Visual Computing and Biometric Security Lab (VCBSL)
The Visual Computing and Biometric Security Lab is a research group comprising undergraduates, Masters, and Ph.D. students directed by Dr. Ajita Rattani.
The lab's mission is to conduct cutting-edge research in advanced techniques concerning Visual Computing and Biometric Security.
Visual Computing is a broad term that encompasses several areas in computer science including computer vision image and video processing, machine learning,
deep learning, and pattern recognition. Biometrics is the art of recognizing individuals based on their physiological or behavioral characteristics.
Current research activities of the research group include studying the Bias and Fairness of AI systems, Deepfake Detection, Models for On-device AI, Wearable Biometrics,
Harnessing Unlabeled Data for Domain Adaptation, Computer Vision for Natural Disaster Assessment, and AI for Healthcare and Obesity Prediction.
News
- 04/29/2026 Dr. Rattani received the CSE Tenure-Track Faculty Teaching Award at the University of North Texas for excellence in teaching and student mentorship.
- 04/26/2026 Our paper titled "DF-OOD: Real-Only Deepfake Detection via Confidence Dynamics under Perturbations” is accepted at IEEE Intl Conf. on Automatic Face and Gesture Recognition (FG 2026) workshop, 2026.
- 03/31/2026 Our paper titled "DATS-AV: A Dissonance-Aware Two-Stage Framework for Audio–Visual Deepfake Detection” is accepted at IAPR ICPR, 2026.
- 03/29/2026 Congratulations to Dr. Ramachandran on being appointed as a Postdoctoral Associate at Yale University.
- 03/27/2026 Our paper titled "AudioAuth: A Dual-Watermarking Framework for Robust Audio Integrity and Source Attribution" is accepted at IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), 2026.
- 02/21/2026 Our paper titled "MMFace-DiT: A Dual-Stream Diffusion Transformer for High-Fidelity Multimodal Face Generation" is accepted at The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
- 01/17/2026 Our paper titled "VOXMORPH: Scalable Zero-Shot Voice Identity Morphing via Disentangled Embeddings" is accepted at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2026.
