{"691199":{"#nid":"691199","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Xinhui Li","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003Cem\u003E:\u0026nbsp; Data-Driven, Multi-View, and Multimodal Representation Learning for Neuroimaging\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Vince Calhoun, ECE, Chair, Advisor\u003C\/p\u003E\u003Cp\u003EDr. Rogers Silva, TReNDS, Co-Advisor\u003C\/p\u003E\u003Cp\u003EDr. Christopher Rozell, ECE\u003C\/p\u003E\u003Cp\u003EDr. Anqi Wu, CSE\u003C\/p\u003E\u003Cp\u003EDr. Shella Keilholz, BME\u003C\/p\u003E\u003Cp\u003EDr. Tulay Adali, U of Maryland\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EMental disorders affect more than one billion people worldwide, and timely intervention is critical; however, current diagnostic practice remains largely subjective. Magnetic resonance imaging (MRI) provides a noninvasive way to measure brain structure and function and identify objective biomarkers of mental disorders. Despite these advances, several challenges remain in mental disorder diagnosis and neuroimaging analysis, including objective characterization of the neuropsychiatric continuum and heterogeneity, preprocessing-related variability, and heterogeneous information integration from high-dimensional, multimodal data. This dissertation develops data-driven, multi-view, and multimodal representation learning approaches, which learn low-dimensional representations from high-dimensional MRI data, to characterize the neuropsychiatric continuum and heterogeneity, mitigate preprocessing-related variability, and identify phenotypic and psychiatric biomarkers from structural and functional MRI. For unsupervised representation learning, our data-driven interpolation framework effectively characterizes individual differences within a group and continuous patterns between groups. For multi-view representation learning, our methods substantially improve both neural network representational similarity across preprocessing pipelines and prediction robustness for brain-phenotype relationships. For multimodal representation learning, our multimodal latent variable models, developed in the MISA PyTorch framework, successfully identify linked sources associated with phenotypic and psychiatric measures. Together, our methods and toolboxes contribute to reproducible neuroimaging analysis and reliable brain-behavior relationship discovery.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Data-Driven, Multi-View, and Multimodal Representation Learning for Neuroimaging "}],"uid":"28475","created_gmt":"2026-07-21 17:44:49","changed_gmt":"2026-07-21 17:45:26","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-07-28T10:00:00-04:00","event_time_end":"2026-07-28T12:00:00-04:00","event_time_end_last":"2026-07-28T12:00:00-04:00","gmt_time_start":"2026-07-28 14:00:00","gmt_time_end":"2026-07-28 16:00:00","gmt_time_end_last":"2026-07-28 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Room 1802, TReNDS Center ","extras":[],"related_links":[{"url":"https:\/\/gatech.zoom.us\/j\/9859501596?pwd=NDc4WjhVcWV1QzlXMDdobUNmbk9vZz09","title":"Zoom Link "}],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"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":""}},"691198":{"#nid":"691198","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Jonas Theumer","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003Cem\u003E:\u0026nbsp; Electromagnetic Sensing for Monitoring Physical and Embedded Systems\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Milos Prvulovic, CoC, Chair, Advisor\u003C\/p\u003E\u003Cp\u003EDr. Morris Cohen, ECE\u003C\/p\u003E\u003Cp\u003EDr. Ashutosh Dhekne, CoC\u003C\/p\u003E\u003Cp\u003EDr. Gregory Durgin, ECE\u003C\/p\u003E\u003Cp\u003EDr. Moinuddin Qureshi, CoC\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EElectromagnetic (EM) sensing is a powerful tool to non-invasively monitor internal states of systems that are otherwise hard to access. This thesis leverages EM sensing across two distinct domains: biological plants and embedded systems. First, we perform EM modeling and measurements to non-destructively track plant water content. We show that Ka-band EM transmission loss strongly correlates with leaf water content. To overcome the practical limitations of transmission measurements, we develop a model and measurement technique with a single antenna that tracks the loss due to leaf water content via backscattering. The second part of this thesis shifts the focus to systems that are themselves sources of EM signals that can be used to reveal internal operational states. Specifically, we demonstrate how to accurately classify serial protocols used by an embedded device for internal communications via unintentional EM emanations. Measuring the magnetic near field, we are able to distinguish different protocols, data rates, and even message contents with high accuracy. We are also able to perform similar classification using far-field data recorded at lower sampling rates in a noisy laboratory environment. Finally, we consider an integrated embedded platform periodically executing tasks. Instead of passively sensing EM leakage, we create the side channel by intentionally transmitting an EM wave toward the device. Just as the backscatter reflecting off leaves reveals the internal state of the underlying plant, the embedded device modulates the incident wave based on its physical operation. We are able to accurately profile the embedded platform in an unsupervised fashion by analyzing the backscatter. We further characterize the backscattering link under various configurations, and find that our unsupervised framework is highly robust to changes in the backscattering link. This approach can serve as a foundation for profiling inaccessible embedded systems. Ultimately, this thesis demonstrates how EM sensing can serve as a tool to non-invasively obtain hard to access information across disciplines.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Electromagnetic Sensing for Monitoring Physical and Embedded Systems "}],"uid":"28475","created_gmt":"2026-07-21 17:37:16","changed_gmt":"2026-07-21 17:38:14","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-07-27T13:00:00-04:00","event_time_end":"2026-07-27T15:00:00-04:00","event_time_end_last":"2026-07-27T15:00:00-04:00","gmt_time_start":"2026-07-27 17:00:00","gmt_time_end":"2026-07-27 19:00:00","gmt_time_end_last":"2026-07-27 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Room W218, Van Leer","extras":[],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"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":""}},"691098":{"#nid":"691098","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Samuel Medeiros Araujo Morais","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003Cem\u003E:\u0026nbsp; Ultrasound Shear Wave Elastography Methods for Tissue Therapy Guidance and Monitoring\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Stanislav Emelianov, ECE, Chair, Advisor\u003C\/p\u003E\u003Cp\u003EDr. Brooks Lindsey, BME\u003C\/p\u003E\u003Cp\u003EDr. Scott Hollister, BME\u003C\/p\u003E\u003Cp\u003EDr. Levent Degertekin, ECE\u003C\/p\u003E\u003Cp\u003EDr. Francisco Robles, BME\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe biomechanical properties of biological tissues are closely related to their physiological state, including inflammation and the development of disease. Since ancient times, clinicians have assessed tissue elasticity through palpation, making it one of the oldest diagnostic techniques in medicine. Although palpation remains a valuable clinical screening tool for detecting superficial abnormalities, the advent of medical imaging has transformed tissue elasticity assessment into a noninvasive modality capable of visualizing and quantifying tissue mechanical properties. Ultrasound elastography, in particular, combines the advantages of conventional ultrasound imaging, such as portability, real-time imaging, and cost-effectiveness, with the ability to quantitatively assess tissue mechanical properties by measuring shear wave propagation. These measurements enable not only the detection and monitoring of disease progression but also the guidance of therapeutic interventions and the evaluation of tissue response to treatment. This research expands the application of ultrasound shear wave elastography techniques to several clinically relevant challenges. In aim 1, a miniaturized source of longitudinal shear wave is investigated to enable intracardiac measurement of myocardial stiffness for heart failure therapy guidance. In aim 2, shear wave elasticity imaging is used to detect early biomechanical changes associated with skin breakdown and implant exposure following subcutaneous implantation. Finally, in aim 3, shear wave elasticity imaging is applied to assess the risk of reherniation after patch repair of congenital diaphragmatic hernia.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Ultrasound Shear Wave Elastography Methods for Tissue Therapy Guidance and Monitoring "}],"uid":"28475","created_gmt":"2026-07-13 08:04:41","changed_gmt":"2026-07-13 08:06:14","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-07-28T14:00:00-04:00","event_time_end":"2026-07-28T16:00:00-04:00","event_time_end_last":"2026-07-28T16:00:00-04:00","gmt_time_start":"2026-07-28 18:00:00","gmt_time_end":"2026-07-28 20:00:00","gmt_time_end_last":"2026-07-28 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Room L1255, Ford ES\u0026T","extras":[],"related_links":[{"url":"https:\/\/gatech.zoom.us\/j\/92770520516?pwd=rTBISRIAtHn4YbQXnJOr5EBs2jEU34.1","title":"Zoom link"}],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"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":""}},"691097":{"#nid":"691097","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Afra Nawar","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003Cem\u003E:\u0026nbsp; Enabling Robust Ambulatory Cardiovascular Monitoring inthe Context of Stress for Those with a Prior Myocardial Infarction\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Omer Inan, ECE, Chair, Advisor\u003C\/p\u003E\u003Cp\u003EDr. Amit Shah, Emory\u003C\/p\u003E\u003Cp\u003EDr. Mark Davenport, ECE\u003C\/p\u003E\u003Cp\u003EDr. Matthieu Bloch, ECE\u003C\/p\u003E\u003Cp\u003EDr. Douglas Bremmer, Emory\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EOne in four people who have experienced a myocardial infarction (MI) will go on to experience a second event in their lifetime, often resulting in early mortality. Despite this known high incidence of adverse outcomes, preventative monitoring for this population remains largely absent. In particular, there is a lack of continuous and objective assessment of the capability of the patient\u0027s cardiovascular system to withstand and adapt to daily stressors following an MI. This dissertation describes biosignal processing and algorithm development efforts towards enabling reliable ambulatory cardiovascular monitoring in the context of stress for this population. Such a system would be able to automatically identify abnormal stress-induced cardiovascular changes remotely, enabling preventative care. Towards this goal, we make the following key contributions through the research described. We first demonstrate the feasibility of quantifying complex stress-induced changes in cardiomechanical function, vascular dynamics, and eletrophysiology using a compact multimodal wearable patch, previously only possible through a disjoint collection of obtrusive wired devices. We then make several advances towards improving the usability of these signals. We validate that ECG features can be derived from the patch with equivalent fidelity to gold-standard wired devices. Utilizing the unique morphology of the SCG signal, we develop a novel TDA-based algorithm with potential to enable robust SCG signal quality assessment without reliance on an reference signal. We additionally take the first step towards the understanding the physiological origins and signal quality of core-body PPG signals as compared to peripheral measurement sites. Importantly, we find that the core-body PPG amplitude reacts in an opposite fashion to that of the peripheral site during respiratory challenges. Finally, using these insights, we create the first automated algorithm with capability to identify abnormal hemodynamic responses to stress in the post-MI population, uncovering novel potential SCG-based biomarkers of cardiac dysfunction in the process. Thus, this work presents a step towards continuous cardiovascular monitoring in at-home settings, which can provide clinicians with real-time physiological information to enable early, personalized clinical intervention for the growing population of post-MI survivors.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Enabling Robust Ambulatory Cardiovascular Monitoring inthe Context of Stress for Those with a Prior Myocardial Infarction "}],"uid":"28475","created_gmt":"2026-07-13 07:37:27","changed_gmt":"2026-07-13 07:38:35","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-07-24T14:00:00-04:00","event_time_end":"2026-07-24T16:00:00-04:00","event_time_end_last":"2026-07-24T16:00:00-04:00","gmt_time_start":"2026-07-24 18:00:00","gmt_time_end":"2026-07-24 20:00:00","gmt_time_end_last":"2026-07-24 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Room 523A, TSRB","extras":[],"related_links":[{"url":"https:\/\/gatech.zoom.us\/j\/9676069","title":"Zoom link"}],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"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":""}}}