PhD Biomedical Engineering,
Carnegie Mellon University, 2018

Research area:

extracorporeal life support (ECLS), automation of ECLS, blood-contacting medical devices

Short biography:

Rei Ukita PhD is a Research Assistant Professor in the Department of Cardiac Surgery at 91������ Medical Center and in the Department of Biomedical Engineering at 91������. He holds Sc.B. in Biomedical Engineering from Brown University and PhD in Biomedical Engineering from Carnegie Mellon University. During his PhD, he worked in Professor Keith Cook’s laboratory to evaluate the efficacy of polycarboxybetaine zwitterionic polymer coatings for reducing blood clots inside artificial lungs, including rabbit and sheep animal models of extracorporeal circulation. For his postdoctoral research, he moved to 91������ Medical Center to join the Laboratory for Organ Regeneration, Recovery, and Replacement (LOR3) headed by Dr. Matthew Bacchetta. There, he developed and established the large animal sheep model of pulmonary hypertension and right heart failure. Dr. Ukita has used this sheep model to develop and evaluate a wearable device platform to prevent right heart failure and ameliorate exercise intolerance in pulmonary hypertension patients. Currently, he serves as one of the Co-Directors of LOR3. He continues to focus his research on innovations in extracorporeal membrane oxygenation (ECMO), including methods of automating the device function to enable real-time physiologic support.

VISE affiliate

Matthew Bacchetta, MD, MBA, FACS
Professor of Cardiac Surgery, Thoracic Surgery, and Biomedical Engineering

Lab

Laboratory for Organ Regeneration, Recovery, and Replacement (LOR3

2022, Ph.D., Mechanical Engineering, University of California, Los Angeles, US

2018, M.S., Mechanical Engineering, University of California, Los Angeles, US

2016, B.S., Automotive Engineering, Harbin Institute of Technology, China

Research Area/Focus:

Our lab focuses on advancing bioelectronics and intelligent systems through three key areas:

1. Wearable and Implantable Bioelectronic Sensors: We design, fabricate, and develop signal processing for multimodal, multi-point bioelectronic systems, with applications in intelligent health monitoring, disease diagnosis, and prevention, particularly in brain and cardiovascular science.
2. Human-in-the-Loop Interaction: We create safe and efficient systems for human-robot/computer interaction, leveraging bioelectronics and brain-computer interfaces to enhance functionality and user experience.
3. Adaptive Robotics and Automation: We integrate sensing, control, and machine learning (including reinforcement learning) to develop adaptive robotics for challenging medical environments, such as hospital wards and ICUs.

Bio:

Dr. Yayun Du got her Ph.D. in Robotics and System Control (Minor: Solid Mechanics) from the University of California, Los Angeles.  From 2022 to 2024, Dr. Du was a postdoctoral scholar at the Rogers Group at Northwestern University, where she led 5 disparate projects, focused on developing multimodal and multiparametric wearable and implantable sensors with integrated edge AI for monitoring cardiopulmonary (e.g., aortic stenosis, atrial fibrillation, and heart failure), neurological (e.g., sleep studies, delirium, coma, and epilepsy), and vocal system health, as well as for disease diagnosis and drug delivery. Her work has led to the deployment of four types of sensors across seven hospitals, benefiting hundreds of users globally, from neonates to the elderly, in countries including China, Canada, Mexico, the U.S., and the U.K.

Dr. Du is actively involved in commercializing innovative sensors she has developed and serves as an Associate Editor for the prestigious IEEE International Conference on Robotics and Automation (ICRA) 2025. She has an impressive publication record in top-tier journals and conferences, including Proceedings of the National Academy of Sciences (PNAS), IEEE Robotics and Automation Letters (RAL), ACS Sustainable Chemistry & Engineering, IEEE International Conference on Robotics and Automation (ICRA), and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Notably, her work was recognized as a finalist for the Best Paper Award in Agri-Robotics and the Best Paper Award in Robot Mechanisms and Design at IROS 2021, a distinction given to only 4 out of 1261 papers in each category. Dr. Du also has several first-authored manuscripts with impact factors exceeding 25 and 55 currently under review.

Lab:

Du Group
Just Du It – Leading Innovations in Bioelectronics, Robotics, and Human-in-the-Loop Interaction

Bachelors of Science in Mechanical Engineering  – Texas Tech University, 2020
Masters of Science in Mechanical Engineering – The University of Texas at Austin, 2022

PhD in Mechanical Engineering – The University of Texas at Austin, 2025

Research Area:

Surgical Robotics, Continuum Robots, Concentric Tube Robots

Awards:

Featured Article – Transactions on Biomedical Engineering (TBME) for paper titled “A Concentric Tube Steerable Drilling Robot for Minimally Invasive Spinal Fixation of Osteoporotic Vertebrae.” 2023.

Education:

PhD, Electrical and Computer Engineering
Johns Hopkins University, May 2024

Research Area:

development of clinically relevant image analysis methodologies to enable large-scale analysis and facilitate personalized treatment strategies

VISE Affiliate:

Bennett Landman, PhD
Director, 91������ Lab for Immersive AI Translation (VALIANT)
Stevenson Chair
Professor of Electrical and Computer Engineering

Lab:

Medical-image Analysis and Statistical Interpretation Lab (MASI)

Research area:

Augmented / mixed reality surgery

Short bio:

Michael Topf, MD joined the 91������ Department of Otolaryngology–Head and Neck Surgery in 2020. Since relocating from Stanford University, he has initiated multiple clinical trials. His clinical practice consists of treatment of benign and malignant lesions of the head and neck including transoral robotic surgery (TORS). His research interests include the use of 3D scanning to improve communication between surgeons and pathologists and augmented / mixed reality surgery.  

Head And Neck Surgical Oncology Medical Student Research Fellowship

The Division of Head and Neck Surgical Oncology within the Department of Otolaryngology at 91������ Medical Center has created a , beginning July 1, 2023.

Ph.D. in Electrical and Computer Engineering
Carnegie Mellon University, 2010

M.S. in Electrical and Computer Engineering
Carnegie Mellon University, 2007

B.S. in Electrical Engineering
Purdue University, 2005

Research area:

My research develops foundations and tools for safety guarantees and predictable performance of learning-enabled cyber-physical systems (CPS) – primarily targeting the internet-of-medical-things (IoMT) and autonomy. Specifically, my research aims to develop tools and techniques to address challenges arising from unmodeled variability, dataset shifts, anomalies, limited data, and sensing constraints. I apply my research to address real-world (medical) problems with an eye towards technology transfer and commercialization.

Lab:

Internet of Medical Things (IoMT) Lab

PhD, Computer Science
University of Southern California, 2019, PhD

Research Area:

Medical Imaging, Machine Learning

Lab:

Moyer Lab
Prof. 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.

Education

PhD (Biomedical Engineering), 2007, Duke University
BSE (Electrical Engineering), 2001, Princeton University

Research area

Biomedical optics, point of care diagnostics

Lab

Bowden Biomedical Optics Laboratory (BBOL)

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.

Ph.D. Electromechanical Engineering
Ghent University, 2019

Research area:

Computational modeling for biomedical applications

PhD, Johns Hopkins University, 2021
MSE, Johns Hopkins University, 2020
MSc, École normale supérieure Paris-Saclay, 2016
BSc, Brown University, 2015

Areas of research:

Surgical robotics, soft-tissue simulation, user action recognition, cognitive load assessment

Main project:

Combining models and observations to create real-time, patient-specific soft-tissue simulation

Lab name:

Machine Automation, Perception, and Learning (MAPLE)