Postdoctoral Researchers

  1. Dr. Eun Lee
    I am deeply interested in the lens people use to perceive the world and how people react with the perception. I believe the structure of social networks and unequal distribution of attributes (such as wealth, talents, prestige and so on) can form the perception which leads people’s collective behaviors. This collective action could restructure their social environments and adjust their perception of the world. I am eager to understand the mechanisms with the help of the complex system and mathematical modeling based on the data analysis. Eun Lee

Doctoral Students

  1. Andy Kavran (PhD Chemistry and Biochemistry and IQ Biology, co-advised with Prof. Natalie Ahn)
    I am interested in using network models to describe the behavior of biological systems, typically at the cellular and molecular scales. My research pairs community detection algorithms with high-throughput data in order to understand the differences in community structure between systems. Currently, I am applying this approach to protein expression data in order to understand the molecular relationships among several different types of cancer. Also, I am using protein phosphorylation data to investigate how melanoma cancer cells respond differently to intermittent and continuous drug treatment. Andy Kavran

  2. Nick LaBerge (PhD Computer Science, co-advised with Prof. Dan Larremore)
    As a former physicist, I am drawn to understand the underlying rules that govern real world systems, and I’m interested in using and developing analytical methods to study them. My current research in the science of science aims to better understand the academic ecosystem. In this research I am particularly motivated to examine how academia can become a more equitable environment for all. Nick LaBerge

  3. Allison Morgan (PhD Computer Science, and a NSF Graduate Research Fellow)
    I’m interested in measuring the structural factors that drive a lack of diversity in science and showing how they reinforce inequalities. For example, I’ve investigated how prestige shapes the spread of ideas in science and how parenthood impacts women’s careers. I’m currently researching the early childhood socioeconomic status of faculty. My work often draws upon network science, causal inference, statistics, and software engineering. Prior to graduate school, I worked as a data scientist and studied physics. Allie Morgan

  4. Katie Spoon (PhD Computer Science, co-advised with Prof. Dan Larremore, and a NSF Graduate Research Fellow)
    My past experiences in computer science, specifically in deep learning, caused me to hesitate at the speed in which deep neural networks are deployed and the amount of trust people have in their fairness and accuracy. This is especially concerning when those networks are used in healthcare, policing, education, and other areas that have a direct impact on people’s lives. I decided to pivot to computational social science to focus on explanation rather than prediction. Specifically, I’m interested in studying structural inequality in social systems. Katie Spoon

  5. Ian Van Buskirk (PhD Computer Science, co-advised with Prof. Dan Larremore)
    I’m here because I still don’t know what a complex system is. My favorite account? A complex system is a collection of agents that interact to manipulate a causal narrative. This suggests that analysis of such systems must bridge many divides, central among them the divide between an agent and the narrative it (often indirectly) attempts to manipulate. I seek to help build such bridges and hope my work shapes how we interact with complex systems for the better. Ian Van Buskirk

  6. Lucy Van Kleunen (PhD Computer Science, co-advised with Prof. Laura Dee)
    I'm interested in working at the intersection of network science and ecology. My research explores how the interactions between species are structured and predicts how these networks will react to shocks such as the introduction of nonnative species by humans. This work can suggest strategies for conserving and managing the natural systems to which humans are fundamentally connected. Lucy Van Kleunen

  7. Sam Zhang (PhD Applied Mathematics, and a NSF Graduate Research Fellow)
    As a programmer turned mathematician, I enjoy working at the boundary between pure mathematics and computational science. I am particularly interested in complex societal problems with rich geometric and network structure. Currently I am studying large-scale patterns in the ecosystem of science production and higher education. Sam Zhang

Masters Students

  1. Upasana Dutta (MS Computer Science)
    My interest lies in the intersection of Social Network Analysis and Data Science. I like exploring how the study of networks can help answer many unanswered social questions. During my undergrad, I worked on building computational models for dynamic co-authorship networks. My current research involves exploring a method, based on modularity maximisation, of detecting ordered or ranked groups in complex networks. Upasana Dutta

Undergraduate Students

  1. Sky Martin (BS Computer Science)
    I am currently curious about how reverse engineering biological systems can expose local rules and dynamics. A goal of mine is to do research that is not only interesting to me but also applicable, accessible, and impactful to others. My thesis research is studying the “grammar” of Mycobacteriaphage genomes using multi-order Hidden Markov Models. The goal of this project is to assist biologists to alter phage genomes to make them more effective in phage therapy. Sky Martin

Past Group Members

Postdoctoral Fellows

  1. Dr. Andrea E. Berardi (funded by NSF, 2015-2016, then postdoc at University of Bern)

  2. Dr. Daniel B. Larremore (funded by NIH, 2012-2015, now faculty in Computer Science at Colorado)

  3. Dr. Leto Peel (funded by DARPA, 2013-2015, now faculty in Data Science at Maastricht University, Netherlands)
Doctoral Students

  1. Dr. Anna Broido (Applied Mathematics, 2015-2019, then machine learning engineer at Apple)

  2. Dr. Amir Ghasemian (Computer Science, 2014-2018, then postdoctoral fellow at Temple)

  3. Dr. Nora Connor (Computer Science, 2011-2018, NSF GRF, then data scientist at Tuple Health)

  4. Dr. Samuel F. Way (Computer Science, 2014-2017, now research scientist at Spotify Research)

  5. Dr. Abigail Z. Jacobs (Computer Science, 2011-2017, NSF GRF, now faculty in Complex Systems and Information Science at Michigan)

  6. Dr. Lauren G. Shoemaker (Ecology and Evolutionary Biology, 2011-2017, NSF GRF, now faculty in Botany at Wyoming)

  7. Dr. Sears Merritt (Computer Science, 2011-2013, then data scientist at Mass. Mutual)
Masters Students

  1. Trevor DiMartino (Computer Science, 2016-2017, then developer and manager at Cognizant Accelerator)

  2. Kansuke Ikehara (Computer Science, 2015-2016, then developer at LingK)

  3. Christopher Aicher (Applied Math, 2012-2014, then pursuing PhD in Statistics at University of Washington)

  4. Pooneh Mortazavi (Computer Science, 2012-2013, then developer at Microsoft)

  5. Yogesh Virkar (Computer Science, 2011-2012, then pursuing PhD in Computer Science at Colorado)

  6. Chris Schenk (Computer Science, 2010-2011)
Undergraduates

  1. Christoph Uhl (BS Computer Science, 2018-2020, then software engineer at Oracle)

  2. Alexander Ray (BS Computer Science, 2017-2019, then developer at Amazon)

  3. McKenzie Weller (BS Computer Science, 2017-2019, then developer at Google)

  4. Tetsumichi (Telly) Umada (Computer Science, 2017-2018, then system engineer at NEC)

  5. Ellen Tucker (Mathematics, 2015-2016, then pursuing PhD in Computer Science at Northwestern University)

  6. Matthias Sainz (Computer Science, 2014-2016, then software developer at FullContact)

  7. Nico Tonozzi (Computer Science, 2014-2015)

  8. Andrew Zizzi (Aerospace Engineering, 2011-2012)

  9. Ken Sheedlo (Computer Science, 2011-2012)