جست‌وجوی استاد و پژوهشگر

Ian Abelمشاهده پروفایل

پژوهشگر

• Fusion Energy
• Plasma Physics
• Magnetic Confinement Systems
• +۳ مورد دیگر

Dr. Ian Abel is an Associate Research Scientist at the Institute for Research in Electronics & Applied Physics (IREAP) at the University of Maryland, where he has been since 2018. His expertise spans fusion energy, plasma physics, and computational modeling. Abel holds a B.A. in Mathematics (2006) and M.S. in Applied Mathematics (2007) from the University of Cambridge, followed by a Ph.D. in Theoretical Physics from the University of Oxford (2012). His research focuses on magnetically confined fusion systems, particularly edge dynamics in tokamaks and innovative centrifugal mirror concepts. He has contributed to the development of gyrokinetic simulation tools like the GX code and the MaNTA transport model. Abel’s work also explores machine learning applications in plasma turbulence analysis and centrifugal mirror fusion reactor design for space propulsion. His research leverages advanced numerical methods, including GPU-native algorithms and adjoint-based optimization techniques for plasma equilibria. Key projects include the Centrifugal Mirror Fusion Experiment (CMFX), where he investigates plasma confinement and transport phenomena. His publications emphasize interdisciplinary approaches, integrating computational fluid dynamics, statistical physics, and high-performance computing to address challenges in fusion energy and plasma dynamics. While no specific awards are listed, his contributions to gyrokinetic turbulence modeling and centrifugal confinement systems are central to current fusion research.

Henrik Myhre Jensenمشاهده پروفایل

استاد

• Mechanics of Materials
• Solid Mechanics
• Mechanical Engineering
• +۴ مورد دیگر

Henrik Myhre Jensen is a Professor at the College of Engineering , Aarhus University, specializing in Mechanics of Materials , Solid Mechanics , and Mechanical Engineering . His research focuses on fracture mechanics, composite materials, and computational modeling of structural behaviors. Research Focus Fracture mechanics in composites and layered materials Computational modeling of kink band propagation Surface wear and coating technologies Ultrasound imaging applications in mechanical systems Notable Contributions Henrik has contributed to understanding crack propagation in cantilever beams, developed numerical methods for simulating delamination in composites, and explored buckling instabilities in solids. His recent work connects machine learning (holomorphic neural networks) to traditional fracture mechanics problems. Key Projects MAGFLY (2017-2021): Magnets for Flywheel Energy Storage InnoVacc (2009): Pressure Testing of Vacuum Chambers Simulation of composite structures (2011-2020): Micro-mechanical modeling

Kathryn Hess Bellwaldمشاهده پروفایل

استاد

• Algebraic Topology
• Homotopy Theory
• Neuroscience
• +۴ مورد دیگر

Kathryn Hess Bellwald is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in both the School of Life Sciences and School of Basic Sciences . She leads the Laboratory for Topology and Neuroscience and serves as Academic Director for the Euler Programme . Her work bridges pure mathematics and interdisciplinary applications in neuroscience, materials science, and data analysis. Education : PhD in Mathematics (MIT, 1989), preceded by positions at Stockholm, Nice, and Toronto universities. Her research spans algebraic topology , homotopy theory , operad theory , and algebraic K-theory , with applications in neuroscience and materials science . She has pioneered topological data analysis methods for classifying neuronal morphologies , microglia phenotypes , and nanoporous materials , creating a parameter-free framework linking neural network structure to activity. The 15 most recent publications highlight her work on topological inverse problems , neuroinflammation , and equivariant homotopy . These studies often involve collaborations with the Blue Brain Project and EPFL teams in neuroscience , machine learning , and materials science . Scientific Awards : Fellow, American Mathematical Society (2017); Distinguished Speaker, European Mathematical Society (2017); Crédit Suisse Teaching Prize (2012); Polysphère d'Or (2013); Full Member, Swiss Academy of Engineering Sciences (2016); Chaire de la Vallée Poussin (2023); Fellow, Association for Women in Mathematics (2024). She has mentored numerous PhD students in mathematics and neuroscience, including Adélie Eliane Garin , Varvara Karpova , and Dimitri Zaganidis . Her EPFL Mathematics affiliations include the DIVISION MATH , while her Neuroscience lab operates under the Brain Mind Institute (BMI) in the School of Life Sciences (SV). Grants and collaborations are evident in her work on neurodegenerative diseases , synthetic materials , and machine learning frameworks .

Philippe Schwallerمشاهده پروفایل

استادیار

• Artificial Intelligence in Chemistry
• Machine Learning for Molecular Discovery
• Sustainable Chemistry
• +۶ مورد دیگر

Philippe Schwaller is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), School of Basic Sciences, within the Institute of Chemical Sciences and Engineering. He leads the Laboratory of Artificial Chemical Intelligence (LIAC), a research group focused on leveraging artificial intelligence to accelerate molecular discovery and sustainable chemistry. He is also a core Principal Investigator of the NCCR Catalysis, a national Swiss research center. His research lies at the intersection of chemistry, materials science, and computer science, with a strong emphasis on developing machine learning models for molecular design and synthesis. LIAC's work is driven by real-world sustainability challenges, aiming to reduce the time and cost of discovering new functional molecules and materials. The recent publications and projects from his lab highlight a strong trend in generative AI for chemistry, including memory-augmented models, hypergraph neural networks, and large language models tailored for scientific discovery. These efforts are complemented by educational initiatives such as the 'AI for Chemistry' course and practical programming resources for chemists. He actively supervises a diverse group of PhD students and contributes to multiple doctoral programs at EPFL, including EDCH and EDPY. His teaching portfolio includes courses on computational chemistry, AI applications in chemistry, and scientific machine learning. Philippe Schwaller is deeply involved in advancing AI-driven scientific discovery through both research and education, positioning his lab at the forefront of artificial chemical intelligence. The lab maintains active open-source contributions on GitHub, fostering collaboration and transparency in scientific AI development.

Sumanta Dasمشاهده پروفایل

دانشیار

• Sustainable Cementitious Materials
• Microstructure and Material Modeling
• Materials Design for Sustainable and Durable Infrastructure
• +۵ مورد دیگر

Dr. Sumanta Das is an Associate Professor and Graduate Director in the Department of Civil and Environmental Engineering at the University of Rhode Island. His research focuses on sustainable infrastructure materials, with particular expertise in cementitious materials, composite structures, and advanced computational modeling techniques. He directs a vibrant research group that bridges experimental mechanics with computational modeling and machine learning approaches to address challenges in infrastructure durability and performance. Dr. Das received his educational training from prestigious institutions: Ph.D. in Materials and Structures from Arizona State University (2015) M.Tech. in Structural Engineering from Indian Institute of Technology, Kanpur (2012) B.E. in Civil Engineering from Jadavpur University (2010) His research interests center around developing sustainable and durable infrastructure materials through innovative design approaches. Dr. Das investigates microstructure-property relationships in cementitious systems, with special focus on materials containing microencapsulated phase change materials for freeze-thaw durability, fiber-reinforced composites, and smart cementitious materials with self-sensing capabilities. His work integrates advanced experimental techniques like nanoindentation with computational modeling approaches including finite element analysis, molecular dynamics simulations, and machine learning algorithms to predict material behavior and optimize performance. Dr. Das's recent publications demonstrate a clear trajectory toward integrating machine learning with traditional materials science approaches. His research group has made significant contributions to understanding the behavior of cementitious composites under extreme conditions, developing multifunctional composites with embedded sensing capabilities, and creating computational frameworks that bridge multiple scales from molecular to structural levels. The work shows increasing sophistication in combining experimental validation with predictive modeling. Dr. Das has successfully secured numerous research grants as PI or Co-PI from diverse funding sources including the Office of Naval Research, Department of Defense, US Department of Transportation, and industry partners like Goetz Composites. His research portfolio spans infrastructure durability, composite materials for marine applications, and smart sensing technologies for structural health monitoring. As an educator and mentor, Dr. Das has supervised multiple doctoral and master's students who have completed theses on topics including: Multiscale simulation and machine learning-assisted performance prediction for cementitious composites Performance-based multiscale tuning of inclusion-modified and 3D printed composites Enhancing freeze-thaw durability of cementitious composites through innovative materials design Underwater explosion response of composite structures Implosion pulse mitigation using additively manufactured filler profiles

Srishti Banerjiمشاهده پروفایل

استادیار

• Construction Materials
• Structural Fire Engineering
• Sustainable Infrastructure
• +۴ مورد دیگر

Dr. Srishti Banerji is an Assistant Professor in the Department of Civil and Environmental Engineering at Utah State University and Director of the Systems, Materials, and Structural Health (SMASH) Lab. She leads research on advanced construction materials, structural resilience under extreme loads (particularly fire), sustainable infrastructure, and structural health monitoring. Her group focuses on experimental testing, numerical simulations, and developing design solutions for civil infrastructure. Education: PhD in Civil (Structural) Engineering, Michigan State University (2021) MS in Civil (Structural) Engineering, Concordia University (2016) BS in Civil Engineering, National Institute of Technology Silchar (2013) Research Focus: Her work spans: 1) Characterization of high-performance/sustainable materials (e.g., UHPC, recycled glass pozzolan), 2) Structural behavior under fire exposure, 3) Integration of electric charging systems in concrete pavements, 4) Non-destructive testing and structural health monitoring, and 5) Retrofitting techniques for infrastructure strengthening. She employs machine learning, thermo-mechanical modeling, and full-scale experimentation. Publication Trends: Her 13+ journal articles primarily analyze fire resistance of concrete/timber structures, UHPC material properties at high temperatures, sensor-based infrastructure monitoring, and sustainable material development. Recent works increasingly incorporate machine learning and electrification concepts. Awards & Honors: Teacher of the Year (USU, 2025) ASCE ExCEEd Faculty Teaching Fellowship (2023) Top Cited Article Award, Fire and Materials Journal (2023) SHMII-11 Early Career Grant (2022) NSERC Scholarship (2015) Best Conference Paper (SEC 2016) Current Projects & Teams: She leads 5+ funded projects including fire performance of polymer concrete, self-healing concrete for bridges, and Utah-sourced UHPC development. Mentees include 3 PhD students (Abdullah Al Sarfin, Mehrnoosh Nazari, Mahmoud Ali) and alumni working on sustainable materials and additive manufacturing.

• Structural Health Monitoring
• Civil Infrastructure
• Machine Learning for Engineering
• +۷ مورد دیگر

Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.

Sueda SAYLANمشاهده پروفایل

استادیار

• Memristive Devices
• Photovoltaics
• Light-Matter Interactions
• +۳ مورد دیگر

Dr. Sueda Saylan is an Assistant Professor at the Faculty of Engineering, Özyeğin University, since 2024. Her academic journey includes a Ph.D. in Interdisciplinary Engineering (2016) from Masdar Institute (now Khalifa University), postdoctoral research at Khalifa University (2016-2022), and an MSCA Postdoctoral Fellowship at Bilkent University (2022-2024). She has also held visiting researcher positions at MIT (2014) and the University of Tokyo (2016). Education Doctorate: Interdisciplinary Engineering, Masdar Institute of Science and Technology (2016) Master's: Microelectronic Manufacturing Engineering, Rochester Institute of Technology (2004) Bachelor's: Mechanical Engineering, Middle East Technical University (2002) Dr. Saylan's research focuses on memristive devices , photovoltaics , and light-matter interactions at micro/nanoscale . Her work bridges materials science and electronic engineering, with recent publications on memristor-based sensors, spectral filtering in silicon, and machine learning integration for biomedical diagnostics. Key trends from her 15 most recent articles (2013-2025) include: Advancing memristor technology for radiation sensing and vacuum monitoring Optimizing photovoltaic efficiency through light management and antireflection coatings Developing compact, low-power diagnostic devices for pathogen detection Exploring nanoscale electrode materials and switching mechanisms Applying Fourier transforms and interferometry in optical systems Scientific Awards Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship (2022-2024) Dr. Saylan has received research support from prestigious programs and has contributed to interdisciplinary projects involving semiconductor physics, optical engineering, and biomedical diagnostics. Her collaborations span institutions like Khalifa University, MIT, and the University of Tokyo.

S. Scott Grahamمشاهده پروفایل

دانشیار

• Computational Rhetorics
• Science, Technology & Medicine Studies
• New Materialisms
• +۱۳ مورد دیگر

S. Scott Graham is an Associate Professor of Rhetoric & Writing and Associate Director for A.I. Science & Culture at the Humanities Institute of the University of Texas at Austin . He is affiliated with the Center for Health Communication , the Addiction Research Institute , the University of Texas Opioid Response Consortium , and the Health Informatics Research Interest Group . PhD, Iowa State University Research focuses on AI and machine learning in bioscience/health policy communication, bioethics, and health AI Author of three books: The Doctor & The Algorithm , The Politics of Pain Medicine , and Where's the Rhetoric? Projects include Transparency to Visibility (T2V) and Spectacular Specimens: A Global Study of Cadaverous Rhetorics at Anatomical Museums His work combines science and technology studies , critical algorithm studies , and public interest informatics to analyze health AI's societal implications. He has developed tools for parsing conflicts of interest in biomedical publishing and studies the ethics of anatomical museum displays. Scientific Awards & Grants: NEH Digital Humanities Advancement Grant (T2V project) NSF's XSEDE computational resources NIH funding for health communication research National Endowment for the Humanities support for Spectacular Specimens He teaches courses like Arguing With Scientists , Rhetoric And Algorithms , and Research Methods In Rhet/Wrt . Current research explores ethical frameworks for health AI and global anatomical museum rhetorics.

Steven Y. Liangمشاهده پروفایل

استاد

• precision manufacturing
• additive manufacturing
• materials science
• +۳ مورد دیگر

Steven Y. Liang , Regents' Professor at the Georgia Institute of Technology 's Woodruff School of Mechanical Engineering, focuses on precision manufacturing , additive manufacturing , and materials-driven process optimization . His research program bridges materials science and computational mechanics to develop predictive models for advanced manufacturing systems. Ph.D., University of California, Berkeley (1987) M.S., Michigan State University (1984) B.S., National Cheng-Kung University, Taiwan (1980) Dr. Liang's work emphasizes physics-based modeling of thermal-mechanical interactions in machining and additive manufacturing, particularly for Ti6Al4V and Inconel 718 alloys. Recent publications highlight tool wear prediction , laser-assisted micro-milling , and residual stress modeling using machine learning and analytical mechanics. His research has been recognized with the ASME Milton C. Shaw Manufacturing Research Medal (2016) , SME Gold Medal (2021) , and Outstanding Lifetime Service Award of NAMRI/SME (2021) , among others. Funded by federal agencies and aerospace/automotive industries, his work provides scientific foundations for process planning and optimization.

Aric Rindfleischمشاهده پروفایل

استاد

• 3D Printing
• New Product Development
• Consumer Values
• +۴ مورد دیگر

Aric Rindfleisch is the John M. Jones Professor of Marketing and Executive Director of the Illinois MakerLab at the University of Illinois Urbana-Champaign’s Gies College of Business. He serves as area chair of marketing and Vernon Zimmerman Faculty Fellow. His research focuses on 3D printing, new product development, consumer values, and AI applications in marketing. Rindfleisch has held editorial roles across 10 journals and received teaching accolades, including recognition by Princeton Review as one of America’s top professors. Education: Bachelor of Science from Connecticut State University (1987) Master of Business Administration from Cornell University (1990) Doctor of Philosophy from University of Wisconsin-Madison (1998) Rindfleisch’s research interests span innovation ecosystems, digital manufacturing, consumer behavior in the sharing economy, and materialism’s societal impact. His work bridges academic rigor with practical applications, particularly in leveraging technology like 3D printing for sustainable innovation. His recent publications highlight themes such as AI’s role in qualitative research, consumer responses to crises like the pandemic, and disruptive innovations in retail and transportation. Rindfleisch actively contributes to academic discourse through editorial roles and serves as a thought leader in marketing strategy and innovation management. Awards: Princeton Review’s “The Best 300 Professors” (2020) His leadership at Illinois MakerLab drives hands-on innovation, emphasizing collaboration between academia and industry. Rindfleisch’s work integrates marketing, technology, and consumer psychology to address modern challenges in product development and societal consumption patterns.

Juan Wachsمشاهده پروفایل

استاد

• Robotics
• Human Computer Interaction
• Assistive Technologies
• +۵ مورد دیگر

Juan Wachs is the James H. and Barbara H. Greene Professor at the Edwardson School of Industrial Engineering, Purdue University. He holds a courtesy appointment in Biomedical Engineering and is an Adjunct Professor of Surgery at the IU School of Medicine. His research focuses on the intersection of robotics, human-AI interaction, and healthcare systems, with a particular emphasis on surgical robotics, assistive technologies, and telemedicine. Education: PhD in Industrial Engineering (Intelligent Systems), Ben-Gurion University of the Negev MSc in Industrial Engineering (Information Systems), Ben-Gurion University of the Negev BEdTech in Electrical Education, ORT Academic College in Jerusalem Research interests include surgical telementoring via augmented reality, gesture-based interfaces for sterile environments, and semi-autonomous robotic systems for healthcare. His ISAT Lab develops solutions like the STAR telementoring system and robotic assistants like Gesturenurse and FIST-D for explosive ordnance disposal. Recent work emphasizes AI-driven medical decision support (Trauma THOMPSON), burn wound characterization, and robotic ultrasound automation. Key contributions include over 100 publications in robotics, medical AI, and human factors. Scientific Awards: James H. and Barbara H. Greene Professorship Purdue University Faculty Scholar Advising & Labs: Guides over 10 PhD/Master’s students in robotics and healthcare tech ISAT Lab fosters interdisciplinary projects in surgical robotics, human-robot interaction, and accessibility

• Mobile and cloud computing
• Energy-efficient computing
• Image and video processing
• +۲ مورد دیگر

Yung-Hsiang Lu is a Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. His research focuses on mobile/cloud computing, energy-efficient computing, and image/video processing. He holds a BSEE from National Taiwan University (1992), an MSEE (1996), and a PhD (2002) from Stanford University. Dr. Lu's academic background includes significant contributions to VLSI and circuit design, with primary emphasis on computer engineering. His work spans theoretical and applied domains, including optimizing neural networks for edge devices, securing deep learning models, and leveraging large language models for software development. Recent research trends in his articles emphasize energy efficiency in AI systems, interdisciplinary applications of transformers (e.g., music analysis), and challenges in model interoperability and security. His publications also highlight innovations in global camera networks and real-time visual data analysis. While no specific grants or awards are explicitly mentioned, his extensive list of publications reflects sustained academic engagement. His educational contributions include developing C programming resources and teaching large-scale image processing using global camera networks. Dr. Lu's professional address is at Purdue's Materials and Electrical Engineering Building in West Lafayette, Indiana, where he maintains an active research lab focused on embedded systems and low-power computing innovations.

• Structural Health Monitoring
• Civil Engineering
• IoT/Edge Computing
• +۵ مورد دیگر

Dr. Zhen Peng is a Research Fellow at Curtin University's School of Civil and Mechanical Engineering, part of the Faculty of Science and Engineering. He holds an ARC Early Career Industry Fellowship (2025–2028), focusing on developing cost-effective bridge monitoring systems using computer vision and edge computing in collaboration with Main Roads WA. His work bridges structural engineering, IoT/edge computing, and machine learning to enhance infrastructure safety. Dr. Peng earned his PhD from Curtin University (Chancellor's Commendation, 2022). His research emphasizes structural dynamics, nonlinear damage detection, and mobile crowdsensing frameworks for infrastructure monitoring. He has published extensively in top journals like Engineering Structures and Structural Control and Health Monitoring , receiving notable awards such as the 2023 Best Paper Award and a Gold Medal in the China Postdoctoral Innovation Competition. His current projects include deploying IoT-driven systems for real-time bridge condition assessment and training students via available 2025 PhD scholarships. Dr. Peng teaches courses in civil engineering and structural analysis, contributing to both academia and industry through innovation in smart infrastructure technologies.

• Digital Writing
• Generative AI in Education
• Digital Media Studies
• +۴ مورد دیگر

Robert E. Cummings is a Professor of Writing and Rhetoric and Executive Director of Academic Innovation at the University of Mississippi. He directs the Interdisciplinary Minor in Digital Media Studies and leads the Academic Innovations Group (AIG) and Center for Excellence in Teaching and Learning (CETL), focusing on evidence-based teaching strategies and professional development for faculty. His academic roles emphasize bridging technology and pedagogy, particularly in digital writing instruction. Education: B.A. in English, University of Tennessee-Knoxville (1990) M.A. and Ph.D. in English, University of Mississippi (1999, 2006) Research Interests: Cummings explores the intersection of digital tools and writing pedagogy, including generative AI’s impact on writing, Wikipedia’s role in education, and post-pandemic digital instruction. He collaborates with computer science researchers to study AI-human dynamics in writing processes. His work emphasizes open educational practices, resilience in teaching, and inclusive digital platforms. Publications Trends: His articles analyze AI writing tools, pandemic-era pedagogy shifts, and long-term trends in digital writing instruction. Recent work focuses on frameworks for integrating AI into first-year writing programs while addressing ethical and practical challenges. Awards: No scientific awards explicitly mentioned in the provided materials. Advising & Grants: No student advising records or grant details are listed. Current responsibilities include curriculum development and institutional innovation initiatives. Labs/Teams: Leads the Academic Innovations Group and collaborates with CETL to advance teaching strategies across the University of Mississippi campus.