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Ian BrownView profile

Professor

• Energy Conversion
• Electric Machines
• Adjustable Speed Drives
• +6 more

Ian Brown is a Professor of Electrical and Computer Engineering at Illinois Institute of Technology, part of the Armour College of Engineering. He holds a Ph.D. (2009), M.S. (2003), and B.S. (1999) in Electrical and Computer Engineering from the University of Wisconsin-Madison and Swarthmore College. His research focuses on energy conversion, electric machines, and renewable energy systems, with emphasis on sensorless control, machine design optimization, and traction motor development for electric vehicles. He has extensive industry experience as a principal engineer at A.O. Smith, contributing to electric machine and drive technologies. Research interests include adjustable speed drives, high-power density motors, and applications in sustainable energy. He has advised multiple graduate students and published over 50 peer-reviewed articles in IEEE Transactions and conferences. His recent work explores superconducting circuit breakers, thermal management systems, and advanced winding designs to minimize harmonic distortions. Brown's contributions bridge academic research with industrial applications, particularly in improving energy efficiency and reliability in power conversion systems. He is affiliated with the IEEE and has contributed to journal editorials on electric machines in renewable energy. His lab focuses on experimental prototyping and simulation-driven optimization of electric drives. Current projects include developing brushless capacitive excitation systems for traction motors and analyzing driving cycle-based machine design optimization strategies. Teaching responsibilities include graduate courses on electric machines and power electronics. He maintains active collaborations with industry partners like A.O. Smith and Siemens, emphasizing translational research with commercialization potential.

Carmel MajidiView profile

Professor

• Soft Robotics
• Wearable Robotics
• Soft Electronics
• +12 more

Carmel Majidi is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering. He leads the Soft Machines Lab, where his research focuses on soft robotics, wearable computing, and advanced materials that mimic biological systems. His work enables robots and machines to safely interact with humans through soft, deformable technologies. Education: Ph.D. in EECS, University of California, Berkeley (2007) B.S. in Civil and Environmental Engineering, Cornell University (2001) His research interests span soft robotics, stretchable electronics, liquid metal materials, and bio-inspired engineering. He develops soft electromechanical materials for applications in haptics, medical devices, and human-machine interfaces. His group pioneers fabrication methods for soft composites and microfluidic systems that function as artificial skin, nervous tissue, and muscle. The recent trend in his publications highlights a strong focus on soft actuators, self-healing materials, liquid metal composites, and haptic interfaces for virtual and augmented reality. His work integrates materials science, robotics, and advanced manufacturing to enable scalable, robust, and practical soft systems. Scientific Awards: 2023 Inno Fire Award for Trailblazing Innovators, Pittsburgh Business Times Majidi leads a major research thrust in a new NSF Engineering Research Center (ERC) dedicated to improving robot dexterity, funded up to $52 million. He has been instrumental in developing soft robotic systems inspired by prehistoric organisms, such as the pleurocystitid, and in creating healthcare devices powered by body heat using liquid metal technologies. His research has been featured in Popular Science , Communications of the ACM , and Ars Technica . He is actively involved in advancing scalable manufacturing of soft electronics and enabling robust integration between soft materials and conventional microelectronics. His lab collaborates across disciplines to push the boundaries of physical AI and wearable robotics.

• Magnetic recording
• Information storage technology
• Resistive memory devices
• +5 more

James Bain is a Professor in the Electrical and Computer Engineering (ECE) Department at Carnegie Mellon University, with a courtesy appointment in the Department of Materials Science and Engineering. He serves as Associate Director of the Data Storage Systems Center (DSSC) within the College of Engineering. B.S. in Materials Science and Engineering from the University of Pennsylvania (1988) M.S. (1991) and Ph.D. (1993) in Materials Science and Engineering from Stanford University His research spans magnetic, optical, electrical, thermal, and mechanical devices for information storage. Current programs focus on heat-assisted magnetic recording and resistive switches for memory and reconfigurable electronics, with interdisciplinary applications in energy security, industrial decarbonization, and nanofabrication. His work intersects materials science , electrical engineering , and nanotechnology . Scott Institute Seed Grant (2018) for energy research Member of Materials Research Society and IEEE Magnetics, Electron Devices, and Photonics Societies Bain has co-authored over 225 publications and leads research at the interface of data storage and energy systems . He actively contributes to multiphysics modeling, nanoscale thermal transport, and phase-change materials. His lab is affiliated with Carnegie Mellon’s Data Storage Systems Center, advancing technologies for grid-interactive and high-performance buildings.

Sorin MitranView profile

Professor

• Computational simulation of multiscale, multiphysics systems
• Data-driven constitutive relations for hyperelastic materials
• Nonlinear mode reduction
• +4 more

Sorin Mitran is a Professor in the Department of Mathematics at the University of North Carolina at Chapel Hill. His research focuses on computational simulation of multiscale and multiphysics systems, data-driven constitutive relations for hyperelastic materials, and information geometry for reduced stochastic models. PhD in Aerospace Engineering from Politehnica University Bucharest (1995) Professional background includes fellowships at University of Tokyo (1993), Karlsruhe Institute of Technology (1998-1999), and University of Washington (1999-2002) His research develops numerical tools to predict macro-scale behavior from micro-scale interactions, such as plastic deformation of metals from lattice defect dynamics, microtubule mechanics from molecular dynamics, and protein folding from atomic-level simulations. Mathematical approaches include adaptive computation, machine learning for constitutive law prediction, and information geometry for stochastic process analysis. Recent publications (2023-2018) span computational biology, multiscale fluid dynamics, and medical applications of continuum mechanics. Articles frequently explore data-driven modeling, wave propagation in biological systems, and GPU-accelerated numerical methods like Lattice Boltzmann and Lattice Fokker-Planck formulations.

• Mechanical Engineering
• Tribology
• Multimodal Sensing
• +5 more

Dr. Min Yu is an Imperial College Research Fellow (ICRF) in the Department of Mechanical Engineering at Imperial College London . He leads an independent research program focused on in-situ multimodal sensing of mechanical interfaces , integrating advanced materials, intelligent control, multiphysics modeling, and data-driven technologies. His work bridges tribology, robotics, and sensing with applications in lubrication systems and robotic haptic interfaces. Education: PhD in Mechanical Engineering, Imperial College London (2014–2018) MSc in Engineering, Zhejiang University (2011–2014) BEng in Engineering, Xi’an Jiaotong University (2007–2011) Research Interests: Dr. Yu’s core research areas include tribology , ultrasonic sensing , robotic haptics , lubrication systems , and data-driven control . He develops novel sensing technologies for real-time monitoring of mechanical interfaces, with applications in engines, bearings, transmissions, and robotic systems. His work emphasizes closed-loop intelligent lubrication and bio-inspired robotic sensing . Publications & Trends: Dr. Yu has authored over 60 peer-reviewed papers and holds 6 patents . His recent work (2024–2025) focuses on ultrasonic-based oil film measurement, triboelectric sensors for robotics, and advanced control systems for automotive suspensions. These publications reflect a strong interdisciplinary approach combining mechanical engineering , AI-driven control , and sensor innovation . Awards & Grants: Imperial College Research Fellowship (ICRF 2022–2026) Royal Society International Exchanges – Cost Share Scheme State Key Laboratory of Fluid Power and Mechatronic Systems Open Foundation Taiho Kogyo Tribology Research Foundation Grant Dame Julia Higgins Engineering Postdoc Collaborative Research Fund (2019) Peter Jost Travel Fund (2022) Collaborations & Labs: Dr. Yu collaborates with multiple groups at Imperial College London including the Tribology Group , Non-Destructive Evaluation (NDE) Group , Control and Power Group , Optical & Semiconductor Devices Group , and Geotechnics Group . He also partners with international institutions such as Georgia Tech , Xi’an Jiaotong University , Zhejiang University , HUST , and Tsinghua University , as well as industry leaders like Shell , ExxonMobil , Toyota , and Jaguar Land Rover .

John MooreView profile

Assistant Professor

• Computational mechanics
• Materials science
• Engineering design
• +4 more

Dr. John Moore is an Assistant Professor in the Department of Mechanical Engineering at Marquette University . He leads the Computational Mechanics of Materials Laboratory, focusing on computational mechanics, materials science, and high-performance computing. His research spans alloys, polymers, and biomedical devices. Education Ph.D., Mechanical Engineering, Northwestern University (2015) M.S.E., Civil Engineering, University of Washington (2007) B.S., Aeronautical and Astronautical Engineering, University of Washington (2005) Research Focus Dr. Moore's work combines computational modeling with experimental validation to understand material behavior under extreme conditions. Key areas include: Crystal plasticity modeling of metallic alloys Nonlocal damage mechanics for fatigue prediction Dynamic spallation and porosity evolution High-throughput X-ray imaging of additively manufactured materials UV-sensitive resin material modeling Recent Publications His recent work focuses on advanced computational techniques for material failure analysis, including: Nonlocal approaches for statistical fatigue prediction Microinertia effects in spall modeling Betatron X-ray tomography applications UV resin optimization studies Phase transformation fatigue mechanisms Contact Email: john.a.moore@marquette.edu | Phone: (414) 288-6641 Location: Haggerty Hall, 225, Marquette University, Milwaukee, WI 53201

• Magnetic Recording
• Resistive Switching
• Phase Change Materials
• +3 more

James A. Bain is a Professor in the Electrical and Computer Engineering (ECE) Department at Carnegie Mellon University’s College of Engineering. He also holds a courtesy appointment in the Department of Materials Science and Engineering and serves as Associate Director of the Data Storage Systems Center (DSSC). Bain’s research focuses on magnetic, optical, and resistive switching devices for information storage, including heat-assisted magnetic recording (HAMR) and phase change materials. Education : B.S. (1988) in Materials Science and Engineering from the University of Pennsylvania; M.S. (1991) and Ph.D. (1993) in Materials Science and Engineering from Stanford University. His work spans nanotechnology, energy-efficient computing, RF metrology, and multiphysics modeling. Bain’s research has received recognition through the Scott Institute seed grant for energy research. He has co-authored over 225 papers and holds a leadership role as ECE’s Associate Department Head for Academic Affairs since 2018. His laboratory investigates thermal transport, device reliability, and emerging memory architectures. Recent publications highlight advancements in HAMR thermal management, resistive switching dynamics, and phase-change RF switches. Bain’s expertise intersects with the IEEE Magnetics, Electron Devices, and Photonics Societies, as well as the Materials Research Society.

Piotr KulikView profile

Assistant Professor

• Electrical Engineering
• Materials Science
• Nanofabrication of thin-film materials
• +2 more

Piotr Kulik is an Assistant Professor at the University of Central Florida (UCF) in the Department of Electrical and Computer Engineering within the College of Engineering and Computer Science. His research focuses on nanofabrication of thin-film materials, microsystems for sensing and communication, and multiphysics devices. Ph.D. in Electrical Engineering, Northeastern University (2020) Dr. Kulik’s research bridges advanced materials synthesis with microwave and MEMS device design. His work on magnetodielectric composites and ferrite thin films enables next-generation RF components for wireless systems. Current projects explore spatiotemporal modulation techniques to achieve magnetic-free non-reciprocal devices, reducing size and complexity in communication hardware. His recent publications emphasize broadband impedance tuning, miniaturized RF circulators, and zero-power wake-up receivers. These contributions leverage multiphysics modeling and nanofabrication to optimize microwave performance in magnetic-free topologies and composite materials. Scientific Awards Association of Old Crows, Nonprofit for Electronic Spectrum Management, Future 5 Award (2022) Experiential PhD Leadership Program (LEADERs Fellow), Gordon Institute of Engineering Leadership (2020) Dr. Kulik actively contributes to academic communities as an affiliate member of the IEEE Microwave Theory & Techniques Society (MTT-13) and serves as a reviewer for journals including IEEE Microwave and Wireless Components Letters and Thin Solid Films . He collaborates with teams in the AIMS Lab on microwave magnetics and system design challenges.

Niels AageView profile

Associate Professor

• Topology Optimization
• Acoustics and Vibroacoustics
• Biomechanics
• +5 more

Niels Aage is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on topology optimization, biomechanics, and multiphysics modeling, with applications in acoustic devices, biomedical implants, and microelectromechanical systems (MEMS). He holds roles such as Vice President of the International Society for Structural and Multidisciplinary Optimization (2023–2027). Education and Professional Background: Conducted a 5-month research visit at the University of Colorado, Boulder (USA) in 2010. Specializes in giga-scale numerical modeling, finite element methods, and topology optimization algorithms. Research Interests: Develops novel methods for topology optimization of fluidic, thermal, and acoustic systems. Explores applications in patient-specific spinal implants, metamaterials with vibroacoustic bandgaps, and nonlinear dynamic substructuring. His work integrates machine learning and reduced-order modeling for efficient simulation. Publications: Over 100 peer-reviewed articles, including recent contributions on connectivity promotion in topology optimization (2025), vibroacoustic metamaterial design (2025), and anatomically conforming spinal fusion cages (2024). Research emphasizes high-resolution modeling and bridging computational design with additive manufacturing. Scientific Awards: ISSMO Haftka Young Investigator Award (2021), Equinor Prize 2020, and Hyperion Innovation Excellence Award (2017). Recognized for contributions to structural optimization and computational mechanics. Advising and Grants: Supervises multiple PhD projects, including work on vibroacoustic shape optimization, quantum-opto-mechanical systems, and smart hearing aid modeling. Engages in collaborative projects funded by industry and academia. Labs/Teams: Collaborates with DTU’s Solid Mechanics group and industry partners on projects involving topology optimization, multiphysics simulation, and biomedical engineering. Active in international conferences and serves on editorial boards.

• High Performance Computing
• Multiscale and Multiphysics Simulations
• Fusion Energy Systems
• +3 more

Jacob Merson is an Assistant Professor in the Department of Mechanical, Aerospace, and Nuclear Engineering at Rensselaer Polytechnic Institute (RPI). He is affiliated with the Scientific Computation Research Center (SCOREC) and the Center for Materials, Devices, and Integrated Systems (CMDIS). His primary research focuses on High Performance Computing (HPC), with a particular emphasis on multiscale and multiphysics simulations. Key areas include fusion energy systems, plasma physics, and biomaterials modeling, leveraging machine learning and advanced computational frameworks. His work integrates cutting-edge tools like the XGC plasma simulation code and the PCMS parallel coupler, supporting digital twin development for fusion energy applications. He has contributed to open-source frameworks for fibrous materials modeling and unstructured mesh tools for energy systems. His research bridges computational methods with practical engineering challenges in fusion, biomechanics, and materials science. Notable contributions include machine learning approaches for constitutive modeling of fibrous materials and plasma turbulence studies in stellarator configurations. His articles emphasize fusion energy innovation, biomaterials mechanics, and HPC workflows. Merson collaborates extensively on multimodel simulation integration and has pioneered tools like Benesh for in situ workflow coordination. Despite his prolific research output, no specific grants or student advisees are explicitly listed in the provided materials.

Fang LuoView profile

Associate Professor

• Power Electronic Converters and Systems
• Power Module Packaging
• EMI Modeling and Mitigation

Fang Luo is the Empire Innovation Associate Professor and Director of the Spellman High Voltage Power Electronics Laboratory at Stony Brook University's Department of Electrical and Computer Engineering. He is affiliated with the College of Engineering and Applied Sciences, focusing on advancing power electronics technologies. His research interests encompass Power Electronic Converters and Systems, Power Module Packaging, and EMI Modeling and Mitigation. These areas address challenges in high-voltage systems, renewable energy integration, and electromagnetic compatibility. Dr. Luo's work emphasizes practical applications, such as optimizing power converters for offshore wind farms and developing advanced packaging solutions for wide bandgap (WBG) semiconductors. His laboratory, the Spellman High Voltage Power Electronics Lab, drives innovation in high-voltage systems and energy-efficient power electronics. His recent publications highlight advancements in HVDC wind energy systems, GaN-based converter designs, and EMI mitigation strategies. He has contributed to the design of modular power converters and cryogenic power electronics for electric aircraft propulsion. As a leader in his field, Dr. Luo's research bridges theoretical modeling and practical engineering solutions, with a focus on sustainable energy systems and cutting-edge semiconductor technologies.

Lisa Prahl WittbergView profile

Professor

• Fluid Mechanics
• Multiphase Flows
• Biomedical Engineering
• +4 more

Lisa Prahl Wittberg is a Professor of Fluid Mechanics with a specialization in Multiphase Flows at the Department of Engineering Mechanics, KTH Royal Institute of Technology , since 2021. She leads the Biomedical Flows research group , focusing on multiphase flow dynamics in clinical and industrial applications. Her research integrates engineering principles with biomedical challenges, particularly in extracorporeal life support systems, blood pumps, and hemodynamic modeling. She holds an MSc (Mechanical Engineering) and PhD in Fluid Mechanics from Lund University (2007), followed by a Docentship in 2014. Her work addresses pathological processes and device performance in clinical applications, such as ECMO, hemodialysis, and respirators. Key areas include blood flow dynamics in artificial devices, particle transport in biological systems, and improving device safety through computational models. Her publications emphasize cannula design optimization, blood pump performance, and patient-specific vascular modeling. She collaborates on translating engineering insights into clinical practice, enhancing treatment efficacy and reducing complications in critically ill patients. Education: MSc (Lund University), PhD in Fluid Mechanics (2007), Docentship (2014). Labs/Teams: Biomedical Flows research group. Focus Areas: Multiphase flows, biomedical devices, hemodynamics, extracorporeal support systems.

• Semiconductor Devices
• Silicon Carbide Technology
• Optogenetics
• +3 more

Professor Anthony O'Neill at Newcastle University is a leading researcher in semiconductor device physics, optogenetic neuroprosthetics, and strained silicon engineering. His work spans silicon carbide MOSFETs, graphene fabrication, and implantable neural interfaces, with a focus on improving device performance through material science innovations. Semiconductor Device Physics Optogenetic Neuroprosthetics Strained Silicon Technology Micromachining Processes Advanced Material Characterization His 15 most recent publications (2018-2024) demonstrate expertise in: 4H-SiC MOSFET optimization Nitridation techniques Implantable neuroprosthetic systems Molecular dynamics simulations for silicon processing High-κ dielectrics in microelectronics Flexible electrode arrays

James CampbellView profile

Professor

• Numerical Modelling
• Impact Engineering
• Crashworthiness
• +4 more

Dr James Campbell is a Reader in Structural Integrity at Brunel University London's Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences. With a PhD in hypervelocity impact on spacecraft and 20+ years of experience leading multidisciplinary projects, he specializes in non-linear numerical methods (FE and SPH), structural integrity, and impact analysis across aerospace, defense, and automotive sectors. BEng in Aeronautical Engineering, Imperial College London MSc and PhD in Astronautics and Space Engineering, Cranfield University His research focuses on: Transient response of materials/structures (e.g., space debris impact, aircraft crashworthiness) Meshless methods like Smoothed Particle Hydrodynamics (SPH) Constitutive models for isotropic/orthotropic materials Fluid-structure interaction in ditching and extreme wave events Recent work trends include space debris removal tools, composite material development for offshore energy, and advanced SPH algorithms for impact simulations. Awards include the Derek George Astridge Safety in Aerospace Award (2009) and Royal Institute of Naval Architects Medal (2010). He supervises PhD/MSc students and delivers CPD courses for industry (Boeing, Leonardo). Research group: IMM (International Marine and Offshore). Collaborations include Airbus, DLR, and ESA.

Yu U. WangView profile

Professor

• Phase Transforming Materials
• In-Situ Synchrotron X-Ray Diffraction
• Neutron Scattering
• +5 more

Yu U. Wang is a Professor in the Department of Materials Science and Engineering at the College of Engineering, Michigan Technological University. His research integrates experimental characterization and computational modeling to advance functional materials science, with a focus on phase transformations and microstructure-property relationships. Dr. Wang's educational background includes: PhD in Mechanical and Aerospace Engineering from Rutgers University BS in Mechanical Engineering from the University of Science and Technology of China His research spans phase transforming materials, in-situ synchrotron X-ray and neutron scattering techniques, diffuse scattering analysis, ferroelectric/magnetoelectric composites, colloidal self-assembly systems, and computational microstructure modeling. This work bridges fundamental materials physics with applications in energy harvesting, sensing, and advanced ceramics, emphasizing the interplay between nanoscale phenomena and macroscopic properties. Analysis of Dr. Wang's publications reveals a sustained focus on computational materials science, particularly phase field modeling applied to ferroelectric and shape-memory systems. His research consistently combines theoretical frameworks with experimental validation through diffraction techniques, targeting high-strain piezoelectrics, magnetoelectric composites, and nanodomain engineering for next-generation functional materials. Scientific awards received by Dr. Wang are not specified in the available documentation. Details regarding graduate student advising, research grants, and laboratory facilities are not provided in the source material, though his extensive publication record indicates active research supervision and project leadership.