Benoit Dawant, Ph.D.

Cornelius Vanderbilt Professor of Engineering
Professor of Electrical Engineering
Professor of Computer Science
Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Neurological Surgery
Professor of Otolaryngology-Head and Neck Surgery
Director, Vanderbilt Institute for Surgery and Engineering (VISE)

Bio

The medical image processing (MIP) laboratory of the Electrical Engineering and Computer Science (EECS) Department conducts research in the area of medical image processing and analysis. The core algorithmic expertise of the laboratory is image segmentation and registration. The laboratory is involved in a number of collaborative projects, both with others in the engineering school and with investigators in the medical school. Ongoing research projects include developing and testing image processing algorithms to (1) automatically localize radiosensitive structures to facilitate radiotherapy planning, (2) assist in the placement and programming of Deep Brain Stimulators used to treat Parkinson’s disease, (3) localize automatically structures that need to be avoided while placing cochlear implants, (4) develop methods for cochlear implant programming or (5) track brain shift during surgery. The laboratory expertise spans the entire spectrum between algorithmic development and clinical deployment. Several projects that have been initiated in the laboratory have been translated to clinical use or have reached the stage of clinical prototype at Vanderbilt and at other collaborative institutions. Components of these systems have been commercialized.

Yuankai Huo, Ph.D.

Assistant Professor of Computer Science
Assistant Professor of Computer Engineering

Bio

The HRLB lab aims to facilitate data-driven healthcare and improve patient outcomes through innovations in medical image analysis as well as multi-modal data representation and learning. Our current focus is on quantifying high-resolution and spatial-temporal data from microscopy imaging techniques, including renal pathology, cancer pathology, cytology and computational biology. The quantitative imaging information is associated with molecular, genetic and clinical features for precise diagnosis and treatment.

Bennett Landman, Ph.D.

Chair, Department of Electrical and Computer Engineering
Professor of Electrical and Computer Engineering
Professor of Computer Science
Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Psychiatry and Behavioral Sciences
Professor of Biomedical Informatics
Professor of Neurology

Bio

My primary area of scientific focus is medical image processing with robust and scalable methods for large-scale data analysis. Across my research portfolio, projects in my laboratory seek to connect the image processing methods with both the medical physics underpinning of the data and their clinical applications. My overarching goal is to combine image-processing technologies and electronic health data to improve understanding of individual anatomy and personalized medicine. In this direction, I have worked extensively in machine learning pertaining to neuroimaging and medical image processing.

Jack Noble, Ph.D.

Assistant Professor of Electrical and Computer Engineering
Assistant Professor of Computer Science
Assistant Professor of Biomedical Engineering
Assistant Research Professor of Hearing and Speech Sciences (DHSS)
Assistant Professor of Head and Neck Surgery
Director of Graduate Student Recruitment

Bio

Biomedical image analysis techniques are transforming the way many clinical interventions are performed and enabling the creation of new computer-assisted interventions and surgical procedures. The Biomedical Image Analysis for Image-Guided Interventions Lab (BAGL) investigates novel medical image processing and analysis techniques with emphasis on creating image analysis-based solutions to clinical problems. The lab explores state-of-the-art image analysis techniques, such as machine learning, statistical shape models, graph search methods, level set techniques, image registration techniques and image-based bio-models. The lab is currently developing novel systems for cochlear implant procedures including systems that use image analysis techniques for (1) comprehensive pre-operative surgery planning and intra-operative guidance and (2) post-operative informatics to optimize hearing outcomes.

Ipek Oguz, Ph.D.

Assistant Professor of Computer Science
Assistant Professor of Electrical and Computer Engineering

Bio

The Medical Image Computing Lab (MedICL) develops image analysis and machine learning algorithms in the context of medical imaging studies. Our algorithmic work mainly focuses on the image segmentation and image synthesis tasks. We have a wide portfolio of clinical applications including brain MRIs, retinal OCT, placenta ultrasound and kidney ureteroscopy. 

Brett Byram, Ph.D.

Associate Professor of Biomedical Engineering

Bio

The biomedical elasticity and acoustic measurement (BEAM) lab is interested in pursuing ultrasonic solutions to clinical problems. Brett Byram and the BEAM lab’s members have experience with most aspects of systems level ultrasound research, but our current efforts focus on advanced pulse sequencing and algorithm development for motion estimation and beamforming. The goal of our beamforming work is to make normal ultrasound images as clear as intraoperative ultrasound, the gold-standard for many applications. We have recently demonstrated non-contrast tissue perfusion imaging with ultrasound at clinical frequencies, and we are developing novel ultrasound transducers to enhance guidance for percutaneous procedures.

Catie Chang, Ph.D.

Sally and Dave Hopkins Faculty Fellow
Assistant Professor of Computer Science
Assistant Professor of Electrical and Computer Engineering
Assistant Professor of Biomedical Engineering

Bio

The goal of our research is to advance understanding of brain function in health and disease. We develop approaches for studying human brain activity by integrating functional neuroimaging (fMRI, EEG) and computational analysis techniques. In one avenue, we are examining the dynamics of large-scale brain networks and translating this information into novel fMRI biomarkers. To enable clearer inferences about brain function with fMRI, we also work toward resolving the complex neural and physiological underpinnings of fMRI signals. Our research is highly interdisciplinary and collaborative, bridging fields such as engineering, computer science, neuroscience, psychology and medicine.

Dario Englot, M.D., Ph.D.

Associate Professor of Neurological Surgery
Associate Professor of Radiology and Radiological Sciences
Associate Professor of Biomedical Engineering
Associate Professor of Electrical and Computer Engineering
Associate Professor of Neurology
Director of Functional Neurosurgery

Bio

The BIEN lab integrates human neuroimaging and electrophysiology techniques to study brain networks in both neurological diseases and normal brain states. The lab is led by Dario Englot, a functional neurosurgeon at Vanderbilt. One major focus of the lab is to understand the complex network perturbations in patients with epilepsy, by relating network changes to neurocognitive problems, disease parameters and changes in vigilance in this disabling disease. Multimodal data from human intracranial EEG, functional MRI, diffusion tensor imaging and other tools are utilized to evaluate resting-state, seizure-related and task-based paradigms. Other interests of the lab include the effects of brain surgery and neurostimulation on brain networks in epilepsy patients, and whether functional and structural connectivity patterns may change in patients after neurosurgical intervention. Through studying disease-based models, the group also hopes to achieve a better understanding of normal human brain network physiology related to consciousness, cognition and arousal. Finally, surgical outcomes in functional neurosurgery, including deep brain stimulation, procedures for pain disorders and epilepsy, are also being investigated.

Yuankai Huo, Ph.D.

Assistant Professor of Computer Science
Assistant Professor of Computer Engineering

Bio

The HRLB lab aims to facilitate data-driven healthcare and improve patient outcomes through innovations in medical image analysis as well as multi-modal data representation and learning. Our current focus is on quantifying high-resolution and spatial-temporal data from microscopy imaging techniques, including renal pathology, cancer pathology, cytology and computational biology. The quantitative imaging information is associated with molecular, genetic and clinical features for precise diagnosis and treatment.

Nicholas Kavoussi, M.D.

Assistant Professor  Department of Urology
Division of Endourology and Stone Disease

Bio

Minimally invasive urologic surgery improves recovery time, pain, bleeding and cosmesis compared to traditional, open surgical approaches. Despite this, lack of visualization, navigation and haptic feedback limit minimally invasive interventions and contribute to complications and disease recurrence events. My team and I are leveraging computer vision and machine learning technology to improve navigation and surgical vision intraoperatively to enhance minimally invasive urologic surgery.

Soheil Kolouri, Ph.D.

Assistant Professor of Computer Science

Bio

At the Machine Intelligence and Neural Technologies (MINT) Lab, we develop next-generation core Machine Learning (ML) solutions for practical problems in medicine and strive to advance healthcare. Our interdisciplinary team at MINT Lab uses biological inspirations together with mathematical and geometrical tools to innovate theoretically grounded algorithms that address the current deficiencies in ML technologies regarding lifelong/continual learning, sample/label efficiency, explainability and brittleness. In one of our main research thrusts, we develop brain-inspired, robust machine intelligence that can continually learn and adapt to the input stream of nonstationary multimodal data. Continual learning is specifically relevant to medical applications where: 1) the data is continually accumulated from new patients and 2) diseases constantly mutate and new variants emerge. We are developing next-generation computational models that adapt to these constant variations, learn from the past to solve future problems and leverage new knowledge to improve the previous solutions. Our research is highly interdisciplinary, and we have collaborations across fields including computer science, biomedical engineering, cognitive science, electrical engineering and neuroscience.

Bennett Landman, Ph.D.

Chair, Department of Electrical and Computer Engineering
Professor of Electrical and Computer Engineering
Professor of Computer Science
Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Psychiatry and Behavioral Sciences
Professor of Biomedical Informatics
Professor of Neurology

Bio

My primary area of scientific focus is medical image processing with robust and scalable methods for large-scale data analysis. Across my research portfolio, projects in my laboratory seek to connect the image processing methods with both the medical physics underpinning of the data and their clinical applications. My overarching goal is to combine image-processing technologies and electronic health data to improve understanding of individual anatomy and personalized medicine. In this direction, I have worked extensively in machine learning pertaining to neuroimaging and medical image processing.

Victoria Morgan, Ph.D.

Professor of Radiology and Radiological Sciences
Professor of Biomedical Engineering
Professor of Neurology
Professor of Neurological Surgery

Bio

The Morgan Engineering and Imaging in Epilepsy Lab works closely with the departments of Neurology and Neurosurgery to develop Magnetic Resonance Imaging (MRI) methods to improve neurosurgical outcomes, particularly for patients with epilepsy. We directly support clinical care by developing and providing functional MRI to localize the eloquent cortex in the brain to aid in surgical planning to minimize functional and cognitive deficits post-surgery. Our research focuses on mapping functional and structural brain networks in epilepsy before and after surgical treatment. Our research is funded by the National Institutes of Health.

Daniel Moyer, Ph.D.

Assistant Professor of Computer Science

Bio

Professor Moyer’s group is working to bridge the gap between Machine Learning and Medical Imaging. We work directly with clinicians and researchers to translate advances in computer vision to better outcomes for patients and new discoveries in imaging-based scientific fields. While we’re most used to MRI and CT, we’re not afraid to look into new domains, and we’re always happy to meet with new potential collaborators to discuss what might be possible.

Ipek Oguz, Ph.D.

Assistant Professor of Computer Science
Assistant Professor of Electrical and Computer Engineering

Bio

The Medical Image Computing Lab (MedICL) develops image analysis and machine learning algorithms in the context of medical imaging studies. Our algorithmic work mainly focuses on the image segmentation and image synthesis tasks. We have a wide portfolio of clinical applications including brain MRIs, retinal OCT, placenta ultrasound and kidney ureteroscopy. 

Mikail Rubinov, Ph.D.

Assistant Professor of Biomedical Engineering
Assistant Professor of Computer Science
Assistant Professor of Psychiatry
Assistant Professor of Psychology

Bio

The Rubinov Lab focuses on network analysis and modeling of whole-brain structure and activity across species and scales. The lab pursues a three-pronged approach to achieve these aims. First, we develop unbiased algorithms and software tools for network analysis of structural and functional neuroscience datasets. Second, we collaborate with computational geneticists to investigate the genetic and transcriptomic basis of brain network organization in health and disease. Third, we create interpretable models of whole-brain activity that bridge the gap between micro- and macroscales of brain-network organization.

James Weimer, Ph.D. 

Assistant Professor of Computer Science

Bio

The internet of medical things (IoMT) consists of devices, infrastructure and software connected through communication networks (e.g., the internet or hospital intranet). Consequently, in the past decade, the IoMT has grown to incorporate most commercial medical devices and consumer health products. In the IoMT lab, we seek to push the boundaries of how the IoMT can impact clinical care and patient health. The IoMT lab connects clinicians and engineers with the IoMT to create new inter-operable learning-enabled medical systems. Through collaborative interdisciplinary use-inspired research, we seek to address three foundational challenges facing the IoMT. First, the IoMT requires systems and protocols for identifying and collecting the right data in a timely manner. Second, the IoMT data must be processed to provide actionable feedback to clinicians and caregivers. Third, the IoMT should safely automate some aspects of care to reduce clinician and caregiver workload. To maximize the real-world IoMT lab impact, we go beyond traditional academic research and innovate — often developing intellectual property that is licensed to commercial entities. Through licensing and research, the IoMT lab has partnered with startup companies such as Neuralert and Vasowatch, as well as larger companies including Hill-Rom. Graduate and undergraduate students in the IoMT Lab have a unique educational experience that includes working side-by-side with clinicians. In the IoMT lab, students are encouraged to not only work on lab projects, but to pursue their own ideas as they learn to be both researchers and innovators in medical devices and health technologies.

Jie Ying Wu, Ph.D.

Assistant Professor of Computer Science

Bio

At the MAPLE lab, our goal is to build intelligent surgical robots that can assist surgeons in the operation room. While surgical robots have changed many procedures by providing higher dexterity, motion scaling and other innovations, they are still only extensions of the surgeon’s arms. By modeling different aspects of surgery and how they interact, we aim to make the robots more capable. We use machine learning to augment traditional modeling techniques, such as correcting physics-based soft-tissue models with observations of tissue interactions. We work with clinicians to use accurate soft-tissue models to provide guidance during surgeries based on preoperative imaging. Another project looks at modeling how expert surgeons move surgical instruments and the endoscope during procedures, which can help us develop better ways to train novice surgeons. At the same time, we are building models of the trainee’s actions, eye-gaze and pupillometry to obtain insight into their cognitive load. We use this to develop a personalized curriculum and feedback.

Maizie Zhou, Ph.D.

Assistant Professor of Biomedical Engineering

Bio

The overarching goal of my lab is to understand how we generate intelligent behavior through normal brain development and learning-induced plasticity, and the consequences of defects in these processes. We investigate multiple dimensions of these questions, spanning computational genomics, bioinformatics, computational neuroscience and machine learning. Our approach tackles a range of data science problems, including designing new probabilistic models in high-throughput sequencing data with applications to human genomics and metagenomics, data mining of large cohort studies in neurological diseases and understanding dynamical behavior and function of neural circuits. Our work has wide-ranging implications for the normal function of the brain, for the causes and treatments of neurodevelopmental disorders, and for practical applications for the next generation of intelligent systems.

Eric Barth, Ph.D.

Professor of Mechanical Engineering
Director of Graduate Studies
Faculty Head of Hank Ingram House

Bio

Our Lab seeks to develop and experimentally apply a system-dynamics and control perspective to problems involving the control and transduction of energy. This is typically applied to problems in the fluid power domain (pneumatics and hydraulics) mixed with other energy domains (mechanical, thermal, etc.). Our specific expertise in precision pneumatic control and mechanical design has enabled the realization of MRI compatible, pneumatically actuated, robotic platforms capable of accurate manipulation and force control for surgical tasks. Our lab is one of a handful in the world that have experimentally achieved control of pneumatic systems at the submillimetric accuracies needed for MRI compatible surgical systems. Pneumatic systems are highly nonlinear, high order dynamic systems and require sophisticated model-based nonlinear control for stability robustness, desirable dynamic response and high accuracy positioning. Our lab also has an interest in designing and controlling pneumatic and hydraulic-powered soft robots for clinical and non-clinical applications. Most recent research efforts have focused on MRI compatible pneumatically actuated robotics, mechanical circulatory support devices including artificial hearts and soft robotics, a new class of robot.

Benoit Dawant, Ph.D.

Cornelius Vanderbilt Professor of Engineering
Professor of Electrical Engineering
Professor of Computer Science
Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Neurological Surgery
Professor of Otolaryngology-Head and Neck Surgery
Director, Vanderbilt Institute for Surgery and Engineering (VISE)

Bio

The medical image processing (MIP) laboratory of the Electrical Engineering and Computer Science (EECS) Department conducts research in the area of medical image processing and analysis. The core algorithmic expertise of the laboratory is image segmentation and registration. The laboratory is involved in a number of collaborative projects, both with others in the engineering school and with investigators in the medical school. Ongoing research projects include developing and testing image processing algorithms to (1) automatically localize radiosensitive structures to facilitate radiotherapy planning, (2) assist in the placement and programming of Deep Brain Stimulators used to treat Parkinson’s disease, (3) localize automatically structures that need to be avoided while placing cochlear implants, (4) develop methods for cochlear implant programming or (5) track brain shift during surgery. The laboratory expertise spans the entire spectrum between algorithmic development and clinical deployment. Several projects that have been initiated in the laboratory have been translated to clinical use or have reached the stage of clinical prototype at Vanderbilt and at other collaborative institutions. Components of these systems have been commercialized.

Craig Duvall, Ph.D.

Cornelius Vanderbilt Professor of Engineering
Professor of Biomedical Engineering
Professor of Chemical and Biomolecular Engineering
Professor of Ophthalmology and Visual Sciences
Director of Graduate Studies in Biomedical Engineering

Bio

The Duvall Advanced Therapeutics Laboratory specializes in design and application of smart polymer-based technologies for: (1) wound healing and tissue repair, (2) intracellular delivery of biological drugs such as peptides and nucleic acids, (3) targeting of drugs to disease sites and (4) long-term, “on-demand” drug release from localized depots. Outside of polymeric biomaterials, we also work on RNA chemistry, carrier-fre RNA therapeutic design and protein and RNA engineering for gene editing applications. We generally seek to innovate technologies that improve the therapeutic index of existing drugs and/or to serve as enabling technologies for manipulation of conventionally “undruggable” intracellular targets.

Alexander Langerman, M.D.

Associate Professor  Department of Otolaryngology, Head & Neck Surgery
Director  Surgical Ethics Program
Course Director  Foundations of Clinical Care Ethics Curriculum

Bio

Dr. Langerman focuses on the intersection of ethics, data science and management in the operating room, and he has faculty positions in the Vanderbilt Center for Biomedical Ethics and Society and the Vanderbilt Institute for Surgery and Engineering. Dr. Langerman holds a master’s degree in clinical and administrative data science and is a fellowship-trained clinical medical ethicist. He is also Chief Medical Officer of ExplORer Surgical, a startup he co-founded that specializes in real-time surgical data acquisition.

Michael Miga, Ph.D.

Harvie Branscomb Professor
Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Neurological Surgery
Professor of Otolaryngology
Director of Graduate Studies in Engineering in Surgery and Intervention

Bio

The focus of the Biomedical Modeling Laboratory (BML) is on new paradigms in detection, diagnosis, characterization and treatment of disease through the integration of computational models into research and clinical practice. With the continued improvements in high performance computing, the ability to translate computational modeling from predictive roles to ones that are more integrated within diagnostic and therapeutic applications is becoming a rapid reality. With respect to therapeutic applications, efforts in deformation correction for image-guided surgery applications in brain, liver, kidney and breast are being investigated. Other applications in deep brain stimulation, ablative therapies, neoadjuvant chemotherapy and convective chemotherapy are also being investigated. With respect to diagnostic imaging, applications in elastography, strain imaging, model-based chemotherapeutic tumor response and radio-therapy response parameterizations are also of particular interest. The common thread that ties the work together is that, throughout each research project, the integration of mathematical models, tissue mechanics, instrumentation and analysis is present with a central focus at translating the information to directing therapy/intervention or characterizing tissue changes for diagnostic value.

Jack Noble, Ph.D.

Assistant Professor of Electrical and Computer Engineering
Assistant Professor of Computer Science
Assistant Professor of Biomedical Engineering
Assistant Research Professor of Hearing and Speech Sciences (DHSS)
Assistant Professor of Head and Neck Surgery
Director of Graduate Student Recruitment

Bio

Biomedical image analysis techniques are transforming the way many clinical interventions are performed and enabling the creation of new computer-assisted interventions and surgical procedures. The Biomedical Image Analysis for Image-Guided Interventions Lab (BAGL) investigates novel medical image processing and analysis techniques with emphasis on creating image analysis-based solutions to clinical problems. The lab explores state-of-the-art image analysis techniques, such as machine learning, statistical shape models, graph search methods, level set techniques, image registration techniques and image-based bio-models. The lab is currently developing novel systems for cochlear implant procedures including systems that use image analysis techniques for (1) comprehensive pre-operative surgery planning and intra-operative guidance and (2) post-operative informatics to optimize hearing outcomes.

Nabil Simaan, Ph.D.

Professor of Mechanical Engineering
Professor of Computer Science
Professor of Otolaryngology

Bio

ARMA is focused on advanced robotics research including robotics, mechanism design, control and telemanipulation for medical applications. We focus on enabling technologies that necessitate novel design solutions that require contributions in design modeling and control. ARMA has led the way in advancing several robotics technologies for medical applications including high dexterity snake-like robots for surgery, steerable electrode arrays for cochlear implant surgery, robotics for single port access surgery and natural orifice surgery. Current and past funded research includes transurethral bladder cancer resection (NIH), trans-oral minimally invasive surgery of the upper airways (NIH), single port access surgery (NIH), technologies for robot surgical situational awareness (National Robotics Initiative), Micro-vascular surgery and microsurgery of the retina (VU Discovery Grant), Robotics for cochlear implant surgery (Cochlear Corporation). We collaborate closely with industry on translation of our research. Examples include technologies for snake robots licensed to Intuitive Surgical, technologies for microsurgery of the retina which lead to the formation of AURIS surgical robotics Inc., the IREP single port surgery robot which has been licensed to Titan Medical Inc. and serves as the research prototype behind the Titan Medical Inc. SPORT (Single Port Orifice Robotic Technology).

Michael Topf, M.D.

Assistant Professor of Otolaryngology-Head and Neck Surgery

Bio

Dr. Michael Topf's research aims to improve communication between cancer surgeons and pathologists through real time 3D scanning of surgical specimens. He is also interested in augmented/mixed reality surgery to guide resection of tumors. His current research in collaboration with Jie Ying Wu PhD focuses on auto-alignment of holographic images to improve surgical decision making.

Robert Webster, Ph.D.

Richard A. Schroeder Professor of Mechanical Engineering
Professor of Mechanical Engineering
Professor of Electrical Engineering
Professor of Otolaryngology
Professor of Neurological Surgery
Professor of Urologic Surgery
Professor of Medicine

Bio

The Vanderbilt School of Engineering’s Medical Engineering and Discovery (MED) Laboratory pursues research at the interface of surgery and engineering. Our mission is to enhance the lives of patients by engineering better devices and tools to assist physicians. Much of our current research involves designing and constructing the next generation of surgical robotic systems that are less invasive, more intelligent and more accurate. These devices typically work collaboratively with surgeons, assisting them with image guidance and dexterity in small spaces. Creating these devices involves research in design, modeling, control and human interfaces for novel robots. Specific current projects include needle-sized tentacle-like robots, advanced manual laparoscopic instruments with wrists and elbows, image guidance for high-accuracy inner ear surgery and abdominal soft tissue procedures and swallowable pill-sized robots for interventions in the gastrointestinal tract.

Justin Baba, Ph.D.

Adjoint Associate Professor of Biomedical Engineering

Bio

The Baba Lab is a part of the Vanderbilt Biophotonics Center and focuses on optical-based non-invasive sensing and diagnostics developments that include imaging and low-cost solutions for clinical translation. We have ongoing collaborations with several departments at Vanderbilt University Medical Center and the Children’s hospital.

Matthew D. Bacchetta, M.D.

Professor of Cardiac Surgery, Thoracic Surgery, and Biomedical Engineering
H. William Scott, Jr. Chair in Surgery
Department of Cardiac Surgery
Surgical Director Vanderbilt Respiratory Institute
Director VUMC ECMO Program

Bio

The LOR3 is focused on creating organ support systems that provide extended physiologic support for injured organs, bioengineering platforms for organ recovery and regeneration as well as developing artificial pulmonary assist devices. The lab maintains a full complement of devices used for extracorporeal life support and has developed durable support systems for lung and liver with translational potential. It works in partnerships with programs at VUMC, Carnegie Mellon University and Columbia University. The LOR3 is dedicated to translating basic science research into clinical platforms for patients with end organ failure.

Audrey Bowden, Ph.D.

Dorothy J. Wingfield Phillips Chancellor's Faculty Fellow
Associate Professor of Biomedical Engineering
Associate Professor of Electrical Engineering

Bio

The primary aim of the Bowden Biomedical Optics Laboratory (BBOL) is to develop and deploy novel imaging and sensing technologies to address unmet clinical needs in medicine and biology. We blend knowledge and experience from diverse fields such as optics, microfluidics, signal processing and computer science to develop software- and hardware-based tools for the healthcare provider that advance the state of the art and aid in scientific discovery. While the majority of our solutions are relevant to optics, as engineers, we are committed to taking a “whatever means necessary” approach to solving the clinical problem. We are also committed to developing novel solutions to improve delivery and affordability of healthcare in low-resource and resource-constrained environments. Our technologies and projects have found application in various clinical departments, including urology, dermatology, otolaryngology and women’s health.

Christos Constantinidis, Ph.D.

Professor of Biomedical Engineering and Stevenson Chair
Professor of Neuroscience
Professor of Ophthalmology & Visual Sciences

Bio

A closed-loop stimulation system of cortical activity. Research in our laboratory investigates the neural basis of cognitive functions, using non-human primate models. Recordings from arrays of microelectrodes implanted in the cerebral cortex can allow us to monitor ongoing patterns of activity as animals engage in cognitive functions. The project involves designing an apparatus that will allow us to decode the contents of working memory in real time and stimulate a pattern of activity to induce artificial patterns of memories.

Dan France, Ph.D., MPH

Research Professor of Anesthesiology
Research Professor of Medicine
Research Professor of Biomedical Engineering

Bio

Dr. France is a Research Professor of Anesthesiology, Nursing, Medicine and Biomedical Engineering at the Vanderbilt University School of Medicine. He is a research scientist in the Department of Anesthesiology’s Center for Research and Innovation in Systems Engineering (CRISS). In the School of Nursing, Dr. France teaches courses in Quality Improvement and Patient Safety and Design Thinking and Healthcare Innovation in the Master of Science and Doctor of Nursing Practice programs. Dr. France earned a doctorate in Biomedical Engineering from Vanderbilt University and a Master of Public Health from the University of Utah. He has also received advanced training in Healthcare Delivery Improvement from Intermountain Health Care in Salt Lake City, Utah. Prior to joining Vanderbilt, Dr. France worked as a systems engineer for the Department of Defense, the MITRE Corporation and L-3 Communications. His professional focus is on health systems engineering and his primary research aims are to model and explain the relationships between hospital efficiency, provider performance and patient safety. Dr. France is particularly interested in applying knowledge from other high-risk industries and methods from human factors and systems engineering to study and improve operational efficiency and individual and team performance in complex, high-risk clinical environments. He has received grant support from the Agency for Healthcare Research and Quality (AHRQ), National Institutes of Health (NIH), National Science Foundations (NSF), Department of Homeland Security (DHS) and Veteran’s Health Administration (VHA). As an example, ongoing projects are in (1) surveillance-and response systems to detect and respond to clinical deterioration in cancer outpatients, (2) realtime measurement of situational workload, (3) measuring NICU nurse practitioner workload and (4) health record usability and detection of medical error.

E. Duco Jansen, Ph.D.

Senior Associate Dean for Graduate Education and Faculty Affairs
Professor of Biomedical Engineering
Professor of Neurological Surgery

Bio

Laser-tissue interaction; optical neural interfaces; modulation of neural activity using infrared laser light; cellular effects of laser-induced stimuli; application of light, lasers and optical technology in medicine and biology.

Alexander Langerman, M.D.

Associate Professor  Department of Otolaryngology, Head & Neck Surgery
Director  Surgical Ethics Program
Course Director  Foundations of Clinical Care Ethics Curriculum

Bio

Dr. Langerman focuses on the intersection of ethics, data science and management in the operating room, and he has faculty positions in the Vanderbilt Center for Biomedical Ethics and Society and the Vanderbilt Institute for Surgery and Engineering. Dr. Langerman holds a master’s degree in clinical and administrative data science and is a fellowship-trained clinical medical ethicist. He is also Chief Medical Officer of ExplORer Surgical, a startup he co-founded that specializes in real-time surgical data acquisition.

Anita Mahadevan-Jansen, Ph.D.

Professor of Biomedical Engineering
Orrin H. Ingram Professor of Engineering
Director of Undergraduate Studies in Biomedical Engineering
Professor of Neurological Surgery
Director of the Biophotonics Center at Vanderbilt

Bio

The Vanderbilt Biophotonics Center (VBC) is a trans-institutional initiative focusing on biophotonics research, technology development and education at Vanderbilt University. The center spans across multiple schools (Engineering, Medicine and Arts & Science) and interfaces with existing centers and institutes (VICC, VINSE, VUIIS, VBI, VIIBRE, ViSE) while being anchored in Engineering. The research mission is centered around three main areas: Cancer photonics, Neuro-photonics and Multiscale photonics. Faculty at VBC seek to develop and apply photonics technologies for fundamental discovery and clinical translation. Dr. Mahadevan-Jansen serves as the director of VBC. Her own research expertise is in the clinical translation of optical techniques for solving specific problems in patients with light.

Yuankai (Kenny) Tao, Ph.D.

Assistant Professor of Biomedical Engineering

Bio

The Diagnostic Imaging & Image-Guided Interventions Laboratory (DIIGI Lab) develops novel optical imaging systems for clinical diagnostics and therapeutic monitoring. Optical technologies provide access to multi-scale resolutions that span single cells to whole organs. We employ a combination of technology and algorithms development to provide unique solutions to address challenges in basic sciences and clinical care. Our research primarily focuses on applications in ophthalmology and are centered on the following thrusts: 1) Intraoperative Optical Coherence Tomography (iOCT); 2) Point-of-Care Ophthalmic Diagnostics; and 3) Mechanisms of Retinal Regeneration.

Wesley P. Thayer, M.D., Ph.D.

Professor of Plastic Surgery and Orthopaedic Surgery
Vice Chair, Research

Bio

My lab focuses on translational research including wounds, hand surgery, and nerve repair strategies to improve outcomes after injury. We have published multiple peer reviewed publications focusing on these techniques. Our Lab is funded through a collaborative DOD grant with AxogenTM Corporation. Our most recent grant includes industry funding to studying bio scaffolds for use as a nerve scaffold. We are also playing a role in the advancement of techniques to enhance recovery of acutely injured nerves including axonal outgrowth augmentation strategies and axonal fusion strategies. In our animal models, we are able to assess interventions ability to foster improvement and optimize those strategies that may translatable to clinical application. Our treatment strategies have applications for trauma patients, oncology patients, and in composite tissue transplantation. At present I am motivated to participate in both bench and clinical research. To that end, I direct the Vanderbilt arm of the Multicenter Retrospective Study of Avance™ Nerve Graft Utilization, Evaluations and Outcomes in Peripheral Nerve Injury Repair, or RANGER study and completed a trial for evaluation of Xiaflex™ in treatment of Dupuytren’s contractures. Our most recent human trial involves using MRI based diffusion tensor tractography to evaluate individual axonal recovery after human nerve injury. We have built an infrastructure at Vanderbilt University Medical Center to efficiently and accurately assess strategies to augment nerve repair at the cellular level with our in vitro models, at the surgical level with our animal models, and translate these strategies to the clinic via IRB approved clinical trials.

Michael Topf, M.D.

Assistant Professor of Otolaryngology-Head and Neck Surgery

Bio

Dr. Michael Topf's research aims to improve communication between cancer surgeons and pathologists through real time 3D scanning of surgical specimens. He is also interested in augmented/mixed reality surgery to guide resection of tumors. His current research in collaboration with Jie Ying Wu PhD focuses on auto-alignment of holographic images to improve surgical decision making.

James Weimer, Ph.D. 

Assistant Professor of Computer Science

Bio

The internet of medical things (IoMT) consists of devices, infrastructure and software connected through communication networks (e.g., the internet or hospital intranet). Consequently, in the past decade, the IoMT has grown to incorporate most commercial medical devices and consumer health products. In the IoMT lab, we seek to push the boundaries of how the IoMT can impact clinical care and patient health. The IoMT lab connects clinicians and engineers with the IoMT to create new inter-operable learning-enabled medical systems. Through collaborative interdisciplinary use-inspired research, we seek to address three foundational challenges facing the IoMT. First, the IoMT requires systems and protocols for identifying and collecting the right data in a timely manner. Second, the IoMT data must be processed to provide actionable feedback to clinicians and caregivers. Third, the IoMT should safely automate some aspects of care to reduce clinician and caregiver workload. To maximize the real-world IoMT lab impact, we go beyond traditional academic research and innovate — often developing intellectual property that is licensed to commercial entities. Through licensing and research, the IoMT lab has partnered with startup companies such as Neuralert and Vasowatch, as well as larger companies including Hill-Rom. Graduate and undergraduate students in the IoMT Lab have a unique educational experience that includes working side-by-side with clinicians. In the IoMT lab, students are encouraged to not only work on lab projects, but to pursue their own ideas as they learn to be both researchers and innovators in medical devices and health technologies.

Matthew Weinger, M.D.

Norman Ty Smith Chair in Patient Safety and Medical Simulation
Professor of Anesthesiology, Biomedical Informatics and Medical Education
Professor of Civil and Environmental Engineering
Director, Center for Research and Innovation in Systems Safety (CRISS)

Bio

The Center for Research and Innovation in Systems Science (CRISS) conducts basic and applied human factors and systems engineering research in healthcare technology and information systems, clinical quality and safety, and designs and evaluates user experiences, user interfaces, care processes and systems across multiple domains and disciplines. Our faculty collaborate with faculty in Vanderbilt's Schools of Engineering, Music, Medicine and Nursing. We also collaborate on surgical innovation and training with the Hospital virtual Valdecilla and the Hospital Universitario Marquis de Valdecilla in Santander, Spain.

Eric Barth, Ph.D.

Professor of Mechanical Engineering
Director of Graduate Studies
Faculty Head of Hank Ingram House

Bio

Our Lab seeks to develop and experimentally apply a system-dynamics and control perspective to problems involving the control and transduction of energy. This is typically applied to problems in the fluid power domain (pneumatics and hydraulics) mixed with other energy domains (mechanical, thermal, etc.). Our specific expertise in precision pneumatic control and mechanical design has enabled the realization of MRI compatible, pneumatically actuated, robotic platforms capable of accurate manipulation and force control for surgical tasks. Our lab is one of a handful in the world that have experimentally achieved control of pneumatic systems at the submillimetric accuracies needed for MRI compatible surgical systems. Pneumatic systems are highly nonlinear, high order dynamic systems and require sophisticated model-based nonlinear control for stability robustness, desirable dynamic response and high accuracy positioning. Our lab also has an interest in designing and controlling pneumatic and hydraulic-powered soft robots for clinical and non-clinical applications. Most recent research efforts have focused on MRI compatible pneumatically actuated robotics, mechanical circulatory support devices including artificial hearts and soft robotics, a new class of robot.

Xiaoguang Dong, Ph.D.

Assistant Professor of Mechanical Engineering

Bio

Research at the Dong Lab includes designing the shape-morphing behaviors (single-body deformation and collective formations) in various soft matter to create functional miniature soft machines or minimally invasive medical devices, tightly integrated with their wireless actuation (e.g. magnetic), control and sensing systems, for biomedical applications. Ongoing research highlights include developing novel minimally invasive medical functions of magnetic soft robots, soft capsule endoscopes and other continuum robots, such as targeted drug delivery, onsite biofluid pumping and targeted biopsy. Alumni from Dong Lab will potentially work for medical device and medical robotics companies such as Medtronic, Stryker, Johnson & Johnson, Boston Scientific, etc.

Nicholas Kavoussi, M.D.

Assistant Professor  Department of Urology
Division of Endourology and Stone Disease

Bio

Minimally invasive urologic surgery improves recovery time, pain, bleeding and cosmesis compared to traditional, open surgical approaches. Despite this, lack of visualization, navigation and haptic feedback limit minimally invasive interventions and contribute to complications and disease recurrence events. My team and I are leveraging computer vision and machine learning technology to improve navigation and surgical vision intraoperatively to enhance minimally invasive urologic surgery.

Keith Obstein, M.D.

Associate Professor of Medicine

Bio

At the STORM Lab we strive to improve the quality of life for people undergoing endoscopy and abdominal surgery by creating miniature and non-invasive capsule robots. The continuous quest for miniaturization has made the science fiction vision of miniature capsule robots working inside the human body a reality. At the STORM Lab, we are designing and creating mechatronic and self-contained devices to be used inside specific districts of the human body to detect and cure diseases in a non-invasive and minimally invasive manner.

Capsule robots represent a challenging paradigm for both research and learning. They embed sensors, actuators, digital intelligence, miniature mechanisms, communication systems and power supply, all in a very small volume. Capsule robots may be autonomous or teleoperated, they can work alone or as a team and they can be customized to fulfill specific functions.  We are currently applying capsule robot technologies to early detection and treatment of gastrointestinal cancers (i.e. colorectal cancer, gastric cancer) and are developing a new generation of surgical robots that can enter the patient’s abdomen by a single tiny incision. Building upon these competences, we are always ready to face new challenges by modifying our capsule robots to emerging medical needs.

Nabil Simaan, Ph.D.

Professor of Mechanical Engineering
Professor of Computer Science
Professor of Otolaryngology

Bio

ARMA is focused on advanced robotics research including robotics, mechanism design, control and telemanipulation for medical applications. We focus on enabling technologies that necessitate novel design solutions that require contributions in design modeling and control. ARMA has led the way in advancing several robotics technologies for medical applications including high dexterity snake-like robots for surgery, steerable electrode arrays for cochlear implant surgery, robotics for single port access surgery and natural orifice surgery. Current and past funded research includes transurethral bladder cancer resection (NIH), trans-oral minimally invasive surgery of the upper airways (NIH), single port access surgery (NIH), technologies for robot surgical situational awareness (National Robotics Initiative), Micro-vascular surgery and microsurgery of the retina (VU Discovery Grant), Robotics for cochlear implant surgery (Cochlear Corporation). We collaborate closely with industry on translation of our research. Examples include technologies for snake robots licensed to Intuitive Surgical, technologies for microsurgery of the retina which lead to the formation of AURIS surgical robotics Inc., the IREP single port surgery robot which has been licensed to Titan Medical Inc. and serves as the research prototype behind the Titan Medical Inc. SPORT (Single Port Orifice Robotic Technology).

Robert Webster, Ph.D.

Richard A. Schroeder Professor of Mechanical Engineering
Professor of Mechanical Engineering
Professor of Electrical Engineering
Professor of Otolaryngology
Professor of Neurological Surgery
Professor of Urologic Surgery
Professor of Medicine

Bio

The Vanderbilt School of Engineering’s Medical Engineering and Discovery (MED) Laboratory pursues research at the interface of surgery and engineering. Our mission is to enhance the lives of patients by engineering better devices and tools to assist physicians. Much of our current research involves designing and constructing the next generation of surgical robotic systems that are less invasive, more intelligent and more accurate. These devices typically work collaboratively with surgeons, assisting them with image guidance and dexterity in small spaces. Creating these devices involves research in design, modeling, control and human interfaces for novel robots. Specific current projects include needle-sized tentacle-like robots, advanced manual laparoscopic instruments with wrists and elbows, image guidance for high-accuracy inner ear surgery and abdominal soft tissue procedures and swallowable pill-sized robots for interventions in the gastrointestinal tract.

Jie Ying Wu, Ph.D.

Assistant Professor of Computer Science

Bio

At the MAPLE lab, our goal is to build intelligent surgical robots that can assist surgeons in the operation room. While surgical robots have changed many procedures by providing higher dexterity, motion scaling and other innovations, they are still only extensions of the surgeon’s arms. By modeling different aspects of surgery and how they interact, we aim to make the robots more capable. We use machine learning to augment traditional modeling techniques, such as correcting physics-based soft-tissue models with observations of tissue interactions. We work with clinicians to use accurate soft-tissue models to provide guidance during surgeries based on preoperative imaging. Another project looks at modeling how expert surgeons move surgical instruments and the endoscope during procedures, which can help us develop better ways to train novice surgeons. At the same time, we are building models of the trainee’s actions, eye-gaze and pupillometry to obtain insight into their cognitive load. We use this to develop a personalized curriculum and feedback.

Justin Baba, Ph.D.

Adjoint Associate Professor of Biomedical Engineering

Bio

The Baba Lab is a part of the Vanderbilt Biophotonics Center and focuses on optical-based non-invasive sensing and diagnostics developments that include imaging and low-cost solutions for clinical translation. We have ongoing collaborations with several departments at Vanderbilt University Medical Center and the Children’s hospital.

Audrey Bowden, Ph.D.

Dorothy J. Wingfield Phillips Chancellor's Faculty Fellow
Associate Professor of Biomedical Engineering
Associate Professor of Electrical Engineering

Bio

The primary aim of the Bowden Biomedical Optics Laboratory (BBOL) is to develop and deploy novel imaging and sensing technologies to address unmet clinical needs in medicine and biology. We blend knowledge and experience from diverse fields such as optics, microfluidics, signal processing and computer science to develop software- and hardware-based tools for the healthcare provider that advance the state of the art and aid in scientific discovery. While the majority of our solutions are relevant to optics, as engineers, we are committed to taking a “whatever means necessary” approach to solving the clinical problem. We are also committed to developing novel solutions to improve delivery and affordability of healthcare in low-resource and resource-constrained environments. Our technologies and projects have found application in various clinical departments, including urology, dermatology, otolaryngology and women’s health.

Brett Byram, Ph.D.

Associate Professor of Biomedical Engineering

Bio

The biomedical elasticity and acoustic measurement (BEAM) lab is interested in pursuing ultrasonic solutions to clinical problems. Brett Byram and the BEAM lab’s members have experience with most aspects of systems level ultrasound research, but our current efforts focus on advanced pulse sequencing and algorithm development for motion estimation and beamforming. The goal of our beamforming work is to make normal ultrasound images as clear as intraoperative ultrasound, the gold-standard for many applications. We have recently demonstrated non-contrast tissue perfusion imaging with ultrasound at clinical frequencies, and we are developing novel ultrasound transducers to enhance guidance for percutaneous procedures.

Catie Chang, Ph.D.

Sally and Dave Hopkins Faculty Fellow
Assistant Professor of Computer Science
Assistant Professor of Electrical and Computer Engineering
Assistant Professor of Biomedical Engineering

Bio

The goal of our research is to advance understanding of brain function in health and disease. We develop approaches for studying human brain activity by integrating functional neuroimaging (fMRI, EEG) and computational analysis techniques. In one avenue, we are examining the dynamics of large-scale brain networks and translating this information into novel fMRI biomarkers. To enable clearer inferences about brain function with fMRI, we also work toward resolving the complex neural and physiological underpinnings of fMRI signals. Our research is highly interdisciplinary and collaborative, bridging fields such as engineering, computer science, neuroscience, psychology and medicine.

Mark Does, Ph.D.

Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Electrical Engineering
Director of Graduate Recruiting in Biomedical Engineering

Bio

The Does lab is motivated by development, evaluation and application of magnetic resonance imaging (MRI) methods for characterizing tissue microstructure, composition, and function. To this end, we develop novel MRI pulse sequences and analysis methods; evaluate and apply methods in studies of humans and small animal models of disease/injury/abnormal development; and develop and utilize statistical methods and computational models to predict and explain MRI contrast in tissues.

E. Duco Jansen, Ph.D.

Senior Associate Dean for Graduate Education and Faculty Affairs
Professor of Biomedical Engineering
Professor of Neurological Surgery

Bio

Laser-tissue interaction; optical neural interfaces; modulation of neural activity using infrared laser light; cellular effects of laser-induced stimuli; application of light, lasers and optical technology in medicine and biology.

Anita Mahadevan-Jansen, Ph.D.

Professor of Biomedical Engineering
Orrin H. Ingram Professor of Engineering
Director of Undergraduate Studies in Biomedical Engineering
Professor of Neurological Surgery
Director of the Biophotonics Center at Vanderbilt

Bio

The Vanderbilt Biophotonics Center (VBC) is a trans-institutional initiative focusing on biophotonics research, technology development and education at Vanderbilt University. The center spans across multiple schools (Engineering, Medicine and Arts & Science) and interfaces with existing centers and institutes (VICC, VINSE, VUIIS, VBI, VIIBRE, ViSE) while being anchored in Engineering. The research mission is centered around three main areas: Cancer photonics, Neuro-photonics and Multiscale photonics. Faculty at VBC seek to develop and apply photonics technologies for fundamental discovery and clinical translation. Dr. Mahadevan-Jansen serves as the director of VBC. Her own research expertise is in the clinical translation of optical techniques for solving specific problems in patients with light.

Victoria Morgan, Ph.D.

Professor of Radiology and Radiological Sciences
Professor of Biomedical Engineering
Professor of Neurology
Professor of Neurological Surgery

Bio

The Morgan Engineering and Imaging in Epilepsy Lab works closely with the departments of Neurology and Neurosurgery to develop Magnetic Resonance Imaging (MRI) methods to improve neurosurgical outcomes, particularly for patients with epilepsy. We directly support clinical care by developing and providing functional MRI to localize the eloquent cortex in the brain to aid in surgical planning to minimize functional and cognitive deficits post-surgery. Our research focuses on mapping functional and structural brain networks in epilepsy before and after surgical treatment. Our research is funded by the National Institutes of Health.

Daniel Moyer, Ph.D.

Assistant Professor of Computer Science

Bio

Professor Moyer’s group is working to bridge the gap between Machine Learning and Medical Imaging. We work directly with clinicians and researchers to translate advances in computer vision to better outcomes for patients and new discoveries in imaging-based scientific fields. While we’re most used to MRI and CT, we’re not afraid to look into new domains, and we’re always happy to meet with new potential collaborators to discuss what might be possible.

Keith Obstein, M.D.

Associate Professor of Medicine

Bio

At the STORM Lab we strive to improve the quality of life for people undergoing endoscopy and abdominal surgery by creating miniature and non-invasive capsule robots. The continuous quest for miniaturization has made the science fiction vision of miniature capsule robots working inside the human body a reality. At the STORM Lab, we are designing and creating mechatronic and self-contained devices to be used inside specific districts of the human body to detect and cure diseases in a non-invasive and minimally invasive manner.

Capsule robots represent a challenging paradigm for both research and learning. They embed sensors, actuators, digital intelligence, miniature mechanisms, communication systems and power supply, all in a very small volume. Capsule robots may be autonomous or teleoperated, they can work alone or as a team and they can be customized to fulfill specific functions.  We are currently applying capsule robot technologies to early detection and treatment of gastrointestinal cancers (i.e. colorectal cancer, gastric cancer) and are developing a new generation of surgical robots that can enter the patient’s abdomen by a single tiny incision. Building upon these competences, we are always ready to face new challenges by modifying our capsule robots to emerging medical needs.

Mikail Rubinov, Ph.D.

Assistant Professor of Biomedical Engineering
Assistant Professor of Computer Science
Assistant Professor of Psychiatry
Assistant Professor of Psychology

Bio

The Rubinov Lab focuses on network analysis and modeling of whole-brain structure and activity across species and scales. The lab pursues a three-pronged approach to achieve these aims. First, we develop unbiased algorithms and software tools for network analysis of structural and functional neuroscience datasets. Second, we collaborate with computational geneticists to investigate the genetic and transcriptomic basis of brain network organization in health and disease. Third, we create interpretable models of whole-brain activity that bridge the gap between micro- and macroscales of brain-network organization.

Yuankai (Kenny) Tao, Ph.D.

Assistant Professor of Biomedical Engineering

Bio

The Diagnostic Imaging & Image-Guided Interventions Laboratory (DIIGI Lab) develops novel optical imaging systems for clinical diagnostics and therapeutic monitoring. Optical technologies provide access to multi-scale resolutions that span single cells to whole organs. We employ a combination of technology and algorithms development to provide unique solutions to address challenges in basic sciences and clinical care. Our research primarily focuses on applications in ophthalmology and are centered on the following thrusts: 1) Intraoperative Optical Coherence Tomography (iOCT); 2) Point-of-Care Ophthalmic Diagnostics; and 3) Mechanisms of Retinal Regeneration.

Junzhong Xu, Ph.D.

Associate Professor of Radiology & Radiological Sciences
Associate Professor of Biomedical Engineering

Bio

My lab focuses on the development, validation and application of new magnetic resonance imaging (MRI) methods in cancer and other neurodegenerative diseases. There are projects that are suitable for master’s students, such as developing a computer simulation tool for MRI and a pipeline for analyzing MRI animal and human data.

Matthew D. Bacchetta, M.D.

Professor of Cardiac Surgery, Thoracic Surgery, and Biomedical Engineering
H. William Scott, Jr. Chair in Surgery
Department of Cardiac Surgery
Surgical Director Vanderbilt Respiratory Institute
Director VUMC ECMO Program

Bio

The LOR3 is focused on creating organ support systems that provide extended physiologic support for injured organs, bioengineering platforms for organ recovery and regeneration as well as developing artificial pulmonary assist devices. The lab maintains a full complement of devices used for extracorporeal life support and has developed durable support systems for lung and liver with translational potential. It works in partnerships with programs at VUMC, Carnegie Mellon University and Columbia University. The LOR3 is dedicated to translating basic science research into clinical platforms for patients with end organ failure.

Christos Constantinidis, Ph.D.

Professor of Biomedical Engineering and Stevenson Chair
Professor of Neuroscience
Professor of Ophthalmology & Visual Sciences

Bio

A closed-loop stimulation system of cortical activity. Research in our laboratory investigates the neural basis of cognitive functions, using non-human primate models. Recordings from arrays of microelectrodes implanted in the cerebral cortex can allow us to monitor ongoing patterns of activity as animals engage in cognitive functions. The project involves designing an apparatus that will allow us to decode the contents of working memory in real time and stimulate a pattern of activity to induce artificial patterns of memories.

Xiaoguang Dong, Ph.D.

Assistant Professor of Mechanical Engineering

Bio

Research at the Dong Lab includes designing the shape-morphing behaviors (single-body deformation and collective formations) in various soft matter to create functional miniature soft machines or minimally invasive medical devices, tightly integrated with their wireless actuation (e.g. magnetic), control and sensing systems, for biomedical applications. Ongoing research highlights include developing novel minimally invasive medical functions of magnetic soft robots, soft capsule endoscopes and other continuum robots, such as targeted drug delivery, onsite biofluid pumping and targeted biopsy. Alumni from Dong Lab will potentially work for medical device and medical robotics companies such as Medtronic, Stryker, Johnson & Johnson, Boston Scientific, etc.

Craig Duvall, Ph.D.

Cornelius Vanderbilt Professor of Engineering
Professor of Biomedical Engineering
Professor of Chemical and Biomolecular Engineering
Professor of Ophthalmology and Visual Sciences
Director of Graduate Studies in Biomedical Engineering

Bio

The Duvall Advanced Therapeutics Laboratory specializes in design and application of smart polymer-based technologies for: (1) wound healing and tissue repair, (2) intracellular delivery of biological drugs such as peptides and nucleic acids, (3) targeting of drugs to disease sites and (4) long-term, “on-demand” drug release from localized depots. Outside of polymeric biomaterials, we also work on RNA chemistry, carrier-fre RNA therapeutic design and protein and RNA engineering for gene editing applications. We generally seek to innovate technologies that improve the therapeutic index of existing drugs and/or to serve as enabling technologies for manipulation of conventionally “undruggable” intracellular targets.

Dario Englot, M.D., Ph.D.

Associate Professor of Neurological Surgery
Associate Professor of Radiology and Radiological Sciences
Associate Professor of Biomedical Engineering
Associate Professor of Electrical and Computer Engineering
Associate Professor of Neurology
Director of Functional Neurosurgery

Bio

The BIEN lab integrates human neuroimaging and electrophysiology techniques to study brain networks in both neurological diseases and normal brain states. The lab is led by Dario Englot, a functional neurosurgeon at Vanderbilt. One major focus of the lab is to understand the complex network perturbations in patients with epilepsy, by relating network changes to neurocognitive problems, disease parameters and changes in vigilance in this disabling disease. Multimodal data from human intracranial EEG, functional MRI, diffusion tensor imaging and other tools are utilized to evaluate resting-state, seizure-related and task-based paradigms. Other interests of the lab include the effects of brain surgery and neurostimulation on brain networks in epilepsy patients, and whether functional and structural connectivity patterns may change in patients after neurosurgical intervention. Through studying disease-based models, the group also hopes to achieve a better understanding of normal human brain network physiology related to consciousness, cognition and arousal. Finally, surgical outcomes in functional neurosurgery, including deep brain stimulation, procedures for pain disorders and epilepsy, are also being investigated.

Wesley P. Thayer, M.D., Ph.D.

Professor of Plastic Surgery and Orthopaedic Surgery
Vice Chair, Research

Bio

My lab focuses on translational research including wounds, hand surgery, and nerve repair strategies to improve outcomes after injury. We have published multiple peer reviewed publications focusing on these techniques. Our Lab is funded through a collaborative DOD grant with AxogenTM Corporation. Our most recent grant includes industry funding to studying bio scaffolds for use as a nerve scaffold. We are also playing a role in the advancement of techniques to enhance recovery of acutely injured nerves including axonal outgrowth augmentation strategies and axonal fusion strategies. In our animal models, we are able to assess interventions ability to foster improvement and optimize those strategies that may translatable to clinical application. Our treatment strategies have applications for trauma patients, oncology patients, and in composite tissue transplantation. At present I am motivated to participate in both bench and clinical research. To that end, I direct the Vanderbilt arm of the Multicenter Retrospective Study of Avance™ Nerve Graft Utilization, Evaluations and Outcomes in Peripheral Nerve Injury Repair, or RANGER study and completed a trial for evaluation of Xiaflex™ in treatment of Dupuytren’s contractures. Our most recent human trial involves using MRI based diffusion tensor tractography to evaluate individual axonal recovery after human nerve injury. We have built an infrastructure at Vanderbilt University Medical Center to efficiently and accurately assess strategies to augment nerve repair at the cellular level with our in vitro models, at the surgical level with our animal models, and translate these strategies to the clinic via IRB approved clinical trials.

Dan France, Ph.D., MPH

Research Professor of Anesthesiology
Research Professor of Medicine
Research Professor of Biomedical Engineering

Bio

Dr. France is a Research Professor of Anesthesiology, Nursing, Medicine and Biomedical Engineering at the Vanderbilt University School of Medicine. He is a research scientist in the Department of Anesthesiology’s Center for Research and Innovation in Systems Engineering (CRISS). In the School of Nursing, Dr. France teaches courses in Quality Improvement and Patient Safety and Design Thinking and Healthcare Innovation in the Master of Science and Doctor of Nursing Practice programs. Dr. France earned a doctorate in Biomedical Engineering from Vanderbilt University and a Master of Public Health from the University of Utah. He has also received advanced training in Healthcare Delivery Improvement from Intermountain Health Care in Salt Lake City, Utah. Prior to joining Vanderbilt, Dr. France worked as a systems engineer for the Department of Defense, the MITRE Corporation and L-3 Communications. His professional focus is on health systems engineering and his primary research aims are to model and explain the relationships between hospital efficiency, provider performance and patient safety. Dr. France is particularly interested in applying knowledge from other high-risk industries and methods from human factors and systems engineering to study and improve operational efficiency and individual and team performance in complex, high-risk clinical environments. He has received grant support from the Agency for Healthcare Research and Quality (AHRQ), National Institutes of Health (NIH), National Science Foundations (NSF), Department of Homeland Security (DHS) and Veteran’s Health Administration (VHA). As an example, ongoing projects are in (1) surveillance-and response systems to detect and respond to clinical deterioration in cancer outpatients, (2) realtime measurement of situational workload, (3) measuring NICU nurse practitioner workload and (4) health record usability and detection of medical error.

Soheil Kolouri, Ph.D.

Assistant Professor of Computer Science

Bio

At the Machine Intelligence and Neural Technologies (MINT) Lab, we develop next-generation core Machine Learning (ML) solutions for practical problems in medicine and strive to advance healthcare. Our interdisciplinary team at MINT Lab uses biological inspirations together with mathematical and geometrical tools to innovate theoretically grounded algorithms that address the current deficiencies in ML technologies regarding lifelong/continual learning, sample/label efficiency, explainability and brittleness. In one of our main research thrusts, we develop brain-inspired, robust machine intelligence that can continually learn and adapt to the input stream of nonstationary multimodal data. Continual learning is specifically relevant to medical applications where: 1) the data is continually accumulated from new patients and 2) diseases constantly mutate and new variants emerge. We are developing next-generation computational models that adapt to these constant variations, learn from the past to solve future problems and leverage new knowledge to improve the previous solutions. Our research is highly interdisciplinary, and we have collaborations across fields including computer science, biomedical engineering, cognitive science, electrical engineering and neuroscience.

Haoxiang Luo, Ph.D.

Professor of Mechanical Engineering
Associate Chair of Mechanical Engineering
Associate Professor of Otolaryngology

Bio

In the Computational Flow Physics Lab, we develop computational approaches and quest after fundamental understanding of a range of fluid-flow problems, especially those involving the interaction of multi-physics. Examples of our current focus include: (1) flow-structure interaction and low-Reynolds number aerodynamics of insect flight with application in the biomimetic, extremely agile micro air vehicles (MAV); (2) hydrodynamics of fish swimming for developing biomimetic, highly maneuverable autonomous underwater vehicles (AUV); (3) interaction of airflow and vocal folds in the larynx during voice production for understanding voice pathology and developing novel diagnostic and treatment tools; (4) electrophoresis-driven particle motions in micro-channels for design of the lab-on-a-chip devices.

Michael Miga, Ph.D.

Harvie Branscomb Professor
Professor of Biomedical Engineering
Professor of Radiology and Radiological Sciences
Professor of Neurological Surgery
Professor of Otolaryngology
Director of Graduate Studies in Engineering in Surgery and Intervention

Bio

The focus of the Biomedical Modeling Laboratory (BML) is on new paradigms in detection, diagnosis, characterization and treatment of disease through the integration of computational models into research and clinical practice. With the continued improvements in high performance computing, the ability to translate computational modeling from predictive roles to ones that are more integrated within diagnostic and therapeutic applications is becoming a rapid reality. With respect to therapeutic applications, efforts in deformation correction for image-guided surgery applications in brain, liver, kidney and breast are being investigated. Other applications in deep brain stimulation, ablative therapies, neoadjuvant chemotherapy and convective chemotherapy are also being investigated. With respect to diagnostic imaging, applications in elastography, strain imaging, model-based chemotherapeutic tumor response and radio-therapy response parameterizations are also of particular interest. The common thread that ties the work together is that, throughout each research project, the integration of mathematical models, tissue mechanics, instrumentation and analysis is present with a central focus at translating the information to directing therapy/intervention or characterizing tissue changes for diagnostic value.

Matthew Weinger, M.D.

Norman Ty Smith Chair in Patient Safety and Medical Simulation
Professor of Anesthesiology, Biomedical Informatics and Medical Education
Professor of Civil and Environmental Engineering
Director, Center for Research and Innovation in Systems Safety (CRISS)

Bio

The Center for Research and Innovation in Systems Science (CRISS) conducts basic and applied human factors and systems engineering research in healthcare technology and information systems, clinical quality and safety, and designs and evaluates user experiences, user interfaces, care processes and systems across multiple domains and disciplines. Our faculty collaborate with faculty in Vanderbilt's Schools of Engineering, Music, Medicine and Nursing. We also collaborate on surgical innovation and training with the Hospital virtual Valdecilla and the Hospital Universitario Marquis de Valdecilla in Santander, Spain.

Maizie Zhou, Ph.D.

Assistant Professor of Biomedical Engineering

Bio

The overarching goal of my lab is to understand how we generate intelligent behavior through normal brain development and learning-induced plasticity, and the consequences of defects in these processes. We investigate multiple dimensions of these questions, spanning computational genomics, bioinformatics, computational neuroscience and machine learning. Our approach tackles a range of data science problems, including designing new probabilistic models in high-throughput sequencing data with applications to human genomics and metagenomics, data mining of large cohort studies in neurological diseases and understanding dynamical behavior and function of neural circuits. Our work has wide-ranging implications for the normal function of the brain, for the causes and treatments of neurodevelopmental disorders, and for practical applications for the next generation of intelligent systems.