{"647204":{"#nid":"647204","#data":{"type":"event","title":"PhD Defense by Guanlin Li","body":[{"value":"\u003Cp\u003EIn partial fulfillment of the requirements for the degree of\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDoctor of Philosophy in Quantitative Biosciences\u003C\/p\u003E\r\n\r\n\u003Cp\u003Ein the School of Physics\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EGuanlin Li\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nDefends his thesis:\u003Cbr \/\u003E\r\n\u003Cstrong\u003EOPTIMIZATION AND CONTROL OF VIRUS-HOST SYSTEMS\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nThursday, May 20, 2021\u003Cbr \/\u003E\r\n12:00pm Eastern Time\u003Cbr \/\u003E\r\nVia BlueJeans: \u003Ca href=\u0022https:\/\/bluejeans.com\/3040782917\u0022\u003Ehttps:\/\/bluejeans.com\/3040782917\u003C\/a\u003E\u003Cbr \/\u003E\r\nOpen to the Community\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAdvisor:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Joshua S. Weitz\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Biological Sciences \u0026amp; School of Physics\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECo-advisor:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Yao Yao\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Mathematics\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003Cbr \/\u003E\r\n\u003Cbr \/\u003E\r\nCommittee Members:\u003Cbr \/\u003E\r\nDr. Sam Brown; School of Biological Sciences, Georgia Tech\u003Cbr \/\u003E\r\nDr. Yorai Wardi; School of Electrical and Computer Engineering, Georgia Tech\u003Cbr \/\u003E\r\nDr. Kurt Wiesenfeld; School of Physics, Georgia Tech\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nAbstract:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOptimization and control are powerful tools to design a system that works as effectively as possible. In this thesis, we focus on applications of model-based optimization and control in complex virus-host systems at multiple scales. Viruses that infect bacteria, i.e., bacteriophage or \u0026lsquo;phage\u0026rsquo;, are increasingly considered as treatment options for the control and clearance of bacterial infections, particularly as compassionate use therapy for multi-drug resistant infections. Here, we evaluate principles underlying why careful application of multiple phage (i.e., a \u0026lsquo;cocktail\u0026rsquo;) might lead to therapeutic success in contrast to the failure of single-strain phage therapy to control an infection. We combine dynamical modeling of phage, bacteria, and host immune cell populations with control-theoretic principles (via optimal control theory) to devise phage cocktails and delivery schedules to control the bacterial populations. However, a risk in using cocktails of different phage is that bacteria could simultaneously develop resistance to all injected phage (i.e., selecting for multi-phage resistant). The next step is to understand how to pre-select phage that have adapted via co-evolution with bacterial strains and then to efficiently use these \u0026lsquo;future\u0026rsquo; phage to clear the infection early on. In doing so, we develop the evolutionarily robust phage therapy in immunodeficient hosts given the infection networks that was identified in co-evolutionary training. Optimization and control not only can be applied to bacteria-phage-immune systems (i.e., at the microbial level) to help design phage therapy, but also can be applied to epidemiological systems (i.e., at the large-scale population level) to guide the development and deployment of efficient interventions. Lockdowns and stay-at-home orders have reduced the transmission of SARS-CoV-2 but have come with significant social and economic costs. Here, we describe a control theory framework combining population-scale viral and serological testing as part of an individualized approach to control COVID-19 spread. The aim is to develop policies for modulating individualize contact rates depending on both personalized disease status and the status of the epidemic at the population scale. Altogether in this thesis, we apply control strategies to alleviate the burden or spread of disease at multiple scales.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"OPTIMIZATION AND CONTROL OF VIRUS-HOST SYSTEMS "}],"uid":"27707","created_gmt":"2021-05-06 13:14:44","changed_gmt":"2021-05-06 13:14:44","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-05-20T13:00:00-04:00","event_time_end":"2021-05-20T15:00:00-04:00","event_time_end_last":"2021-05-20T15:00:00-04:00","gmt_time_start":"2021-05-20 17:00:00","gmt_time_end":"2021-05-20 19:00:00","gmt_time_end_last":"2021-05-20 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}