{"689868":{"#nid":"689868","#data":{"type":"event","title":"PhD Defense by Zihan Zhang","body":[{"value":"\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;Tensor-based Predictive Modeling and Control for High-dimensional Data\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EDate: \u003C\/strong\u003EMay 15, 2026 (Friday)\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E10:00 am - 12:00 pm EST\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EZoom link:\u003C\/strong\u003E\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fgatech.zoom.us%2Fj%2F97178700611%3Fpwd%3Dx3BIcKHMf0trFzXunDRap84ARbL8nx.1%26from%3Daddon\u0026amp;data=05%7C02%7Ctm186%40gtvault.onmicrosoft.com%7Cbf5b420afd4b4afda4ce08de9ba85fd5%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639119344643210516%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=q%2BrTI3%2FhlAmsVCT2ZnNO%2FnJ3EfoTz8NAXePr3rFs1SE%3D\u0026amp;reserved=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/gatech.zoom.us\/j\/97178700611?pwd=x3BIcKHMf0trFzXunDRap84ARbL8nx.1\u0026amp;from=addon. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/97178700611?pwd=x3BIcKHMf0trFzXunDRap84ARbL8nx.1\u0026amp;from=addon\u003C\/a\u003E\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E(Meeting ID: 971 7870 0611; Passcode: 387776)\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EZihan Zhang\u003C\/strong\u003E\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EPh.D. Candidate in Industrial Engineering\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EH. Milton Stewart School of Industrial and Systems Engineering\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EThesis Committee:\u003C\/strong\u003E\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli\u003EDr. Jianjun Shi (Advisor), H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli\u003EDr. Kamran Paynabar (Advisor), H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli\u003EDr. Yao\u0026nbsp;Xie, H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli\u003EDr. Xiao Liu, H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli\u003EDr. Mostafa Reisi, Department of Industrial and Systems Engineering, University of Florida\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EAdvances in sensing technologies have dramatically increased the volume and complexity of high-dimensional data, such as high-resolution images and videos, that challenge the foundations of traditional control methodologies. Conventional approaches, rooted in low-dimensional signal processing, often struggle to capture the complex spatio-temporal dependencies inherent in such data. Naive vectorization techniques destroy essential structural information, while many learning-based methods require large datasets and often lack interpretability.\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003EThis dissertation develops tensor-based control frameworks that preserve the underlying spatial and temporal structure of high-dimensional data. Chapter 2 addresses incomplete sensing in automatic process control by introducing methods for response imputation and control under missing-data conditions. Chapter 3 presents a system modeling framework that captures localized correlations in system responses and the spatial effects of control actions, followed by a dynamic controller design that optimizes controller placement to improve performance. Chapter 4 incorporates diffusion models to capture nonlinear spatio-temporal correlations and enable uncertainty quantification.\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003ETogether, these contributions advance a data-efficient and interpretable framework for controlling intelligent systems that operate with high-dimensional, multimodal sensory data.\u003C\/p\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ETensor-based Predictive Modeling and Control for High-dimensional Data\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Tensor-based Predictive Modeling and Control for High-dimensional Data"}],"uid":"27707","created_gmt":"2026-04-19 04:47:48","changed_gmt":"2026-04-19 04:48:40","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-05-15T10:00:00-04:00","event_time_end":"2026-05-15T12:00:00-04:00","event_time_end_last":"2026-05-15T12:00:00-04:00","gmt_time_start":"2026-05-15 14:00:00","gmt_time_end":"2026-05-15 16:00:00","gmt_time_end_last":"2026-05-15 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"ZOOM","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":""}}}