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Please list your areas of interest/expertise (related to collective behavior); up to 250 words: -Role of cell-cell interactions and collective behavior in the tumor microenvironment, especially in regards to interactions between tumor cells and cells of the innate immune system. -Collective behavior of complex systems, specifically, identifying general properties of how emergent, global behaviors arise out of simple interactions within groups of genes, cell, species, etc. -Adaptive coevolutionary networks: in particular, the study of spatially extended networks of interacting nodes (e.g., species) with both natural selection and spatial diffusion at the individual level. -Agent-based modeling -Dynamical processes on networks -Numerical algorithms for the control of complex networks -Mathematical modeling -Nonlinear dynamics -Scientific computing -Systems biology -Synthetic biology Please list the institution, degree and year completed for up to your two of your most recent and highest degrees (up to 200 characters): Carleton College, B.A. in Mathematics, 2010, Northwestern, M.S. in Applied Mathematics (Ph.D. ongoing), 2011 Personal statement (should consist of a brief bio and include a few sentences on current research related to collective behavior; up to 250 words; will be published in conference roster if selected.): I am an applied mathematician with a background in nonlinear dynamics drawn to biology by way of studying complex systems and network theory. In my doctoral research I have investigated how the interactions between genes in a genetic regulatory network naturally lead to the emergence of global attracting states, like “healthy” or “diseased”, and how these interactions can be manipulated with therapeutics to eliminate such diseased states. This research lead me to study similar interactions in cell-cell communication, particularly in the developing tumor microenvironment. Here, using a simplified agent-based modeling framework to capture interactions between a tumor and the innate immune system, I demonstrated that even when the initial collective behavior of this system is unpredictable, at the onset of tumorigenesis it quickly becomes determined due to key intracellular decisions and cell-cell signaling events. Notably, I found that immune system metrics based on these events provide insight into tumor fate long before more standard metrics like tumor size do, illustrating how patient immune response might be utilized to predict prognosis at early stages of tumor development. Most recently, I expanded this approach to a general setting by developing a new class of model, termed the “network state diffusion” model. I am utilizing these models to study how in an interacting community of agents (bacteria, metazoan, etc.), natural-selection on the individual level coupled with system dynamics and spatial diffusion effectively places evolutionary pressure on both the collective behavior and network structure of the community as a whole. Key accomplishments related to collective behavior - from microbes to metazoans: (e.g., publications, awards/honors, presentations, patents, or other output applicable to your field; up to 250 words): Key Publications: 1. Wells D, Kath W, Brockmann D. Diffusion promotes and stabilizes network evolution, in preparation 2. Wells D, et al. Spatial and functional heterogeneity shape tumor-immune network dynamics, in preparation 3. Wells D, Kath W, Motter A. Control of stochastic and induced switching in biological networks, submitted 4. Wells D, Kath W. A universally applicable method to identify bifurcations in complex multi-parameter dynamical systems, in preparation 5. Wells D, Ward M. (2010) Nephritis and the Risk of Acute Myocardial Infarction in Patients with Systemic Lupus Erythematosus. Clinical & Experimental Rheumatology, 28. Key Awards: Marine Biological Laboratory Course in Cell Physiology (2014) Cold Spring Harbor Course in Synthetic Biology (2013) Chicago Biomedical Consortium Scholar (2012) National Cancer Institute Physical Sciences-Oncology Trainee (2011) National Science Foundation Graduate Research Fellowship (2011) Northwestern University Cabell Fellowship (2010) Carleton College Steven P. Galovich Prize (2010) Key Talks: Heterogeneity mediates proliferation in coupled tumor-immune networks: -National Cancer Institute Young Investigator’s Meeting (2014) Control of Stochastic and Induced Switching in Biological Networks: -Network Frontiers Workshop (2013) -National Cancer Institute Young Investigator’s Meeting (2013) -Winter q-bio Meeting (2013) -Purdue University: Model-Based Analysis and Control of Cellular Processes (2010) What is the most pressing issue or question that needs to be addressed by an interdisciplinary audience in order to redefine the frontiers of research on the challenges and opportunities of collective behavior, and to initiate a new synthesis of the regulation, dynamics and evolution of collective behavior from microbes to metazoans.(up to 250 words): While research in collective behavior has given deep insights into how and why many social traits exist, there has been less work in leveraging this knowledge for technological progress. Thus, I feel that most important question in collective behavior that could be addressed by an interdisciplinary audience is “how can we utilize knowledge of collective behavior to optimally achieve a desired goal in natural or engineered systems?” Said another way, “how can we implement and/or control a desired collective behavior in a particular system?” I am particularly interested in this question with the advent of engineered cell-based therapies to fight diseases. In the context of such therapies, a key question is whether engineering such systems to collectively respond to disease based upon communication through diffusible signals will substantially increase their efficacy. An understanding of how to implement and control collective behaviors in systems has clear applications to other fields outside of medicine as well: from robotics, in the design of self-assembling robots, to social networks, by identifying the key members of a community to influence the behavior of the entire group. I feel that this question in particular requires a strongly interdisciplinary audience to be able to identify the unifying, foundational characteristics of collective behavior as well as to determine what the key features of a successful, broadly applicable approach for implementing/controlling these characteristics will be.