Prof. Eleni Chatzi is a Full Professor and Chair of Structural Mechanics at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. She holds a PhD from Columbia University (2010) and has held roles from Assistant to Full Professor at ETH since 2010. Her research focuses on intelligent structural monitoring and data-driven asset management, emphasizing nonlinear dynamics and sensor integration. Affiliations : Institute of Structural Engineering, European Academy of Wind Energy (EAWE President), Swiss Community for Computational Methods (SWICCOMAS Chair) Research interests include Structural Health Monitoring (SHM), system identification, and advanced simulation tools. She pioneered work on data-driven diagnostics and self-aware infrastructure, supported by grants like the ERC Starting Grant (2015). Awards include the 2020 Walter L. Huber Prize and 2024 SHM Person of the Year Award. Her work spans wind energy infrastructure, metamaterials for vibration control, and AI-driven structural analytics. Over 600 publications and 200k+ citations highlight her impact. She teaches computational science and structural dynamics in ETH's programs and collaborates globally on sustainable infrastructure projects.
Tracey Galloway is an Associate Professor in the Department of Anthropology at the University of Toronto Mississauga (UTM), where she conducts critical research on Indigenous health disparities and policy interventions in northern Canada. Her work bridges medical anthropology, public health, and community-based participatory research to address systemic inequities affecting circumpolar populations. Education: PhD, McMaster University, 2008 MA (institution unspecified) BA (institution unspecified) BScN (institution unspecified) Dr. Galloway's research program centers on chronic disease risk assessment and health system improvement in Indigenous communities, with specific expertise in nutrition transition, food security, child growth patterns, and public health policy evaluation. She examines the impact of federal programs like Nutrition North Canada while developing community-led solutions for health equity. Her methodological approach combines quantitative analysis of health outcomes with qualitative community engagement, emphasizing Indigenous research sovereignty and decolonizing methodologies. Her publication record reveals consistent thematic focus across 15 recent articles, demonstrating interdisciplinary collaboration between anthropology, epidemiology, and health economics. Key trends include rigorous evaluation of colonial impacts on Indigenous food systems, innovative analysis of subsidy program effectiveness, and centering Indigenous patient experiences in healthcare design. Her work consistently prioritizes community-defined research questions and actionable policy recommendations. Dr. Galloway actively mentors graduate students including Darci Belmore, Carly Checholik, Neda Maki, and Hiliary Monteith, guiding research on Indigenous health determinants and policy interventions. While specific grant details aren't publicly enumerated, her collaborative projects involve partnerships with Indigenous communities across Northern Canada and interdisciplinary teams addressing complex health system challenges. She maintains strong community partnerships for her applied research, particularly in Nunavut and Northwestern Ontario, working directly with Anishinabeck and Inuit communities to translate findings into culturally safe health initiatives and policy reforms that address the root causes of health inequities.
Dr Bahareh Zaghari (MSc, PhD, CEng, FHEA) is a Lecturer in the Electrical Power Engineering group at the University of Southampton's School of Electronics and Computer Science. Her research focuses on electrified aircraft systems, sensors with machine learning applications, electrical power systems, and nonlinear dynamics modeling. Current projects include acoustic sensing for temperature/flow measurement Co-design of electrical machines for aircraft electrification Research activities span hybrid-electric aircraft design (FutPrint50 Horizon project), fully electric aircraft development (EnabEl Innovate UK), and smart sensing systems for aerospace components. Industrial collaborations include KISTLER, iNetic, PALL Aerospace, Safran, ARUP, Embraer, and BAE Systems. Conference coordinator for IEEE Transportation Electrification Council's Electrified Aircraft committee Chair of IEEE/AIAA Electrified Aircraft Technology Symposium (2023) Panel moderator at AIAA Propulsion and Energy (2021) Her work demonstrates innovative applications of acoustic transducers in harsh environments, with contributions to temperature mapping, fault analysis, and energy harvesting systems. She currently supervises PhD student Shikhar Singh.
Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.
Aditi Das is a Full Professor in the School of Chemistry and Biochemistry at the Georgia Institute of Technology, College of Sciences. She leads the Das Laboratory, which focuses on the biochemistry and chemical biology of lipids, particularly studying cytochrome P450 enzymes and their role in lipid metabolism, endocannabinoid systems, and inflammatory pathways. Her educational background includes: B.Sc. in Chemistry from St. Stephen's College M.Sc. in Chemistry from Indian Institute of Technology, Kanpur (I.I.T) Ph.D. in Chemistry from Princeton University Postdoctoral research at Northwestern University (NSF-NSEC fellow) and Beckman Institute for Advanced Science and Technology, University of Illinois UC Professor Das's research interests center around understanding the physiological role of lipids in sustaining homeostasis and their implications in disease states such as neurodegenerative disorders, cancer, and cardiovascular diseases. Her laboratory specializes in: Enzymology of cytochrome P450s, particularly CYP2J2 epoxygenase Metabolism of ω-3 and ω-6 fatty acids and their derivatives Minor cannabinoid metabolism by cytochrome P450 enzymes Discovery of novel anti-inflammatory lipid metabolites and endocannabinoids Mechanistic studies of membrane proteins using nanodisc technology Her work bridges biochemistry, chemical biology, and pharmacology to uncover novel therapeutic targets related to lipid signaling pathways. Analysis of Professor Das's recent publications (2023-2025) reveals a strong focus on cannabinoid metabolism by cytochrome P450 enzymes, with particular emphasis on how these metabolic processes generate bioactive compounds that interact with the endocannabinoid system. Her research increasingly explores the therapeutic potential of omega-3 derived endocannabinoid epoxides in inflammatory and neurodegenerative conditions. The use of nanodisc technology for studying membrane proteins in near-native environments remains a consistent methodological thread throughout her work, enabling detailed mechanistic insights into enzyme function. Professor Das has received numerous prestigious awards recognizing her research excellence and teaching: 2024 NIH Outstanding Researcher Award (MIRA R35) for established investigators 2024 Vasser Woolley Faculty Fellowship 2023 Plenary Lecture at the International Society of the Study of Xenobiotics (ISSX) 2021 E.L.R. Stokstad Award 2019-2021 List of Teachers Ranked as Excellent 2019 Eicosanoid Research Foundation Young Investigator Award 2019 Zoetis Research Excellence Award 2019 Mary Swartz Rose Young Investigator Award 2015 National Scientist Development Award from the American Heart Association 2022 El Sohly Award from the American Chemical Society Professor Das actively mentors a diverse group of students and postdoctoral researchers, with several former lab members now holding faculty positions or working at prestigious institutions. Her laboratory has secured significant funding from NIH, NSF, and other sources to support research on lipid metabolism, cannabinoid pharmacology, and membrane protein biochemistry. Notable grants include an NIH R35 Outstanding Investigator Award (MIRA), an NIH R21 grant from NIDA, and multiple collaborative grants with other research groups. The Das Laboratory operates within the Petit Institute of Bioengineering and Biosciences (IBB) at Georgia Tech, utilizing state-of-the-art facilities for biochemical and biophysical studies. The lab specializes in nanodisc technology to study membrane proteins in near-native environments, with particular expertise in cytochrome P450 enzymes and their interactions with lipid substrates. Recent work has expanded into collaborative projects involving lipidomics, structural biology, and translational applications of lipid signaling research.
Jon Miller is a Research Associate Professor in the Department of Civil, Environmental and Ocean Engineering at Stevens Institute of Technology. He holds dual roles as Director of the NJ Coastal Protection Technical Assistance Service and NJ Sea Grant Coastal Processes Specialist. Miller earned a B.E. in Civil Engineering from Stevens (1999), followed by M.S. and Ph.D. in Coastal Engineering from the University of Florida (2001, 2004). His research focuses on coastal hazard mitigation, nature-based solutions, and numerical modeling of coastal systems. Education: - Ph.D. Coastal Engineering, University of Florida (2004) - M.S. Coastal Engineering, University of Florida (2001) - B.E. Civil Engineering, Stevens Institute of Technology (1999) Research Interests: Miller's work emphasizes coastal resilience through innovative engineering approaches. Key areas include: - Wave attenuation mechanisms of natural/nature-based features - Climate change impacts on coastal erosion - Living shoreline design and implementation - Sediment management strategies for inlets and beaches - Dune system vulnerability analysis Grants & Awards: - $1M+ funding from NOAA, NSF, and state agencies - 2024 ASCE Educator of the Year Award - 2023 Robert G. Dean Coastal Award - Over 20+ technical reports guiding coastal policy Professional Leadership: - Editorial roles in Shore & Beach and Journal of Coastal Research - Leadership in NJ Coastal Resilience Collaborative - Advisor for 3 Technogenesis Summer Scholars Labs & Projects: - Principal Investigator for SEECPRS disaster response system - Co-developed NJ Living Shorelines Engineering Guidelines - Conducts fieldwork on Hudson River shoreline restoration
Brian S Woodard serves as a Teaching Associate in the Department of Aerospace Engineering at the University of Illinois Urbana-Champaign, teaching undergraduate courses including AE 100 (Intro to Aerospace Engineering), AE 140 (CAD), and ENG 100/101 (Engineering Orientation). Education Doctor of Philosophy, Aerospace Engineering, University of Illinois Urbana-Champaign, 2012 Master of Science, Aerospace Engineering, University of Illinois Urbana-Champaign, 2004 Bachelor of Science, Aerospace Engineering, University of Illinois Urbana-Champaign, 2001 Research Interests His research focuses on High-Energy Lasers , Aerodynamics , and Aircraft Icing , with specialized work in electric discharge-pumped atomic iodine and oxygen-iodine laser systems. He investigates plasma discharge geometries for oxygen singlet delta production and their application in high-power laser development, while also studying aerodynamic effects of aircraft icing for flight safety. Publication Trends Publications from 2008-2011 reveal concentrated expertise in laser physics and plasma engineering, particularly in electric discharge pumping mechanisms for iodine-based laser systems. His work demonstrates consistent innovation in resonator design and discharge configuration to enhance laser efficiency, bridging aerospace engineering principles with advanced optical technologies for potential defense and propulsion applications. Scientific Awards No scientific awards were mentioned in the provided text. Advising and Grants Dr. Woodard mentors students through AE 298 RES (Research Seminar Mentoring and Introduction to Research courses), guiding undergraduate research projects. He has instructed over 20 distinct undergraduate courses spanning aerospace fundamentals, computational design, global engineering experiences, and leadership training, though no research grants are documented in the source material. Labs and Teams His research is conducted within Talbot Laboratory (Room 319K) at the University of Illinois, collaborating with prominent researchers including J.W. Zimmerman, G.F. Benavides, and W.C. Solomon on electric oxygen-iodine laser projects.
Dr Dongbin Wei is an Associate Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney (UTS), with a career spanning academia and industry. He holds a PhD in Materials Processing Engineering from the University of Science and Technology Beijing (2001) and academic appointments from 2005–2012 at the University of Wollongong (Research Fellow to Lecturer) and 2013–2017 at UTS (Senior Lecturer) before his promotion to Associate Professor in 2018. His research lies at the intersection of Mechanical Engineering , Manufacturing Engineering , and Materials Processing , focusing on: Ultrasonic Additive Manufacturing (UAM) Micro Metal Forming and Size Effects Tribology and Lubrication Numerical Simulations of Material Processing Composite Material Fabrication Key contributions include: Development of the Springback Path–Displacement Adjustment (SP-DA) method for stamping accuracy Advancements in femtosecond laser texturing for silicon wettability control Studies on nanolubrication in hot rolling Optimization of micro-deep drawing parameters He has secured competitive grants from the Australian Research Council (ARC) and industry partners like Weir Minerals Australia Ltd , including projects on: Revolutionizing mineral separation via additive manufacturing Super high-speed grinding technologies Mechanics of micro composite drill fabrication As a lead supervisor, he guided the 2022 thesis 'Creation and Validation of 3D Printable Mineral Separation Spiral' . His work bridges theoretical analysis, computational modeling (FEM/FEA), and practical validation in advanced manufacturing systems.
Adam de la Zerda is an Associate Professor at Stanford University's Department of Structural Biology (School of Medicine) and Electrical Engineering (by courtesy). He develops advanced optical molecular imaging technologies combining nanoparticle contrast agents and adaptive OCT systems for cancer and ophthalmic disease research. Technion-Israel Institute of Technology (BSc, 2005) Stanford University (PhD, 2011) UC Berkeley (Postdoctoral Fellowship) Research Themes : Virtual biopsy using machine learning-enhanced OCT Gold nanorod-based molecular contrast agents Speckle noise reduction for cellular resolution Needle beam optical coherence tomography angiography His 15 most recent publications demonstrate technical innovations in: Metasurface optics for extended depth-of-field Spectral deconvolution of multiple contrast agents Speckle modulation for improved diagnostic clarity Noninvasive lymphatic system mapping Scientific Honors : Pew-Stewart Scholar for Cancer Research AFOSR Young Investigator NIH Early Independence Award Forbes 30 Under 30 (x2) Chan Zuckerberg BioHub Investigator His lab team has developed clinical prototypes including OcuBell Inc. 's ophthalmic imaging systems and Visby Medical 's diagnostic platforms. Current research spans from in vivo glycoprotein imaging to de novo biosensor development for real-time disease monitoring in awake animal models.
Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.
Colby Haggerty is an Assistant Professor at the Institute for Astronomy (IfA Mānoa) at the University of Hawaiʻi at Mānoa. He specializes in computational plasma physics, focusing on magnetospheric, heliospheric, and astrophysical systems. His research emphasizes collisionless plasma shocks, magnetic reconnection, and kinetic plasma turbulence. He holds a Ph.D. in Plasma Physics from the University of Delaware (2017) and conducted postdoctoral work at the University of Chicago (2017–2021). His work bridges theory, numerical simulations, and observational data analysis using advanced computational tools like Python, C++, Fortran, and MPI/OpenMP frameworks. Research Interests: He investigates collisionless plasma shocks and energetic particle acceleration (e.g., Earth’s bow shock, coronal mass ejections), plasma instabilities, magnetic reconnection dynamics, and the role of turbulence in energy dissipation. His studies often involve hybrid and particle-in-cell (PIC) simulations to model cosmic phenomena like supernova remnants and solar wind interactions. Articles & Trends: His recent publications highlight advancements in understanding shock-drift acceleration mechanisms, the saturation of plasma instabilities (e.g., Bell instability), and scaling laws for magnetic reconnection in asymmetric and relativistic regimes. Collaborations with institutions like NASA Goddard, Columbia University, and the University of Chicago underscore his interdisciplinary approach. He has also contributed to developing Python-based plasma physics tools (e.g., PlasmaPy) for the scientific community. Grants & Impact: His CAREER award (2024) supports studies on collisionless magnetic reconnection as a heliospheric process. He emphasizes computational methods and educational outreach, reflecting his dual focus on advancing science and training future researchers. Labs & Teams: While no specific lab is named, his work relies on collaborative networks with leading institutions, leveraging state-of-the-art simulation infrastructure to tackle complex plasma problems.
Benyamin Davaji serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, where he joined in January 2022. He holds additional appointments as a Center Member of The Plastics Center and Core Faculty of the Institute for NanoSystems Innovation (NanoSI). His work bridges microsystems engineering, nanofabrication, and data science to develop next-generation sensing technologies. Dr. Davaji's educational background includes: Postdoctoral Associate in Electrical and Computer Engineering at Cornell University (2016-2021) Ph.D. in Electrical Engineering from Marquette University (2016) His research centers on integrated microsystems with emphasis on mechanical wave-based sensing and computation, ultrasound transducers, bio-interfaces, and microcalorimetry. The Autonomous Integrated Microsystems (AIMS) Laboratory combines physics with AI/ML to invent novel sensors and computational devices through advanced nanofabrication. Key thrusts include power-sustaining architectures and analog/digital computational integration. Recent publications (2024-2025) reveal strong trends in MEMS/NEMS optimization using digital twins, plasmonically enhanced infrared detection, ferroelectric actuators for high-speed scanning, and ultrasound-enabled metrology. His work increasingly integrates machine learning for design automation and process optimization across semiconductor manufacturing and flexible hybrid electronics. Dr. Davaji advises graduate students including Yilmaz Arin Manav (PhD'28), who won the FLEX 2024 Future Student Poster Award. He has secured over $3 million in competitive funding as PI/Co-PI, including a $550k NSF grant for MEMS actuators, $330k NSF grant for quantum detectors, and $2M DARPA grant for inertial sensors. He directs the interdisciplinary AIMS Laboratory focused on MEMS, ultrasound, and calorimetric technologies. The lab collaborates extensively with NanoSI and The Plastics Center, developing autonomous microsystems for biomedical, environmental, and industrial applications through advanced manufacturing techniques.
Dr. Chiara Bertelli is a Lecturer in Biosciences at Swansea University within the Faculty of Science and Engineering, School of Biosciences, Geography and Physics. With over 15 years of experience in coastal and marine ecological surveys, she specializes in seagrass ecology and restoration, marine conservation, and habitat suitability modeling. Dr. Bertelli has extensive field experience including boat-based surveys, SCUBA diving, and snorkeling in both temperate and tropical environments. She is currently completing her PhD part-time focusing on environmental drivers of change in seagrass meadows in the UK and Brazil. Her educational background includes advanced training in marine biology with specialization in ecological survey techniques and data analysis using R and Primer. Her primary research focuses on seagrass ecology as nature-based solutions for climate change. She develops habitat suitability models to inform optimal locations for seagrass restoration, with applications in carbon sequestration (blue carbon) and marine biodiversity enhancement. Her work aligns with UN Sustainable Development Goals 13 (Climate Action) and 14 (Life Below Water). Analysis of Dr. Bertelli's recent publications (2020-2025) reveals a strong emphasis on practical applications of seagrass research to inform restoration efforts. Her work spans habitat suitability modeling, environmental stress responses, nutrient dynamics, and decision-support tool development. A significant portion addresses seed-based restoration techniques, ecosystem services, and the socio-ecological dimensions of marine conservation. Dr. Bertelli actively collaborates with external organizations including Project Seagrass, Sky Ocean Rescue, WWF, Natural England, and the National Oceanographic Centre. Her current ReSOW project aims to develop the CEEDS (Coastal Ecosystem Enhancement Decision Support) tool, an open-source platform to guide seagrass restoration practitioners. As an educator, Dr. Bertelli teaches several field-based marine biology courses including BIO260 Marine Biology Field Course, BIO327 Tropical Marine Ecology Field Course, and BIO346 Professional Skills in Marine Biology. Her teaching emphasizes practical, field-based learning and professional skill development for marine biologists, with a focus on survey techniques, data analysis, and environmental impact assessment. Dr. Bertelli is actively involved in research teams focused on marine ecosystem restoration and coastal management. Her work bridges academic research with practical conservation applications, working closely with government agencies, NGOs, and international research partners to translate scientific findings into actionable conservation strategies.
Fu-Kuo Chang is a Professor in the Department of Aeronautics and Astronautics at Stanford University, with a secondary affiliation in the Bio-X program. His research focuses on multifunctional materials, intelligent structures, and structural health monitoring (SHM), emphasizing applications in aerospace, robotics, and medical devices. He has pioneered work on embedded sensors, self-diagnostic systems, and energy storage composites. Academic Appointments: Professor (Stanford), Editor-in-Chief of International Journal of Structural Health Monitoring (since 2012), and Chair of the International Workshop on Structural Health Monitoring (since 1997). Honors: Multiple lifetime achievement awards in SHM, AIAA and ASME Fellowships, and the NSF Presidential Young Investigator Award (1988). Research interests include bio-inspired sensory materials, autonomous systems (e.g., 'fly-by-feel' vehicles), and multidisciplinary integration of structural mechanics, electrical engineering, and materials science. His recent work addresses challenges in smart skins for robotics, thermoplastic composites, and predictive modeling of material degradation. Publications span structural health monitoring, advanced composites, and robotics, reflecting expertise in both theoretical and applied domains. His lab, the Structures and Composites (SACL) laboratory, drives innovation in smart materials and system integration. Advising: Supervises doctoral and master’s students in aeronautics and materials science. Grants/Contributions: Active in industry and government collaborations, including roles on the US Army Research Laboratories Advisory Board and leadership in SHM industry initiatives.
Allon Guez is a Professor in the Department of Electrical and Computer Engineering at Drexel University. His research focuses on control systems, robotics, artificial intelligence, medical robotics, and automated decision making. He actively bridges academia and industry through high-tech entrepreneurship. Education PhD in Electrical Engineering, University of Florida MS in Electrical Engineering, University of Florida MBA in Finance, Drexel University BS in Electrical Engineering, Technion - Israel Institute of Technology His research portfolio spans medical robotics, automated decision making systems, and advanced control algorithms. Key areas include wearable safety devices, radiation control in imaging systems, and closed-loop brain stimulation technologies. Notable contributions include founding ControlRad (radiation reduction systems) and GraceFall (fall detection technology). His work demonstrates a strong emphasis on translating academic research into commercial medical devices. Recent publications highlight innovations in: Fetal brainwave monitoring Postural disturbance detection Seizure prediction algorithms Magnetic microrobotics Dynamic CT collimation Cardiac tissue modeling
