biomechanics lab imageBiomechanics Laboratory:
Current studies aim to develop and apply computational models to study disorders of the oculomotor system and the musculoskeletal system. Specific projects are focused on quantifying measurement of extraocular muscle dynamics in vivo, studying the biomechanics of the rat hind limb to help understand fundamental problems in the neural control of movement, and examining the coordination of extraocualr muscles and biomechanics of strabismus.

biomedical imaging lab imageBiomedical Imaging Laboratory:
The overall thrust of our research is the development of new diagnostic ultrasound techniques and applications and translating them from laboratory experiments into practical solutions that can be used in a clinical setting (bench to bedside). Furthermore, using these techniques in a clinical setting, we seek to develop new insights and make novel observations about human physiology and function, which would be the stimulus for further basic investigations.

CN3 Lab imageThe Center for Neural Informatics, Neural Structures, and Neural Plasticity (CN3):
The Center for Neural Informatics, Structures, and Plasticity (CN3) pursues fundamental breakthroughs in neuroscience by fostering neuroinformatic and computational approaches to neuroplasticity and neuroanatomy. By bringing together faculty expertise in these multiple disciplines, the Center provides opportunities for cross-training in neuroscience, psychology, and engineering, both at the graduate and postdoctoral levels. CN3 researchers investigate the relationship between brain structure, activity, and function from the subcellular to the network level, with a specific focus on the biophysical and biochemical mechanisms of learning and memory.

Computational Biology Lab imageComputational Biology Lab:
Our lab focuses on developing algorithms to bridge between computer science and the life sciences. Our work falls in newly-coined areas such as computational structural biology and bioinformatics and combines artificial intelligence, robotics, computational geometry, statistical mechanics, and distributed computing. We investigate problems from a computational perspective concerning sequence, structure, dynamics, function, and interactions of biological molecules.

Computational and Experimental Neuroplasticity LaboratoryComputational and Experimental Neuroplasticity Laboratory:
The Computational and Experimental Neuroplasticity Laboratory is a multidisciplinary research group devoted to the study of learning and memory. We investigate the mechanisms whereby particular spatio-temporal patterns of inputs produce changes in synaptic plasticity and intrinsic excitability using both modeling and electrophysiology. As part of this research we creates novel software, both using deterministic approaches and stochastic approaches, either stand-alone or working in conjunction with other neural modeling software, in order to address otherwise intractable problems.

Computational Hemodynamics Lab
At the Computational Hemodynamics Laboratory we specialize in patient-specific modeling of blood flows in cerebral aneurysms. We develop methods and techniques to model intracranial aneurysms from 3D medical images. We combine computational modeling with clinical observations, biological and mechanical data to: 1) understand the mechanisms responsible for the development, enlargement and rupture of cerebral aneurysms; 2) enhance aneurysm risk assessment and patient evaluation; and 3) evaluate endovascular devices and procedures such as flow diversion for minimally invasive treatment of brain aneurysms.

Machine Learning and Bioinformatics lab imageMachine Learning and Bioinformatics:
The Machine Learning in Biomedical Informatics (MLBio+) Laboratory performs interdisciplinary research aimed at development of machine learning and data mining methods for problems in biology, medicine and social media analysis.There is an emphasis on development of novel algorithms, and engineering of effective solutions to discover knowledge from emerging data. Our research has resulted in development in useful and efficient software tools that aid biologists to make key discoveries, and have also advanced the field of computer science.

Microfluidic Single Cell Analysis Laboratory in Engineering (µ-SCALE)Microfluidic Single Cell Analysis Laboratory in Engineering (µ-SCALE)
The µ-SCALE lab uses a multidisciplinary approach to develop novel technologies for diagnosing and investigating diseases at the single cell level. We are enhancing our conceptual understanding of real-time cellular responses under controlled spatial and temporal micro-environments utilizing microfluidic technologies that offer an ideal approach for manipulating cells on individual basis and provide robust platforms to analyze small samples. Results from this research will solve challenges that rendered the precise identification of rare cell responses difficult at the population level.

Nanotechnology lab imageLaboratory of Nanotechnology:
The Laboratory of Nanotechnology at George Mason University focuses on the synthesis and applications of a wide range of carriers at the nano and micron-size scale including polymeric and metallic particles, micelles, liposomes, carbon nanotubes and metal-organic frameworks. At the fundamental level, we aim to understand the mechanisms involved in the formation of such carriers to acquire high control in their physicochemical properties. At the applied level, we use those carriers in drug delivery, vaccines, imaging, biodefense, agriculture, medical devices and microelectronics projects.

Neural lab imageNeural Engineering Lab:
Our two main thrusts are the development of prosthetic devices (or parts of devices) to help people with disabilities, in particular with pathologies of the nervous system. The second area we work on is neuronal cell cultures and biosensors.

Sensorimotor Integration lab imageSensorimotor Integration Laboratory:
Our translational research investigates human sensory integration, motor learning and control. This encompasses two major themes. The first involves applying engineering control theory to biological systems, specifically modeling the behavior of the oculomotor and arm movement systems. The second, using behavioral approaches, involves determining the neural mechanisms that underlie visual stability and perception, specifically during the disruptions to visual input that occur during eye movements used to sample the environment.