جست‌وجوی استاد و پژوهشگر

• Thermal Engineering
• Renewable Energy
• Nanotechnology
• +۳ مورد دیگر

Omid Mahian is a professor at Ningbo University, Ningbo, China, with significant contributions to thermal engineering, renewable energy, and nanotechnology. His research focuses on optimizing heat transfer mechanisms in systems like supercritical CO 2 cycles, printed circuit heat exchangers, and photovoltaic thermal modules. He has over 14,597 documents cited, with an h-index of 81 and 287 publications on Scopus. Key research areas: Thermal Load, Surface Roughness, Microchannel Flow, Exergy Destruction, Renewable Energy, Forced Convection. Recent work explores advanced cooling techniques (e.g., wicked heat pipes, grooved copper foam) and nanofluid applications for atmospheric water harvesting and CO 2 absorption. His studies address energy efficiency in off-grid systems, including predictive dispatch strategies for hybrid renewable energy, supersonic separation for carbon capture, and thermal management in electric vehicle motors. Omid Mahian has authored 180 articles on ScienceDirect, with a focus on improving energy systems through innovative designs and materials. His collaborations span numerous disciplines, emphasizing sustainability and technological feasibility.

Kawal Rhodeمشاهده پروفایل

استاد

• Image-guided interventions
• Medical image processing
• Patient-specific cardiac biophysical modelling
• +۷ مورد دیگر

Kawal Rhode is a Professor in Biomedical Engineering and the Head of Education at the School of Biomedical Engineering & Imaging Sciences , King’s College London. His work bridges engineering, clinical practice, and education, with a focus on image-guided interventions, medical robotics, and 3D printing in healthcare. He leads the educational strategy for multiple taught programs, including the BEng/MEng in Biomedical Engineering and MSc programs in Healthcare Technologies and Clinical Sciences. His educational background includes a BSc in Basic Medical Sciences and Radiological Sciences from Guy's & St. Thomas' Hospitals Medical School (1992) and a PhD in arterial blood flow analysis from University College London (2006). He joined King’s in 2001 as a postdoctoral researcher and progressed through academic ranks to full Professor in 2016. Prof. Rhode’s research centers on image-guided interventions , medical robotics , and innovative pedagogy . His team develops intelligent systems for catheter-based procedures, robotic ultrasound, and simulation platforms using 3D printing. His work integrates AI, biomechanics, and translational engineering to improve clinical outcomes. His recent publications (2024–2025) reflect a strong trend in autonomous robotic systems , AI-driven image analysis , and simulation-based training , particularly in cardiac and interventional applications. These works span journals and conferences in medical imaging, robotics, and biomedical engineering, showcasing interdisciplinary innovation. Wellcome EPSRC Centre for Medical Engineering (Co-Investigator) Three-Dimensional Hybrid Guidance System for Cardiac Interventional Procedures (PI, EPSRC-funded) SIE CDT: Haemodynamics of complex aortic aneurysms (Co-I, Artivion Inc) He leads the Success for Black Engineers initiative, funded by the Royal Academy of Engineering, to improve diversity and inclusion in engineering education. This includes outreach, mentoring, industry engagement, and wellbeing support for Black students. He has supervised numerous students and collaborators, many of whom appear as co-authors on recent publications. His lab is part of a broader network within the School of Biomedical Engineering & Imaging Sciences, collaborating with clinicians at St Thomas’ Hospital and industry partners.

• Experimental Fluid Dynamics
• Data Assimilation
• Network Science
• +۳ مورد دیگر

Prof. Dr.-Ing. David E. Rival is a full Professor at the Institute of Fluid Mechanics within the Faculty of Mechanical Engineering at Technische Universität Braunschweig. His research spans interdisciplinary domains at the intersection of experimental fluid dynamics, data assimilation, network science, and bio-inspiration, with applications in renewable energy systems and bio-mimetic engineering. Former Associate Professor at Queen’s University, Canada Doctoral work on dragonfly flight aerodynamics at TU Darmstadt Alexander von Humboldt research fellowship recipient (2020) Postdoctoral associate at MIT studying shape morphing in nature Research chair at University of Calgary on atmospheric sensing His work focuses on unsteady flow phenomena, bio-inspired design, and advanced measurement techniques. Key projects include: Co-chairing NATO AVT task group on flow separation International collaborations with AFOSR, NATO, and ONR Development of cost-effective flow-tracking sensors for natural environments Investigations into shear-thinning suspension dynamics and vortex ring behavior Recent publications demonstrate a strong emphasis on: Large-scale particle tracking with natural light and UAVs Machine learning for sparse data reconstruction in fluid flows Soft coastal protection methods and ecohydraulics Advanced sensing techniques for atmospheric and industrial applications Scientific Awards: 2020: Alexander von Humboldt Research Fellowship Notable research achievements include textbook authorship on Biological and Bio-Inspired Fluid Dynamics (Springer) and media features in The Nature of Things (David Suzuki) and Discovery Channel’s Daily Planet .

• Transmission Electron Microscopy (TEM) Method Development
• Charge Particle Optics and Scattering Theory
• Magnetic Nanotextures
• +۳ مورد دیگر

Dr. Axel Lubk is a Group Leader at the Institute for Solid State Research (IFW Dresden) , specializing in advanced electron microscopy techniques for materials science. His research spans four key areas: (1) TEM method development (high-resolution imaging, tomography, holography, and in-situ techniques), (2) charge particle optics and scattering theory , (3) magnetic nanotextures (domain walls, skyrmions), and (4) plasmonics (mode hybridization in heterogeneous structures and semiconductor heterostructures). Dr. Lubk’s work focuses on three-dimensional magnetic texture analysis using electron holography and tomography, particularly in systems like skyrmion tubes , FeGe , and Cr2O3 thin films . He has pioneered techniques for vector-field electron tomography and phase retrieval under varying boundary conditions, advancing nanoscale magnetic imaging. His recent studies include plasmonic properties in AgAu nanosphere chains , thermoelectric multilayer systems , and topological insulators like NiRh2Sb and TaTMTe4 . Dr. Lubk has published extensively in high-impact journals such as Nature Communications and Advanced Materials , with a focus on TEM instrumentation and quantitative analysis . He frequently presents at international conferences like the International Microscopy Congress and European School of Magnetism , emphasizing applications in spintronics , quantum materials , and nanostructured systems . His contributions to holographic vector-field electron tomography and machine learning for spectrum-image data have set new standards in electron microscopy.

Ninghao Liuمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Explainable AI (XAI)
• +۶ مورد دیگر

Dr. Ninghao Liu is an Assistant Professor of Computer Science in the School of Computing at the University of Georgia, part of the Franklin College of Arts & Sciences - Division of Physical & Mathematical Sciences. He holds a Ph.D. in Computer Science from Texas A&M University (2021) and an M.S. in Electrical and Computer Engineering from Georgia Institute of Technology (2015). His research focuses on Explainable AI (XAI), Graph Mining, Model Fairness, Recommender Systems, and Outlier Detection, with notable contributions to foundational AI techniques and their applications in education, healthcare, and environmental sciences. Dr. Liu has secured significant funding, including a three-year NSF grant (2022–2025) for 'Graph-Oriented Usable Interpretation' and a five-year $10 million grant from the U.S. Department of Education (2024–2029) for the GenAI Empowered National Initiative for STEM+C Education. He has also been honored with the Outstanding Paper Award at ICML 2022, Best Paper Award Shortlist at WWW 2019, and other distinctions. His work emphasizes interpretable machine learning, graph neural networks, and addressing algorithmic bias. He collaborates across disciplines, contributing to radiology AI, climate-smart forestry, and pandemic prediction through knowledge-enhanced deep learning. His lab is based at the Boyd Research and Education Center, where he advances research in trustworthy AI systems and data-centric solutions.

Malay Kumar Dasمشاهده پروفایل

استاد

• Fluid Dynamics
• Thermal Science
• Energy Conversion
• +۳ مورد دیگر

Malay Kumar Das is a Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur, specializing in Fluid and Thermal Science. His academic journey includes a PhD from Pennsylvania State University (2008), M.Tech from IIT Kanpur (2003), and B.E. from Bengal Engineering College, Shibpur (1989). Previously, he worked at the West Bengal Power Development Corporation from 1990 to 2001 before transitioning to academia. His research focuses on Energy Conversion and Storage, Hydrodynamic Instability, and Thermal Science. Dr. Das's work bridges fundamental fluid dynamics with practical applications in energy systems and biomedical engineering. His expertise spans computational fluid dynamics, heat transfer phenomena, and energy conversion technologies. Analysis of Dr. Das's recent publications reveals a strong trend toward interdisciplinary research, particularly at the intersection of fluid mechanics with biomedical applications (such as blood flow modeling in cerebral aneurysms) and sustainable energy technologies (including fuel cells, methane production, and nanofluid applications). His work demonstrates both theoretical depth and practical relevance to contemporary engineering challenges. Dr. Das actively supervises research students, currently guiding 9 PhD candidates and having successfully completed 22 MTech theses with 3 more in progress. His professional activities reflect a commitment to advancing knowledge in thermal and fluid sciences while training the next generation of engineers. Outside academic pursuits, he engages in adventure sports, photography, and aerobics.

James St Johnمشاهده پروفایل

استاد

• Spinal Cord Injury Repair
• Peripheral Nerve Injury
• Neurodegeneration
• +۴ مورد دیگر

Professor James St John is a translational neuroscientist and HTH Dean (Research) at Griffith University, leading the Clem Jones Centre for Neurobiology and Stem Cell Research. His work focuses on developing cell-based therapies for spinal cord injury, leveraging olfactory glial cells and three-dimensional nerve bridges. He holds a PhD in Agricultural Science from the University of Melbourne and has secured over $35 million in research funding. Affiliations: Institute for Biomedicine and Glycomics, Griffith University Roles: Professor, Head of Clem Jones Centre, HTH Dean (Research) Research interests include spinal cord injury repair, peripheral nerve regeneration, microbial contributions to neurodegeneration, and olfactory system biology. His team is advancing a Phase I/IIA clinical trial for spinal cord injury therapy using autologous olfactory cell transplantation combined with rehabilitation. Key grants include Perry Cross Spinal Research Foundation funding ($5M+), NHMRC/MRFF support, and philanthropic donations from the Clem Jones Foundation. Supervised over 30 doctoral and master’s students in neural repair research. Labs/Teams: Clem Jones Centre for Neurobiology and Stem Cell Research, collaborating with Making Strides Rehabilitation for clinical trial readiness.

Matthew A. Franchekمشاهده پروفایل

استاد

• Dynamic Systems
• Control Systems Engineering
• Nonlinear Control Theory
• +۴ مورد دیگر

Matthew A. Franchek is a Professor in the Department of Mechanical and Aerospace Engineering at the University of Houston, where he has served since 2002. His career spans over three decades, including prior roles as Professor and Chair at the University of Houston (2002–2009), Director of the Biomedical Engineering Program (2002–2009), and faculty positions at Purdue University from 1992 to 2002. He earned his Ph.D. (1991), M.S. (1988), and B.S. (1987) in Mechanical Engineering from Texas A&M University and the University of Texas at Arlington, respectively. Dr. Franchek’s research focuses on Dynamic Systems, Measurement and Control , with expertise in linear/nonlinear system identification, multivariable control theory, diagnostics/prognostics, and adaptive control. His engineering applications span internal combustion engines , exhaust after-treatment , noise/vibration control , and health prognostics for cardiovascular/respiratory systems . His recent publications highlight applications in superconductor manufacturing, aeroelastic stability, magnetic actuators, and subsea engineering. 2002 Best Paper Award, ASME Journal of Dynamic Systems, Measurement and Control 2001 ASME Dynamic Systems and Control Division Young Investigator Award 1997 CASA/SME University Lead Award 1997 Feddersen Faculty Fellow, Purdue University Multiple teaching awards at Purdue University (1994–2001) and Texas A&M University (1991) He has served as an Associate Editor for the ASME Journal of Dynamic Systems, Measurement and Control, held leadership roles in ASME and IEEE, and organized symposia on nonlinear control and robust control at international conferences. His professional activities include advisory roles at Cummins Incorporated and reviewing for NSF and numerous journals.

• Political Theory
• Democratic Theory
• Theories of Power
• +۵ مورد دیگر

Clarissa Rile Hayward is Professor of Political Science at Washington University in St. Louis, where she also serves as Associate Chair of the department and holds courtesy appointments in Philosophy and American Culture Studies. A contemporary political theorist, she is known for integrating empirical studies of institutions and urban life into normative debates about power, democracy, and identity. Education: PhD, Yale University. Research focus: Hayward interrogates how social power operates through institutional rules, spatial arrangements, and everyday practices that shape both freedom and identity. Refusing abstract “ideal theory,” she analyzes concrete cases—especially American urban politics and racial formation—to show how seemingly neutral structures enact “thick injustice.” Her books— De-Facing Power , How Americans Make Race , and Justice and the American Metropolis —have reshaped conversations on structural power, racial identity, and metropolitan inequality. Articles in American Political Science Review , Political Theory , and The Journal of Politics extend these themes, while recent work turns to digital democracy and the normative stakes of publicity and disruption. Awards: American Political Science Association Best Book in Urban Politics (2014) for How Americans Make Race Grants & Fellowships: National Academy of Education/Spencer Foundation National Endowment for the Humanities Institute for Advanced Study, Princeton Edmond J. Safra Center for Ethics, Harvard Ash Center for Democratic Governance & Innovation, Harvard Kennedy School Visiting Fellowship, All Souls College, Oxford (2024-2025) She teaches undergraduate surveys in American political thought and graduate field seminars in political theory, and mentors a large cohort of doctoral students working on power, democracy, and urban justice.

• Machine Learning
• Statistical Computing
• Cluster Analysis
• +۲ مورد دیگر

Theresa Scharl-Hirsch is a Senior Scientist and Deputy Scientific Director at the Core Facility Bioinformatics, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds concurrent appointments at the Institute of Statistics, BOKU, and has extensive experience in bioprocess modeling, machine learning, and statistical computing. Her work bridges biochemical engineering with advanced data science methodologies. Her research focuses on real-time monitoring of biopharmaceutical processes, clustering of high-dimensional data (particularly RNA sequencing), and application of explainable machine learning techniques. She has developed statistical models for process optimization and quality prediction in antibody capture and protein purification, with a strong emphasis on industrial implementations using R programming. Key trends in her publications include three-way data analysis, matrix-variate Gaussian mixture models, and permutation-based variable importance methods for deep learning architectures. Her work spans bioprocess engineering, bioinformatics, and industrial data science applications.

Dharanidhar Dangمشاهده پروفایل

استادیار

• Photonic Computing
• AI Hardware Acceleration
• Memristor-based Computing
• +۳ مورد دیگر

Dharanidhar Dang serves as Assistant Professor in the Department of Computer Engineering at the College of AI, Cyber and Computing, The University of Texas at San Antonio (UTSA), where he advances hardware-centric artificial intelligence solutions through photonic and memristor technologies. Education Ph.D., Texas A&M University His research program bridges hardware innovation and biomedical applications, with primary focus on photonic computing architectures for real-time AI acceleration and memristor-based neuromorphic systems. He investigates critical challenges in hardware reliability (particularly degradation in memristor crossbars), energy efficiency in photonic accelerators, and co-design methodologies that optimize both algorithms and physical implementations. His biomedical work applies machine learning to macrophage biology, identifying predictive signatures for inflammatory diseases through computational immunology approaches. Analysis of his 2020-2025 publications reveals three dominant research trajectories: 1) Silicon photonic accelerators (P-ReTI, P-ReTiNA, SOFTONIC) targeting real-time and energy-efficient AI, 2) Memristor reliability frameworks addressing aging effects in deep learning hardware, and 3) Translational biomedical applications where machine learning deciphers macrophage behavior in inflammatory bowel disease and preterm infant lung conditions. This tripartite focus demonstrates exceptional versatility across hardware engineering and life sciences.

Wolfgang Hillertمشاهده پروفایل

استاد

• Accelerator Physics
• Superconducting Accelerator Technology
• Free-Electron Lasers (FEL)
• +۴ مورد دیگر

Prof. Dr. Wolfgang Hillert is a leading physicist at the University of Hamburg , serving as the Bjørn-Wiik Professor for Accelerator Physics since 2016. Affiliated with the Institute of Experimental Physics under the Faculty of Mathematics, Informatics and Natural Sciences, he specializes in Accelerator Physics , Superconducting Accelerator Technology , and Free-Electron Lasers (FEL) . His work focuses on polarized electron beams, SRF cavity optimization, and gravitational wave detection methods. Education: Physics degree from University of Bonn (1987), Promotion in Atmospheric Physics (1992), Habilitation in Physics (2001) Leadership Roles: Head of Accelerator Physics Group (2016–present), Managing Director of Institute of Experimental Physics (2019–2021) Research Trends: His recent work spans superconducting RF cavities for gravitational wave detectors ( 2025 ), resonant slow extraction in electron boosters, and atomic layer deposition of superconducting thin films. Publications highlight advancements in beam dynamics , cryogenic systems , and terahertz generation . Teaching & Outreach: He has lectured on Accelerator Physics since 2002 and engaged in public science communication, including talks on Physics of Music (2005–2021) and teacher training programs at DESY. Labs & Collaborations: Leads the Accelerator Physics Group at DESY, collaborates on projects like XFELO and BGO-OD beamline , and contributes to international schools (CAS) and symposia.

• Personalized Learning
• AI in Education
• Equity in STEM
• +۵ مورد دیگر

Leonora Kaldaras is an Assistant Professor in the Department of Curriculum & Instruction at Texas Tech University College of Education. Her research focuses on equitable personalized learning, AI-driven assessment systems, and cognitive development in STEM education. She holds a dual Ph.D. in Curriculum, Instruction and Teacher Education and Measurement and Quantitative Methods from Michigan State University (2020) and has worked with Nobel laureate Carl Wieman on AI-guided feedback tools. Education: Dual Ph.D. (2020), Michigan State University Science Education Certificate, BGSU B.S. in Chemistry (2009), BGSU Research Interests: Personalizing learning through technology, equity in blended/personalized learning, and fostering knowledge transfer via self-guided strategies. She specializes in NGSS-aligned assessments and AI-enhanced feedback systems for STEM education. Article Trends: Her recent work (2023-2025) emphasizes AI-driven assessment design, NGSS-aligned learning progressions, and cognitive frameworks for math-science integration. Earlier publications (2012-2016) focus on biophysics but transitioned to education post-2020. Scientific Awards: New and Noteworthy Invited Symposium by American Chemical Society Top Downloaded Article (JRST, 2019) Top Cited Article (JRST, 2021-2022) Grants: NSF DrK-12 Co-PI (2022-2026) for AI feedback systems in NGSS classrooms. Labs & Collaborations: Formerly at Stanford University Graduate School of Education and University of Colorado Boulder PhET Interactive Simulations Project, working closely with Nobel laureate Dr. Carl Wieman.

Nicholas Borottoمشاهده پروفایل

استادیار

• Mass Spectrometry
• Proteomics
• Bioanalytical Chemistry
• +۳ مورد دیگر

Nicholas Borotto is an Assistant Professor in the Department of Chemistry at the University of Nevada, Reno (UNR), within the College of Science. His research focuses on advancing mass spectrometry techniques for analyzing biomolecules, particularly proteins, by integrating methods like chemical derivatization, laser irradiation, ion mobility, and radical chemistry. His lab develops tools to study protein three-dimensional structures, post-translational modifications, and the acidic proteome. Education Postdoctoral Scholar (2016-2019), University of Michigan Ph.D., Chemistry (2016), University of Massachusetts B.S., Biochemistry (2007), Northeastern University Research Interests Borotto’s work bridges chemistry and biology, addressing both biochemical questions and methodological advancements in mass spectrometry. Current projects include: 1. Equipping a carbon monoxide laser for IRMPD studies in unconventional pressure regimes. 2. Developing photocaged probes for in vivo protein structure analysis. 3. Applying free-radical initiated peptide sequencing (FRIPS) to complex anion mixtures. Publications His recent work emphasizes trapped-ion mobility spectrometry, protein footprinting, and radical-driven peptide sequencing. Publications highlight innovations in protein conformation analysis, ion mobility separations, and gas-phase chemistry. Labs & Teams The Borotto Lab, part of UNR’s Department of Chemistry, focuses on bioanalytical mass spectrometry. The lab combines instrumentation development with biochemical applications, offering students training in analytical chemistry, proteomics, and biophysical methods.

Zhurun (Judy) Jiمشاهده پروفایل

استادیار

• Quantum Sensing
• Quantum Materials
• Quantum Devices
• +۴ مورد دیگر

Zhurun (Judy) Ji is an Assistant Professor of Physics at MIT (starting January 2026), currently a Panofsky Fellow at SLAC National Lab. Her research focuses on quantum sensing, quantum materials, and quantum device development using advanced scanning probe techniques. She leads the Ji Quantum Lab, investigating quantum phenomena such as electron topology, correlation, and phase transitions to advance quantum technologies. Education: B.Sc. in Physics from University of Science and Technology of China (2015), Ph.D. in Physics from University of Pennsylvania (2021). Postdoctoral training includes Stanford University (2021–2024) as a Stanford Science Fellow and Urbanek-Chodorow Postdoc Fellow. Research Interests: Development of novel RFlexiscope techniques for microwave probing of quantum materials Study of coherence properties in 2D materials and quantum phase transitions Design of solid-state quantum circuits using insights from quantum phenomena Awards: Recognized with prestigious fellowships including the Panofsky Fellowship (SLAC), Boeing Quantum Creators Prize, and multiple graduate/postdoc awards. Labs: Ji Quantum Lab at MIT, active collaborations with SLAC and Stanford. Current work integrates quantum sensing advancements with device applications for next-generation technologies.