Upcoming Events

Guess what, Panthers! 🐾 The deadline for the PVAMU 2026–2027 General Scholarship Application has been EXTENDED to May 15th! 🎉 There’s still time to secure funding for your future. Don’t miss this opportunity. 🔗Apply today: https://pvamu.academicworks.com/ Best regards,   Default Prevention - Financial Aid  

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 [...]

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 [...]

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 [...]

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 [...]

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 [...]

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 [...]