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Robert RohlingView profile

Professor

• Biomedical Engineering
• Medical Imaging
• Medical Information Systems
• +3 more

Robert Rohling is a Professor at the University of British Columbia's Faculty of Applied Science, affiliated with the Department of Mechanical Engineering and holding a joint appointment with the Department of Electrical and Computer Engineering. As Director of the Institute of Computing, Information and Cognitive Systems (ICICS), his research focuses on biomedical engineering, medical imaging, robotics, and computational methods. B.A.Sc. (UBC) M.Eng. (McGill) Ph.D. (Cambridge) Rohling's work spans three primary research areas: medical imaging (3D ultrasound, spatial compounding, elasticity reconstruction), medical information systems (radiologist navigation tools for large image datasets), and robotic calibration for surgical applications. His multidisciplinary approach integrates mechanical and electrical engineering principles with clinical needs. Rohling's publications (2020-2022) reveal trends in advanced ultrasound techniques (e.g., shear wave vibro-elastography), AI-driven image processing (cycleGAN translation), and computational optimization for diagnostic accuracy. Keywords across his work include Medical Imaging, Biomedical Engineering, Robotics, and Computational Modeling. As director of the Robotics and Control Laboratory , Rohling leads interdisciplinary collaborations with industry and clinical partners to address practical challenges in medical diagnostics and surgical robotics. His research emphasizes translating engineering innovations into clinical practice.

Gary FedderView profile

Professor

• Microelectromechanical Systems (MEMS)
• Advanced Manufacturing
• Nanomanufacturing
• +6 more

Gary Fedder is the Howard M. Wilkoff Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with courtesy appointments in Biomedical Engineering, Mechanical Engineering, and Robotics. He serves as Faculty Director of the Manufacturing Futures Institute (MFI) and previously held roles such as Vice Provost for Research and Interim CEO of the Advanced Robotics for Manufacturing (ARM) Institute. Fedder’s research focuses on MEMS, advanced manufacturing, and implantable microsystems. He earned his B.S., M.S., and Ph.D. in EECS from MIT and UC Berkeley, respectively. Education: Ph.D., Electrical Engineering and Computer Science, UC Berkeley (1994) M.S., Electrical Engineering and Computer Science, MIT (1984) B.S., Electrical Engineering and Computer Science, MIT (1982) Research Interests: Microelectromechanical systems (MEMS), digital twins, aerosol jet printing, stretchable electronics, and manufacturing innovation. His work integrates MEMS with CMOS processes, emphasizing low-cost, high-performance systems. Key Contributions: Co-founded the ARM Institute; developed MEMS-based sensors and actuators; pioneered methods for manufacturing innovation through projects like America Makes. His research spans over 300 publications and 21 patents. Awards: IEEE Fellow (2007), Ross Tucker Award (1993), NSF CAREER Award (1996), and leadership roles in Manufacturing USA initiatives. Leadership & Outreach: Directed the Institute for Complex Engineered Systems and led national initiatives to advance U.S. manufacturing competitiveness. Active in editorial roles for journals like IoP Journal of Micromechanics .

Yamin ZhangView profile

Assistant Professor

• Bioelectronics
• Bioresorbable Medical Devices
• Electrotherapy
• +6 more

Dr. Yamin Zhang (张亚敏) holds a Presidential Young Professorship as an Assistant Professor in the Department of Chemical & Biomolecular Engineering at the National University of Singapore (NUS), College of Engineering. She leads the Zhang Group which focuses on interdisciplinary research at the intersection of electrochemistry, materials science, and biomedical engineering. 07/2023 – 01/2024: Research Associate, Northwestern University 02/2021 – 06/2023: Postdoctoral Fellow, Northwestern University 08/2016 – 12/2020: Ph.D., Chemical Engineering, Georgia Institute of Technology 09/2012 – 07/2016: B.S., Chemical Engineering, Tianjin University; B.S., Finance (Double Major), Nankai University Dr. Zhang's research centers on developing advanced electrochemical strategies for next-generation medical devices (implantable, bioresorbable, and wearable) and sustainable energy solutions. Her work bridges bioelectronics , battery technology , and medical therapeutics , with particular emphasis on creating devices that can safely dissolve in the body after serving their purpose. Key areas include bioresorbable optoelectronic systems for electrotherapy, self-powered drug delivery platforms, and eco-safe battery technologies that can harmlessly resorb in biological environments. Analysis of Dr. Zhang's publication record reveals a clear trajectory from fundamental battery chemistry (2021-2022) toward increasingly sophisticated medical applications (2023-2025). Her recent work demonstrates mastery in integrating multiple functionalities into single bioresorbable platforms, as evidenced by her Nature (2025) paper on millimeter-scale optoelectronic systems for electrotherapy and Cell Biomaterials (2025) paper on wireless bioelectronic devices. The research shows strong interdisciplinary collaboration with leading institutions including Northwestern University and Georgia Tech. AHA Early Faculty Independence Award (2023) MIT ChemE Rising Stars (2022) Sigma Xi Best PhD Thesis Award (2021) Chinese Government Award for Outstanding Students Abroad (2021) A*STAR MTC Young Individual Research Grants (YIRG) (2025) Early Career Board Member for ACS Applied Materials & Interfaces (2025) Dr. Zhang has secured significant research funding including the AHA's Second Century Early Faculty Independence Award as Principal Investigator (2023) and the A*STAR MTC Young Individual Research Grant (2025). Her group serves on advisory boards for Cell Biomaterials and ACS Applied Materials & Interfaces. The Zhang Group at NUS maintains active collaborations with Northwestern University researchers including the Rogers group, with whom she has co-authored multiple high-impact publications in Nature, Science, and PNAS. Current research focuses on advancing battery technology and developing sophisticated electrochemical strategies for medical devices with an overarching focus on healthcare innovation and environmental sustainability.

• Aerospace Composites
• Damage Tolerance Analysis
• Impact Mechanics
• +3 more

Dr Andrew Rhead is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, specializing in aerospace composites and damage tolerance analysis. His research focuses on impact damage detection, failure mechanism modeling, and Non-Destructive Evaluation (NDE) techniques for composite structures. MSci in Mathematical Sciences (Dynamical Systems) - University of Bristol (2006) PhD in Composite Damage Tolerance - University of Bath (2009) His work develops computationally efficient analytical models for compression after impact (CAI) strength prediction in composite laminates, surpassing traditional finite element methods. Key projects include hydrogen storage systems for aircraft, cryogenic composite testing, and steered fiber manufacturing optimization. Active in 10 projects including ASPIRE and HyFIVE Collaborates with Airbus, GKN Aerospace, and EPSRC Research trends show emphasis on sustainable aviation materials, structural battery integration, and advanced testing methodologies. Current affiliations include the Institute for Mathematical Innovation (IMI) and Centre for Integrated Materials, Processes & Structures (IMPS).

Steffen MarburgView profile

Professor

• Numerical Methods in Vibroacoustics
• Aeroacoustics
• Structural Optimization
• +6 more

Prof. Dr. Steffen Marburg is a Full Professor at the Chair of Acoustics of Mobile Systems within the TUM School of Engineering and Design at the Technical University of Munich. His research focuses on numerical methods in vibroacoustics, structural optimization, and acoustic modeling for applications in automotive, maritime, and musical instrument domains. Education: PhD from Technical University of Dresden (1998). Academic Career: Junior Professor at TU Dresden (2004), Chair of Technical Dynamics at University of the Federal Armed Forces Munich (2010), Full Professor at TUM (2015–present). Editorial Roles: Co-Editor-in-Chief of Journal of Theoretical and Computational Acoustics, Associate Editor of Journal of the Acoustical Society of America, Editor of Acoustics Australia and Mechanical Systems and Signal Processing. His research integrates computational acoustics, boundary element methods, and machine learning to address noise control and structural optimization challenges. Recent work explores acoustic metamaterials, viscothermal losses, and data-driven modeling. He has co-authored over 150 publications and led advancements in multifrequency solution methods and noise-insulating structures. Scientific awards include the Innovation Award of the Industrieclub Sachsen e.V. (1999). His editorial contributions and leadership in journals highlight his influence in computational acoustics and structural dynamics.

• Advanced Manufacturing
• Materials Science
• Mechanical Engineering
• +7 more

Dr. Ling Yin is an Associate Professor in the School of Electrical and Mechanical Engineering at the University of Adelaide, Faculty of Sciences, Engineering and Technology. She joined the University of Adelaide in 2018 as an Associate Professor in manufacturing and served as Faculty Research Theme Leader in Advanced Manufacturing from 2019 to 2022. Dr. Yin leads multi-institutional projects on advanced manufacturing funded by Defence SA (2024-2025) and the National Health and Medical Research Council (NHMRC) (2025-2028). Dr. Yin's educational background includes B.Sc., M.Sc., and Ph.D. degrees in mechanical engineering from Huazhong University of Science & Technology in Wuhan, China. Her academic career spans five countries across three continents, including positions at Tianjin University in China, Kumamoto University in Japan, Kansas State University in the USA, the Australian National University and James Cook University in Australia, the National Institute of Standards & Technology (NIST) in the USA, and A*STAR Singapore Institute of Manufacturing Technology (SIMTech) in Singapore. Dr. Yin's research focuses on manufacturing and mechanical characterization of advanced materials with applications in optics, semiconductors, mechanical structures, dental restorations, osteoporosis/osteoarthritis studies, and marine/animal sciences. Her work involves extensive collaborations across multiple disciplines. Her recent publications demonstrate expertise in ultrasonic vibration-assisted machining of dental ceramics, particularly zirconia and lithium silicate glass-ceramics, as well as advanced characterization techniques like micro-CT and in-situ SEM testing for understanding material behavior at micro and nano scales. JSPS Invitation Fellowship from the Japan Society for the Promotion of Science Japanese Government Scholarship from the Ministry of Education, Culture, Sports, Science and Technology, Japan Supervisor for a PhD Thesis cum laude with a Medal of Excellence awarded by James Cook University in 2017 Supervisor for a Best Honours Project in Mechanical Engineering at Ingenuity awarded by the University of Adelaide in 2023 Dr. Yin is actively involved in supervising higher degree research students and has available PhD projects in 2025 focused on ultrasonic-vibration assisted manufacturing techniques for dental applications. She has successfully led international academic delegations through the New Colombo Plan to manufacturing facilities in Singapore and Japan. Dr. Yin is a senior member of the North American Manufacturing Research Institution (NAMRI) and the Society of Manufacturing Engineers (SME), and also a member of several professional organizations including ASME, OSA, American Ceramic Society, ASM International, and SPIE.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +5 more

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

Jeremy DahlView profile

Professor

• Medical Ultrasound Imaging
• Ultrasonic Beamforming
• Image Reconstruction
• +7 more

Jeremy Dahl is a Professor of Radiology (Pediatric Radiology) at Stanford University School of Medicine. He directs the Ultrasound Imaging & Instrumentation Lab and serves as Director of Research Academic Affairs in the Department of Radiology since 2020. He holds multiple affiliations across Stanford including Bio-X, the Cardiovascular Institute, Wu Tsai Human Performance Alliance, Maternal & Child Health Research Institute, Stanford Cancer Institute, and Wu Tsai Neurosciences Institute. Dr. Dahl received his B.S. in Electrical Engineering from the University of Cincinnati (1999) and Ph.D. in Biomedical Engineering from Duke University (2004). His research focuses on developing ultrasonic beamforming and image reconstruction methods for diagnostic imaging applications, particularly techniques that generate high-quality images in difficult-to-image patients. His laboratory specializes in B-mode and Doppler imaging techniques that utilize additional information from ultrasonic wavefields to improve image quality and develop real-time imaging systems for clinical applications including cardiac, liver, and fetal imaging. Dr. Dahl's research has led to significant advancements in ultrasound molecular imaging platforms, sound speed estimation, aberration correction, and reverberation noise suppression. His work often bridges engineering innovation with clinical applications for cancer detection and other diseases. His recent publications demonstrate strong focus on machine learning applications in ultrasound, distributed aberration correction, and molecular imaging techniques. Fellow, American Institute of Ultrasound in Medicine (2021) Senior Member, Institute of Electrical and Electronics Engineers (2020) Distinguished Investigator Award, The Academy for Radiology & Biomedical Imaging Research (2018) Outstanding Paper Award, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (2011) Dr. Dahl serves in editorial roles for major journals including IEEE Transactions on Medical Imaging (2017-2024) and IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2013-Present). His laboratory has successfully translated numerous innovations into clinical applications, with multiple patents including recent developments in pulsed focused ultrasound therapy and speed of sound quantification.

Ioannis GkioulekasView profile

Assistant Professor

• Computational Imaging
• Computer Vision
• Computer Graphics
• +6 more

Ioannis Gkioulekas is an Assistant Professor at the Robotics Institute within Carnegie Mellon University's School of Computer Science, with a courtesy appointment in Electrical and Computer Engineering. He leads the Computational Imaging Lab at CMU, focusing on joint hardware-software approaches to develop advanced imaging systems. His research spans computational imaging, computer vision, and graphics, addressing challenges like non-line-of-sight imaging, 3D sensing, and adaptive optics. Research interests include: Computational imaging systems design Non-line-of-sight and single-photon imaging LiDAR, SONAR, and interferometry applications Physics-based and differentiable rendering Probabilistic modeling and Monte Carlo methods Recent publications (2019-2021) demonstrate strong focus on waveguides, light transport simulation, 3D sonar reconstruction, and computational tomography. Common themes include inverse problems, wave-based imaging, and differentiable simulation techniques bridging graphics and sensing. Current advising includes Master's student Neham Jain and affiliates Bakari Hassan, John Liu, Bailey Miller, Sreekar Ranganathan, and Arjun Teh. Past students include PhD graduates Arpit Agarwal and Shumian Xin, and Master's student Shirsendu Halder.

• Machine Learning
• Deep Learning
• Signal Processing
• +9 more

Prof. Dr.-Ing. Ahmad Osman is a Professor at the Saarland University of Applied Sciences (htw saar), specializing in Test Technologies and Test Methods within the Faculty of Engineering. He also holds an Adjunct Professor position at Laval University in Quebec, Canada, in the Department of Electrical Engineering and Computer Science. His research focuses on Artificial Intelligence applications in Signal and Image Processing for Non-destructive Testing (NDT) , with extensive work on Deep Learning , 3D Ultrasound Tomography , and Sensor Data Fusion in industrial contexts. Engineering Artificial Intelligence Signal Processing Image Processing Non-destructive Testing Quality Control Augmented Reality Osman leads the AutomaTiQ research group and serves as Head of the Algorithms/Signal and Data Processing Department at Fraunhofer IZFP . His recent publications (2017–2022) emphasize Deep Learning for defect detection in CFRP , Terahertz Imaging for artwork diagnostics, and Acoustic Sensors for agricultural quality control. He has organized international conferences on Structural Health Monitoring and contributed to Springer books on NDT technologies. His projects include ComforTex-AI (2024) and development of 3D positioners for ultrasound measurements. Collaborations span institutions in Germany, Canada, Italy, and Brazil, with advisory roles in the German Society for NDT and technical committees for conferences in Montreal and Egypt.

• Differential Privacy
• Machine Learning
• Privacy-Preserving Data Analysis
• +3 more

Daniel Kifer is a Professor in the Computer Science and Engineering department at Pennsylvania State University, with affiliations to the Huck Institutes of the Life Sciences. His work bridges computer science, privacy-preserving machine learning, and geoscience applications. With over 10,000 citations and a high h-index, he focuses on methods to unify theoretical and applied research. Research Interests: Differential Privacy, Privacy-Preserving Machine Learning, Physics-Informed Neural Networks, Landslide Prediction, and Formal Verification of Privacy Systems. Recent projects include grants from the National Science Foundation: SaTC: CORE: Small (2024): privacy-preserving user data embedding in machine learning pipelines. SaTC: CORE: Medium (2017-2023): formal methods for differential privacy and accuracy optimization. His research outputs span domains like geoscience, database systems, and policy analysis, emphasizing precision and scalability of privacy-preserving algorithms.

Kim Yong-JoeView profile

Associate Professor

• Acoustics and Applied Signal Processing
• Nonlinear Acoustics
• Biomedical Acoustics
• +2 more

Dr. Kim Yong-Joe is an Associate Professor in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University. He serves as the Director of the Acoustics and Signal Processing Laboratory (ASPL), founded in 2009. His research focuses on acoustics, applied signal processing, nonlinear acoustics, biomedical acoustics, noise and vibration control, and structural dynamics. He has received notable awards including the 2014 Department of Mechanical Engineering Graduate Teaching Award and the 2014 Pioneer Natural Resources Faculty Fellow II. His lab specializes in wave propagation analysis, ultrasonic structural health monitoring, and acoustophoresis in microfluidic systems. He has collaborated with sponsors like the National Science Foundation, Qatar National Research Fund, and Samsung Techwin. His research has led to advancements in noise reduction technologies, biomedical diagnostics, and nondestructive evaluation methods.

• Computational Fluid Dynamics
• Internal Combustion Engines
• Cavitation
• +13 more

Professor Manolis Gavaises is a leading academic in the field of mechanical engineering and computational fluid dynamics at City St George's, University of London, where he holds the position of Professor in the School of Engineering and Mathematical Sciences. He earned his PhD from Imperial College London and has been a faculty member since 2001, progressing to full Professor in 2009. His research is centered on advanced modeling of multi-phase flows, cavitation, and fuel injection systems, with extensive collaborations across Europe and industry partners such as Delphi, Caterpillar, and BP. Education: DIC, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 PhD, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 Diploma (5 years), Mechanical Engineering, National Technical University of Athens, 1992 His research interests span computational fluid dynamics, cavitation, fuel injection, atomization, high-pressure and supercritical flows, and alternative fuels . He has developed advanced numerical models and experimental techniques, including X-ray phase contrast imaging and high-pressure test rigs. His work integrates fundamental DNS and LES simulations with industrial applications in automotive, marine, aerospace, and medical devices such as heart valves. The recent publications reflect a strong trend toward real-fluid thermodynamic modeling (e.g., PC-SAFT), multi-component fuel behavior, cavitation erosion, and advanced diagnostics . His research increasingly incorporates machine learning and high-fidelity imaging to understand complex flow phenomena across energy, transportation, and biomedical domains. Scientific Awards and Recognitions: Richard Way Prize (1998) Arch T. Collwell Merit Award (1998) Best Oral Paper, SAE World Congress (2006) PE Publication Award, IMechE (2007) Best Presentation Award, Engine Combustion Processes (2009) Fellow, IMechE (2013) Fellow, IMA (2015) As a dedicated mentor, Professor Gavaises has supervised 13 PhDs to completion and currently guides 23 doctoral students. He has secured over €16 million in EU and UK funding, including multiple Horizon 2020 Marie Skłodowska-Curie ITN projects (CAFÉ, HAOS, IPPAD), which support 46 early-career researchers globally. He has created academic opportunities for post-docs and junior faculty, significantly advancing the research profile of his institution. He leads the International Institute of Cavitation Research (IICR), co-founded in 2011 with partners from Loughborough University, TU Delft, and Imperial College, supported by The Lloyd’s Register Foundation. His lab maintains strong experimental capabilities, including a 2000bar pressure flow rig with micro-transparent nozzles and collaborations with Argonne National Laboratory for X-ray imaging.

• Friction stir welding
• Steel metallurgy
• Materials engineering
• +4 more

Dr. Athanasios Toumpis is a Senior Lecturer in Mechanical and Aerospace Engineering at the University of Strathclyde, UK. He holds a Master of Science from the University of Glasgow (2012) and a Master of Engineering from the National Technical University of Athens (2003). His research focuses on friction stir welding (FSW), steel metallurgy, and fatigue analysis of structural materials. Key areas include defect analysis in FSW joints, thermal-mechanical behavior of materials, and gigacycle fatigue testing of welded steels. He has led multiple research projects funded by organizations like the Royal Society and Weir Group, including the development of novel FSW technologies for nuclear applications and investigations into steel joint performance under extreme conditions. Dr. Toumpis has authored over 50 publications, with recent work emphasizing very high-cycle fatigue behavior and additive manufacturing processes. He actively participates in international conferences and serves as a principal investigator on various collaborative projects. His teaching includes courses on applied metallurgy, biomaterials, and materials selection. Research Interests: Friction stir welding of low-alloy and stainless steels Fatigue analysis of welded joints, including gigacycle testing Thermal-mechanical analysis of additive manufactured materials Metallurgical characterization of dissimilar material joints Environmental impact assessment of manufacturing processes Professional Activities & Awards: Recipient of the Global Engagement Fund (2024) Organized the First Joint International Conference on Advances in Mechanical and Aerospace Engineering (2023) Participant in the International Institute of Welding Assembly (2024) and Very High Cycle Fatigue Conference (2024) Hosted visiting researchers and collaborated with institutions like Graz University of Technology Grants & Projects (Recent): Development of a novel friction stir additive manufacturing technology (Royal Society, 2025–2026) Investigation of friction stir welded steel joints for giga-cycle applications (Weir Group, 2025–2027) ESCO buckets weld performance investigation (University of Strathclyde, 2024–2027)

• Additive Manufacturing
• Micro Metal Forming
• Tribology
• +4 more

Dr Dongbin Wei is an Associate Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney (UTS), with a career spanning academia and industry. He holds a PhD in Materials Processing Engineering from the University of Science and Technology Beijing (2001) and academic appointments from 2005–2012 at the University of Wollongong (Research Fellow to Lecturer) and 2013–2017 at UTS (Senior Lecturer) before his promotion to Associate Professor in 2018. His research lies at the intersection of Mechanical Engineering , Manufacturing Engineering , and Materials Processing , focusing on: Ultrasonic Additive Manufacturing (UAM) Micro Metal Forming and Size Effects Tribology and Lubrication Numerical Simulations of Material Processing Composite Material Fabrication Key contributions include: Development of the Springback Path–Displacement Adjustment (SP-DA) method for stamping accuracy Advancements in femtosecond laser texturing for silicon wettability control Studies on nanolubrication in hot rolling Optimization of micro-deep drawing parameters He has secured competitive grants from the Australian Research Council (ARC) and industry partners like Weir Minerals Australia Ltd , including projects on: Revolutionizing mineral separation via additive manufacturing Super high-speed grinding technologies Mechanics of micro composite drill fabrication As a lead supervisor, he guided the 2022 thesis 'Creation and Validation of 3D Printable Mineral Separation Spiral' . His work bridges theoretical analysis, computational modeling (FEM/FEA), and practical validation in advanced manufacturing systems.