جست‌وجوی استاد و پژوهشگر

Seth Lichterمشاهده پروفایل

استاد

• Statistical Mechanics
• Fluid Mechanics
• Energy
• +۳ مورد دیگر

Seth Lichter is a Professor of Mechanical Engineering at Northwestern University, specializing in molecular-scale dynamics. His research focuses on polymer dynamics, surface diffusion, and energy-related phenomena. He holds a Ph.D. and M.S. from MIT in Mechanical and Aerospace Engineering, respectively, and a B.A. in Engineering and Applied Physics from Harvard University. His current projects include collaborations on polymer dynamics with Prof. Chris Goedde and Prof. Anupam Garg, as well as studies on liquid-surface interactions under shear. Lichter emphasizes analytical modeling and closed-form solutions to complex problems, combining computation with physical insight. He teaches courses such as Modeling Energy in Society , Molecular Motors in Biology , and the interdisciplinary Nonlinear Dynamics , which spans eight departments across Engineering and Arts & Sciences. Notable awards include the Office of Naval Research Young Investigator Award and the Clemens Herschel Prize for Excellence in Engineering.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۳ مورد دیگر

Dr. Ulas Bagci is an Associate Professor at Northwestern University's Feinberg School of Medicine, Department of Radiology. He holds courtesy appointments in Biomedical Engineering (BME), Electrical and Computer Engineering (ECE) at Northwestern, and Computer Science at the University of Central Florida. As the director of the Machine and Hybrid Intelligence Lab, his research focuses on AI and machine learning applications in biomedical and clinical imaging. Education: BS: Bilkent University (2003) MS: Koç University (2005) Fellow: University of Pennsylvania (2009) PhD: University of Nottingham (2010) ISTP Fellow: NIH (2012) Research Interests: Dr. Bagci’s work spans artificial intelligence, machine learning, and their integration into medical imaging workflows. His lab develops algorithms for tumor segmentation, radiomics analysis, and ethical AI frameworks in healthcare. Notable projects include large-scale MRI segmentation of cirrhotic livers and predictive models for clinical outcomes in oncology and cardiology. Publications: His recent work emphasizes AI-driven solutions for challenges in radiology, including lung disease detection, pulmonary embolism mortality prediction, and ethical considerations in foundational AI models. His articles reflect a focus on bridging clinical needs with advanced computational methods. Lab & Affiliations: The Machine and Hybrid Intelligence Lab collaborates with the Robert H. Lurie Comprehensive Cancer Center. Research themes include federated learning, medical image synthesis, and AI ethics in clinical decision-making.

Blanka Sharmaمشاهده پروفایل

دانشیار

• Nanomedicine
• Stem Cells
• Biomaterials
• +۳ مورد دیگر

Blanka Sharma, Ph.D., is an Associate Professor in the J. Crayton Pruitt Family Department of Biomedical Engineering at the University of Florida's Herbert Wertheim College of Engineering. Her research focuses on nanomedicine, stem cells, biomaterials, and targeted delivery systems for regenerative medicine and cancer therapy. She holds a B.A.Sc. in Chemical Engineering from the University of Waterloo (1999), a Ph.D. in Biomedical Engineering from Johns Hopkins University (2005), and completed a postdoctoral fellowship at the Cleveland Clinic (2005–2008). Dr. Sharma’s work explores material-cell interactions to develop therapies addressing inflammatory mechanisms in diseases like osteoarthritis and cancer. Notable achievements include pioneering biomaterials for cartilage repair and nanoparticle-based drug delivery systems. She has received prestigious awards, including the NSF CAREER Award (2019) and the UF Pramod P. Khargonekar Junior Faculty Award (2019–2020). Her research spans nanomedicine, tumor microenvironment engineering, and immunotherapy optimization. Recent studies include ROS-scavenging manganese dioxide nanoparticles for osteoarthritis and NK cell mechanosensing in tumors. She leads the Sharma Laboratory, advancing translational research in regenerative medicine and oncology.

Rob Pooleمشاهده پروفایل

استاد

• Rheology
• Fluid Mechanics
• Non-Newtonian Fluid Mechanics
• +۵ مورد دیگر

Professor Rob Poole holds the Harrison Chair in Mechanical Engineering at the University of Liverpool’s School of Engineering, part of the Faculty of Science and Engineering. Previously Head of Department (2017–2021), he co-edits the Journal of Non-Newtonian Fluid Mechanics . His research focuses on rheology, fluid mechanics, and turbulence, with recent work on polymeric drag reduction, superhydrophobic surfaces, and viscoelastic instabilities. Education: BEng (Hons) and PhD in Mechanical/Aerospace Engineering. Research Interests: Non-Newtonian fluid mechanics Elastic turbulence and viscoelastic instabilities Polymer solutions and additive effects Heat transfer in porous media Constitutive equation development Awards & Fellowships: EPSRC Complex Fluids and Rheology Fellowship (2015–2021) British Society of Rheology Annual Award (2018) 2015 Best Paper Award (Theoretical and Applied Mechanics Letters) Grants & Projects: Funded projects include Flexible Heat Pump development (£1.5M), Instabilities in Complex Fluid Flows (£1.2M), and Superhydrophobic Surface Drag Reduction (£0.8M) Industry collaborations: Schlumberger, Procter & Gamble, National Nuclear Laboratory Professional Activities: Editorial roles: Journal of Non-Newtonian Fluid Mechanics (Co-Editor-in-Chief), Physics of Fluids External examiner at Warwick, Strathclyde, and multiple Indian Institutes of Technology

Guillaume Balمشاهده پروفایل

استاد

• Inverse Problems
• Medical Imaging
• Geophysical Imaging
• +۴ مورد دیگر

Guillaume Bal is a Professor at the University of Chicago, holding joint appointments in the Departments of Statistics and Mathematics, and affiliated with the Committee on Computational and Applied Mathematics (CCAM). His research focuses on inverse problems in medical and geophysical imaging, partial differential equations with random coefficients, and the mathematical analysis of topological insulators. He explores applications in wave propagation, uncertainty quantification, and hybrid imaging modalities. His recent work delves into theoretical and computational aspects of stochastic partial differential equations and topological edge states. Research Interests: Inverse Problems (Geophysical/Medical Imaging) Topological Insulators and Edge States Wave Propagation in Heterogeneous Media Uncertainty Quantification Publications Trends: Recent articles emphasize topological insulator dynamics, hybrid imaging techniques, and stochastic PDE models. Key themes include bulk-edge correspondence, dual-energy CT optimization, and semiclassical propagation in curved interfaces.

Paul O'Gormanمشاهده پروفایل

استاد

• Atmospheric Dynamics
• Climate Change
• Hydrological Cycle
• +۳ مورد دیگر

Paul O'Gorman is a Professor at the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at the Massachusetts Institute of Technology. He currently serves as the Faculty Chair of the EAPS Committee on Education and as the EAPS Graduate Officer. His research focuses on understanding how climate change affects atmospheric circulation and precipitation patterns, particularly extreme events. Education: BA in Theoretical Physics, Trinity College Dublin MSc in High-Performance Computing, Trinity College Dublin PhD in Aeronautics with Minor in Applied Mathematics, California Institute of Technology Research Interests include atmospheric dynamics, hydrological cycle responses to climate change, moist convection, and the application of machine learning to climate modeling. His work addresses regional variability in extreme precipitation, vertical warming profiles in the tropics, and the fluid dynamics of land-ocean warming contrasts. Scientific Awards : Bernhard Haurwitz Memorial Lectureship (2023), American Meteorological Society MIT School of Science Graduate Teaching Prize (2018) Recent Contributions include co-leading the MIT Climate Grand Challenges flagship project "Preparing for a new world of weather and climate extremes" , which develops tools for predicting climate extremes and transitioning to low-carbon resources. He has also explored the asymmetrical generalization capabilities of machine learning algorithms in climate models under warming versus cooling scenarios.

Colin Jacksonمشاهده پروفایل

استادیار

• Solid Earth Geochemistry
• Petrology
• High-Pressure Synthesis
• +۳ مورد دیگر

Colin Jackson is an Assistant Professor in the Department of Earth and Environmental Sciences at Tulane University's School of Science & Engineering. He leads the High Temperature and Pressure (HiTaP) Laboratory, researching chemical reactions governing planetary evolution under extreme conditions using experimental techniques. His work focuses on geochemical processes during planet formation and differentiation. Dr. Jackson holds a Ph.D. from Brown University (2014) and a B.S. from the University of California, Santa Cruz (2008). His primary research interests include: Solid Earth geochemistry and petrology High-pressure experimental techniques Planetary formation and evolution Magma ocean dynamics Volatile element distribution in terrestrial planets His recent publications demonstrate a focus on geochemical modeling of planetary formation processes, experimental studies of element partitioning under extreme conditions, and interpretation of lunar geological data. Research trends include magma ocean crystallization, core-mantle differentiation, volatile cycling, and noble gas systematics. The HiTaP Laboratory provides research opportunities for students interested in experimental planetary science. Dr. Jackson encourages student involvement in high-pressure synthesis experiments and geochemical analysis techniques.

Dirk Ziegenbalgمشاهده پروفایل

استاد

• Photochemical Engineering
• Chemical Reaction Engineering
• Process Intensification
• +۴ مورد دیگر

Prof. Dirk Ziegenbalg is a Professor of Chemical Engineering and Deputy Director at the Institute of Chemical Engineering at Ulm University. He holds a doctorate from Friedrich-Schiller-University Jena (2013) and previously served as Group Leader at the Institute of Chemical Technology, University Stuttgart (2012-2018). His research focuses on photochemical engineering, reactor design, and photocatalytic processes for applications in energy and environmental technology. Key contributions include advancements in photoreactor engineering, light-driven catalysis, and scalable water purification systems. He has been recognized with the Hanns Hofmann Award (2017) for innovations in microstructured reactor design. Teaching responsibilities include courses such as Strömungsmechanik , Chemische Prozesstechnik , and Industrial Catalysis . His research group, Photochemical Engineering, develops modular and industrially scalable photoreactor systems, emphasizing process intensification and dynamic irradiation control. Recent work addresses challenges in CO₂ conversion, selective Grignard reagent formation, and real-time process analytics using spectroscopy. Publications highlight interdisciplinary approaches, integrating chemical engineering with materials science and environmental applications. Ongoing projects involve 3D-printed catalytic materials, radiation field tomography for photoreactor characterization, and cross-disciplinary collaborations for sustainable water treatment technologies.

• Numerical Analysis
• Scientific Computing
• Computational Mathematics
• +۹ مورد دیگر

Dr. Fengyan Li is a Professor in the Department of Mathematical Sciences at Rensselaer Polytechnic Institute (RPI). She holds a PhD in Applied Mathematics from Brown University (2004) and previously held a postdoc at the University of South Carolina. Her research focuses on numerical analysis and scientific computing, particularly discontinuous Galerkin methods for applications in wave propagation, fluid dynamics, plasma physics, and nonlinear optics. She has received prestigious awards including the NSF-CAREER Award (2009) and Alfred P. Sloan Fellowship (2008). Dr. Li serves on editorial boards of journals like SIAM Journal of Numerical Analysis and IMA Journal of Numerical Analysis. Education: PhD in Applied Mathematics (Brown University, 2004); MS & BS in Computational Mathematics (Peking University, 2000 & 1997). Research interests emphasize multi-scale simulations, reduced-order modeling, and high-order methods. Her work addresses challenges in kinetic transport, nonlinear optics, and plasma dynamics. She has delivered plenary talks at major conferences, including ICOSAHOM (2018) and NAHOMCon (2022). Professional service includes leadership roles in the Association for Women in Mathematics (AWM), co-organizing symposiums, and mentoring. She is a 2025 AWM Fellow and advises RPI's AWM Student Chapter.

• Fluid Power (Hydraulics)
• Acoustic Sensing
• Dynamic Modelling
• +۴ مورد دیگر

Travis Wiens is an Associate Professor in the Department of Mechanical Engineering at the University of Saskatchewan. His research focuses on fluid power systems, acoustic sensing, dynamic modeling, mining mechatronics, and artificial intelligence applications in engineering. He holds a B.Sc., M.Sc., and Ph.D. in Mechanical Engineering from the same institution, completed in 2002, 2004, and 2008 respectively. His research interests emphasize innovative solutions for hydraulic control systems, pipeline resonance reduction, and mining safety through acoustic technologies. He has developed low-cost electrohydrostatic actuators and explored additive manufacturing in valve design. Notable contributions include vibrational data communication tools for extractive industries and machine learning models for mine roof stability assessment. Dr. Wiens teaches ENGC 01A - Introduction to Fluid Power Components . His work bridges theoretical fluid dynamics with practical applications in energy efficiency, structural health monitoring, and biomimetic systems. Ongoing research trends include integrating AI with hydraulic systems and advancing non-destructive testing methods for infrastructure integrity. His publications highlight interdisciplinary approaches, combining mechanical engineering principles with computational modeling, neural networks, and mechatronics. Collaborative efforts focus on mining safety, oil and gas infrastructure, and sustainable hydraulic technologies.

• Biophysics
• Molecular Motors
• Cytoskeletal Dynamics
• +۳ مورد دیگر

Janet Sheung is an Assistant Professor of Physics at Scripps College, specializing in biophysical systems and cytoskeletal dynamics. She teaches courses such as Principles of Physics, Electronics Laboratory, and Senior Thesis in Physics/Biophysics. Her research focuses on the interplay between molecular motors, cytoskeletal networks, and active matter, with a particular emphasis on mechanical properties, transport phenomena, and microscopy innovations. Dr. Sheung's work explores how motor proteins like kinesin and myosin drive structural and mechanical changes in cytoskeletal composites, influencing DNA transport, phase separation, and stress propagation. She has pioneered customizable light-sheet microscopy techniques for visualizing these systems in vivo. Her studies integrate experimental and theoretical approaches to understand non-equilibrium dynamics in biological materials. Her articles highlight themes of motor competition, topological effects on DNA transport, and the design of advanced imaging tools. While no awards are explicitly listed, her contributions to biophysics and microscopy instrumentation are evident in her publication record. Advising and grant details are not provided in the available text, but her teaching and research roles suggest active involvement in student mentorship.

Juan Alonsoمشاهده پروفایل

استاد

• Aerospace System Design
• Computational Fluid Dynamics
• Multi-Disciplinary Optimization
• +۷ مورد دیگر

Prof. Juan Alonso is the Vance D. and Arlene C. Coffman Professor and James & Anna Marie Spilker Chair in the Department of Aeronautics & Astronautics at Stanford University. He directs the Aerospace Design Laboratory (ADL), focusing on high-fidelity computational methods for aerospace system design. His expertise spans transonic/supersonic/hypersonic aircraft, rotorcraft, and launch vehicles. Alumni include record-holding teams for human-powered watercraft and lightweight unmanned aerial vehicles. Education: PhD (1997) from Princeton University in Mechanical & Aerospace Engineering; M.A. (1993) Princeton; B.S. (1991) MIT Aeronautics/Astronautics. Research emphasizes multi-disciplinary optimization, numerical methods, and parallel computing applied to advanced aircraft design, sustainable aviation, and UAS systems. Notable contributions include computational design frameworks like SU2 and SUAVE, and initiatives in curriculum development for engineering education. Recent work focuses on: GPU-accelerated CFD solvers, multi-fidelity surrogate models (e.g., VortexNet), contrail simulation frameworks, and battery degradation modeling for electric aircraft. Active in urban air mobility and high-fidelity trajectory optimization for hypersonic systems. Labs/Teams: Aerospace Design Laboratory (ADL) leading open-source computational tools development. Involved in NASA-funded projects and industry partnerships for advanced propulsion systems.

Joanna Austinمشاهده پروفایل

استاد

• Hypervelocity Flight
• Planetary Entry
• Supersonic Combustion and Detonation
• +۵ مورد دیگر

Joanna Austin is a Professor of Aerospace and serves as the Graduate Option Representative for Aeronautics and Space Engineering, as well as the Undergraduate Option Representative for Aerospace at the California Institute of Technology (Caltech). She leads the Caltech Hypersonics Group, which operates facilities like the T5 Reflected Shock Tunnel and the Hypervelocity Expansion Tube (HET). Her research focuses on reactive, compressible flows in applications such as hypervelocity flight, planetary entry, supersonic combustion, bubble dynamics, and explosive geological events. Key projects include studying shock-boundary layer interactions, Martian atmospheric entry aerothermodynamics, and high-speed fluid-structure interactions. She advises four Ph.D. students and collaborates with a team including staff members like Liza Bradulina and research assistants such as Noel Esparza-Duran. Her work bridges experimental fluid dynamics with geophysical phenomena, leveraging advanced diagnostics like Focused Laser Differential Interferometry (FLDI) and laser spectroscopy. The group’s facilities enable studies of high-enthalpy flows and hypersonic aerodynamics critical for aerospace and planetary exploration. Research highlights include investigations into CO₂ Martian entry conditions, boundary layer transition mechanisms, and fluid-structure coupling in high-speed flows. The Hypersonics Group’s experimental setups replicate extreme environments to advance predictive models for aerospace systems. Her contributions span both fundamental fluid mechanics and applied engineering challenges, with a focus on real-gas effects and shock dynamics. Collaborations with institutions like NASA and academic partners further her interdisciplinary impact.

H. Jane Baeمشاهده پروفایل

استادیار

• Turbulence Modeling
• Computational Fluid Dynamics
• Fluid Mechanics
• +۳ مورد دیگر

H. Jane Bae is an Assistant Professor of Aerospace at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. Her research focuses on turbulence modeling, particularly developing high-fidelity computational methods to simulate high-Reynolds-number flows for applications in aircraft design, wind farms, and atmospheric predictions. She integrates machine learning, information theory, and numerical techniques to enhance turbulence modeling efficiency. Education: B.S. in Aerospace Engineering from Caltech (2011), Ph.D. in Mechanical Engineering from Stanford University (2018). She joined Caltech in 2021. Research interests include near-wall turbulence dynamics, resolvent analysis, sparse identification of nonlinear dynamics, and reinforcement learning for wall models in LES. Her work addresses computational cost reduction and model accuracy in complex flow simulations. Awards: 2023 Outstanding Referee Award from Physical Review. Teaching includes courses on fluid mechanics (Ae/APh/CE/ME 101 abc) and turbulence (Ae 239 ab). Her lab combines turbulence theory, high-performance computing, and data-driven methods to study unsteady flows over complex surfaces. Notable contributions include machine learning-based wall models and resolvent analysis frameworks for non-stationary flows.

Douglas Dregerمشاهده پروفایل

استاد

• Seismology
• Geophysics
• Earthquake Source Analysis
• +۵ مورد دیگر

Douglas Dreger is a Professor in the Department of Earth and Planetary Science at the University of California, Berkeley. His research focuses on seismic source analysis, wave propagation, Earth structure, and geophysical inverse problems. He primarily uses waveform data to investigate earthquake mechanics, stress orientations, and fluid-faulting interactions. Email: dreger@seismo.berkeley.edu His work spans diverse tectonic and geothermal environments, including the Ridgecrest earthquake sequence, Mendocino Triple Junction, North Korean nuclear tests, and The Geysers geothermal field. Recent studies examine graviquake hypotheses, long-period volcanic tremors, and stress drop validation through advanced inversion techniques. Dreger's publications reveal a strong emphasis on moment tensor inversion, fault geometry modeling, and seismic hazard assessment. He has contributed to understanding earthquake rupture heterogeneity, coseismic deformation, and 3D seismic simulations for hazard scenarios.