Find Academic Supervisors

Fabrizio SergiView profile

Associate Professor

• Biomechanical Engineering
• Robotics
• Neural Control of Movements
• +4 more

Fabrizio Sergi is an Associate Professor in the Department of Mechanical Engineering at the University of Delaware, with joint appointments in the Biomedical Engineering Department and the Biomechanics and Movement Science Program. He leads the Human Robotics Lab and focuses on rehabilitation robotics, neural control of movements, and functional neuroimaging. Sergi holds a PhD, MS, and BS in Biomedical Engineering from Università Campus Bio-Medico di Roma. His research explores robotic tools to study motor control in healthy and post-stroke individuals, with a focus on MRI-compatible robots and functional magnetic resonance imaging (fMRI). He has secured grants from NIH, NSF, and AHA, including the NSF CAREER Award (2020) and AHA Scientist Development Grant (2017). His work includes developing protocols for studying brainstem contributions to motor responses and creating exoskeletons for gait assistance. Sergi’s research bridges robotics, biomechanics, and neuroscience, aiming to improve stroke recovery and neuromotor adaptation. His lab develops advanced technologies like Multi-Muscle Magnetic Resonance Elastography (MM-MRE) to non-invasively measure muscle forces and investigate neural substrates of motor control. He also studies adaptive control strategies for exoskeletons and the effects of torque assistance on walking mechanics. Key achievements include pioneering MRI-compatible robotic systems and identifying neural correlates of motor recovery. Current projects focus on optimizing robotic training protocols and understanding how proprioceptive feedback influences rehabilitation outcomes.

Michael LustigView profile

Associate Professor

• Computational Magnetic Resonance Imaging (MRI)
• Medical Imaging
• Signal Processing
• +3 more

Michael Lustig is an Associate Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley. His research focuses on computational imaging methods in magnetic resonance imaging (MRI), with emphasis on compressed sensing, motion correction, and machine learning applications in medical imaging. He has contributed significantly to the development of open-source tools like SparseMRI and reconstruction algorithms such as ENLIVE and DSLR+. PhD in Electrical Engineering, Stanford University (2008) MSc in Electrical Engineering, Stanford University (2004) BSc in Electrical Engineering, Technion, Israel Institute of Technology (2002) Lustig’s work spans advanced MRI techniques including ultra-short echo time (UTE) imaging , low-rank reconstruction , and physics-informed neural networks . He has pioneered methods for integrating RF motion sensing via beat pilot tones during MRI scans and developed tools for memory-efficient large-scale image reconstruction. His recent publications focus on MRDust (wireless implantable interfaces), Twstr coils (discrete-component-free MRI hardware), and Resonet (noise-trained off-resonance correction). These works reflect trends in self-supervised learning, contact-free motion detection, and hardware-software co-design for diagnostic imaging. Scientific Awards & Fellowships International Society for MR in Medicine Gold Medal (2025) Pioneer Award (2023) ISMRM Fellow (2017) Electrical Engineering Outstanding Teaching Award (2016) Bakar Spark Award (2015) Okawa Research Grant (2014) Sloan Research Fellow (2013) Hellman Fellow (2012) Lustig advises PhD students like Frank Ong and leads research at the MikLab , contributing to open-source software platforms such as SigPy and DeepInPy . His work bridges computational methods, hardware innovation, and clinical translation in MRI.

• Robotics
• Mechatronics
• Mechanical Engineering
• +3 more

Marc Vedrines is a Lecturer in the Department of Mechanical Engineering, associated with the ICube Research Unit's Automatic Vision Robotics (AVR) team. His educational responsibilities include managing the mechatronics engineering training program through work-study and teaching courses in mechanical construction, strength of materials, mechatronic systems, and projects. His research spans robotics and mechanical systems, with key interests in tensegrity mechanisms, compliant mechanisms, variable stiffness joints, and applications in medical robotics (MR-compatible robots) and aerial vehicles (VTOL UAVs). He investigates the structural behavior and design of innovative robotic components through theoretical analysis and practical implementation. Analysis of his publications from 2010 to 2016 reveals a consistent focus on robotic mechanism design, including tensegrity workspace computation, variable stiffness joints for medical applications, singularity analysis in compliant mechanisms, and aerodynamic optimization of VTOL UAVs. His work demonstrates strong interdisciplinary connections between mechanical engineering, robotics, and biomedical/aerospace applications. Marc Vedrines actively contributes to the AVR team at ICube, advancing research in robotics, computer vision, and automatic systems through collaborative projects and publications in high-impact venues like ASME journals and IEEE conferences.