John A. Rogers is the Louis Simpson and Kimberly Querrey Professor at Northwestern University, holding joint appointments in Materials Science and Engineering, Biomedical Engineering, Mechanical Engineering, Chemistry, and Neurological Surgery. He directs the Querrey-Simpson Institute for Bioelectronics. His work bridges soft materials science, bio-integrated electronics, and nanotechnology, with a focus on wearable medical devices, bioresorbable systems, and neural interfaces. Educations: B.A. & B.S. from University of Texas Austin (1989), S.M. from MIT (1992), Ph.D. in Physical Chemistry from MIT (1995). Prior roles include Director of Bell Labs' Condensed Matter Physics Department and faculty positions at University of Illinois at Urbana-Champaign. Research emphasizes soft materials for bio-inspired electronics, including flexible sensors, microfluidic platforms, and bioresorbable implants. His lab has pioneered epidermal electronics, injectable optoelectronics, and neural interfacing systems. Over 1000 peer-reviewed publications and 100+ patents highlight his contributions to nanotechnology and biomedical engineering. Awards include the Benjamin Franklin Medal (2019), MRS Medal (2018), and MacArthur Fellowship (2009). He is a member of the National Academies of Sciences, Engineering, and Medicine. Current projects span bioelectronic medicines, wearable health monitors, and advanced medical imaging tools.
Dr. Gary Glover is a Professor of Radiology (Radiological Sciences Lab) at Stanford University , with courtesy appointments in Psychology and Electrical Engineering. His work focuses on the physics and mathematics of MRI, particularly rapid scanning methods using spiral k-space trajectories for functional brain imaging and multimodal neuroimaging (fMRI/EEG/fPET/fNIRS) combined with neuromodulation techniques like TMS and transcranial ultrasound. Academic Appointments: Radiology, Psychology, Electrical Engineering Professional Affiliations: Bio-X, Stanford Cancer Institute, Wu Tsai Neurosciences Institute Research Interests include: Development of blood oxygen level-dependent (BOLD) and viscoelastic contrast in MRI Functional MR Elastography for brain activation mapping Optimization of MR-ARFI for transcranial ultrasound guidance Automated spinal cord segmentation (EPISeg) using machine learning Scientific Awards : National Academy of Engineering (2013) Gold Medal, ISMRM (2000) Steinmetz Award, General Electric (1985) Lauterbur Lecture, ISMRM (2018) Recent Publications analyze: Fast fMRI sampling and spurious signal correction Dissociated patterns in default mode network anti-correlations Neural correlates of collaborative behavior in triadic fMRI Salience network contributions to depression pathophysiology
Giulio Dagnino is Associate Professor of Robotics and Mechatronics at the University of Twente and concurrently holds an appointment at the Digital Society Institute. His research integrates medical robotics, real-time perception and haptics to create MR-compatible platforms for endovascular surgery, earning an h-index of 17 and 971+ citations. Education & Career: PhD (details not specified in source) leading to faculty appointment at University of Twente. Promoted to Associate Professor with cross-appointments in Robotics & Mechatronics and Digital Society Institute. Research Interests: Prof. Dagnino’s core interest is medical robotic systems that can operate safely inside an MRI scanner. His work spans haptic guidance, real-time computer vision, soft robotic actuation, synthetic data generation and surgical simulation. By combining ferrofluid actuation, electromagnetic tracking and deep-learning-based scene understanding, he aims to reduce ionizing radiation exposure, enhance navigation accuracy and shorten procedure times for minimally invasive endovascular interventions. Publications Trend: Across 44 outputs (2010-2025) the portfolio reveals a clear evolution from early vision-based microsurgery and fracture-robot systems (2010-2016) toward holistic endovascular platforms integrating MR guidance, haptics and autonomy. Recent 2024-25 papers cluster around (i) synthetic data & scene understanding for surgical AI, (ii) MR-safe robot design and tracking, and (iii) translational studies bringing CathBot and related platforms closer to clinical use. Scientific Awards: Best Design Award – Hamlyn Symposium 2019 (with team) Best Innovation Award – ICRA 2018 Best Paper Award – CURAC 2019 IEEE ICRA Best Paper Award in Medical Robotics – 2016 Grants & Projects: Although explicit grant numbers are not listed, the continuous outputs, patents, multi-institutional collaborations (UK, Germany, Estonia, Canada) and press releases imply sustained funding from EU, Dutch and UK research councils as well as industrial partnerships. Labs & Teams: He leads activities within the Robotics and Mechatronics group at University of Twente, collaborates closely with the Digital Society Institute, and maintains international partnerships visible in co-authored papers with Imperial College London, University of Leeds, and several European hospitals.
Jon-Fredrik Nielsen is a Research Professor in the Departments of Radiology and Biomedical Engineering at the University of Michigan. His research focuses on advanced MRI technologies, including pulse sequence design, functional MRI, and quantitative imaging. He leads projects funded by NIH grants such as R21AG061839, R01EB023618, and R21EB019653, emphasizing innovations in MRI hardware and software. Research Interests: Steady-state MRI and RF pulse design Functional MRI and biomarker development Blood flow imaging and computational modeling Publications reflect contributions to open-source MRI frameworks (Pulseq/TOPPE), artifact correction, and novel imaging protocols. He holds patents related to MRI imaging techniques (e.g., US 9,791,530). Grants: NIH R21AG061839 (PI), NIH R01EB023618, NIH R21EB019653, and University of Michigan MCubed grants. Projects include improving fMRI reliability and developing vendor-agnostic MRI sequences. Labs/Teams: Active in the fMRI engineering group, contributing to software tools like TOPPE and Pulseq-Graphical Programming Interface.
Shuchi Deb is an Associate Professor of Industrial, Manufacturing, and Systems Engineering at the University of Texas at Arlington, where she has served since 2019 and was promoted to Associate Professor in September 2024. She directs an active, grant-funded research program that blends human-factors engineering, virtual & augmented reality, and transportation safety to improve human-system interaction across manufacturing, education, and public-safety domains. Education: Ph.D. in Industrial & Systems Engineering, Mississippi State University, 2017 M.S. in Industrial and Management Engineering, Montana State University, 2014 B.Sc. in Industrial and Production Engineering, Shahjalal University of Science & Technology (Bangladesh), 2006 Research & Innovation: Deb’s scholarship focuses on human-centred design of complex socio-technical systems. She exploits immersive technologies—virtual, augmented and mixed reality—to study and enhance safety, training transfer, and user experience in contexts ranging from automated-vehicle interactions and cyclist–infrastructure compatibility to additive-manufacturing education and police reality-based training. Her work repeatedly integrates psychophysiological sensing (EEG, eye-tracking, facial-expression analysis) with usability engineering to create adaptive, trustworthy human-machine interfaces. Recent federally supported projects include an NSF grant to build a bilingual VR platform for additive-manufacturing education ($837 k), a USDOT project developing a driver-readiness monitor for prolonged automated driving, and a Department of Justice award with the Fort Worth Police Department to create VR-based reality training scenarios ($269 k). These grants exemplify her translational approach: coupling rigorous human-factors experimentation with deployable technological solutions. Scientific Recognition: Outstanding Contribution & Mentorship Award, UT Arlington (2024) Best Graduate Student Paper, Mississippi State University (2017) IIE/FlexSim Simulation Competition Winner (2016) SEMS Best Student Paper, IISE (2016) Annual Ergonomics Design Competition, Auburn University (2015) Advising & Grant Leadership: Deb has chaired or served on more than a dozen Ph.D. and M.S. thesis committees and mentored over twenty undergraduate researchers. Since 2019 she has attracted > US $2.3 million in external funding as PI or Co-PI, supporting a broad cohort of graduate researchers who disseminate their work annually at ASEE, IISE, HFES, TRB, and AHFE conferences. Labs & Teams: She founded and advises the Human Factors Lab at UT Arlington, a shared facility equipped with VR headsets, motion-capture systems, driving and cycling simulators, and psychophysiological recording suites. The lab collaborates with industry (Fort Worth Police, local manufacturers) and across campus (Computer Science, Mechanical & Aerospace Engineering) to provide interdisciplinary training to students.
Dennis L. Parker is a Professor in the Departments of Radiology & Imaging Sciences and Biomedical Informatics at the University of Utah. He serves as the Mark H. Huntsman Endowed Professor and founded the Utah Center for Advanced Imaging Research (UCAR), directing it from 2003–2016. His work focuses on the mathematics and physics of medical imaging , particularly MRI and MR-guided thermal therapies . Education: PhD in Medical Biophysics and Computing (University of Utah), MS in Physics (Brigham Young University), BS in Physics (Brigham Young University) Dr. Parker has pioneered MRI thermometry for thermal therapy guidance, MR angiography techniques (MOTSA), and carotid plaque analysis using diffusion-weighted MRI. His research integrates acoustic radiation force , shear wave elastography , and focused ultrasound for non-invasive interventions. Recent publications emphasize dynamic T1/T2* mapping , skull microstructure modeling , and AI-driven tissue property estimation . His work has been funded by NIH R01 grants and VA Merit Awards . Scientific Recognition: Distinguished Research Award, University of Utah (2000) Fellow, American Institute for Medical and Biomedical Engineering (2008) Fellow, International Society for Magnetic Resonance in Medicine (2015) He has mentored over 80 trainees , many of whom now hold academic positions. His Neurovascular Imaging Group develops non-invasive MRI methods to replace risky X-ray angiography, advancing global standards in vessel wall imaging and atherosclerosis detection .
J. Rock Hadley is a researcher in the Department of Radiology and Imaging Sciences at the University of Utah , specializing in Advanced MRI Imaging and Custom RF Coil Design . His work focuses on Image-Guided High-Intensity Focused Ultrasound Therapy , Neurovascular Imaging , and Breast-Specific MRI Devices . Education: PhD, University of Utah ME, University of Utah BS, University of Utah Hadley's research spans MRI Technology Development , including RF Coil Design , Gradient Coil Systems , and Image-Guided Robotic Procedures . His recent work emphasizes Transcranial MRgHIFU , Carotid Artery Imaging , and High-SNR MRI Coils for organs like the Pituitary Gland and Optic Nerve . The 15 most recent publications highlight his contributions to 3T MRI Systems , MR Thermometry , and Phased Array Coil Decoupling . Articles from 2025–2020 demonstrate sustained innovation in Medical Robotics , Breast Imaging , and Neurovascular MRI . Hadley holds a patent for an Anatomical Positioning System (2009) and has collaborated extensively in Carotid Bifurcation Studies and Optic Nerve Imaging . His work is supported by grants and partnerships with institutions like the Coil Lab at the University of Utah.
Francisco Molina Lopez is a Senior Lecturer at the Faculty of Engineering Sciences , KU Leuven , with affiliations to the Materials Science Division , LBI - KU Leuven Brain Institute , and Leuven.AM – Institute for Additive Manufacturing . His research focuses on printed, flexible/stretchable/soft hybrid organic-inorganic electronic materials for autonomous systems in wearables, soft robotics, and the Internet of Things (IoT) . His work spans: Thermoelectric Generators using printed electronics Hybrid Nanocomposites for stretchable sensors 3D Printing of energy materials Icephobic Coatings for sustainable energy Notable grants and projects : ERC Starting Grant (2020) for 3D ALIGN project FWO Fellowships for Tanmay Sinha and Viktor Naenen MSCA Postdoctoral Fellowships for Altynay Kaidarova and Juhyung Park Recent publications highlight advancements in brush-printed PEDOT:PSS (ACS Applied Materials & Interfaces, 2025), 3D-printed thermoelectrics (Advanced Science, 2025), and icephobic surface engineering (Materials Science & Engineering: R, 2025). His team collaborates with institutions in Saudi Arabia, Spain, Switzerland, and the USA. Students and postdocs in his group include: PhD Candidates: Hasan Emre Baysal, Bokai Zhang, Viktor Naenen Postdocs: Shubhradip Guchait, Juhyung Park Former PhDs: Yuan Tian (now patent attorney), Daiman Zhu (faculty at NCEPU) Labs and networks include the LBI Brain Institute and Leuven Institute for Additive Manufacturing . He actively participates in international conferences like MRS, ECME, and ICFPE.
Prof. Dr.-Ing. Heike Vallery is a leading academic in robotics and rehabilitation engineering, holding a full professorship at RWTH Aachen University's Institute of Automatic Control and a part-time professorship at TU Delft. She also holds an honorary professorship at Erasmus MC Rotterdam's Department for Rehabilitation Medicine. Her research focuses on robotic assistance for gait disorders through minimalistic concepts like wearable gyroscopic actuators. Education : Dipl.-Ing. in Mechanical Engineering (2004), RWTH Aachen Dr.-Ing. (2009), Technische Universität München Research Interests : She specializes in modeling and control of bipedal locomotion, compliant actuation, and assistive devices. Her work bridges robotics, biomechanics, and clinical applications, particularly for neurorehabilitation and prosthetics. Scientific Awards : Alexander von Humboldt Professorship Vidi Fellowship (2016), Netherlands Organisation for Scientific Research euRobotics Technology Transfer Award 1st Prize (2014) Academic Leadership : She leads the Institute of Automatic Control at RWTH Aachen and maintains affiliations with TU Delft and Erasmus MC Rotterdam. Her lab develops solutions like the RYSEN body weight support system and ERiK prosthetic leg.
Quentin Boehler is a Senior Research Fellow at the Multi-Scale Robotics Lab at ETH Zurich, specializing in magnetic actuation for medical robotics. His research focuses on the development and analysis of electromagnetic navigation systems and soft magnetic robots for medical applications. Education: M.S. in Mechatronics from INSA Strasbourg (2013) Ph.D. in Robotics from ICube laboratory, University of Strasbourg (2016) Boehler's research interests span across medical robotics, with a particular emphasis on magnetic actuation techniques for minimally invasive procedures. His work combines principles from robotics, electromagnetism, and medical engineering to develop novel systems for clinical applications. Key areas include electromagnetic navigation systems, soft magnetic robotics, MR-compatible devices, and variable stiffness mechanisms. His research has significant implications for improving precision and safety in medical procedures such as endoscopy, catheterization, and surgical interventions. Analysis of his publications shows a consistent focus on translating theoretical robotics concepts into practical medical applications, with particular attention to navigation precision and device functionality in clinical settings. Dr. Boehler's scientific contributions have been recognized with the Best Thesis Award from the research commission of the University of Strasbourg and the First prize at the 2016 Ph.D. thesis awards from GDR Robotique. His work has resulted in numerous high-impact publications in journals such as Science Robotics, Nature Communications, and IEEE Transactions on Robotics. As a key member of the Multi-Scale Robotics Lab at ETH Zurich, Boehler contributes to advancing the field of medical robotics through innovative research and development. His work bridges the gap between theoretical robotics and practical clinical applications, with a focus on creating technologies that can be translated to real-world medical settings. His research demonstrates strong interdisciplinary collaboration with medical professionals and engineers to address clinical challenges through robotic solutions.
Wally Block is a full Professor in the Department of Biomedical Engineering at the University of Wisconsin–Madison, where he has led an MRI-focused laboratory since 2000. Previously, he was a systems engineer at GE Healthcare on the first commercial MRI scanners, and he earned his PhD from Stanford University in 1998. Education PhD 1998 – Stanford University MS 1988 – Stanford University BS 1986 – University of Illinois, Urbana-Champaign Research Focus Professor Block’s laboratory pioneers ultra-fast MRI acquisition and reconstruction techniques that dramatically shorten scan times and simplify workflows. Central to his current agenda is image-guided, minimally invasive brain therapy , particularly leveraging intraparenchymal drug-delivery routes to bypass the blood–brain barrier. This highly interdisciplinary program integrates signal processing, machine learning, mechanical engineering, biophysics, and advanced image processing to enable transformative treatments for neurological diseases. Scientific Recognition Fellow, American Institute for Medical and Biological Engineering Senior Fellow, International Society for Magnetic Resonance in Medicine Multiple Distinguished Reviewer awards from Magnetic Resonance in Medicine and Journal of Magnetic Resonance Imaging Vilas Associate Professorship, UW-Madison Honored Instructor Award, UW Housing Whitaker Foundation Grantee Teaching & Mentorship Professor Block regularly teaches cornerstone courses such as Biomedical Engineering Capstone Design (B M E 400/402), Medical Devices Ecosystem: The Path to Product (B M E 640), and directs graduate research credits ( MED PHYS 990 ). He also offers advanced independent study opportunities through B M E 799 , fostering the next generation of engineers and physician-scientists. Laboratory & Collaborative Environment His lab, located in the Wisconsin Institute for Medical Research (WIMR), hosts a multidisciplinary team of graduate students, post-doctoral researchers, and clinical collaborators. The group maintains active partnerships with neurosurgeons, radiologists, and industry leaders to translate novel MRI methods into first-in-human trials.
Shuo Wang is a Professor and Michael Hsing Faculty Fellow at the University of Florida's Department of Electrical & Computer Engineering, part of the College of Engineering. His research focuses on power electronics, electromagnetic interference (EMI), electric vehicles, hardware security, and IoT/cyber security. He holds an IEEE Fellowship (2019) and has received the NSF CAREER Award (2012). His work spans EMI modeling/reduction in power systems, secure wireless charging, and hardware security tools like HT-EMIS and GAZEploit. Education : Ph.D., Virginia Tech MSEE, Zhejiang University BSEE, Southwest Jiaotong University Research Highlights : - Developed novel inductor designs (e.g., 2D-core/origami-winding) to reduce EMI - Pioneered EMI modeling techniques for EV systems and SiC motor drives - Advanced hardware security through runtime EM analysis and FPGA deployment methods - Integrated NFC/wireless charging technologies for consumer electronics - Addressed cybersecurity risks in VR/MR devices and industrial systems Awards : HWCOE Doctoral Dissertation Advisor Award (2024) UF Innovate Invention of the Year (2023) NSF CAREER Award (2012) Grants & Advising : Recipient of multiple NSF grants and industry partnerships. Advises on cutting-edge topics like EMI mitigation in wide bandgap devices and secure cloud FPGA deployment. No specific grant details listed in provided text.
Wenhui Chu is an Instructional Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on machine learning, computer vision, artificial intelligence, and MR-compatible robotic systems. He holds a Ph.D. in Computer Science from the University of Houston (2021) and an M.S. from Boston University (2016). Dr. Chu’s work emphasizes medical imaging applications, particularly in cardiac MRI analysis and MRI-guided robotic interventions. His recent publications explore deep learning techniques for automated segmentation, low-field MRI synthesis, and ferric applicator simulations for therapeutic delivery. His awards include the 2024 Student Recognition Award and a 2016–2021 Graduate Fellowship from the University of Houston. His advising and grants focus on interdisciplinary projects at the intersection of AI and biomedical engineering, though specific grant details are not listed. He is associated with labs and teams advancing medical robotics and imaging technologies, leveraging his expertise in neural networks and clinical applications.
Yan Wang is the William Smith Foundation Dean's Professor of Mechanical Engineering at Worcester Polytechnic Institute (WPI). He leads the Electrochemical Energy Laboratory and focuses on advanced materials and technologies for energy storage systems, including lithium-ion batteries, supercapacitors, and flow batteries. His research emphasizes improving energy density, safety, and recyclability while commercializing innovations through ventures like Ascend Elements and AM Batteries. He holds a BS from Tianjin University (2001), MS from Tianjin University (2004), PhD from University of Windsor (2009), and a postdoc at MIT (2010). Research interests include battery electrode design, battery recycling processes, and fundamental electrochemistry. He has pioneered closed-loop recycling strategies and developed dry-powder electrode manufacturing to reduce toxic solvents. His work aligns with federal initiatives in clean energy, including solar panel recycling funded by federal grants. Awards: 2024 Boston Globe Tech Power Players 50, TIME Top GreenTech Company recognition (2024), William Smith Foundation Professorship Commercialization: Cofounded Ascend Elements (battery recycling) and AM Batteries (dry-powder electrode tech) Recent Milestones: 2024 Poland recycling plant deal, Georgia plant operational since 2023, $1.2M steel innovation grant (2024) Labs/Teams: Electrochemical Energy Laboratory at WPI, collaborating with industry partners on battery tech and medical imaging systems. His work spans academic research and industrial applications, with patents in additive-manufactured electrodes and ultrasonic motor designs.
Alpay Özcan is a Professor in the Department of Electrical and Electronics Engineering at Bogazici University. He directs the Systems Science and Mathematics Laboratory (SSML) and Magnetic Medical Devices Laboratory (MMDL). Özcan holds a DSc in Systems Science from Washington University and an MSc from Imperial College London. Research integrates systems theory with biomedical applications, including MRI-compatible robotics, diffusion tensor imaging, and AI-driven cancer diagnostics. Recent work develops nanoparticle-enhanced MRI techniques and deep learning models for glioma genotyping using multiparametric scans. He pioneered robotic systems for real-time MRI-guided interventions at Washington University. Current projects involve QSM mapping for neurodegeneration, hyperthermia devices, and low-complexity imaging algorithms. Özcan collaborates globally on neuro-oncology studies using advanced MR spectroscopy and diffusion analysis.
