[{"id":8577,"date":"2026-04-10T17:28:34","date_gmt":"2026-04-10T22:28:34","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8577"},"modified":"2026-04-10T17:28:46","modified_gmt":"2026-04-10T22:28:46","slug":"rahul-debnath-masters-thesis-defense-wednesday-april-29-2026-130-pm-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/rahul-debnath-masters-thesis-defense-wednesday-april-29-2026-130-pm-central-time\/","title":{"rendered":"Rahul Debnath Master\u2019s Thesis Defense, Wednesday, April 29, 2026 @ 1:30 pm Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Ahmed Ahmed
\nCO-COMMITTEE CHAIR<\/strong>: Dr. Md. Jobair Bin Alam
\n
\nTITLE<\/strong>: MULTI-TASK GROWING INTERPRETABLE NEURAL NETWORK FOR MULTI-TARGET SYMBOLIC REGRESSION<\/p>\n

ABSTRACT: <\/strong>This research presents a comprehensive, three-phase hierarchical data collection framework integrating Internet of Things (IoT) sensors, aerial RGB imagery, and Electrical Resistivity Imaging (ERI) to correlate multi-scale hydro-geophysical soil parameters for comprehensive slope stability assessment. The first phase established a laboratory-scale physical slope model using Fat Clay (CH) to replicate failure-prone conditions. The prototype was instrumented with distributed IoT sensors measuring tilt, volumetric moisture content, and soil matric suction. Real-time data was transmitted to a custom cloud-based web graphical user interface (GUI) for remote visualization. Controlled artificial rainfall simulations validated the system\u2019s sensitivity to subtle kinematic and hydrological changes, establishing a foundational point-scale measurement infrastructure. To transition from lab-scale point measurements to vast field-scale analysis, the second phase focused on surface data extraction. Close-range aerial RGB imagery was captured for a targeted field location to extract multiple quantitative optical indices (e.g., Green Leaf Index (GLI), Visible Atmospherically Resistant Index (VARI), Normalized Green-Red Difference Index (NGRDI), etc.). The index exhibiting the highest statistical correlation score was selected to map surface-level variations. This optical data collection validated the visual monitoring infrastructure and serves as a foundational proxy for future, large-scale Unmanned Aerial Vehicle (UAV) deployment. The third phase conducted ERI surveys at the same field location to capture subsurface resistivity profiles. The core of this research establishes a direct data correlation framework between the extracted surface features (RGB) and subsurface geophysical conditions (soil resistivity). Utilizing Pearson correlation to assess linear relationships and Spearman rank correlation to evaluate monotonic trends, these distinct spatial datasets are systematically aligned. Quantifying these statistical relationships allows for the identification of underlying soil behavior patterns, enabling an in-depth analysis of near-surface anomalies and potential landslide triggers. This multi-scale approach bridges the critical gap between controlled laboratory validation and operational field mapping. By hierarchically correlating continuous IoT point-sensing with expansive RGB and ERI spatial data, this research delivers a robust, scalable data collection infrastructure. This framework addresses the limitations of conventional techniques, providing a cost-effective, multi-tiered solution for proactive anomaly detection and landslide risk mitigation.<\/p>\n

Keywords: <\/strong>AI, IoT, UAV, ERI, Data Fusion<\/p>\n

Room Location: <\/strong>S. R. Collins. Room 111: CS Main Conference Room.<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Ahmed Ahmed CO-COMMITTEE CHAIR: Dr. Md. Jobair Bin Alam TITLE: MULTI-TASK GROWING INTERPRETABLE NEURAL NETWORK FOR MULTI-TARGET SYMBOLIC REGRESSION ABSTRACT: This research presents a comprehensive, three-phase hierarchical data collection framework integrating Internet of Things (IoT) sensors, aerial RGB imagery, and Electrical Resistivity Imaging (ERI) to correlate multi-scale hydro-geophysical soil parameters for comprehensive […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[133],"class_list":["post-8577","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8577","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8577"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8577\/revisions"}],"predecessor-version":[{"id":8578,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8577\/revisions\/8578"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8577"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8577"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8577"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8577"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8572,"date":"2026-04-10T12:37:40","date_gmt":"2026-04-10T17:37:40","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8572"},"modified":"2026-04-10T12:38:26","modified_gmt":"2026-04-10T17:38:26","slug":"natures-intelligence-a-photography-exhibit","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/natures-intelligence-a-photography-exhibit\/","title":{"rendered":"NATURE\u2019S INTELLIGENCE A PHOTOGRAPHY EXHIBIT @ Northwest Houston Center Library"},"content":{"rendered":"

\n

Good afternoon\u00a0<\/span><\/p>\n<\/div>\n

\n

Please join us on Thursday, April 23, 2026, from 6:00 pm-8:00 pm for another great art exhibit here at the Northwest. The Northwest Houston Center Library would like to invite you to the Nature’s Intelligence, A Photography Exhibit opening night reception. Click the link on the flyer or click the link below to RSVP.<\/p>\n<\/div>\n

\n

https:\/\/pvamu.co1.qualtrics.com\/jfe\/form\/SV_eg62rDvMcHKZDTg<\/a><\/p>\n<\/div>\n

\n
<\/div>\n
\n

Kind regards,<\/p>\n<\/div>\n

\n

Northwest Houston Center<\/p>\n<\/div>\n

\n

9449 Grant Rd.<\/p>\n<\/div>\n

\n

Houston, TX\u00a0 77070<\/p>\n<\/div>\n

\n

(713) 790-7146<\/p>\n<\/div>\n

\n

<\/p>\n<\/div>\n

To reserve a space at the NWHC<\/b>\u00a0<\/i><\/b>click here<\/i><\/b><\/a>.\u00a0<\/b><\/p>\n

For rental rates at the NWHC<\/b>\u00a0<\/i><\/b>click here<\/i><\/b><\/a>.\u00a0<\/b><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Good afternoon\u00a0 Please join us on Thursday, April 23, 2026, from 6:00 pm-8:00 pm for another great art exhibit here at the Northwest. The Northwest Houston Center Library would like to invite you to the Nature’s Intelligence, A Photography Exhibit opening night reception. Click the link on the flyer or click the link below to […]<\/p>\n","protected":false},"author":432,"featured_media":8574,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[848,386,852,854,314,847,851,853],"class_list":["post-8572","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8572","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8572"}],"version-history":[{"count":2,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8572\/revisions"}],"predecessor-version":[{"id":8576,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8572\/revisions\/8576"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/8574"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8572"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8572"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8572"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8572"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8566,"date":"2026-04-09T10:03:13","date_gmt":"2026-04-09T15:03:13","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8566"},"modified":"2026-04-10T12:32:10","modified_gmt":"2026-04-10T17:32:10","slug":"8566","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/8566\/","title":{"rendered":"Student Counseling Services Informational"},"content":{"rendered":"

Good morning.<\/div>\n
<\/div>\n
Please join us on Tuesday, April 14th, at 6:30 pm, for our virtual informational series. Ms. Destiny Anderson from the Student Counseling Services Department will cover counseling for students at PVAMU. To join the Zoom, please click on “Join Zoom Meeting” on the flyer. The Zoom will be active on the day of the informational session.<\/div>\n
<\/div>\n
Register using the link below or the attached flyer to receive the recording of the informational session<\/div>\n
https:\/\/pvamu.co1.qualtrics.com\/jfe\/form\/SV_8eajdA8MeSGjuui<\/a><\/div>\n
<\/div>\n","protected":false},"excerpt":{"rendered":"

Good morning. Please join us on Tuesday, April 14th, at 6:30 pm, for our virtual informational series. Ms. Destiny Anderson from the Student Counseling Services Department will cover counseling for students at PVAMU. To join the Zoom, please click on “Join Zoom Meeting” on the flyer. The Zoom will be active on the day of […]<\/p>\n","protected":false},"author":432,"featured_media":8569,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[928,388,396,387],"class_list":["post-8566","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8566","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8566"}],"version-history":[{"count":2,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8566\/revisions"}],"predecessor-version":[{"id":8571,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8566\/revisions\/8571"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/8569"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8566"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8566"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8566"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8566"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8560,"date":"2026-04-08T23:08:52","date_gmt":"2026-04-09T04:08:52","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8560"},"modified":"2026-04-08T23:08:59","modified_gmt":"2026-04-09T04:08:59","slug":"maowen-tang-masters-thesis-defense-wednesday-april-22-2026-1100-am-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/maowen-tang-masters-thesis-defense-wednesday-april-22-2026-1100-am-central-time\/","title":{"rendered":"Maowen Tang Master\u2019s Thesis Defense, Wednesday, April 22, 2026 @ 11:00 am Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Yonghui Wang<\/p>\n

TITLE<\/strong>: STRUCTURED REPRESENTATION LEARNING FOR GENERALIZABLE DEEPFAKE VIDEO DETECTION<\/p>\n

ABSTRACT<\/strong> Deepfake video detection has become an important problem in multimedia forensics as modern generative models produce increasingly realistic facial manipulations. Although many existing detectors achieve strong performance on the datasets on which they are trained, their performance often degrades substantially on unseen manipulation methods and evaluation conditions. A major reason for this limitation is the premature collapse of spatial structure: many vision transformer based detectors aggregate patch tokens into a single global representation, thereby suppressing the localized and temporally uneven forensic cues that characterize manipulated video. This thesis presents the Spatio-Temporal Slot Aggregation Network (ST-SAN), a video-level deepfake detection framework designed to preserve structured forensic evidence before final classification. ST-SAN extracts patch tokens from three intermediate layers of a frozen DINOv2 backbone and aligns them through a lightweight bottleneck projection. A K-slot soft aggregation module then forms multiple learned slot summaries for each frame, allowing the model to retain several localized views of manipulation evidence instead of collapsing all patch information into one vector. These slot features are further integrated through adaptive frame weighting and slot weighting so that frames and slot summaries with stronger forensic content contribute more to the final decision. Training is stabilized by structural regularization terms that encourage locality, orthogonality, diversity across slot summaries, and weak coverage. Experiments show that ST-SAN achieves 0.960 AUC on FaceForensics++ under in-domain evaluation. Under cross-domain evaluation, it achieves 0.917 AUC on Celeb-DF v2, 0.872 AUC on DeepFakeDetection, and 0.890 AUC on the DeepFake Detection Challenge Preview dataset, indicating competitive cross-domain performance on the reported benchmarks. Ablation results show that parallel soft slot aggregation is an important architectural component, while adaptive weighting and structural regularization help stabilize the full model. These findings indicate that preserving multiple localized forensic summaries prior to video-level classification is a promising strategy for improving robustness under cross-domain evaluation in deepfake video detection.<\/p>\n

Keywords: <\/strong>Deepfake detection, video forensics, representation learning, vision transformer, slot aggregation, adaptive weighting.<\/p>\n

Room Location: <\/strong>S. R. Collins Building, Room 111L<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Yonghui Wang TITLE: STRUCTURED REPRESENTATION LEARNING FOR GENERALIZABLE DEEPFAKE VIDEO DETECTION ABSTRACT Deepfake video detection has become an important problem in multimedia forensics as modern generative models produce increasingly realistic facial manipulations. Although many existing detectors achieve strong performance on the datasets on which they are trained, their performance often degrades substantially […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8560","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8560","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8560"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8560\/revisions"}],"predecessor-version":[{"id":8561,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8560\/revisions\/8561"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8560"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8560"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8560"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8560"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8555,"date":"2026-04-08T22:40:54","date_gmt":"2026-04-09T03:40:54","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8555"},"modified":"2026-04-08T23:03:28","modified_gmt":"2026-04-09T04:03:28","slug":"tarek-aziz-masters-thesis-defense-tuesday-april-21-2026-1000-am-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/tarek-aziz-masters-thesis-defense-tuesday-april-21-2026-1000-am-central-time\/","title":{"rendered":"Tarek Aziz Master\u2019s Thesis Defense, Tuesday, April 21, 2026 @ 10:00 am Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Suxia Cui
\nCO-COMMITTEE CHAIR<\/strong>: Dr. Lujun Zhai<\/p>\n

TITLE<\/strong>: EFFECTIVE DATA AUGMENTATION STRATEGIES FOR SMALL OBJECT DETECTION<\/p>\n

ABSTRACT: <\/strong>Data augmentation remains the most effective method of improving object detection, particularly in scenes where small objects dominate and the annotated datasets are small. While geometric augmentation techniques such as flipping, cropping, and photometric augmentations such as brightness, color jittering adjustments, and content-level augmentations such as mixup and copy-paste augmentation have proved useful, current research suggests the viability of learned augmentation policies, instance-level generative augmentations, and diffusion-based augmentations. Here, we present a structured comparison of the augmentation methods on the YOLO11m detector, focusing particularly on the detection of small objects on the SODA-D dataset. We benchmark the standard YOLO11m model with models learned with (i) conventional transforms, (ii) learned augmentation policies, (iii) diffusion-based semantic editing, and (iv) instance-level redrawing of images by employing pre-trained generative models. Through different experimental configurations, we see that dataset augmentation by instance-level augmentations always outperforms the rest, achieving the highest boosts in mean Average Precision (mAP) for object categories of small size. Our research also indicates that augmentations at the object-instance level guarantee preservation of scene context and introduce visual diversity, which overcomes overfitting and improves robustness. These findings provide empirical evidence for instance-aware generative augmentations being a robust and generalizable method of detecting small objects, and leave the possibility of data-efficient training pipelines for future vision tasks.<\/p>\n

Keywords: <\/strong>Small Object Detection, Data Augmentation, Generative Models, YOLO11m<\/p>\n

Room Location: <\/strong>Electrical Engineering Conference Room 315D<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Suxia Cui CO-COMMITTEE CHAIR: Dr. Lujun Zhai TITLE: EFFECTIVE DATA AUGMENTATION STRATEGIES FOR SMALL OBJECT DETECTION ABSTRACT: Data augmentation remains the most effective method of improving object detection, particularly in scenes where small objects dominate and the annotated datasets are small. While geometric augmentation techniques such as flipping, cropping, and photometric augmentations […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8555","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8555","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8555"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8555\/revisions"}],"predecessor-version":[{"id":8556,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8555\/revisions\/8556"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8555"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8555"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8555"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8555"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8521,"date":"2026-03-31T13:23:35","date_gmt":"2026-03-31T18:23:35","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8521"},"modified":"2026-03-31T14:20:55","modified_gmt":"2026-03-31T19:20:55","slug":"hussein-rajabu-masters-thesis-defense-friday-april-17-2026-230-pm-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/hussein-rajabu-masters-thesis-defense-friday-april-17-2026-230-pm-central-time\/","title":{"rendered":"Hussein Rajabu Master\u2019s Thesis Defense, Friday, April 17, 2026 @ 2:30 pm Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Xishuang Dong<\/p>\n

TITLE<\/strong>: MULTI-TASK GROWING INTERPRETABLE NEURAL NETWORK FOR MULTI-TARGET SYMBOLIC REGRESSION<\/p>\n

ABSTRACT: <\/strong>Over the past decade, deep learning has achieved remarkable success across a wide range of domains, including computer vision and natural language processing. Despite their strong performance, these models often operate as black boxes, making it difficult to understand how decisions are made. This lack of transparency poses significant challenges for deploying deep learning techniques in high-stakes applications such as healthcare and business analytics, where interpretability is essential. To address this issue, explainable artificial intelligence (XAI) and interpretable AI techniques have been developed to provide insights into model behavior. However, most existing approaches primarily capture statistical associations between inputs and outputs rather than uncovering the underlying functional mechanisms driving predictions. Symbolic regression (SR) has recently gained attention as a promising approach within interpretable AI. Unlike traditional methods, SR aims to discover explicit mathematical expressions that describe the relationships between variables, offering both interpretability and competitive predictive performance. Although SR has advanced significantly in recent years, two major challenges remain. First, SR methods are primarily developed and validated on scientific datasets, such as those from physics and chemistry, where underlying relationships are relatively well understood. This limits their applicability to broader, data-driven machine learning tasks. Second, most SR approaches focus on single-target regression, while many real-world problems involve multiple correlated outputs that share common information. To address these limitations, this thesis proposes Multi-Task Regression GINN-LP (MTRGINN-LP), a novel neuro-symbolic framework for multi-target symbolic regression. Building upon GINN-LP, the model introduces Power-Term Approximator Blocks to effectively capture power-law relationships in data. It further integrates multi-task learning through a shared backbone combined with task-specific output layers, enabling the discovery of shared symbolic representations while maintaining task-level interpretability. Additionally, a symbolic loss function is introduced to align symbolic predictions with regression outputs during training. The proposed method is evaluated on diverse multi-target regression tasks, including energy efficiency analysis and sustainable agriculture. Experimental results demonstrate that the approach achieves competitive predictive performance while preserving strong interpretability, effectively bridging the gap between symbolic regression and practical multi-output learning scenarios.<\/p>\n

Keywords: <\/strong>Interpretable AI, Multi-task Learning, Multi-target Regression, Symbolic AI<\/p>\n

Room Location: <\/strong>Electrical Engineering Conference Room 315D<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Xishuang Dong TITLE: MULTI-TASK GROWING INTERPRETABLE NEURAL NETWORK FOR MULTI-TARGET SYMBOLIC REGRESSION ABSTRACT: Over the past decade, deep learning has achieved remarkable success across a wide range of domains, including computer vision and natural language processing. Despite their strong performance, these models often operate as black boxes, making it difficult to understand […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8521","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8521","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8521"}],"version-history":[{"count":3,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8521\/revisions"}],"predecessor-version":[{"id":8530,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8521\/revisions\/8530"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8521"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8521"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8521"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8521"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8519,"date":"2026-03-31T13:15:00","date_gmt":"2026-03-31T18:15:00","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8519"},"modified":"2026-03-31T14:15:49","modified_gmt":"2026-03-31T19:15:49","slug":"temitayo-ogunsusi-masters-thesis-defense-friday-april-17-2026-1100-am-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/temitayo-ogunsusi-masters-thesis-defense-friday-april-17-2026-1100-am-central-time\/","title":{"rendered":"Temitayo Ogunsusi Master\u2019s Thesis Defense, Friday, April 17, 2026 @ 11:00 am Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Xishuang Dong<\/p>\n

TITLE<\/strong>: LLMS-BASED TEXT-TO-SQL FOR GEOSPATIAL INFORMATION RETRIEVAL<\/p>\n

ABSTRACT: <\/strong>Text-to-SQL aims to translate natural language questions into SQL queries that can be executed on databases, enabling non-expert users to retrieve information without learning formal query languages. Early Text-to-SQL systems relied on rule-based methods and semantic parsers, while recent advances in deep learning have achieved strong performance by jointly encoding user questions and database schemas. However, these approaches typically require large annotated datasets and specific model architectures. With the emergence of large language models (LLMs), such as GPT-4, Llama, and Gemma, Text-to-SQL systems can leverage powerful natural language understanding capabilities to generate SQL queries using zero-shot or few-shot prompting. Despite these advancements, existing research has largely focused on conventional relational databases, with limited attention given to geospatial databases that involve specialized spatial data types and functions. This thesis addresses this gap by investigating LLM-based Text-to-SQL for geospatial information retrieval. We construct a new benchmark dataset with a PostGIS spatial database, containing natural language questions paired with SQL queries that incorporate spatial operations such as distance calculations, spatial joins, and geometric predicates. To expand the dataset and improve diversity, additional question-query pairs are generated through LLM-based data augmentation. Furthermore, building on this benchmark, we develop a Text-to-SQL pipeline that integrates multiple state-of-the-art LLMs to translate natural language queries into executable spatial SQL statements. The system incorporates database schema information within prompts to improve query generation. Experimental results demonstrate that the proposed pipeline can effectively retrieve geospatial information using natural language queries, achieving competitive performance regarding Execution Accuracy and Valid Efficiency Score.<\/p>\n

Keywords: <\/strong>Text-to-SQL, Large Language Models, Information Retrieval, Geospatial Database<\/p>\n

Room Location: <\/strong>Electrical Engineering Conference Room 315D<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Xishuang Dong TITLE: LLMS-BASED TEXT-TO-SQL FOR GEOSPATIAL INFORMATION RETRIEVAL ABSTRACT: Text-to-SQL aims to translate natural language questions into SQL queries that can be executed on databases, enabling non-expert users to retrieve information without learning formal query languages. Early Text-to-SQL systems relied on rule-based methods and semantic parsers, while recent advances in deep […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[535],"class_list":["post-8519","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8519","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8519"}],"version-history":[{"count":3,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8519\/revisions"}],"predecessor-version":[{"id":8526,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8519\/revisions\/8526"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8519"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8519"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8519"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8519"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8517,"date":"2026-03-31T13:11:00","date_gmt":"2026-03-31T18:11:00","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8517"},"modified":"2026-03-31T13:12:57","modified_gmt":"2026-03-31T18:12:57","slug":"carl-daniel-doctoral-project-defense-monday-april-13-2026-300-pm-central-time","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/carl-daniel-doctoral-project-defense-monday-april-13-2026-300-pm-central-time\/","title":{"rendered":"Carl Daniel Doctoral Project Defense, Monday, April 13, 2026 @ 3:00 pm Central Time"},"content":{"rendered":"

COMMITTEE CHAIR<\/strong>: Dr. Sharisse Hebert<\/p>\n

TITLE<\/strong>: IMPROVING HOT DEBRIEF COMPLETION RATES AFTER RAPID RESPONSE TEAM EVENTS THROUGH QR CODE ACCESS AND DIGITAL REMINDERS: A QUALITY IMPROVEMENT PROJECT<\/p>\n

ABSTRACT: <\/strong>Rapid Response Teams (RRTs) are critical for stabilizing acutely deteriorating patients. However, structured hot debriefs, which are brief reflections held immediately after emergencies, are inconsistently documented, despite benefits for communication, safety, and staff well-being. At a large academic hospital in Southeast Texas, only 35.76% of RRT events in 2025 included completed hot debrief forms. A January 2025 hospital-led survey of Clinical Emergency Response Team (CERT) Advanced Practice Registered Nurses (APRNs) identified barriers such as time constraints, limited access, and forgetfulness. Purpose: This Doctor of Nursing Practice (DNP) quality improvement project (QI) evaluated whether a bundled intervention, QR code access to forms, twice daily SMS reminders (9:00 a.m. and 9:00 p.m.), and brief education, increases hot debrief documentation rates after RRT events. Methods: Guided by the Plan-Do-Check-Act (PDCA) framework, this pre- and post-intervention design was implemented at a large academic hospital in Southeast Texas. The project involved 40 CERT APRNs conducting adult inpatient debriefs across about 729 RRT events in three months. Microsoft Forms was used for secure data collection, and pre-\/post-surveys assessed perceived barriers and attitudes. Intervention activities included QR code distribution, scheduled twice-daily SMS reminders (9:00 a.m. and 9:00 p.m.), and structured debriefing education. Descriptive statistics and chi-square tests compared pre- and post-intervention documentation rates. The approach offered a scalable, cost-effective strategy to enhance communication, support staff recovery, and strengthen safety learning.<\/p>\n

Keywords<\/strong>: Hot Debrief, Rapid Response Team, QR Code, Digital Reminder, Advanced Practice Registered Nurse, Quality Improvement, Emergency Response, Documentation Compliance, PDCA Cycle<\/p>\n

Location Online:<\/strong><\/p>\n

Zoom Link<\/strong>: https:\/\/pvpanther.zoom.us\/j\/96912933947?pwd=7JtIHymgoSbo0fIJCofRaQJAiTVN4N.1<\/a><\/p>\n

Meeting ID<\/strong>: 933 2678 4995<\/p>\n

Passcode<\/strong>: 467899<\/p>\n","protected":false},"excerpt":{"rendered":"

COMMITTEE CHAIR: Dr. Sharisse Hebert TITLE: IMPROVING HOT DEBRIEF COMPLETION RATES AFTER RAPID RESPONSE TEAM EVENTS THROUGH QR CODE ACCESS AND DIGITAL REMINDERS: A QUALITY IMPROVEMENT PROJECT ABSTRACT: Rapid Response Teams (RRTs) are critical for stabilizing acutely deteriorating patients. However, structured hot debriefs, which are brief reflections held immediately after emergencies, are inconsistently documented, despite […]<\/p>\n","protected":false},"author":432,"featured_media":7636,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_tribe_events_status":"","_tribe_events_status_reason":"","_tribe_events_is_hybrid":"","_tribe_events_is_virtual":"","_tribe_events_virtual_video_source":"","_tribe_events_virtual_embed_video":"","_tribe_events_virtual_linked_button_text":"","_tribe_events_virtual_linked_button":"","_tribe_events_virtual_show_embed_at":"","_tribe_events_virtual_show_embed_to":[],"_tribe_events_virtual_show_on_event":"","_tribe_events_virtual_show_on_views":"","_tribe_events_virtual_url":"","_expiration-date-status":"","_expiration-date":0,"_expiration-date-type":"","_expiration-date-categories":[],"_expiration-date-options":[],"footnotes":""},"tags":[],"tribe_events_cat":[1296],"yst_prominent_words":[],"class_list":["post-8517","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","tribe_events_cat-main-events","cat_main-events"],"_links":{"self":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8517","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/users\/432"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/comments?post=8517"}],"version-history":[{"count":1,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8517\/revisions"}],"predecessor-version":[{"id":8518,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events\/8517\/revisions\/8518"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media\/7636"}],"wp:attachment":[{"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/media?parent=8517"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tags?post=8517"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/tribe_events_cat?post=8517"},{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/wp\/v2\/yst_prominent_words?post=8517"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":8513,"date":"2026-03-25T14:38:51","date_gmt":"2026-03-25T19:38:51","guid":{"rendered":"https:\/\/www.pvamu.edu\/graduateschool\/?post_type=tribe_events&p=8513"},"modified":"2026-03-25T14:39:01","modified_gmt":"2026-03-25T19:39:01","slug":"pvamu-2026-2027-general-scholarship-application-has-been-extended","status":"publish","type":"tribe_events","link":"https:\/\/www.pvamu.edu\/graduateschool\/event\/pvamu-2026-2027-general-scholarship-application-has-been-extended\/","title":{"rendered":"PVAMU 2026\u20132027 General Scholarship Application has been EXTENDED"},"content":{"rendered":"

\n

Guess what, Panthers! <\/span>🐾<\/p>\n<\/div>\n

\n

The deadline for the PVAMU 2026\u20132027 General Scholarship Application has been EXTENDED to May 15th<\/strong>! 🎉<\/p>\n<\/div>\n

\n

There\u2019s still time to secure funding for your future. Don\u2019t miss this opportunity.<\/p>\n<\/div>\n

\n

🔗Apply today: https:\/\/pvamu.academicworks.com\/<\/a><\/p>\n<\/div>\n

\n

<\/a>Best regards,<\/p>\n

 <\/p>\n

\n
\n

\"This<\/a><\/p>\n<\/div>\n<\/div>\n

Default Prevention – Financial Aid<\/a><\/p>\n

\u00a0<\/i><\/b><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Guess what, Panthers! 🐾 The deadline for the PVAMU 2026\u20132027 General Scholarship Application has been EXTENDED to May 15th! 🎉 There\u2019s still time to secure funding for your future. Don\u2019t miss this opportunity. 🔗Apply today: https:\/\/pvamu.academicworks.com\/ Best regards,   Default Prevention – Financial Aid 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