Carmine Putignano is an Associate Professor at the Politecnico di Bari , affiliated with the Department of Mechanics, Mathematics & Management . His research focuses on contact mechanics, tribology, and viscoelasticity, with applications in polymer bearings, hydrogels, and surface engineering. Recent work includes advancements in viscoelastic contact modeling, lubrication of soft materials, and laser-induced surface texturing. These studies address challenges in friction reduction, material durability, and biomedical applications like articular cartilage lubrication. His 15 most recent publications (2023–2025) span topics such as viscohydrodynamic lubrication, micro-indentation techniques, and multi-laboratory benchmarks for surface topography characterization. The research emphasizes numerical simulations, experimental validation, and energy-based methodologies.
Jessica Davis serves as a Research Assistant Professor in the Department of Public Health and Health Sciences at Northeastern University's Bouvé College of Health Sciences and is an active member of the MOBS Lab within the Network Science Institute. Her interdisciplinary work integrates network science methodologies with epidemic modeling to develop practical tools for public health policy and pandemic preparedness, with significant contributions during the COVID-19 pandemic. Dr. Davis earned her PhD in Network Science from Northeastern University, where her dissertation research examined cryptic transmission patterns and the efficacy of travel restrictions during the initial phases of the COVID-19 outbreak. This foundational work established her expertise in bridging theoretical network analysis with real-world public health applications. Her research program centers on two interconnected domains: Biological and Health Systems , which investigates biological interdependencies through network medicine, systems epidemiology, and public health infrastructure; and Complex Systems Forecasting , which develops network-based computational models for predicting epidemic trajectories and supporting evidence-based decision-making. These areas converge in her development of open-source tools like Epydemix and innovative surveillance frameworks using aircraft wastewater networks. Analysis of her 15 most recent publications (2021-2025) reveals consistent methodological evolution toward real-time modeling with explicit uncertainty quantification, increasing focus on multi-scale heterogeneity in disease transmission, and growing emphasis on practical implementation of forecasting systems. Her work demonstrates strong continuity in applying network science to epidemic dynamics while expanding into influenza surveillance, variant tracking, and vaccine impact assessment. No scientific awards or major honors are documented in the available materials, though her research has generated significant policy impact through presentations at venues like the Rhodes Policy Summit and collaborations with governmental agencies. Dr. Davis has secured substantial research funding including a Gates Foundation partnership investigating equitable global vaccine distribution strategies. While specific advisee relationships aren't publicly listed, she actively contributes to academic training through the MOBS Lab's hiring of computational statistics researchers and participation in the Network Science Student Research Symposium. The MOBS Lab, directed by Alessandro Vespignani and jointly affiliated with Physics, Health Sciences, and Computer Sciences departments, operates as a hub for computational epidemiology with physical locations in Boston, London, and Portland. Current lab initiatives focus on developing mathematical models for complex network systems with immediate applications to pandemic response, including the aircraft-based wastewater surveillance network featured in her 2025 Nature Medicine publication.
Laurent Delannay is a Professor at the Catholic University of Louvain and a Research Director at the Institute of Mechanics, Materials and Civil Engineering (iMMC) within the Louvain Polytechnic School (EPL) . His work focuses on materials science and mechanical engineering , particularly in microstructural modeling , strain heterogeneity , and plasticity . Key research areas: Plasticity, Finite Element Modeling, Microstructure Analysis, Residual Stress, Crystal Plasticity Recent publications analyze aluminum films, tungsten deformation, and biomedical materials Affiliated with the Applied Mechanics and Mathematics (MEMA) research unit Email: laurent.delannay@uclouvain.be His work combines experimental data with computational simulations to understand material behavior under stress, thermal shocks, and mechanical processing. Research trends include grain boundary effects , texture evolution , and multiscale modeling . Teaching activities include courses on Mechanics of Materials , General Mechanics , and Durability of Materials . He leads research in the MEMA laboratory and contributes to projects related to nuclear materials and biomedical applications.
Dr. Philip Marmet is a Researcher and Lecturer at the Institute of Computational Physics (ICP) within the School of Engineering at Zurich University of Applied Sciences (ZHAW). His work focuses on Multiphysics and Multiscale simulations, characterization and stochastic modeling of microstructures, with particular expertise in solid oxide fuel cell electrode design. His educational background includes a PhD in Physics/Modeling and Simulation from the University of Fribourg (2019-2023), an MSc in Physics/Soft Matter Theory from the same institution (2013-2016), and an MSc in Engineering from Bern University of Applied Sciences (2011-2013). PhD in Physics / Modeling and Simulation, Solid Oxide Fuel Cells, University of Fribourg (2019-2023) MSc in Physics / Soft Matter Theory, University of Fribourg (2013-2016) MSc in Engineering BFH / Industrial Technologies, Bern University of Applied Sciences (2011-2013) BSc in Mechanical Engineering / Mechatronics, Bern University of Applied Sciences (2003-2007) Dr. Marmet's research spans Multiphysics Simulation, Multiscale Modeling, Microstructure Characterization, and Digital Materials Design. His work bridges theoretical modeling with experimental validation to optimize materials for energy applications. He has developed specialized methodologies for virtual microstructure variation and optimization of porous materials, particularly for solid oxide fuel cells and aerosol filters. His publication record shows a clear progression toward increasingly sophisticated multiscale modeling approaches, with recent work focusing on stochastic microstructure modeling using pluri-Gaussian methods. His research demonstrates strong integration of computational techniques (including GeoDict, Comsol Multiphysics, ANSYS, OpenFOAM, and Matlab/Simulink) with experimental validation. Best graduation results of 2013 "Gold", Master of Science in Engineering Dr. Marmet supervises student projects and lectures Analysis 1 and 2 for bachelor courses. His research has received funding from the Swiss Federal Office of Energy (SFOE) and Eurostars program. He has developed practical software tools including the Python app for stochastic microstructure modeling of SOC electrodes and the Characterization-app for standardized microstructure analysis, demonstrating his commitment to translating research into practical engineering solutions. His work is organized around the Digital Materials Design workflow, connecting virtual microstructure generation, automated characterization, and multiphysics simulation to enable data-driven optimization of energy materials without extensive experimental iteration.
Bhabani Shankar Mallik is a Professor in the Department of Chemistry at the Indian Institute of Technology Hyderabad . His research focuses on Computational Chemistry , Molecular Dynamics , and First Principle Calculations for energy materials and catalysis. He leads the BSM Lab , which utilizes High-Performance Computing (HPC) resources like ParamSeva@IITH (838 TFLOPS, 7500 cores). Research Areas : Structure/Dynamics of Ionic Liquids, Catalysis (Homogeneous/Heterogeneous), Energy Materials, Microkinetic Theory, Machine Learning in Chemistry, Vibrational Spectroscopy His recent publications analyze ionic transport mechanisms in solid-state electrolytes, electrocatalytic processes for nitrogen reduction, and proton transfer dynamics in aqueous systems. He teaches courses like Modern Simulation Methods and Principles of Quantum Chemistry .
Dr. Ushasi Roy is an Assistant Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur. She specializes in solid mechanics, fracture mechanics, plasticity, finite element analysis, and microstructure-property correlation. Her research focuses on microstructure sensitive deformation and fracture of metals and alloys, high strain rate deformation behavior of metals, ceramics and composites, and multiscale and multiphysics modeling of deformation and fracture. Dr. Roy's research interests span computational mechanics and materials science, with particular emphasis on understanding how microstructural features influence mechanical properties and failure mechanisms. Her work combines advanced computational techniques with fundamental mechanics principles to develop predictive models that can guide material design and engineering applications. She has made significant contributions to understanding fracture mechanics in various materials systems including high entropy alloys, battery materials, and energetic materials. Her publication record shows consistent contributions to high-impact journals in mechanics and materials science, with recent work focusing on lithium anodes, polycrystalline metals, and multiscale computational frameworks. The research demonstrates a progression from fundamental material characterization to sophisticated computational modeling approaches. Dr. Roy has established herself as a promising researcher in computational mechanics and materials science, with her work addressing critical challenges in understanding material behavior under extreme conditions and developing predictive models for engineering applications.
Dr. Fei Fang is an Assistant Professor at the Icahn School of Medicine at Mount Sinai, holding dual appointments in the Department of Orthopedics and the Department of Cell, Developmental & Regenerative Biology. BA in Mechanical Engineering, Huaqiao University MS in Mechatronic Engineering, Zhejiang University MS and PhD in Mechanical Engineering, Washington University in St. Louis Her research focuses on musculoskeletal mechanobiology and cell niche interactions, particularly tendon biology and regenerative medicine. Key areas include: Tendon mechanobiology and developmental biology Tissue engineering for musculoskeletal regeneration Stem cell applications in tendon repair Biomechanical analysis of tendon structures Enthesis healing and Hedgehog signaling pathways Single-cell analysis of immune-mesenchymal interactions Dr. Fang's recent publications emphasize multiscale mechanical evaluation of tendons, Hedgehog signaling mechanisms, and translational approaches for tendon-to-bone healing. Her work combines biomechanical engineering with regenerative medicine to address musculoskeletal disorders. She leads the Fang Laboratory for Musculoskeletal Mechanobiology and Cell Niche at Mount Sinai, located in the Annenberg Building (20th Floor, Room 20-72A), advancing novel therapies for tendon, ligament and meniscus regeneration through mechanobiological insights.
Ankit Srivastava is an Associate Professor in the Department of Materials Science and Engineering at Texas A&M University and serves as the Director of Graduate Programs for his department. He holds a Ph.D. in Materials Science and Engineering from the University of North Texas, with additional Master's degrees in Physics and Materials Science. Ph.D., Materials Science and Engineering, University of North Texas (2013) M.S., Physics, University of North Texas (2013) M.S., Materials Science and Engineering, University of North Texas (2011) B.Tech, Mechanical Engineering, Kamla Nehru Institute of Technology, India (2007) His research focuses on Micromechanical Modeling of Heterogeneous Materials , Crystal Plasticity Finite Element Modeling , and Damage Mechanics . He investigates deformation and fracture mechanisms in materials with spatial-temporal heterogeneities, emphasizing statistical perspectives in microstructural analysis. Recent publications highlight his work on machine learning applications in fracture surface analysis, non-classical crystallographic slip in MAX phases, and multi-objective alloy discovery using Bayesian methods. His research spans computational modeling, experimental mechanics, and materials informatics. 2023 Texas A&M Dean of Engineering Excellence Award 2022 ASME Sia Nemat-Nasser Early Career Award 2020 NSF CAREER Award recipient 2017 ASME Haythornthwaite Foundation Research Initiation Award As head of the M3D (Microstructural Mechanics for Material Design) group, he leads projects combining computational and experimental approaches to link microstructure statistics with material failure modes.
Yuto Otoguro is an Associate Professor (non-tenure-track) at Waseda University's Faculty of Science and Engineering, Department of Modern Mechanical Engineering, and also serves as a Researcher at the Institute for Frontier Fluid-Structure Interaction Analysis. He earned his PhD, M.Eng, and B.Eng in Modern Mechanical Engineering from Waseda University in 2018, 2016, and 2014 respectively. His academic career focuses on advanced computational methods for fluid dynamics and structural mechanics. Dr. Otoguro's primary research interests lie in Fluid Engineering, Computational Fluid Dynamics (CFD), and Isogeometric Analysis (IGA). His work centers on developing and applying space-time computational methods with isogeometric discretization for complex flow problems. He has made significant contributions to element length calculation in B-spline and T-spline meshes, stabilization parameters for variational multiscale methods, and general-purpose NURBS mesh generation techniques for complex geometries. His research has important applications in turbomachinery, wind turbine analysis, fluid-structure interaction, and computational aerodynamics. His publication record shows a strong focus on computational methods development, with particular emphasis on isogeometric analysis applications. His work on local-length-scale calculation in complex geometries, hyperelastic shell models, and space-time computational flow analysis represents cutting-edge research in computational mechanics. His papers frequently address challenges in representing complex geometries and handling moving boundaries in fluid flow simulations. Among his scientific achievements, Dr. Otoguro received the JSCES 20th Anniversary Scholarship Award. He has been actively involved in research projects including 'On new developments of Isogeometric Analysis (IGA) for highly accurate and efficient fracture mechanics analysis' funded by the Japan Society for the Promotion of Science, and 'Compressible-flow engine-valve analysis with response motion and contact' as part of the Early-Career Scientists program. As an educator, Dr. Otoguro teaches multiple courses at Waseda University including Fluid Dynamics, Engineering Thermodynamics, Material Mechanics, and Mechanical Engineering Laboratory courses. He has also organized workshops on isogeometric analysis to promote this emerging computational method within Japan's research community. His academic service includes participation in the Team for Advanced Flow Simulation and Modeling (T*AFSM), where he contributes to advancing computational methods for fluid-structure interaction problems.
Siddiqui Gohar Ali is a Researcher at the Technische Universität München (Technical University of Munich), affiliated with the TUM School of Computation, Information and Technology and the Associate Professorship of Simulation of Nanosystems for Energy Conversion led by Prof. Alessio Gagliardi. His work focuses on computational methods, machine learning, and energy conversion systems. Research Areas : Machine Learning, Multiscale Modelling, Energy Conversion, Electrocatalysis, Organic Solar Cells, Catalyst Modeling Teaching : Collaborates in lectures and seminars on computational nanoelectronics and quantum engineering Recent research highlights include applying machine learning to enhance metadynamics for drug interaction studies and optimizing configuration space sampling techniques. He is actively involved in projects under the DFG e-Conversion Cluster and EU-funded initiatives.
Dr. Emine Sümeyra Turalı-Emre is an Assistant Professor at the Institute of Biomedical Engineering, Bogazici University, where she joined in 2024. She combines expertise in nanotechnology, biomedical engineering, and data science to solve critical healthcare challenges. Previously, she was a Postdoctoral Research Fellow in Chemical Engineering at the University of Michigan (2021-2024) and completed her PhD in Biomedical Engineering from the same institution in 2021. Her educational background includes: PhD in Biomedical Engineering, University of Michigan, 2021 MSc in Biomedical Engineering, University of Michigan, 2015 BSc in Molecular Biology and Genetics, Istanbul University, 2008 Dr. Turalı-Emre's research focuses on engineering inorganic nanoparticles for applications such as drug and gene delivery, antibacterial and anticancer treatments, bone regeneration, and extracellular vesicle capturing for diagnostics. Her work spans chiral nanoparticles, antibacterial nanoparticles, extracellular vesicle capturing, AI-driven nanoparticle-protein interactions, drug and gene delivery systems, cancer therapies, and translational nanotechnology. She approaches biomedical challenges through multidisciplinary collaborations that bridge engineering, life sciences, and computer science. Her recent publications in leading journals like Advanced Materials, Matter, and PNAS demonstrate strong trends in chiral nanomaterials for diagnostics and therapeutics, antibacterial applications against biofilms and antibiotic-resistant bacteria, and the integration of artificial intelligence with nanotechnology. Her work shows a clear progression from fundamental nanoparticle synthesis to translational applications in healthcare. Scientific awards and recognitions include: BioInterfaces Research Community Innovator Award, 2024 Full Member, Sigma Xi, The Scientific Research Honor Society, 2024 Women in Science and Engineering, Cinda Sue Davis STEM Equity Leadership Award (Nominee), 2024 Women in Science and Engineering, Willie Hobbs Moore Achievement Award (Nominee), 2024 Selected Participant, AI in Science & Engineering Summer Academy, 2023 And several other prestigious awards and recognitions Dr. Turalı-Emre is actively involved in mentoring students and fostering interdisciplinary collaboration. She currently leads a TÜBİTAK-BİLGEM project developing an AI-driven database to optimize antibacterial nanoparticles for diagnostics and treatments, in collaboration with Dr. Betül Özateş from the Institute of Data Science and Artificial Intelligence. She has also contributed to Coulter Translational Research Partnership projects focused on extracellular vesicle capture, optimizing RNA isolation from biofilms, and developing antibacterial surfaces using chiral nanoparticles. Her laboratory provides a vibrant environment for undergraduate, graduate, and non-traditional students from various fields, including engineering, life sciences, and computer science, to conduct impactful research and contribute to transformative innovations in healthcare.
Professor Venkat Ganesan holds the Les and Sherri Stuewer Chair in Chemical Engineering at The University of Texas at Austin, where he conducts theoretical and computational research on advanced materials. He serves as a Co-Investigator for both GAP B (focusing on hydration in ion transport and separations) and GAP C (focusing on robust membrane manufacturing). His educational background includes a B. Tech. in Chemical Engineering from the Indian Institute of Technology, Madras (1995), followed by both M.S. and Ph.D. degrees in Chemical Engineering from MIT (1999), and postdoctoral training at the University of California, Santa Barbara (1999-2001). Professor Ganesan's research centers on the theoretical foundations of self-assembled advanced materials, employing a multiscale approach that bridges molecular details with macroscopic properties. His work spans polymer physics, complex fluids, and biological systems with applications in water purification, energy storage, and biophysics. Through his Ganesan Polymer Physics Group, he utilizes molecular simulations to address challenges in membrane science and ion transport. His publication record reveals a strong focus on polymer dynamics, interfacial phenomena, and theoretical modeling of complex materials. Over time, his research has evolved from fundamental polymer physics toward applications in membrane technology and water purification systems, reflecting increasing emphasis on practical solutions to global challenges. John H. Dillon Medal, American Physical Society (2009) Alfred P. Sloan Foundation Fellow (2004-2006) NSF Career Award (2004-2009) Professor Ganesan maintains an active research group with numerous graduate students and postdoctoral researchers. His students have pursued diverse career paths including academic postdoctoral positions, industry research roles at companies like Tokyo Electron, and consulting positions. He collaborates extensively with experimental groups at UT Austin and institutions worldwide including UCSB, Berkeley, MIT, Rice University, and international partners in France, Germany, and India. His laboratory focuses on molecular simulations for water purification membranes, ion separations, and polymer electrolytes, with strong connections to the MWET center and industrial applications.
Dr. Arun Nair serves as an Associate Professor of Aerospace Engineering at the Air Force Institute of Technology (AFIT), contributing to graduate education and research in advanced aerospace systems. His academic foundation includes: Ph.D. in Engineering Science and Mechanics from Virginia Tech Postdoctoral training at the Massachusetts Institute of Technology (MIT) His research program centers on multiscale computational modeling of materials and wave mechanics , employing advanced simulation techniques to analyze material behavior across atomic to macroscopic scales and wave propagation phenomena in complex media. This work bridges computational science, solid mechanics, and aerospace engineering with applications in next-generation material design. No scientific awards were documented in the available source material. Information regarding graduate student mentorship and research funding sources was not provided in the profile. Details about research laboratories or collaborative teams were not included in the extracted content.
Wiyao Azoti is a Lecturer at the National Institute of Applied Sciences of Toulouse (INSA Toulouse), where he is a member of the Composite Materials and Structures group (MSC). His work focuses on the mechanics of composite materials and structures, with particular expertise in multi-scale modeling and micromechanics. Dr. Azoti's educational background includes: PhD in Materials Science from University of Lorraine, France (2012) MSc in Mechanical Engineering from University of Lorraine, France (2009) Engineering degree in Mechanical Engineering from ENSI, Togo (2008) His research interests center on the mechanics of materials, with emphasis on linear, nonlinear, and computational aspects; rate-independent and rate-dependent plasticity; micromechanics and mean-fields homogenization techniques; multi-scale modeling of composite materials; damage and fracture behaviors of composite materials; and multiphysics coupling of thermomechanical fields. His work bridges fundamental mechanics with practical applications in automotive, aerospace, and biomedical fields. Dr. Azoti has published extensively in the field of composite materials, with over 50 scientific contributions. His recent work shows a strong trend toward the application of multi-scale modeling techniques to graphene-reinforced composites, biocomposites, and advanced materials for automotive and aerospace applications. He has made significant contributions to understanding the electromechanical behavior of polymer composites, thermomechanical properties of natural fiber composites, and the crashworthiness of hierarchical composite structures. Professional memberships include: African Society of Eco-Materials (ECOMAT-AFRICA) American Society of Mechanical Engineers (ASME) European Mechanics Society (EUROMECH) Dr. Azoti teaches several courses at INSA Toulouse, including Design of Mechanical Systems, Materials Science and Heat Treatment, Automation of Mechanical Systems, Machine Elements and Eco-design, Eco-design and Innovation, and Composite Materials' Projects. His teaching reflects his research expertise, emphasizing sustainable materials and advanced composite technologies.
Dr. Olga Guskova serves as a Junior Group Leader at the Leibniz Institute of Polymer Research Dresden (IPF), where she directs her own independent research group focused on advanced polymer materials and computational modeling. Her research program centers on material properties of semi-conducting polymers and multiscale modeling for organic electronics applications. Key research interests include: Computer simulation techniques (full atomistic, mesoscale and multiscale) of polymer systems Structure and dynamics of polymeric solutions, melts and composites Self-organization phenomena in complex polymer systems Organic/inorganic interfaces and hybrid materials Properties of polyelectrolytes, polyampholytes, and biomimetic hybrids Dr. Guskova's work bridges computational approaches with experimental characterization to advance understanding of polymer behavior at multiple scales. Her research has significant implications for developing next-generation organic electronic materials and devices. As a Junior Group Leader, she maintains an independent research trajectory within the IPF framework while collaborating across the institute's various departments and research divisions.
