جست‌وجوی استاد و پژوهشگر

Farzad Mashayekمشاهده پروفایل

استاد

• Turbulent Reacting Flow
• Plasma Flow
• Electrostatic Atomization
• +۹ مورد دیگر

Farzad Mashayek is a Professor and Department Head of Aerospace and Mechanical Engineering at the University of Arizona, College of Engineering. He is a member of the Graduate Faculty and leads the Computational Multiphase Transport Laboratory. His research integrates high-fidelity simulations, machine learning, and experimental validation across diverse domains in fluid dynamics and energy systems. Educational Background: PhD in Mechanical Engineering, State University of New York at Buffalo, Buffalo, NY MS in Mechanical Engineering, Sharif University of Technology, Tehran, Iran BS in Mechanical Engineering, Sharif University of Technology, Tehran, Iran His research interests include turbulent reacting flows, plasma dynamics, electrostatic atomization, solid-ion and lithium batteries, computational fluid dynamics, and machine learning applications in engineering. He employs high-order spectral element methods, phase-field modeling, and deep neural networks to study complex multiphysics phenomena such as drop impact, battery degradation, and turbulence modeling. The recent publications reflect a strong trend toward integrating machine learning with multiphysics simulations, particularly in battery safety (thermal runaway prediction), materials characterization (STEM image analysis), and fluid dynamics (modal analysis of turbulence). His work often involves collaboration with experimental groups to validate models, especially in dental aerosol suppression and electrohydrodynamics. Scientific Awards: Sustained Service Award, American Institute of Aeronautics and Astronautics (AIAA), Spring 2022 Best Presentation Award, The 20th International Conference on Computational Mathematics, Parallel and Distributed Computing, Summer I 2018 Dr. Mashayek has secured funding from NSF (GOALI program) for controlled coating via charged droplet deposition. He advises graduate students and postdoctoral researchers in computational mechanics and energy systems, fostering interdisciplinary research. He has contributed to engineering education, particularly during the pandemic, with active learning strategies in online instruction. He leads a dynamic research team focused on advancing simulation tools and applying them to real-world challenges in energy, manufacturing, and public health.

• Adhesion
• Thin Films
• Plasma Polymerization
• +۳ مورد دیگر

F. James Boerio is a Professor of Materials Science at the University of Cincinnati, affiliated with the School of Engineering Education. He holds a Ph.D. in Macromolecular Science from Case Western Reserve University, an M.S. in Macromolecular Science, and a B.S. in Physics from Case Institute of Technology. Education : Ph.D. (Case Western Reserve, 1971), M.S. (Case Western Reserve, 1968), B.S. (Case Institute of Technology, 1966). His research focuses on adhesion , plasma polymerization , and surface characterization using techniques like XPS, FTIR, VASE, and Raman spectroscopy. Key applications include rubber-to-metal bonding , corrosion inhibition , and nanoscale hybrid materials . His work has leveraged plasma reactors for in-situ characterization and large-volume plasma reactors for batch processing. Dr. Boerio’s recent publications emphasize plasma-polymerized films , interfacial analysis , and surface modification for adhesion and durability. He has explored carbon nanofiber actuators , breath figure films , and semiconductor/insulator interfaces , aligning with his expertise in materials science and engineering education. Scientific awards include: Outstanding Teacher by Engineering Tribunal (1983) Professor of the Year (2002-03) College of Engineering Research Award (1989) Dean’s Award for Educational Innovation (2001) Robert L. Patrick Fellow of The Adhesion Society (1997) Adhesion Society Award for Excellence (1999) He has secured significant grants from the National Science Foundation , Boeing , EPA , and others for projects on adhesion science , nanotechnology , and engineering education innovation . His leadership roles include Director of the School of Engineering Education and Interim Head of Materials Science and Engineering departments.

Changhuei Yangمشاهده پروفایل

استاد

• Biophotonics
• Microscopy
• Computational Imaging
• +۳ مورد دیگر

Changhuei Yang is the Thomas G. Myers Professor of Electrical Engineering, Bioengineering, and Medical Engineering at California Institute of Technology, serving as Executive Officer for Electrical Engineering and Investigator at Heritage Medical Research Institute. He holds a Ph.D. and three master's degrees from MIT, with appointments at Caltech since 2003. Research focuses on: Advanced microscopy techniques including Fourier Ptychography Wavefront shaping for biological tissue imaging Optical phase conjugation for deep-tissue applications Compact medical devices for cerebral monitoring Publications demonstrate leadership in computational imaging, with recent advances in stain-free embryo analysis, portable cerebral blood flow monitors, and high-resolution volumetric imaging techniques using neural representations. Honored as National Academy of Inventors member. Research applications span deep-tissue biochemical imaging, incisionless surgery, and optogenetic activation systems.

Amit Singerمشاهده پروفایل

استاد

• Computational Mathematics
• Structural Biology
• Cryo-Electron Microscopy
• +۳ مورد دیگر

Amit Singer is a Professor of Mathematics at Princeton University, specializing in computational methods for structural biology and cryo-electron microscopy (cryo-EM). His work focuses on developing mathematical frameworks and algorithms for analyzing large-scale microscopy datasets, particularly in 3D reconstruction and heterogeneity analysis of molecular structures. He leads research in manifold learning, optimal transport, and harmonic analysis, with applications to cryo-EM, signal processing, and inverse problems. Research interests include: (1) Mathematical methods for cryo-EM, including particle alignment, density map analysis, and subspace-based reconstruction techniques; (2) Development of rotation-invariant representations for imaging problems; (3) Application of machine learning and optimization to biomedical imaging challenges. His contributions bridge pure mathematics (e.g., harmonic analysis, manifold theory) with applied computational techniques for real-world microscopy data. Key trends in his recent articles (2023–2025) include advancements in multi-reference alignment methods, Wasserstein distance-based image registration, and overcoming particle detection limitations in cryo-EM. He also explores sparsity constraints, autocorrelation analysis, and novel algorithms for handling heterogeneous datasets. These methods improve resolution and reduce computational costs in analyzing molecular structures at atomic scales. Notable contributions include the ASPiRE software package for steerable PCA, and foundational work on synchronization problems in cryo-EM orientation estimation. His research often addresses algorithmic scalability and robustness to noise in experimental setups.

Ovijit Chaudhuriمشاهده پروفایل

دانشیار

• Mechanobiology
• Cellular Mechanics
• Extracellular Matrix
• +۵ مورد دیگر

Ovijit Chaudhuri is an Associate Professor of Mechanical Engineering at Stanford University, with a courtesy appointment in Bioengineering. He leads research at the interface of mechanics and biology, focusing on how cellular and extracellular mechanical properties influence biological processes like cancer progression and tissue formation. His work employs advanced tools such as atomic force microscopy and 3D cell culture systems. Education: Ph.D., University of California, Berkeley/San Francisco (Bioengineering, 2009) B.S., University of California, Berkeley (Engineering Physics, 2003) Postdoctoral Fellow, Harvard University (Biomaterials, 2013) Research Interests: His lab explores molecular mechanisms behind cellular mechanics, extracellular matrix dynamics, and how mechanical cues regulate cell behavior. Key areas include cancer metastasis, mechanotransduction, and engineered biomaterials for 3D cell culture. Publications Trends: Recent work emphasizes viscoelastic hydrogels, matrix mechanics in cancer progression, and mechanistic insights into cell migration. Over 50 publications since 2015 highlight interdisciplinary approaches in biomaterials and mechanobiology. Awards: Not explicitly listed in provided materials. Advising & Labs: No specific advisee names listed, but his lab focuses on collaborative projects in mechano-biology. Active in developing biomaterial systems for drug discovery and tissue engineering applications. Labs/Teams: Leads the Chaudhuri Lab at Stanford, which integrates engineering principles with biological systems to address complex disease mechanisms and therapeutic strategies.

John Warren Huntleyمشاهده پروفایل

دانشیار

• Paleobiology
• Paleoecology
• Conservation Paleobiology
• +۲ مورد دیگر

Dr. John Warren Huntley is an Associate Professor in the Department of Geological Sciences at the University of Missouri. His research examines the fossil record of biotic interactions including parasitism, predation, and competition, with additional focus on conservation paleobiology and morphological disparity evolution. Dr. Huntley investigates host-parasite dynamics in marine bivalves, human impacts on mollusk populations, and Phanerozoic predation patterns. His work integrates stratigraphic paleobiology with ecological and evolutionary analyses to reconstruct historical ecosystem dynamics. His recent publications demonstrate expertise in paleoparasitology, taphonomy, and conservation paleobiology, applying novel analytical methods to questions about parasite-host coevolution, preservation biases, and extinction events. This research provides critical insights into long-term ecological patterns and biological responses to environmental change. Dr. Huntley has received significant recognition including an NSF CAREER Award and Humboldt Research Fellowship, and he co-edited the comprehensive volumes 'The Evolution and Fossil Record of Parasitism'.

Vadim Backmanمشاهده پروفایل

استاد

• Physical Genomics
• Chromatin Engineering
• Nanotechnology
• +۵ مورد دیگر

Dr. Vadim Backman is the Sachs Family Professor of Biomedical Engineering and Medicine at Northwestern University's McCormick School of Engineering and Applied Sciences and Feinberg School of Medicine. He holds additional roles as Professor of Medicine (Hematology/Oncology) and Biochemistry and Molecular Genetics, Associate Director of Research Technology and Infrastructure at the Robert H. Lurie Comprehensive Cancer Center, and Director of the Center for Physical Genomics and Engineering. He earned his Ph.D. in Medical Engineering from Harvard-MIT and M.S./B.S. in Physics from St. Petersburg Polytechnic Institute. His research focuses on physical and biological science intersections, developing nanoscale imaging and computational technologies to study chromatin dynamics and their role in disease. Key areas include cancer diagnostics/therapeutics, chromatin engineering, and genome nanoimaging. Dr. Backman has published over 230 papers, holds 20+ patents, and leads large-scale projects like NCI Bioengineering Research Partnerships. Education: Ph.D. (Harvard-MIT), M.S. (MIT), M.S./B.S. (St. Petersburg Polytechnic Institute) Affiliations: PhD Programs in Applied Physics and Interdisciplinary Biological Sciences Research emphasizes chromatin's role in disease, with clinical translation for diagnostics and therapy. His lab develops technologies like nano-CHIA and ChromSTEM, advancing understanding of genomic organization and epigenetic regulation. Awards include the Cozzarelli Prize and MIT Technology Review's Top 100 Innovators. Awards: Cozzarelli Prize (2017), AIMBE Fellowship (2009), NSF CAREER Award (2003) Grants and collaborations include managing multi-investigator projects and co-founding biotech companies. Courses taught: BME 302 (Quantitative Systems Physiology), BME 429 (Advanced Physical and Applied Optics).

Likun Zhuمشاهده پروفایل

استاد

• Lithium-ion Batteries
• Solid-state Batteries
• In Situ and Operando Characterization
• +۷ مورد دیگر

Dr. Likun Zhu is a Professor of Mechanical Engineering at Purdue University's School of Mechanical Engineering in Indianapolis. His research focuses on advanced battery technologies, including lithium-ion and solid-state batteries, with an emphasis on in situ and operando characterization, modeling, and micro/nano fabrication. Dr. Zhu's work addresses critical challenges in battery energy density, safety, and longevity through innovative materials and manufacturing processes. Education: Ph.D. Mechanical Engineering, University of Maryland (2006); M.S./B.S., Tsinghua University (2001/1998). His lab is affiliated with the Birck Nanotechnology Center and equipped with advanced facilities such as gloveboxes, electrochemical analyzers, and microscopy systems. Recent milestones include securing an NSF grant for solid-state battery research (2023) and advising over 30 graduate students. Research Interests: Solid-state batteries, micro/nano fabrication, operando characterization, and sustainable energy materials. His group develops novel electrode materials and designs for high-performance batteries, leveraging cutting-edge in situ techniques to study dynamic processes during cycling. Grants & Awards: NSF grant (2023) for solid-state battery research. Advising: Notable students include Hua Wang (Ph.D. 2024), Xintong Li, and Tianyi Li. Collaborations include work with Professors Hazim El-Mounayri and Andres Tovar on Bayesian optimization of battery materials. Labs & Facilities: The lab, located at ET 118, houses equipment like Arbin battery cyclers, FIB-SEM systems, and Comsol Multiphysics software. Dr. Zhu teaches courses including ME 330 (Dynamic Systems), ME 509 (Fluid Mechanics), and ME 597 (Renewable Energy).

Robert C. Dunnمشاهده پروفایل

استاد

• Analytical Chemistry
• Biophysics
• Optical Microscopy
• +۵ مورد دیگر

Robert C. Dunn is a Professor in the Department of Chemistry at the University of Kansas, where he leads an active research group focused on developing novel optical and spectroscopic techniques for chemical and biological analysis. His laboratory specializes in single-molecule detection methods, high-resolution microscopy, and advanced capillary electrophoresis systems. Professor Dunn's research interests span analytical chemistry, biophysics, and nanotechnology. His group develops instrumentation including backscatter interferometry, near-field scanning optical microscopy, and scanning resonator microscopy to study biological systems at the nanoscale. Key research areas include membrane biophysics (investigating lipid domains and protein dynamics), nuclear pore complex function, and the development of ultrasensitive detection methods for clinical diagnostics and biochemical analysis. His recent publications demonstrate strong focus on miniaturized separation and detection platforms, particularly high-speed capillary electrophoresis systems integrated with novel optical detection schemes. Research trends show advancement towards point-of-care diagnostic tools, with innovations in refractive index sensing, femtoliter-volume detection, and label-free biosensing applications. Professor Dunn mentors graduate and undergraduate researchers in his group, with current students including Prabhavie Opallage (graduate student), Stanslaus M Kariuki (undergraduate), and Mei Ling Upp (undergraduate). His laboratory is developing new chemical analysis approaches using optical techniques including whispering gallery mode sensing, scanning resonator microscopy, and single-molecule fluorescence imaging.

Hari Nairمشاهده پروفایل

استادیار

• Materials Synthesis and Processing
• Semiconductor Physics and Devices
• Advanced Materials
• +۱۲ مورد دیگر

Hari Nair is an Assistant Professor in the Department of Materials Science and Engineering at Cornell University, part of the College of Engineering. His research focuses on the synthesis and characterization of complex oxide thin films using molecular beam epitaxy (MBE), with applications in power electronics, quantum materials, and optoelectronics. B.Tech. in Engineering Physics, Indian Institute of Technology Madras, 2006 M.S. in Electrical and Computer Engineering, The University of Texas at Austin, 2008 Ph.D. in Electrical and Computer Engineering, The University of Texas at Austin, 2013 His research interests lie at the intersection of semiconductor physics, materials synthesis, and advanced functional materials. He specializes in epitaxial strain engineering, heterostructure design, and the control of electronic and magnetic properties in oxide thin films. His vision is to leverage novel materials to enable revolutionary advances in electronic and optoelectronic devices. Analysis of his recent publications reveals a strong focus on β-Ga₂O₃ for high-power devices and ruthenate-based quantum materials such as Sr₂RuO₄ and SrRuO₃. His work spans ultra-wide bandgap semiconductors, strain-engineered phase transitions, superconductivity, and spin-orbit phenomena. Techniques include MBE growth, THz spectroscopy, and advanced electron microscopy. Notable scientific awards include: Student Paper Award, Device Research Conference (DRC), 2013 The Ben Streetman Prize for Outstanding Research in Electronic and Photonic Materials and Devices, 2013 Student Paper Award, Electronics Materials Conference (EMC), 2012 Hari Nair has advised several graduate students and postdoctoral researchers, though specific names are not listed in the provided text. His work has been supported by grants from federal agencies and institutional programs focused on advanced materials and quantum science. He is actively involved in collaborative research through centers and labs at Cornell, particularly those related to materials synthesis and characterization. He leads a research group focused on the growth and study of epitaxial thin films, working closely with the D.G. Schlom group and other collaborators in the Kavli Institute at Cornell. His lab utilizes state-of-the-art MBE systems and advanced characterization tools for probing electronic, magnetic, and structural properties at the nanoscale.

Grethe Wintherمشاهده پروفایل

استاد

• Microstructure of Metals
• Dislocation Structures
• Plastic Deformation
• +۷ مورد دیگر

Grethe Winther is a Professor and Head of Section in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), specializing in Materials and Surface Engineering. Her research is centered on the analysis and modeling of microstructure and mechanical properties of metals, with a strong emphasis on dislocation structures, deformation textures, and recrystallization processes. Her research interests include: Dislocation structures and boundary analysis in deformed metals Crystal plasticity modeling using synchrotron data (3DXRD) Orientation relationships in recrystallization Prediction of mechanical properties in industrial metal forming Multiscale modeling of plastic deformation and surface roughening The recent articles (2025) highlight a consistent focus on advanced characterization techniques like dark-field X-ray microscopy and discrete dislocation dynamics simulations. These works explore the formation of geometrically necessary boundaries, dislocation cell evolution, and multiscale surface deformation, reflecting a strong integration of experimental and computational methods in materials science. Key themes include plastic deformation mechanisms, microstructure evolution, and predictive modeling in metallic systems. Grethe Winther actively supervises multiple PhD projects, including those on dislocation dynamics, X-ray microscopy, and ductile failure simulations. She collaborates extensively with researchers such as H.F. Poulsen and C.V. Nielsen. Her work is supported by ongoing research projects at DTU, focusing on fundamental and applied aspects of metal deformation and microstructure. She is affiliated with the Materials and Surface Engineering section at DTU, where she leads research efforts combining advanced experimental techniques with theoretical modeling to understand and predict metal behavior under deformation.

• Physiology
• Sports Science
• Molecular Biology
• +۳ مورد دیگر

Tommy Lundberg is a Senior Lecturer and Docent in Physiology at Karolinska Institutet. He works at the Department of Laboratory Medicine, Division of Clinical Physiology. His email address is tommy.lundberg@ki.se, and his postal address is H5 Laboratoriomedicin, H5 Klinisk Fysiologi Gustafsson, 141 52 Huddinge. Lundberg is affiliated with the university library and has held positions since 2022. Research Interests: Lundberg's research focuses on skeletal muscle mass and function adaptation, particularly in athletic performance, disease contexts, aging, and transgender individuals undergoing hormone therapy. He investigates molecular, metabolic, morphological, and functional responses to resistance and aerobic exercises. His work also explores biological maturity selection biases in youth sports, bio-banding applications in soccer and ice hockey, and the impact of anti-inflammatory drugs on muscle hypertrophy. Article Trends: Lundberg's recent publications (2025–2024) cover topics like sex differences in disc golf, muscle atrophy in space exposome, longitudinal hormone therapy effects in transgender individuals, and bio-banding in youth sports. Earlier works delve into molecular pathways in muscle hypertrophy, concurrent training effects, mitochondrial function, and imaging techniques (CT/MRI) for muscle assessment. Scientific Recognition: Most prominent young researcher in Sport Science, Swedish Central Association for Sport Promotion (SCIF), 2017 Teaching and Editorial Roles: Lundberg teaches human physiology and sports science in nursing, physiotherapy, and biomedical analytics programs. He leads a contract education course in advanced exercise physiology and contributes to a PhD course on scientific writing. He is an Associate Editor for Frontiers in Physiology - Exercise Physiology (2022) and a member of the editorial board for Translational Exercise Biomedicine (2024). Collaborations and Expertise: He collaborates with the Swedish Football Association and Swedish Ice Hockey Association on bio-banding studies. Lundberg served as an invited speaker at the ACSM Annual Meeting (2024) on transgender athletes and as an expert panelist for World Rugby's transgender workshop (2020). His supervision includes Andrea Tryfonos (2021) and thesis evaluations at Mid Sweden University and Linköping University.

• Composites
• Additive Manufacturing
• Materials Characterization
• +۸ مورد دیگر

Dr. Alexander J G Lunt is a Senior Lecturer in Mechanical Engineering at the University of Bath, specializing in micromechanical testing and materials characterization. He leads the Integrated Materials Processing and Structures Research Centre and has a PhD in Mechanical Microscopy from the University of Oxford. His research focuses on advanced materials, composites, additive manufacturing, and synchrotron/neutron-based techniques. He has supervised 5 PhD students and collaborates with industries like Rolls-Royce and Airbus. Notable awards include the John Willis Award and Vice Chancellor's Engage Award. His work contributes to UN SDGs in sustainable materials and manufacturing.

Joergen Kornfeldمشاهده پروفایل

پژوهشگر

• Connectomics
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Joergen Kornfeld is a researcher at the University of Cambridge, affiliated with the MRC Laboratory of Molecular Biology (LMB) in the Connectomics of Learned Behaviour group. His work focuses on understanding how learned behaviors are encoded in neural circuits through connectomic analysis. Institution: University of Cambridge Role: Connectomics Researcher Research Interests: • Connectomics and synaptic connectivity mapping • High-throughput 3D electron microscopy • Deep learning applications in neural network analysis • Behavioral memory storage mechanisms • Comparative neuroanatomy of learned behaviors • Computational modeling of neural circuits. Recent publications highlight his expertise in developing deep learning tools (e.g., DeepFocus, SyConn2) for connectomic reconstruction, with applications in zebra finch song learning and larval zebrafish neural circuits. His work bridges advanced imaging techniques, computational methods, and behavioral neuroscience. Techniques: High-throughput 3D electron microscopy, flood-filling networks Model Systems: Zebra finch, larval zebrafish

• Radiomics
• Medical Imaging Analysis
• Machine Learning in Healthcare
• +۷ مورد دیگر

Adrien Depeursinge is a Professor at HES-SO Valais-Wallis - Haute Ecole de Gestion, affiliated with the School of Economics and Services and the Management Information Systems department. His research focuses on radiomics, personalized medicine via image-based analysis, and clinical workflow optimization. He leads the development of the QuantImage platform, a physician-centered web-based tool for radiomics research, and contributes to radiomics standardization efforts through initiatives like the Image Biomarker Standardization Initiative (IBSI). His work emphasizes machine learning applications in healthcare, including tumor segmentation, biomarker extraction, and improving diagnostic accuracy through computational models. Key research themes include: 1) Radiomics – developing quantitative imaging features for cancer diagnosis/prognosis; 2) Medical Imaging Analysis – advancing texture-based models, multi-modal fusion, and automated lesion detection; 3) Physician-AI Collaboration – designing user-centric tools for clinical integration. His contributions span neuro-oncology (brain metastases), head-and-neck cancer, and multiple sclerosis imaging. Publications emphasize methodological advancements (e.g., kernel optimization in CNNs, steerable detectors) and clinical validation (e.g., reproducibility of radiomics features across imaging protocols). He collaborates with institutions like the University Hospital of Lausanne (CHUV) and international teams on projects like the HECKTOR challenge for PET/CT tumor segmentation. His work bridges technical innovation with clinical impact, aiming to translate radiomics into actionable clinical tools. QuantImage v2, his flagship tool, enables no-code development of machine learning models using clinical imaging data. Research also includes phantom-based validation of radiomics features and addressing challenges in feature stability across imaging modalities. Current projects explore improving contour quality for radiomics studies and optimizing AI explainability in medical decision-making.