جست‌وجوی استاد و پژوهشگر

Spitas Vasiliosمشاهده پروفایل

استاد

• Gear Dynamics
• Additive Manufacturing
• Mechanical Design Optimization
• +۷ مورد دیگر

Spitas Vasilios is a Professor at the National Technical University of Athens (NTUA), affiliated with the School of Mechanical Engineering and the Department of Mechanical Engineering & Automatic Control. His research focuses on gear dynamics, additive manufacturing, computational modeling, thermal systems, and educational pedagogy in engineering. He leads projects involving advanced gear technologies, material science applications, and sustainable energy systems. His work integrates experimental, analytical, and numerical methods to address challenges in mechanical design and industrial applications. Key research areas include optimizing gear performance through bio-inspired surface texturing, developing novel clutch systems, and enhancing 3D printing precision. He explores interdisciplinary topics like energy-efficient Ericsson engines and hyper-damping systems. His contributions to engineering education emphasize active learning strategies and project-based curricula. His recent publications analyze magnetic gear dynamics, additive-manufactured components, and educational innovations. He collaborates on international projects, such as the HEV Ventilator initiative, merging biomedical and mechanical engineering.

Arthur J. Ragauskasمشاهده پروفایل

استاد

• Biorefining
• Lignocellulosic Biomass Conversion
• Biofuels
• +۴ مورد دیگر

Arthur J. Ragauskas is the UT-ORNL Governor’s Chair for Biorefining and Acting Department Head in the Department of Chemical and Biomolecular Engineering at the University of Tennessee, with a complementary appointment in the Department of Forestry, Wildlife, and Fisheries. He is affiliated with Oak Ridge National Laboratory’s Energy and Environmental Sciences Directorate. Education: PhD (1985) and BS (1980) in Chemistry from the University of Western Ontario. His research focuses on sustainable bioresources, lignocellulosic biomass conversion, biofuels, and upcycling waste plastics. He leads a team of graduate students, postdocs, and researchers, with over 488 publications. Research Interests: Biorefining, lignin valorization, nanolignocellulosics, green chemistry, and bio-based materials. He explores novel technologies for biomass fractionation, enzymatic hydrolysis, and biorefinery integration. Awards: 2024 Lithuanian Global Award, 2022 RSC Environment Prize, 2018 Royal Society of Chemistry Fellow, 2012 AAAS Fellow, and 2008 Fulbright Chair in Alternative Energy. Grants & Collaboration: Sponsored by NSF, USDA, DOE, and industry consortia. He advises on global initiatives, including the U.S. DOE’s Bio Energy Science Center (BESC). Labs & Teams: Directs interdisciplinary research labs focused on biomass conversion, catalytic processes, and sustainable materials. Active in editorships and advisory roles globally.

Ayhan Inceمشاهده پروفایل

استاد

• Computational Damage Modeling
• Fracture Mechanics of Materials
• Fatigue Analysis
• +۵ مورد دیگر

Dr. Ayhan Ince is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His expertise spans computational damage modeling, fracture mechanics of materials, short crack growth behavior, and machine learning-based approaches in engineering. Education: Ph.D. in Mechanical Engineering, University of Waterloo (2007–2012) M.Sc. in Mechanical Engineering, University of Waterloo (2004–2006) Research Interests: Dr. Ince’s work focuses on advanced computational methods for predicting material behavior under cyclic and multiaxial loading conditions. His research integrates peridynamics, finite element analysis, and artificial neural networks to study fatigue crack propagation, residual stress computation in additive manufacturing, and durability assessment of metallic alloys. Key Contributions: Development of peridynamic-based fatigue crack propagation models Integration of machine learning for J-integral prediction and stress-strain analysis Investigation of VHCF behavior in laser powder bed fused materials Advising & Grants: Dr. Ince supervises graduate students in Mechanical Engineering (MASc and PhD programs). His research has been supported by grants focusing on fatigue analysis, additive manufacturing, and computational mechanics.

Golden Kumarمشاهده پروفایل

دانشیار

• Nanomanufacturing
• Metallic glasses
• Nanomechanics
• +۵ مورد دیگر

Golden Kumar is an Associate Professor in the Department of Mechanical Engineering at The University of Texas at Dallas, affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a PhD in Physics from the Technical University Dresden, Germany, and has postdoctoral experience at Yale University. His research focuses on nanomanufacturing, metallic glasses, and additive manufacturing, with emphasis on processing-microstructure-property relationships in advanced materials. Education: Postdoc, Mechanical Engineering (Yale University); PhD, Physics (Technical University Dresden); MTech, Materials Science (IIT Kharagpur); BSc, Panjab University. Research interests include metallic glass nanowires, surface engineering, phase transformations, and photothermal properties. Notable awards include the NSF CAREER Award (2017) and Excellence in Research Awards (2013, 2017). His lab, equipped with advanced facilities like a laser-powder-bed-fusion printer and characterization tools, investigates additive manufacturing, metallic glass fabrication, and material characterization. Recent publications highlight work on metallic glass nanowires, additive manufacturing processes, and lattice structures. He advises graduate and undergraduate students, contributing to over 20+ publications and fostering industry partnerships through his Advanced Materials and Manufacturing Lab.

Uduak Inyang-Udohمشاهده پروفایل

استادیار

• Control Theory
• Graph Theory
• Physics-Guided Machine Learning
• +۵ مورد دیگر

Uduak Inyang-Udoh is an Assistant Professor in the Department of Mechanical Engineering at the University of Michigan, affiliated with the Autonomous & Intelligent Systems (AI-Sys) Lab. Her research focuses on control theory, graph theory, and physics-guided machine learning applied to data-rich advanced manufacturing, thermal systems, and energy storage. Education: PhD (Rensselaer Polytechnic Institute, 2021), BSc (University of Lagos, 2016) Research Areas: Controls, Energy, Manufacturing, Mechatronics & Robotics Email: udinyang@umich.edu Research interests integrate theoretical frameworks with practical applications in real-time optimal control, nonlinear system analysis, and additive manufacturing optimization. Her group has published extensively in control algorithms, thermal management systems, and data-driven industrial processes. Recent publications highlight advancements in neural co-state regulators, hybrid thermal control systems, and machine learning integration in droplet-based manufacturing. She emphasizes control theory applications to complex systems with input constraints and transient dynamics. Scientific Awards ASME Dynamic Systems and Control Division Rising Star Award (2022) ASME Rudolf Kalman Best Paper Award (2024) Mentoring style prioritizes student ownership of projects, collaborative peer mentoring, and structured progress reporting. Funding supports conference attendance (ACC, MECC) through travel grants and lab resources. Lab policies balance research productivity with vacation periods during academic breaks.

Xiaochun Liمشاهده پروفایل

استاد

• Scifacturing (science-driven manufacturing)
• Nanotechnology Enabled Metallurgy
• Scalable Nanomanufacturing
• +۲ مورد دیگر

Xiaochun Li is a Professor at the Department of Mechanical and Aerospace Engineering within the College of Engineering at the University of California, Los Angeles. Holding the Raytheon Endowed Professorship in Manufacturing Engineering, his work bridges materials science and advanced manufacturing technologies. Education: PhD (Mechanical Engineering, Stanford University, 2001), MS (Industrial, System and Welding Engineering, Ohio State University, 1997), BS (Mechanical Engineering and Applied Physics, Tsinghua University, 1992) Research Focus: Dr. Li specializes in science-driven manufacturing (scifacturing), leveraging nanotechnology to revolutionize metallurgy and scalable nanomanufacturing. His work explores smart manufacturing systems, additive manufacturing techniques, and nanoparticle-enabled phase control to overcome traditional material processing limitations. Publication Trends: His research spans nanoparticle integration in metals, fusion-based manufacturing innovations, and sensor-embedded process monitoring. Topics include unconventional welding methods, solidification control, composite synthesis, and thermal behavior analysis, reflecting interdisciplinary expertise in materials science, mechanical engineering, and nanotechnology. Scientific Recognition: Awards include the prestigious SME Frederick W. Taylor Research Medal (2025), ASME William T. Ennor Manufacturing Technology Award (2022), and Fellowships from ASME, SME, and the International Society of Nanomanufacturing. His NSF CAREER Award (2002) and multiple AFS honors highlight early-career impact. Laboratory: Dr. Li leads the Scifacturing Laboratory , which develops science-driven manufacturing solutions that address critical challenges in materials processing and industrial scalability.

Emily D. Sandersمشاهده پروفایل

استادیار

• Mechanics of Materials
• Computer Aided Engineering and Design
• Computational Mechanics
• +۳ مورد دیگر

Dr. Emily D. Sanders is an Assistant Professor at the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. She specializes in computational mechanics, optimization-based design, and design for advanced manufacturing. Her research focuses on topology optimization, metamaterials, and advanced manufacturing techniques. Education: PhD in Civil and Environmental Engineering, Georgia Tech (2021) MS in Civil and Environmental Engineering, Stanford University (2012) BS in Civil Engineering, Bucknell University (2011) Her research interests include mechanics of materials, computer-aided engineering and design. She has developed novel topology optimization methods for cable nets, cloaking devices, and multiscale structures. Recent work emphasizes additive manufacturing and fiber-reinforced composites. Key research trends in her publications include: Advances in metamaterial design for cloaking applications Integration of topology optimization with additive manufacturing constraints Development of efficient computational tools for multi-material systems No scientific awards are listed in her profile. She has advised no graduate students in the provided information. Her work is associated with the Woodruff School's mechanical engineering research initiatives, though specific lab affiliations are not detailed in the text.

• Photovoltaics
• Organic Electronics
• Semiconductor Materials
• +۳ مورد دیگر

Professor David Lidzey is a faculty member at the University of Sheffield's School of Mathematical and Physical Sciences, where he holds the position of Professor of Physics. His research focuses on the development and characterization of advanced photovoltaic materials and optoelectronic devices, including organic and hybrid photovoltaics, semiconductor materials, and exciton-polariton systems. His work spans from fundamental material science to applied device engineering, with a strong emphasis on solution-processed technologies and scalable manufacturing methods. Research interests include: development of high-efficiency organic and perovskite solar cells, investigation of light-matter interactions in microcavities, and structural analysis of thin-film semiconductor materials. He has contributed to advancements in spray-coating techniques, material stability, and device architecture optimization. His studies often integrate experimental and theoretical approaches to understand charge transport, exciton dynamics, and interface engineering. Notable contributions include the exploration of DIO-driven vertical segregation in organic photovoltaics, the design of flexible and scalable perovskite solar modules, and the study of ultrafast energy transfer mechanisms in strongly coupled organic microcavities. His research has implications for sustainable energy technologies and next-generation optoelectronic devices.

Wenbin Liمشاهده پروفایل

مدرس ارشد

• Robotics
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Dr. Wenbin Li is a Senior Lecturer (Associate Professor) in Robotics at the University of Bath's Department of Computer Science. He leads the Pering Laboratory (Perceptual Intelligence Laboratory), affiliated with the AI & Machine Learning and Visual Computing groups. Previously, he held postdoctoral positions at Imperial College London (2016-2018) and UCL (2014-2016), and earned his PhD from the University of Bath in 2013, with earlier degrees from Imperial College London (MSc, 2009) and Xidian University (B.Eng, 2008). His research focuses on unified autonomous systems, including multi-sensory localization/mapping, dynamic motion capture, and uncontrolled scene understanding with applications in manufacturing and professional capture. Key areas include Robotics, Computer Vision, Graphics, and Machine Learning. He actively supervises doctoral students in these fields and has funded PhD openings. Dr. Li has been involved in major initiatives such as the My World - Strength in Places Fund (2021–2027), SLAM with Reinforcement Learning (2022–2023), and the CAMERA MC2 Award (2019–2023). His work aligns with UN Sustainable Development Goals, particularly in advancing technology for societal benefit. Recent publications emphasize aerial robotics, autonomous systems, and computer vision applications, including UAV package delivery reviews, Bayesian optimization for balloon station-keeping, and generative models for intrinsic image decomposition.

• Material Science
• Mathematical Modeling
• Fractal Networks
• +۵ مورد دیگر

Professor Tony Roberts is the Head of School in the School of Mathematical Sciences at Queensland University of Technology (QUT). He holds a PhD from the Australian National University and is a Fellow of the Australian Mathematics Society. His research focuses on the interplay between material microstructure and macroscopic properties, with emphasis on topology optimization, random structure modeling (e.g., Gaussian fields, percolation models), and material property analysis such as conductivity, diffusion, and fluid flow. He develops computational methods for analyzing experimental techniques like 3D statistical reconstruction and small-angle scattering. His recent work includes optimizing piezoelectric materials for robotics, studying diffusion dynamics in fractal networks, and modeling material failure mechanisms. Key contributions span multi-functional piezoelectric components, anisotropic elastic properties of additively manufactured alloys, and fracture mechanics in perforated materials. Awards include his fellowship in the Australian Mathematics Society. Supervision interests include structural optimization, diffusion in random media, and porous material failure modeling. Education: PhD (Australian National University) Affiliations: Faculty of Science, School of Mathematical Sciences Research Themes: Material science, computational modeling, fracture mechanics, stochastic systems

Ana Leite Oliveiraمشاهده پروفایل

استادیار

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +۱۲ مورد دیگر

Ana Leite Oliveira is an Assistant Professor with Habilitation at the Escola Superior de Biotecnologia, Universidade Católica Portuguesa (UCP), where she also serves as the Director of the Master of Biomedical Engineering. She leads the Biomaterials and Biomedical Technology Laboratory at the Centre for Biotechnology and Fine Chemistry (CBQF), a key research center within the university. Her work bridges academic research and industrial innovation in advanced biomaterials. Her research is centered on natural-based biomaterials for tissue regeneration , with a strong emphasis on skin-related applications. She has pioneered work in silk sericin-based hydrogels , decellularized matrices , and supercritical CO₂ technology for sterilization and processing of biological materials. Her research aims to modulate the biofunctionality of biomaterials and ensure their safety for clinical translation, with a vision toward scalable production. Her recent publications (2019–2023) demonstrate a consistent focus on biomaterials innovation , particularly in decellularization , hydrogel development , 3D bioprinting , and wound healing . These works span high-impact journals in materials science and biomedical engineering, reflecting interdisciplinary collaboration and technological advancement in regenerative medicine. Ana Leite Oliveira has been actively involved in scientific service, serving as an Independent Expert for the European Commission since 2008. She has successfully coordinated multiple research projects funded by national, European, and private entities, demonstrating strong leadership in securing and managing research grants. Her innovation has led to 6 patents , with active collaboration with industry to develop new products and processes. She leads the Biomaterials and Biomedical Technology Laboratory , which focuses on developing advanced materials for regenerative medicine. The lab integrates expertise in biomaterials synthesis, processing, characterization, and biological evaluation, fostering a collaborative environment for training the next generation of biomedical engineers.

Habiba Bougheraraمشاهده پروفایل

استاد

• Biomaterials
• Biomechanics
• Additive Manufacturing
• +۷ مورد دیگر

Habiba Bougherara is a Professor and Associate Chair of Graduate Programs in the Department of Mechanical, Industrial, and Mechatronics Engineering at Toronto Metropolitan University. Her research focuses on biomaterials, biomechanics, and advanced composites with applications in biomedical engineering and additive manufacturing. Education: PhD, École Polytechnique, 2005 MASc, École Polytechnique, 2000 Her research interests include developing bone-mimicking composite materials using natural fibers and nanocomposites, with a strong emphasis on improving orthopedic implants through 3D/4D printing and mechanical modeling. She integrates artificial intelligence and machine learning to enhance material design and performance prediction. The recent publications highlight her work in hybrid composites, fatigue analysis of plant-based fibers, mesoscale modeling, and computational biomechanics for bone remodeling. Her research bridges sustainable materials with biomedical innovation. Scientific Awards: Early Researchers Awards (ERA-MRI) Discovery Accelerator Supplements (NSERC-DAS) Dean’s Scholarly, Research and Creative Activity Awards (3) Ryerson’s Collaborative Research Award Habiba Bougherara actively supervises graduate students and leads externally funded research projects. She is involved in interdisciplinary collaborations and has secured competitive grants from NSERC and other agencies. Her lab contributes to innovation in both medical and structural applications of composites. She leads the Laboratory of Biomaterials and Biomechanics (LBB) , which focuses on experimental and computational studies of advanced materials for biomedical and engineering applications.

Mohammed Shafaeمشاهده پروفایل

استادیار

• Cyber-physical systems security
• Smart manufacturing systems
• Statistical process monitoring
• +۷ مورد دیگر

Mohammed Shafae is an Assistant Professor in the Department of Systems and Industrial Engineering at the University of Arizona, where he has been serving since 2018. He is also a member of the Graduate Faculty, contributing to advanced research and mentorship in engineering disciplines. Education: PhD in Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States MS in Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia, United States MS in Production Engineering, Alexandria University, Alexandria, Egypt BS in Production Engineering, Alexandria University, Alexandria, Egypt His research centers on cyber-physical systems security , smart manufacturing systems , and data-driven quality control , with a strong emphasis on leveraging manufacturing data for process monitoring, modeling, and securing machining and additive manufacturing systems. His work integrates statistical process monitoring, machine learning, and advanced metrology to enhance manufacturing resilience and efficiency. His recent publications (2022–2025) reflect a clear trend toward securing Industry 4.0 systems, with a focus on digital twin security, attack detection in machining, and anomaly detection in additive manufacturing using photodiode and thermal data. He also explores futuristic applications such as in-situ lunar manufacturing using regolith-based materials. Scientific Awards: First Place in the ASCEND Propel Pitch Competition (AIAA, Fall 2020) Virginia Tech Teaching Excellence Award (Spring 2017) Harold Schneikert Graduate Fellowship (Spring 2016) David H. Burrows Graduate Fellowship (Fall 2015) Best Track Paper Award (IEOM 2012) Prize for Excellence in Senior Design Project (Cairo, 2009) Dr. Shafae actively mentors graduate students, co-authoring numerous publications with advisees in areas such as cybersecurity, additive manufacturing, and process monitoring. While specific grant details are not listed, his research is clearly funded through competitive fellowships and likely external grants given the volume and quality of his outputs. He has no listed labs or teams in the provided text, but his collaborative work suggests active participation in research groups focused on smart manufacturing and cybersecurity.

Manel del Valleمشاهده پروفایل

استاد

• Analytical Chemistry
• Electrochemistry
• Sensor Technology
• +۶ مورد دیگر

Manel del Valle is a Full Professor of Analytical Chemistry at the Autonomous University of Barcelona (UAB), leading the Sensors & Biosensors Group. He specializes in electrochemical sensors, electronic tongues, and biosensor arrays, with contributions to environmental, pharmaceutical, and security applications. His work integrates nanotechnology and artificial intelligence for advanced data processing. PhD in Chemistry (1992) and B.Sc. in Chemistry (1986) from UAB. Former roles: Associate Professor (1997–2018), Assistant Professor (1989–1997). Research interests focus on sensor array design, electrochemical impedance spectroscopy, and automated analytical systems. He has coordinated EU projects like BORDERSENS (H2020) and authored over 220 publications with an h-index of 84. Awards include the ICREA Academy Distinction and multiple research sexennia. Awards: 3rd National Prize for Studies, Extraordinary Doctorate Award, Medical Journal Research Award. Supervised 28 doctoral theses and 36 final projects across chemistry, engineering, and environmental sciences. Current projects include development of portable drug detection devices and bioelectronic tongues for environmental monitoring. Collaborates widely on electronic tongue applications in food, pharmaceuticals, and security.

Cesar Ruizمشاهده پروفایل

استادیار

• Metal Additive Manufacturing
• Process-Informed Machine Learning
• Quality Control
• +۳ مورد دیگر

Cesar Ruiz is an Assistant Professor in the Department of Industrial & Systems Engineering at The University of Oklahoma. His research focuses on integrating domain knowledge with machine learning and stochastic modeling for engineering applications, particularly in metal additive manufacturing, predictive maintenance, and quality control. He holds a Ph.D. and M.S. in Industrial Engineering from the University of Arkansas and a B.A. in Business Engineering from the Higher School of Economics and Business in El Salvador. His research domains include metal additive manufacturing processes, process-informed machine learning frameworks, and reliability evaluation in complex systems. Notable works address challenges in layer segmentation for quality assessment, predictive maintenance strategies, and degradation-based reliability analysis. Ruiz has received prestigious awards such as the RAMS Golomski Award (2020, 2022), ASQ Best Reliability Paper (2021), and IEEE CASE Best Conference Paper (2021). His affiliations include SRE, INFORMS, and ASME. His research spans aerospace and defense systems, with recent publications emphasizing advanced manufacturing techniques, functional data analysis, and Bayesian modeling for reliability growth. He collaborates on projects involving biosensor optimization and large-scale system maintenance frameworks.