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Becoming a Counselor: Applying Critical Phenomenology to Uncover Narratives from Black Women Counselors about Wounds and Healing
No full textThe purpose of this Critical Phenomenological dissertation study was to explore the lived experiences of becoming a counselor for Black women with self-identified personal histories with woundedness and engagement in processes of healing. In doing so, the experiences of becoming a counselor were explored for 11 Black women counselors at various points in their professional counselor identity development journey (e.g., counselors-in-training, practicing counselors, pre- and post-doctoral counselor educators). Data collection followed Seidman’s critical-in-depth interviewing model and the three main areas of Critical Phenomenological inquiry – The Life History, Experiences in Details, and Reflection on Meaning. Three individual semi-structured interviews were conducted with each participant. This study uncovered 11 first person individual narrative profiles illuminating the voices and experiences of the Black women counselor participants, along with the identification of collective themes and subthemes. Findings from this study show that racialization, racism, and gendered racism are influential to Black women counselors’ lived experiences, meaning-making of those experiences, and their journeys of becoming counselors. Findings also demonstrated that Black women counselors were motivated by experiences with woundedness and engagement in processes of healing to becoming counselors, and to contribute to change within the profession (i.e., increased representation of Black women and more support for Black women who become counselors). Based upon the study findings, there were implications for counselor education, clinical supervision, counseling practice, advocacy, and for Black Women Counselors themselves. These implications are centered on the need for critical approaches to addressing issues of limited diversity, gendered racism, and other forms of discrimination that impact Black women in their journey of becoming counselors. Recommendations for future research highlighted the importance of critical research methodologies within counseling research, including further critical exploration of the lived experiences of Black women (and other marginalized racial groups) have within the counseling profession, as counselors-in-training, as professional or practicing counselors, as clinical supervisors and supervisees, as doctoral students, as counselor education faculty, and as counseling organization leaders
Supporting Veteran and Military-Connected Students: Initiatives and Future Plans at Syracuse University Libraries
No full textOver the past two years, Syracuse University Libraries has been creating services and events tailored to the academic and community needs of veteran and military-connected students. This presentation focuses on two key initiatives: (a) A student veteran exhibit at Bird Library held around Veterans Day, and (b) A Veteran & Military-Connected Students Guide to the Libraries. The annual student veteran exhibit is designed to give student veterans a platform to share their stories with the broader Syracuse University community. The Veteran & Military-Connected Students Guide, developed by liaison librarian Patricia Giles and Information Literacy Scholar Joel Carpenter (MLIS \u2726), aims to support students\u27 academic success and overall well-being. To help veteran and military-connected students acquire skills to achieve their professional and personal goals, the Libraries is planning a Libraries Research Bootcamp for the Fall of 2025 and will continue making improvements to the Students Guide
Introduction to Military Culture and Mental Health Practice
No full textThe Introduction to Military Culture and Mental Health Practice course equips students across disciplines primarily social work with foundational skills for working with service members, veterans, and their families. Developed in 2016 by a former U.S. Air Force officer, the course addresses trauma, ethical dilemmas, dual loyalty, and command structures within military systems. Coursework includes case studies, ethical analysis, and interviews with military-connected individuals, fostering clinical and cultural competence. With 153 students trained to date, the course supports careers in the VA, nonprofits, and the Armed Forces, while advancing the university\u27s commitment to military-affiliated students
Developing an Undergraduate Course on Veteran and Military Behavioral Health
No full textUnderstanding the behavioral health needs of military service members and veterans is important for students who may pursue careers across the helping professions. This poster presentation details the development of a new undergraduate course that provides foundational knowledge in military and veteran behavioral health. The course examines a broad spectrum of psychological and behavioral health issues, including substance use and addiction, trauma and PTSD, military sexual trauma, suicide, pain and physical impairment, depression, anxiety, and the challenges associated with transitioning to civilian life. It also explores family and relationship dynamics, military culture, and barriers to mental health care. Key considerations in course development included selecting diverse lecture topics and course materials that reflect the varied experiences of military populations, as well as designing assignments that foster critical thinking and effective communication of research findings. Through assigned readings, lectures, group discussions, and student presentations, the course aims to deepen students understanding of how military history, culture, and service experiences influence psychological well-being and help-seeking behaviors. By providing insights into both the content and pedagogy of this course, the presentation encourages the integration of military and veteran behavioral health topics into undergraduate curricula. Ultimately, this initiative aims to equip future professionals with the knowledge and skills necessary to address the complex behavioral health concerns of military and veteran populations
Pain-Related Sleep Disturbance and Hazardous Alcohol Use Among Veterans with Chronic Pain
No full textIntroduction: Pain-related sleep disturbances (PRSD) may contribute to patterns of alcohol consumption that elevate risk for negative health outcomes among U.S. military veterans with chronic pain, with this association potentially heightened among those who experienced combat. We are not aware of any prior research that examined either relations between PRSD and hazardous alcohol use among veterans, or the potential influence of combat exposure. The goal of this study was to test the hypothesis that PRSD would be positively associated with hazardous drinking among veterans, and that combat exposure would moderate this relationship. Method: Participants included 430 U.S. veterans (Mage = 56.71  14.8; 23.7% female) with chronic pain who endorsed past-month alcohol use and completed a Qualtrics Panel survey. Results: PRSD was positively associated with hazardous alcohol use (B = .357, p = .018) after controlling for age, sex, and chronic pain intensity. This relationship was moderated by combat exposure, with stronger associations observed among combat-exposed veterans (B = .909, p \u3c .001) compared to deployed veterans without combat exposure (B = .633, p \u3c .001) and veterans with no deployment history (B = .357, p = .018). Discussion: Results indicate that U.S. veterans with chronic pain may be at increased risk of hazardous alcohol use due to PRSD, perhaps especially among combat-exposed veterans. These findings underscore the need for routine PRSD screening and tailored interventions that address both sleep disturbances and hazardous drinking to improve health outcomes among veterans
Power Optimized Co-Registration of Multispectral and Thermal Cameras for Real-Time Urban Pluvial Flood Monitoring
No full textUrban pluvial flooding occurs when local precipitation intensity exceeds the capacity of natural and engineered drainage systems, resulting in dangerous and highly localized inundation that is not captured by traditional stream gaging networks. While satellite imagery and flood maps support regional-scale flood management, a critical gap remains in the real-time, spatially continuous, in-situ monitoring of urban surface flooding. To address this monitoring gap, we develop a low-power, camera-based distributed sensor network flood mapping platform, Urban Flood Observation Network (UFO-Net), featuring two co-mounted sensors: a multispectral optical (capturing RGB and Near-Infrared) and a long-wave infrared (thermal) camera. A five-band image (RGB, NIR, LWIR) is constructed by aligning and fusing optical and thermal images using an optimized registration pipeline implemented on a Raspberry Pi 3B. This iterative method applies a similarity transform via Mattes Mutual Information in SimpleITK to find the optimized alignment of images. This step is vital because a well-calibrated and co-registered flood detection system enhances performance, reliability, and utility, allowing precise data interpretation and fusion to monitor and manage flood events effectively. Data-driven image co-registration is computationally expensive, increasing the latency of data processing and reducing the lifetime of battery-dependent sensor nodes. To reduce edge-computational costs associated with camera co-registration, we introduce the concept of a safety margin, which is a threshold that defines the maximum allowable camera movement using a low-power inertial measurement unit, before re-registration is required. This margin is derived empirically by analyzing alignment error (offset and RMSE) under controlled pitch, yaw, and roll variations. The inertial measurement unit monitors the camera’s position in real time and triggers transformation updates when motion exceeds the safety margin. This approach minimizes computational load while ensuring registration accuracy. Overall, this thesis presents a robust and replicable co-registration framework that enables real-time, edge-based flood monitoring, laying the groundwork for future research of distributed camera networks to enhance urban resilience
A Layin on of Hands: Black Feminist Healing Arts as Wake Work
No full textA Layin on of Hands: Black Feminist Healing Arts as Wake Work explores the work of two Black femme artists who engage in ritualized theater performance. This thesis examines the creations of Oakland-based artist Amara Tabor Smith, a ritual dance theater artist, and New York-based theater ceremonialist Ebony Noelle Golden. The project examines each artist’s unique artistic and spiritual practices as forms of immaterial, emotional, psychic, and social intervention in the afterlives of slavery, which impact Black life. Methodologically, this thesis depends on oral histories, performance analysis, and participant observation to document and explore the emotional, ecological, and spiritual effects that both artists’ work has on their collaborators, their communities, and the legacies of enslavement. This project draws on Saidiya Hartman’s theory of the “afterlives of slavery,” Christina Sharpe’s theory and praxis of “Wake Work,” and concepts of Black feminist hauntology to argue that the afterlives of slavery function as haints — shapeshifting, material, and metaphysical manifestations of anti-Blackness — that influence Black life. By blending their spiritual and artistic practices, these artists exorcise such haints from their communities by challenging hegemonic systems of knowledge and embracing indigenous epistemologies, cosmologies, and ancestral practices, providing their communities with psychic, emotional, and spiritual relief and liberation
UNWANTED LEVIATHAN: THE MODERN IRANIAN STATE AND ITS TRANSFORMATIONS
No full textThis manuscript examines the modern Iranian state and its evolution, focusing on the theme of the state’s \u27unwantedness.\u27 It traces the emergence and evolution of Iran\u27s modern state back to the late nineteenth and early twentieth centuries, a period during which systematic efforts were made to introduce and establish the infrastructures and institutions of the modern state. The manuscript explores the roots of the modern Iranian state\u27s fragility, particularly the factors that have made it vulnerable to grassroots challenges and revolutions. The primary objective of this project is to provide a pathology of the Iranian state by investigating its core issues and the persistence of these problems, despite significant changes in its capacities and control over time. A diachronic analysis of the Iranian state reveals a continuous failure to legitimize its authority and a troubling divide between the state and society, rendering Iran vulnerable to external threats. This divide has led to institutional forms and practices that cause the state to rely on ineffective and costly coercion. This reliance has, in turn, obstructed the transition to democracy, even in the face of strong bottom-up demands for democratic reforms. The manuscript argues that the incongruence between the structure of the state formed during the state-building period and the form of the state demanded by society has had lasting effects on the identity and dynamics of the state in Iran. This discord—a legacy of the defeat of the Constitutional Revolution and the rise of the autocratic Pahlavi state—has become so deeply entrenched that it has persisted even after the 1979 Revolution. Nation-building from above has played a central role in sustaining and reproducing these relationships between the state and society
Data-Efficient 3D Deep Learning
No full text3D data, whether represented as point clouds, volumetric data or meshes, plays a critical role in domains such as autonomous driving, robotics, and medical imaging. However, the complexity of 3D data acquisition and the high cost of annotation often make it impractical to curate large, fully labeled 3D datasets. Furthermore, the unstructured nature of point clouds and the high dimensionality of volumetric data pose additional challenges for designing effective deep learning models. While existing architectures, like PointNet and DGCNN, have made significant progress in learning directly from raw 3D inputs, they typically rely on data-rich scenarios. This dissertation focuses on these challenges, and presents data-efficient 3D deep learning frameworks that reduce reliance on extensive supervision. Specifically, it explores methods for learning from limited labeled data in both point cloud and volumetric settings through few-shot learning, zero-shot learning, and sparse-view reconstruction. We begin with the task of few-shot point cloud classification, where we propose a Cross-Modality Feature Fusion Network that combines 3D point features with depth image features. A support-query mutual attention module is introduced to enhance feature alignment, yielding robust performance under occlusion and missing data. We further introduce SimpliMix, a lightweight manifold mixup strategy that improves generalization by regularizing intermediate features, particularly in cross-domain few-shot settings. Next, we focus on zero-shot point cloud semantic segmentation, which aims to assign labels to points belonging to unseen object categories without requiring annotated samples. We present 3D-PointZshotS, a framework that learns latent geometric prototypes and aligns them with semantic knowledge through a similarity-based re-representation mechanism. This allows the model to generalize effectively to previously unseen classes. To extend data-efficient learning to the volumetric domain, we address the challenge of sparse-view cone-beam computed tomography (CBCT) reconstruction, which aims to recover a high-quality 3D volume from a limited number of 2D X-ray projections. We introduce Trans-CBCT, a model that adopts TransUNet as image encoder, aggregates its multi-scale feature maps to produce a rich, multi-level features, queries view‑specific features for each 3D point, and incorporates a lightweight attenuation‑prediction head. Building on our Trans-CBCT, we propose Trans2-CBCT, a dual-transformer architecture that further integrates a point transformer module to enhance local smoothness and spatial consistency. Experimental results demonstrate that both Trans-CBCT and Trans2-CBCT achieve superior reconstruction quality under extreme data sparsity (as low as six X-ray images), with Trans2-CBCT delivering sharper structural details and achieving even higher PSNR and SSIM scores. In summary, this thesis presents a unified investigation into learning robust and generalizable 3D representations from limited data across both point cloud and volumetric modalities. These contributions pave the way for deploying 3D deep learning in real-world applications where labeled data is scarce or costly to obtain
Christopher Brunt, Raymond Carver Reading Series, February 26, 2025
No full textA video recording of Christopher Brunt reading on February 26, 2025, as part of the Syracuse University Creative Writing Program\u27s Raymond Carver Reading Series