2023_02_03-Engineering - Toor Lab jatorner -0112.JPG
Overview: AI Theory, Methods, and Applications
Foundational research advances machine learning, optimization, representation learning, data mining, explainable AI, statistical learning, signal processing, and distributed intelligent systems, creating new algorithms and computational methods that enable AI systems to learn from complex data, recognize patterns, make predictions, and support intelligent decision-making.
Faculty apply these AI methods to a broad range of engineering and scientific challenges, with particular strengths in healthcare AI, biomedical data science, medical imaging, computer vision, signal and image processing, intelligent sensing, and augmented reality. Their research develops AI-enabled technologies for clinical decision support, disease diagnosis and monitoring, scientific discovery, autonomous and networked systems, immersive environments, and advanced sensing, combining domain knowledge with modern machine learning to address real-world problems.
ECE Faculty
Reinhard R. Beichel
Medical computer vision and graphics, image segmentation, lung image analysis, PET image analysis
Tyler Bell
Applied AI, virtual reality, augmented reality, real-time wireless 4D communications, real-time high-resolution 3D imaging, multimedia on mobile devices, human-computer interaction
Guadalupe Canahuate
Big data, machine learning, data integration, cancer risk modeling, cancer disparities, algorithmic fairness
Gary Christensen
Image and signal processing, medical imaging, image registration, cancer research
Soura Dasgupta
Machine learning, wireless communications systems, robust control, Parkinson’s disease
Mona Garvin
3-D segmentation of anatomic structures, machine-learning and graph-based segmentation strategies, ophthalmic disease diagnosis
Kishlay Jha
Data mining, machine learning, natural language processing, bioinformatics, health informatics
Hans Johnson
Large-scale, heterogeneous, multi-site data collections using modern high-performance computing (HPC) resources
Yang Liu
Augmented reality, imaging systems, biophotonics, 3D computer vision, cyber-physical systems, computer-assisted surgery
Raghuraman Mudumbai
Adversarial vulnerability of deep learning classifiers, asymptotic properties of synthetic text generated by LLMs, signal processing methods, wireless communication systems
Pranav Saha
Tensor scale-based image analysis, digital topology and geometry, virtual bone biopsy, image segmentation and classification
Ananya Sen Gupta
Underwater acoustical signal processing, underwater acoustic communications, raw signal processing, feature extraction, space physics, pollution studies
Milan Sonka
Automated analysis of medical images, machine ;earning-based image analysis, medical image segmentation, coronary border detection, pulmonary image analysis, ophthalmic image analysis
LOGISMOS Image Segmentation Lab, Cardiovascular Image Analysis Lab, Ophthalmic Image Analysis
Xiaodong Wu
Algorithm design and implementation, geometric optimization, biomedical image analysis, computer-aided medical diagnosis and surgery
Weiyu Xu
Signal processing, optimization, machine learning, information theory, adversarial vulnerability of deep learning classifiers