s University, Canada, in 2017 and  2011 and a MSc in Electrical Engineering from ETH Zurich and TU Delft in 2010. 

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Xiaoshuang Jia

Graduate Student, Sun Yat-sen University

I'm interested in social interactions, connections, and their outcomes. From the perspective
of social network, I use computational methods such as network analysis, text analysis, and
Agent-based Modeling to study sociological questions in the field of mobility, survey
methodology, and the sociology of knowledge. As a computational sociologist, I also
interested in the study of the state-of-the-art computational methods and techniques.
At Knowledge Lab, I participate in a project which attempted to use machine learning to
make simplicity-description and causality-prescription of individual-level data generated from
Agent-based Modeling.
I have been visiting the Knowledge Lab at the University of Chicago since Dec 2017. I'm a
doctoral student in the sociology department of Sun Yat-sen University, where I received my
B.A. and M.A. in Sociology.

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Linzhou Li

Graduate Student, University of Chicago

I am a PhD student in Chicago Sociology Department. My research interest is mostly related to economic and cultural change. More specifically, I made efforts in understanding questions such as the substitution and generalization of social, cultural and ideological values; reasoning based upon (and constrained by) the cultural system; and the self-organization of local financial and economic behaviors. 

I employ intensively state-of-the-art computational methods as well as traditional ethnographic tools to guide my research. A most recent project of mine applies a new embedding technique to embed words and tags into hyperbolic space to uncover the hidden hierarchical structure of 21st century physics. I am also collaborating with my colleague Shilin Jia to uncover cultural and ideological autonomy using China’s newspaper People’s Daily from 1946 to 2003.

Before coming to Chicago, I received my BA and MA degree from Tsinghua University. 

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