جست‌وجوی استاد و پژوهشگر

Richi Nayakمشاهده پروفایل

استاد

• Text Mining
• Data Mining
• Machine Learning
• +۲ مورد دیگر

Professor Richi Nayak is an internationally recognized expert in data mining, text mining and web intelligence at Queensland University of Technology's School of Computer Science. As the Applied Data Science Program Leader of the Centre for Data Science, she develops novel methods for text classification, clustering, and information extraction using deep learning, matrix factorization, and ranking-centered approaches. Her research spans three main streams: Text Mining for data organization and understanding, applications of data mining in solving real-world problems across domains including education, healthcare and transportation, and algorithms for automation and personalization. She has successfully commercialized technologies including marketing strategy automation and bias detection systems deployed by Fortune 500 companies. Professor Nayak's recent publications focus on practical applications of machine learning including traffic crash analysis, multimodal learning, biomass modeling, and offensive text detection. Her work consistently addresses real-world problems through innovative machine learning approaches.

• Powder Technology
• Molecular Dynamics Modeling
• Multiscale Modeling
• +۵ مورد دیگر

Bodhisattwa Chaudhuri is a faculty member in the Department of Pharmaceutical Sciences at the University of Connecticut's School of Pharmacy. His research bridges computational modeling and pharmaceutical manufacturing, focusing on multiscale approaches to materials science, drug delivery, and process optimization. Education: B.E. in Chemical Engineering (Jadavpur University), M.S. in Chemical Engineering (Indian Institute of Science), Ph.D. in Mechanical Engineering (New Jersey Institute of Technology), Postdoctoral Training in Chemical and Biochemical Engineering (Rutgers University) His work integrates Molecular Dynamics (MD) and Discrete Element Method (DEM) simulations with Computational Fluid Dynamics (CFD) to address challenges in pharmaceutical systems. Key areas include: Aggregation behavior of viral vectors like AAV8 AI/ML applications for biopharmaceutical process prediction 3D printing of tablets and freeze-thaw stability of biologics Tribotechnical challenges in powder systems The 15 most recent publications highlight his focus on computational modeling (MD, CFD, DEM) for pharmaceutical processes, machine learning applications in stability prediction, and multiscale studies of drug delivery systems like lipid nanoparticles and polymeric micelles. His work spans both fundamental research and industrial translation. Contact: bodhi.chaudhuri@uconn.edu | Personal Website

• Multiscale Phenomena
• Reacting Flows
• Turbulence
• +۴ مورد دیگر

Dr. Alexander Klimenko is a Reader (equivalent to Associate Professor) and Centre Director of the Centre for Multiscale Energy Systems at the School of Mechanical and Mining Engineering, The University of Queensland. He holds a PhD from Moscow University (1991) and a Doctor of Engineering (DEng) from UQ (2007). His research focuses on multiscale energy phenomena, reacting flows, turbulence modeling, and technology evolution. Dr. Klimenko's research interests encompass: Advanced computational methods for turbulent combustion Energy system optimization (particularly supercritical CO 2 cycles) Plasma dynamics and arc stabilization Nanoscale fluid transport Technology evolution modeling Thermodynamic foundations of complex systems His recent publications demonstrate strong focus on energy technology innovation, with recurring themes in: Plasma torch dynamics and stabilization techniques Supercritical CO 2 applications for power generation Turbulent combustion model development Nanoscale transport phenomena Thermodynamic analysis of time asymmetry This reflects his commitment to solving fundamental challenges in energy conversion and fluid dynamics. Dr. Klimenko leads the Centre for Multiscale Energy Systems, supervising doctoral candidates in areas including hydrogen production, turbulent combustion modeling, and plasma systems. He has secured significant research funding, including current projects on: General systems modeling of hydrogen networks (ARC Discovery Project) Advanced combustion modeling for scramjets Coupled thermal-flow modeling for H 2 -based shaft furnaces

• Soil Science
• Environmental Science
• Agricultural Science
• +۳ مورد دیگر

Maoz Dor is a postdoctoral researcher in the Kravchenko Lab at Michigan State University , affiliated with the Department of Plant, Soil and Microbial Sciences. He holds a Ph.D. from the Hebrew University of Jerusalem, Israel. Research Interests: Focused on soil architectural complexity , Maoz investigates the interplay between physical, chemical, and biological mechanisms driving soil structure dynamics. His work emphasizes advanced imaging techniques (cryo-TEM/SEM, ESEM, AFM, X-ray tomography) and computational algorithms to quantify impacts of wet/dry cycles, salinity, and root exudates on soil stability and carbon distribution. Recent projects explore microbial activity in porous media and hydraulic properties in collaboration with Prof. Dorthe Wildenschild at Oregon State University. Scientific Contributions: Utilizing X-ray tomography and spectromicroscopy, his research spans soil carbon mapping, drought adaptation in grasslands, and biochemical effects of land use changes in tropical ecosystems. Key themes include Microbial influence on pore architecture Hydrological implications of soil structure Organic carbon stabilization mechanisms Imaging technology innovation Recognitions: BARD Fellowship

• Friction
• Adhesion
• Lubrication
• +۱۰ مورد دیگر

Michele Scaraggi is an Associate Professor at the Department of Innovation Engineering , University of Salento , Italy. He leads the Advanced BioInterface Technologies Lab and Advanced Driving to X Simulation Lab , a joint lab with Porsche Engineering. His work bridges tribology , contact mechanics , and bio-inspired robotics . Education: PhD in Bio-Mechanical and Mechanical Design (Politecnico di Bari, 2009); MS and BS in Mechanical Engineering (Politecnico di Bari, 2006 and 2004). Research Interests: Tribology: Friction, adhesion, and lubrication in dry/wet contacts. Soft Robotics: Microbots, smart actuators, and bio-inspired designs. Computational Mechanics: Multiscale modeling of hierarchical surfaces. Biomechanics: Applications to seals, tire/road interactions, and biomedical devices. Projects: ELFIN: Electroactive grippers for micro-object manipulation. TRIBOSCORE: Tribological modeling for sustainable industrial interfaces. BRILLIANCE: RFID-enhanced tactile rehabilitation technologies. Scientific Awards: AIMETA Junior Researcher Award (2017). Multiple COST grants for collaborative research in Germany. FFABR 2017 Grant for basic research funding. Teaching: Applied Mechanics (BS Industrial Engineering). Vehicle Mechanics (MS Mechanical Engineering). Fluid Dynamics (MS Aerospace Engineering). Doctoral course: Fundamentals of Adhesion. Collaborations: Imperial College London, IIT Italy, FZ-Jülich, SKF, Freudenberg, and others.

Tobin Driscollمشاهده پروفایل

استاد

• Numerical Analysis
• Data Science
• Mathematical Modeling
• +۳ مورد دیگر

Tobin Driscoll is the UNIDEL Professor of Mathematical Sciences and Director of the Master of Science in Data Science program at the University of Delaware's College of Arts & Sciences. His research focuses on numerical analysis, mathematical modeling, and computational methods with applications in biomedical engineering and data science. He holds a leadership role in interdisciplinary programs, including the Data Science Institute and the Mathematical Sciences department. His work bridges theoretical mathematics with practical applications, particularly in tear film dynamics and scientific computing. Driscoll's academic contributions include pioneering textbooks like Fundamentals of Numerical Computation and Exploring ODEs , which emphasize computational techniques. His research explores complex fluid dynamics, parameter estimation in biological systems, and advanced numerical methods. He collaborates with engineers and clinicians to model tear film breakup mechanisms and their clinical implications in dry eye disease. He advises the MS in Data Science program, fostering interdisciplinary education in data-driven problem-solving. His lab develops algorithms for image analysis and machine learning applications in biomedical contexts. Driscoll’s computational tools, such as the Schwarz-Christoffel Toolbox, are widely used in academic and industrial settings.

Guy K. Germanمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Soft Matter Mechanics
• Tissue Mechanics
• +۴ مورد دیگر

Guy K. German is an Associate Professor and Graduate Program Director in the Department of Biomedical Engineering at Binghamton University. His research focuses on the mechanics of biological soft matter, particularly in multiscale tissue dynamics, cosmetic physics, and colloidal encapsulation for biomedical applications. He previously held industrial roles as a Senior Engineering Consultant (Computational Fluid Dynamics) at I.D.E.A.S. Ltd. and an Aerodynamacist at Airbus U.K. Education: MPhys, University of Edinburgh MS, Cranfield University PhD, University of Edinburgh Research Interests: German’s lab explores the mechanics of heterogeneous tissues, skin disorders, and the effects of cosmetics. Using experimental and computational methods, his team investigates colloidal self-assembly for drug delivery and optical materials. Key areas include traction force microscopy, viscoplastic fluid dynamics, and interfacial phenomena. Awards: Best presentation award at Viscoplastic Fluids Conference (2009) C. N. Davies Scholarship (2006–2008) J. M. Lessells Postgraduate Scholarship (2006) Labs & Teams: Biological Soft Matter Mechanics Lab, focused on biomedical applications of soft matter science.

Shyam Sablaniمشاهده پروفایل

استاد

• Food Engineering
• Polymeric Packaging
• Food Safety
• +۷ مورد دیگر

Dr. Shyam Sablani is a Professor in the Department of Biological Systems Engineering at Washington State University (WSU), part of the College of Agricultural, Human, and Natural Resource Sciences (CAHNRS). He holds a Ph.D. in Food/Process Engineering from McGill University, an M.S. in Mechanical Engineering from the Indian Institute of Technology (Madras), and a B.E. in Mechanical Engineering from the National Institute of Technology, Raipur. His research focuses on food engineering, particularly polymeric packaging solutions, materials science applications in food safety, and advanced processing technologies. Key areas include microwave processing, UV-C light inactivation of pathogens, and biodegradable packaging materials. He has received numerous awards, including the Marcel Loncin Research Prize (2016) and the Distinguished Lecturer honor from the Institute of Food Technologists. Education: Ph.D., Food/Process Engineering, McGill University M.S., Mechanical Engineering, Indian Institute of Technology, Madras B.E., Mechanical Engineering, National Institute of Technology, Raipur Research interests emphasize innovative packaging to enhance food safety and quality, leveraging materials science and transport phenomena. His work addresses challenges in frozen food stability, microbial inactivation, and sustainable food processing. Key awards include the Marcel Loncin Prize, Distinguished Lecturer status, and multiple research fellowships. His grants include USDA-NIFA funding for packaging development and thermal processing studies. He has advised numerous graduate students and collaborates with industry partners like Kuraray America and Shields Bag & Printing. His lab focuses on advancing food packaging technologies and sustainable food systems.

Lei Chenمشاهده پروفایل

دانشیار

• Advanced Manufacturing
• Materials Design
• Additive Manufacturing
• +۴ مورد دیگر

Dr. Lei Chen is an Associate Professor in the Department of Mechanical Engineering at the University of Michigan-Dearborn, part of the College of Engineering and Computer Science. He specializes in advanced manufacturing and materials design, with a focus on additive manufacturing of metals and piezoelectric composites. His research interests include computational materials, energy systems, and mechanics. He has published over 70 papers in top journals like Nature and Advanced Materials , and received awards such as the ASEE Southeastern Section New Researcher Award (2018) and the ORAU Ralph E. Powe Junior Faculty Enhancement Award (2017). Education: Ph.D., National University of Singapore (2012); M.S. and B.S., Huazhong University of Science & Technology (2007 and 2005). Research Interests: Integrated Computational Materials Engineering (ICME), Sustainable Energy, Additive Manufacturing, Data-Driven Models. His work emphasizes battery technology, material microstructure analysis, and energy storage systems. Recent grants include projects funded by DARPA, the Army, General Motors, and the NSF, focusing on topics like predictive modeling for metallic endurance, battery recycling, and solid-state battery interfaces. His lab (DAIR) explores cutting-edge solutions for advanced manufacturing challenges.

Igor Zozoulenkoمشاهده پروفایل

استاد

• Condensed Matter Physics
• Organic Electronics
• Materials Science
• +۳ مورد دیگر

Prof. Igor Zozoulenko is a Professor and Head of Unit at the Department of Science and Technology (ITN) at Linköping University, leading the Theory and Modelling group within the Laboratory of Organic Electronics (LOE). He holds a Ph.D. in theoretical physics from the National Academy of Sciences of Ukraine and has extensive postdoctoral experience at institutions in Norway and Sweden. His research focuses on electronic and transport properties of low-dimensional semiconductors, conducting polymers, and wood-based materials, with applications in organic bioelectronics and photonics. He has pioneered studies on cellulose-based supercapacitors, such as the plant-based energy storage system in roses. Prof. Zozoulenko teaches undergraduate and Ph.D. courses at Linköping University, earning nominations for the prestigious Gyllene Moroten award in 2005 and 2028. He serves as vice-director of the Wallenberg Wood Science Center Academy, fostering industry-academia collaboration. His research spans theoretical modeling of organic electronics, redox electrochemistry in polymers, and multiscale simulations of electronic transport. Key research themes include the electronic structure of conducting polymers, ion diffusion in cellulose composites, and photonics in bio-inspired materials. He has secured Horizon 2020 funding for doctoral students exploring waste heat energy, perovskites, and computer graphics. His lab’s work has redefined understanding of PEDOT polymer behavior and pioneered transparent wood photonics.

David R. Riederمشاهده پروفایل

پژوهشگر

• Multiscale Modeling
• Multiphase Flows
• Porous Media
• +۴ مورد دیگر

David R. Rieder is a Postdoctoral Researcher at Eindhoven University of Technology (TU/e), affiliated with the Department of Mechanical Engineering and the 'Multiscale Operations in Porous Systems' (MOPS) research group. He holds a PhD in Chemical Engineering from TU/e (2024) and a Master’s in Chemical Technology from Karlsruhe Institute of Technology (2017). His research focuses on multiscale modeling of multiphase flows in porous media, particularly in energy and catalysis applications. He contributes to the UN Sustainable Development Goals, addressing renewable energy transitions and climate change mitigation. Academic Background: PhD (2024, TU/e), Master’s (2017, Karlsruhe), Researcher (2017–2019, Boreskov Institute of Catalysis). Current Role: Postdoc in Mechanical Engineering, working on digital porous media twins and high-fidelity models. Research Interests: Reactive multiphase flows in chemical reactors, heat storage, subsurface reservoirs, and multiscale drying processes. His work emphasizes balancing model complexity and reliability. Key Projects: Participates in the H2DeepNL project (2021–2026), focusing on digital rock modeling for energy storage in subsurface reservoirs. Publications: Over 12 peer-reviewed articles from 2020–2025, covering topics like trickle bed reactors, pore network modeling, and fluid interface dynamics. Recent work highlights innovative numerical methods and empirical analyses in porous media. Labs/Teams: Active in the MOPS group and collaborates internationally on porous media research. Engages in conferences and workshops, presenting findings on drying processes and multiphase flow dynamics.

Zhidong Zhangمشاهده پروفایل

مدرس

• Concrete durability
• Mass transport in porous materials
• Cement hydration
• +۱ مورد دیگر

Dr. Zhidong Zhang is a Lecturer at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering, specializing in concrete durability and mass transport phenomena. His research focuses on corrosion mechanisms, moisture retention in porous media, and sustainable low-carbon binders. Research Interests: Zhang's work bridges experimental materials science and practical civil engineering applications. Key areas include: Corrosion-induced cracking and diffusion potentials Advanced characterization of steel-concrete interfaces CO 2 curing techniques for sustainable construction Multiscale modeling of transport phenomena Recent publications demonstrate a strong focus on nano/micro-scale material characterization (2024-2025), with neutron imaging, FIB-SEM nanotomography, and lattice modeling being prominent methodologies. Works consistently address durability enhancement strategies for cementitious systems under varying environmental conditions. Awards: No scientific awards reported. Advising & Grants: Current projects include RILEM TC 309-MCP on recycled aggregates and several ETH-based initiatives on moisture transport. No specific advisees mentioned. Laboratories: Conducts research through ETH's Institute for Baustoffe (IfB) infrastructure, including specialized facilities for pore-scale analysis and accelerated durability testing.

Senyou Anمشاهده پروفایل

پژوهشگر

• Carbon Sequestration
• Fluid Dynamics
• Porous Media
• +۴ مورد دیگر

Senyou An is an Honorary Reader at CE - Academic & Research, specializing in multi-scale technologies for predicting CO₂ plume migration during carbon sequestration. His expertise spans computational and experimental fluid dynamics, including multiscale multiphase flow, reactive transport, and heat/mass transfer through porous materials. He actively contributes to UN Sustainable Development Goals addressing climate action and environmental protection. Education: PhD in 2021 from CE - Academic & Research, focusing on GPU-based pore-scale modeling of two-phase flow and transport in porous media, supervised by Prof. Theodoropoulos and Prof. Joekar-Niasar. Research interests emphasize carbon neutrality strategies, pore-scale analysis, and the integration of deep learning with physics-based models. His work frequently explores porous media heterogeneity, carbonate rock dynamics, and computational methods like the boundary integral approach. Recent publications highlight advancements in three-dimensional foam modeling and upscaling reaction rates in subsurface environments. He collaborates internationally to investigate multiphase flow and wettability effects in porous systems. Advising & Grants: While no current advisees are listed, he is accepting PhD students. His research has been disseminated through datasets such as Mendeley Data (DOI: 10.17632/k9s7ht88mp.1) , which examines pore geometry and wettability interactions in immiscible displacement dynamics. Labs/Teams: Engaged in interdisciplinary teams combining computational physics with environmental engineering, particularly in digital porous media analysis and subsurface flow modeling.

• Nanomechanics
• Nanomaterials
• Low-Dimensional Materials
• +۵ مورد دیگر

Travis Hu is an Associate Professor of Mechanical Engineering at California State University, Los Angeles (Cal State LA), affiliated with the College of Engineering, Computer Science, and Technology. His research focuses on bio-inspired nanomaterials, multifunctional energy materials, and multiscale modeling. He leads the Bio-Nano Materials and Interfaces Lab, investigating bio-inspired smart materials for applications in energy, biomedical, and environmental fields. Dr. Hu's academic background includes postdoctoral research at Case Western Reserve University, University of Florida, and University of Delaware, followed by roles as a Teaching Assistant Professor at the University of Denver. His teaching spans mechanics, materials science, and nanotechnology. His research emphasizes bio-inspired design principles from organisms to create advanced materials with adaptive properties like self-cleaning surfaces, smart adhesives, and energy-efficient coatings. Recent work includes neuromorphic computing memristors, energy harvesting nanogenerators, and self-healing hydrogels. Key grants include NSF CREST and PREM Centers supporting interdisciplinary research initiatives. He collaborates widely, publishing extensively in journals like Science China Materials and Advanced Functional Materials. Dr. Hu is committed to diversity in STEM education, highlighted in a 2023 JOM article showcasing Cal State LA's DEI outcomes. His lab actively recruits students from diverse backgrounds for research in nanomaterials and bio-inspired engineering.

• Scientific Computing
• Numerical Methods for Partial Differential Equations
• Galerkin Methods
• +۳ مورد دیگر

Frank Giraldo is a Distinguished Professor of Applied Mathematics at the Naval Postgraduate School (NPS) and an Adjunct Professor of Applied Mathematics at the University of California, Santa Cruz. He leads the Scientific Computing group at NPS, focusing on numerical methods for partial differential equations (PDEs), particularly in atmospheric and oceanic systems. His research emphasizes discontinuous and continuous Galerkin methods, high-performance computing (HPC), and large-eddy simulations (LES) for modeling geophysical flows. Education: PhD in Applied Mathematics from the University of Virginia (1994), BSE from Princeton University (1987). Research Interests: Nonhydrostatic atmospheric modeling (NUMA), ocean modeling (NUMO), LES of hurricanes and fluid dynamics, scalable algorithms for supercomputers (e.g., GPU acceleration), and implicit-explicit time-integration methods. His work integrates HPC with climate science and has been applied to the U.S. Navy's NEPTUNE system. Awards: Menneken Award (2025), NPS Distinguished Professor (2020), Carl E. Menneken Award (2007), Alan Berman Research Prize (2001). Leadership: Chair of NPS Applied Mathematics Department (2021–2025), member of the U.S. Interagency Council for Advancing Meteorological Services (ICAMS), and scientific advisor to international programs like the German Research Foundation's Geophysical Fluid Dynamics initiative. Labs/Teams: Principal developer of the NUMA atmospheric model and NUMO ocean model. Collaborates with institutions like NJIT, Hampton University, and Lawrence Livermore National Lab on projects funded by ONR, DARPA, and NSF.