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Nazli Cila is a researcher at the Faculty of Industrial Design Engineering (IDE) at Delft University of Technology, specializing in Human-Centered Design and Human-Technology Relations. Her work lies at the intersection of design, artificial intelligence, and robotics, with a strong emphasis on ethical and human-centered approaches. Her research focuses on Human-AI collaboration , Responsible AI , and More-than-human design , exploring how intelligent systems can be designed to align with human values and lived experiences. She investigates design methods for AI and robotics, particularly in contexts such as mental health, smart homes, and agricultural automation. Nazli Cila’s recent publications reveal a strong trend toward integrating ethical considerations and aesthetic experience into AI systems, especially in diagnostic tools and human-robot ecologies. Her work often employs speculative and participatory methods to uncover value conflicts and envision alternative futures for technology. Involved in research projects: AI DeMoS Lab, DCODE Network Teaches course: Research to/for/through… She actively contributes to the academic community through publications and interdisciplinary collaborations, advancing the field of human-centered design in the age of AI.

• Human-AI Collaboration
• Human-Centered AI
• Design Methods
• +7 more

Panayiotis Kolios is an Assistant Professor at the Department of Computer Science, University of Cyprus (UCY). Previously, he served as a Research Assistant Professor at the KIOS Research and Innovation Centre of Excellence (2013–2024) and a Visiting Lecturer at UCY. He holds a BEng and PhD in Telecommunications Engineering from King’s College London (2008 and 2012, respectively). His research focuses on networked intelligent systems, emergency management using AI and UAV technologies, and cyber-physical systems. Education: BEng in Telecommunications Engineering, King’s College London, 2008 PhD in Telecommunications Engineering, King’s College London, 2012 Research Interests: His work centers on autonomous systems, intelligent transportation, and emergency management. Key areas include AI-driven disaster response, UAV-based surveillance, and algorithmic optimization for critical infrastructure. He develops solutions for real-time situational awareness and decision-support in emergencies. Recent work trends show a focus on multi-UAV coordination, disaster management platforms (like AIDERS), and AI applications in emergency response. His team’s 2023 win in the Cooperative Aerial Robots Inspection Challenge highlights advancements in UAV inspection algorithms. Scientific Awards: First Prize in Cooperative Aerial Robots Inspection Challenge (CDC 2023) Grants and Advising: He has secured over €40 million in EU and industrial grants, leading projects like PREDICATE, SWIFTERS, and AIDERS. His team advises on emergency response strategies and has trained first responders through EU-funded programs such as the Exchange of Experts training. Labs and Teams: He leads the Security and Emergency Response Group at KIOS CoE and established the Cyprus Civil Defence Aerial Observation Unit. His team collaborates with institutions like the Cyprus Police and Fire Service to operationalize UAV technologies in disaster scenarios.

• Autonomous Systems
• Intelligent Transportation Systems
• Cyber-Physical Systems
• +7 more

Søren Munch Kristiansen is an Associate Professor in the Department of Geoscience at Aarhus University, Faculty of Natural Sciences. His interdisciplinary research bridges geoscience and archaeology, focusing on the complex interactions between soil, water, and human societies across time. He is actively engaged in transdisciplinary projects involving geoarchaeology, groundwater, and public health. Research Interests: His work centers on how soil and groundwater have shaped human prehistory and continue to influence modern life. Key areas include safe drinking water from a lifelong perspective, geoarchaeological prospection, Viking Age settlements, and the application of geophysical and geochemical methods in archaeological contexts. He is particularly interested in novel, interdisciplinary methodologies. Recent Research Trends: His recent publications reveal a strong focus on integrating geophysical data (e.g., GPR, borehole databases) with archaeological interpretation, especially in 3D urban modeling and landscape change. Themes include Viking Age sites, interglacial deposits, and anthropogenic soil modifications. His work increasingly employs machine learning and large-scale data synthesis. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While specific students are not listed, he leads and participates in multiple funded research projects, indicating an active supervisory role. His grants span from 2016 to 2024, including projects like TITAN, SAGA, and 'Fingerprinting displaced molecular substances,' highlighting sustained funding and leadership in interdisciplinary geoscience-archaeology research. Labs and Teams: He is involved in collaborative networks such as the Soil Science & Archaeo-geophysics Alliance (SAGA), suggesting leadership in interdisciplinary research teams. His work often involves multi-proxy analyses and international collaborations, particularly in Scandinavian archaeological geophysics.

• Geoarchaeology
• Soil Science
• Groundwater
• +7 more

Abdon Pena-Francesch is an Assistant Professor in the Department of Materials Science and Engineering at the University of Michigan. He is also affiliated with the Macromolecular Science and Engineering Program, Chemical Engineering, and the Michigan Robotics Institute. His interdisciplinary research integrates biomaterials science, polymer chemistry, soft matter physics, and nanotechnology to develop programmable soft materials for applications in healthcare, robotics, and environmental science. Education: Ph.D. in Engineering Science and Mechanics, The Pennsylvania State University, 2017 M.Sc. in Chemical Engineering, Institut Químic de Sarrià (Barcelona, Spain), 2013 B.Sc. in Mechanical Engineering, Institut Químic de Sarrià (Barcelona, Spain), 2011 Research Interests: His work focuses on bioinspired materials , soft robotics , self-healing polymers , and biodegradable microrobots . By engineering molecular and nanoscale structures, his lab designs materials with programmable properties for soft robotic systems and biomedical devices. The group emphasizes both fundamental science and translational applications, including tissue repair, actuation, and environmental sensing. Awards and Honors: Humboldt Research Fellowship for Postdoctoral Researchers (2018–2020) Alumni Association Dissertation Award, Penn State University (2017) Rustum and Della Roy Innovation in Materials Research Award (2016) Materials Research Society Graduate Student Award (2016) First Prize, Penn State ESM Graduate Research Symposium (2015) AGAUR MOBINT Fellowship, Government of Catalunya (2012) Labs and Affiliations: He leads the Bioinspired Materials Lab , an interdisciplinary group within the University of Michigan’s Materials Science & Engineering Department. The lab collaborates with the Macromolecular Science & Engineering Program, Chemical Engineering, and the Michigan Robotics Institute.

• Biomaterials science
• Polymer chemistry
• Soft matter physics
• +5 more

Lonny R. Levin is a Professor of Pharmacology at Weill Cornell Medical College , where he has worked since 2009. Collaborating extensively with Dr. Jochen Buck, he pioneered research on bicarbonate-regulated soluble adenylyl cyclase (sAC) , a critical enzyme in cAMP signaling. Education : B.S. from Cornell University (1983), Ph.D. from State University of New York at Stony Brook (1989) His research focuses on: cAMP signaling microdomains in mammalian cells Mitochondrial metabolism and pH sensing Sperm capacitation and energy regulation Nonhormonal contraceptive development via sAC inhibition Recent publications (2025-2023) highlight: Structural insights into sAC activation Metabolic adaptations during sperm capacitation Emerging role in corneal endothelium signaling Drug discovery for on-demand male contraception Grants from NIH (NIAID, NICHD) support his work on: Intravaginal rings for dual HIV/herpes prevention and contraception Metabolic communication in reproductive systems Signalosome regulation in mitochondria He maintains collaborations with institutions like EMD Millipore Corporation and co-founded Sacyl Pharmaceuticals, Inc. , holding proprietary interests in sAC-related intellectual property.

• Biochemistry
• Cell Biology
• Pharmacology
• +5 more

Regina Ragan is a Professor in the Department of Materials Science and Engineering at the Samueli School of Engineering, University of California, Irvine. Her research focuses on nanomaterials, self-assembly, and surface-enhanced Raman scattering (SERS) for applications in optical communication, energy systems, and biomedical diagnostics. Education: Ph.D. in Applied Physics, California Institute of Technology, 2002 M.S. in Applied Physics, California Institute of Technology, 1998 B.S. in Materials Science and Engineering, University of California, Los Angeles, 1996 Her work integrates scanning probe microscopy and first-principles calculations to study thermodynamic driving forces in self-assembly and structure-function relationships. Recent publications highlight applications in antimicrobial susceptibility testing, environmental monitoring, and plasmonic device fabrication. The Ragan group develops low-cost diagnostic tools using SERS for telemedicine applications. Current lab members include graduate students and postdoctoral researchers working on nanoscale systems from atomic to mesoscale. Scientific Awards: NSF CAREER Award for fundamental studies of biological/inorganic interfaces Research Trends: Recent articles show a focus on SERS-based diagnostics, plasmonic nanoantennas, machine learning-assisted spectral analysis, and scalable synthesis of 3D graphene architectures. Subfields span quantum plasmonics, stress-activated materials, and biofilm monitoring.

• Nanomaterials
• Self-Assembly
• Surface-Enhanced Raman Scattering (SERS)
• +4 more

Andreas Näsbom is a researcher at the Institute of Structural Engineering (IBK) , ETH Zürich, Switzerland. His work focuses on structural concrete, hybrid steel/CFRP reinforcement systems, and bond behavior in concrete elements. He specializes in experimental campaigns, distributed fiber optical sensing, and load redistribution analysis in hyperstatic systems. Research Interests: Structural Engineering, Reinforced Concrete durability, Composite Material interactions, and Plasticity Theory limitations in brittle reinforcement systems. His recent study investigates two-span concrete slab strips with hybrid steel/CFRP reinforcement, emphasizing bond stress quantification and cyclic loading effects. Scientific Contributions: This paper represents his current experimental work on hybrid reinforcement behavior, utilizing advanced measurement techniques like Distributed Fiber Optical Sensing (DFOS) to analyze bond-slip relationships and stress redistribution patterns.

• Structural Engineering
• Reinforced Concrete
• Composite Materials
• +4 more

Hyuck Jin Park is a Full Professor in the Department of Energy Resources and Geosystems Engineering at Sejong University, South Korea, where he has been teaching and conducting research since 2003. With a Ph.D. in Engineering Geology from Purdue University, his expertise spans geotechnical engineering, landslide analysis, and geospatial technologies. Professor Park has built a distinguished career in landslide hazard assessment, combining traditional geotechnical approaches with modern machine learning techniques to improve prediction accuracy and risk management. His educational background includes: B.S. in Geology from Yonsei University (1990) M.S. in Geophysics from Yonsei University (1993) Ph.D. in Engineering Geology from Purdue University (2011) Professor Park's research focuses on the spatial and temporal probability of landslide occurrence, utilizing fuzzy logic, probabilistic analysis, GIS, Monte Carlo simulation, and machine learning for landslide hazard assessment. His work integrates physically based models with statistical approaches to better understand landslide mechanisms and improve prediction capabilities. He has made significant contributions to the development of methodologies that account for geological uncertainties in hazard assessment, with applications ranging from rock slope stability to rainfall-induced shallow landslides. His recent publications demonstrate a clear trend toward integrating explainable artificial intelligence with traditional geotechnical approaches for natural hazard assessment. Professor Park's work increasingly focuses on making machine learning models transparent and interpretable while maintaining high predictive accuracy. The research spans multiple hazard types including landslides, earthquakes, and floods, with a growing emphasis on climate change impacts and data-scarce environments. With an h-index of 28 and over 3,421 citations, Professor Park has established himself as a leading researcher in his field. His work has been published in high-impact journals including Engineering Geology, Landslides, and Catena, reflecting the significance and quality of his contributions to geotechnical engineering and natural hazard assessment. Professor Park has mentored numerous researchers through collaborative projects and has secured funding for his innovative work in landslide prediction and hazard assessment. His research has involved significant international collaboration, particularly with researchers from Malaysia, Australia, and Yemen, addressing landslide and flood risks in diverse geographical contexts. He leads research activities within the Department of Geoinformation Engineering at Sejong University and has contributed to the development of specialized tools like DEWS (Distance, Elevation, Watershed, and Slope unit) for landslide early warning systems.

• Landslide Hazard Assessment
• Geotechnical Engineering
• Machine Learning Applications
• +5 more

Luís Miguel Mendonça Rato is an Associate Professor at the Universidade de Évora and a Senior Researcher with a PhD at Centro ALGORITMI. He is affiliated with the CST R&D Group and VISTA Lab R&D Lab, focusing on interdisciplinary research at the intersection of Electrical Engineering, Computer Science, and Agricultural/Biomedical applications. Academic Degree: PhD Current Position: Associate Professor Labs: VISTA Lab Researcher IDs: ORCID 0000-0003-4492-7548, ResearcherID A-9152-2013, CiênciaID A914-6344-CD2D His research spans machine learning applications in Agricultural Engineering (Sentinel-2 satellite data for nutrient analysis), Biomedical Imaging (MRI-ADC texture analysis for tumor classification), and Control Systems (predictive control algorithms for water delivery canals and solar fields). With an h-index of 11 and 51 publications, his work emphasizes hybrid systems combining traditional engineering with computational innovation. Recent publications highlight trends in SLAM efficiency (2024), cloud service optimization (2022), and deep learning for medical imaging (2022-2023). He has contributed to Smart Cities initiatives through projects like M-Traffic (2006) and NanoSen-AQM (2020). As a senior researcher, he leads projects in the CST R&D Group and VISTA Lab , with notable work in the Universidade de Évora ecosystem.

• Machine Learning
• Electrical Engineering
• Computer Science
• +3 more

Bryan K. Clark is an Associate Professor in the Department of Physics at the University of Illinois, with his office located in the Engineering Sciences Building. He leads the Clark Research Group, which works at the intersection of quantum information, condensed matter physics, machine learning, and computing. Clark's research spans four main areas: Quantum Computing , where his group develops quantum algorithms and collaborates with experimentalists on superconducting qubit systems; Quantum Many-Body Physics , where he applies computational methods to understand emergent behavior in strongly correlated systems; Algorithms for the Quantum Many-Body Problem , where his group has pioneered techniques like Neural Network Backflow (NNBF) that represent state-of-the-art accuracy for simulating fermions and frustrated magnetism; and Machine Learning for Experiment , where his group develops techniques to analyze experimental data like scanning transmission electron microscopy images. His publication record demonstrates consistent innovation in bridging theoretical quantum information science with practical applications. Recent work focuses on neural network approaches to quantum simulation, quantum error correction/mitigation, and novel qubit architectures like the Floquet Fluxonium Molecule. His research shows a clear trajectory from fundamental questions about the quantum-classical boundary to practical implementations in quantum hardware. Clark actively mentors graduate students, with recent thesis defenses by Faisal Alam, Matt Thibodeau, Chad Germany, James Allen, and Abid. His group has secured significant funding from the NSF and IBM's IIDAI institute to support research in quantum computing and machine learning applications for nano-photonics manufacturing and error mitigation. The Clark Research Group maintains strong connections with experimental teams, particularly in superconducting qubit development and materials characterization. They've developed computational tools like QOSY (Quantum Operators from SYmmetry) that are publicly available on GitHub and have gained recognition in the quantum information community.

• Condensed Matter Physics
• Quantum Information Science
• Quantum Computing
• +4 more

Charles J. Taylor is Professor of Chemistry and Chair of the Chemistry Department at Pomona College, where he has served since 2002. An analytical chemist specializing in instrumental techniques for volatile organic compound (VOC) analysis, his work bridges medical diagnostics, environmental monitoring, and chemical sensing applications. His educational background includes: Ph.D. from University of Minnesota Bachelor of Arts from Macalester College Taylor's research focuses on developing rapid diagnostic methods through VOC analysis, leveraging microhotplate arrays, Raman spectroscopy, and polymer-carbon composites. His work spans biological systems (nematode chemotaxis, wine fermentation flavor compounds) and environmental applications (trace element profiling in coffee beans). Students in his lab gain hands-on experience with advanced analytical instrumentation and multivariate data analysis. Analysis of his publications reveals consistent themes in chemical sensing materials development, with strong emphasis on microsensor arrays, NASA-collaborative electronic nose projects, and applications in medical/environmental diagnostics. His work demonstrates interdisciplinary integration of materials science, analytical chemistry, and data analysis. His scientific achievements have been recognized with: NASA Board Award for Copolymers for Sensors (2013) NASA Board Award for SO 2 Detection (2012) Provisional U.S. Patent #60/861-617 (2007) Multiple NASA Tech Brief Awards (2007) Taylor actively mentors undergraduate researchers, with students co-authoring publications on diverse projects from medical diagnostics to environmental trace analysis. His teaching includes Advanced Analytical Chemistry, Environmental Chemistry, and General Chemistry, emphasizing practical laboratory experience. Research funding has supported instrumentation development and NASA-collaborative sensor projects. His laboratory focuses on chemical sensing materials development, particularly microhotplate-based sensor arrays and VOC analysis systems, with ongoing collaborations with NASA's Jet Propulsion Laboratory for electronic nose applications and environmental monitoring solutions.

• Analytical Chemistry
• Chemical Sensing
• Environmental Chemistry
• +3 more

Thiago Batista Soeiro serves as a Full Professor with exceptional scholarly impact, evidenced by over 200 research publications and an h-index of 27. His work fundamentally advances power electronics applications in transportation and energy systems, particularly through innovations in electric vehicle infrastructure and sustainable power conversion technologies. Despite the absence of explicit institutional affiliation in source materials, his research permeates critical IEEE journals and conferences. Professor Soeiro's research portfolio centers on: Power converter design for electric vehicle charging systems AI-driven battery health estimation using electrochemical impedance spectroscopy Wireless power transfer optimization for automotive applications High-efficiency topologies for more electric aircraft Hydrogen energy system integration Advanced semiconductor utilization in grid-connected systems Analysis of his 2023-2025 publications reveals accelerating innovation in wide-voltage-range converters, predictive battery management, and fault-tolerant power systems. His work increasingly bridges machine learning with power electronics, notably through computation-light AI models for battery diagnostics, while maintaining strong focus on practical implementation challenges in EV charging and aircraft electrification. No scientific awards or honors were documented in the available materials. Similarly, information regarding student supervision, research grants, laboratory facilities, or collaborative teams was not provided in the source texts.

• Power Electronics
• Electric Vehicle Systems
• Battery Management Systems
• +3 more

Tongcang Li is a Professor of Electrical and Computer Engineering and Physics at Purdue University, affiliated with the Elmore Family School of Electrical and Computer Engineering and the Department of Physics and Astronomy. He holds joint appointments at the Birck Nanotechnology Center and the Purdue Quantum Science and Engineering Institute. His research focuses on quantum photonics, optomechanics, and quantum sensing, with breakthroughs in levitated nanoscale systems and Casimir effects. Education: PhD, The University of Texas at Austin, 2011 BS, University of Science and Technology of China, 2004 Research Interests: Spin qubits in 2D materials (e.g., hexagonal boron nitride) Levitated optomechanics for quantum control and sensing Casimir interactions and vacuum friction Quantum transducers and optically trapped nanoparticles Notable Achievements: 2018: One of 10 APS Physics Highlights of the Year for GHz rotation of levitated nanoparticles 2022: Featured in Optics & Photonics News' 'Optics in 2022' for on-chip optical levitation with metalenses Grants & Funding: Supported by NSF, DOE, Gordon and Betty Moore Foundation, Toyota, ONR, DARPA, Sandia National Laboratories, and Los Alamos National Laboratory. Labs/Teams: Leads the Quantum Sensing and Optomechanics Laboratory at Purdue, advancing quantum sensing and quantum information processing technologies.

• Quantum photonics
• Quantum optomechanics
• Spin qubits in 2D materials
• +5 more

Renate Sachse is a Researcher and Responsible Investigator at the Chair of Structural Analysis, Technical University of Munich (TUM), under Prof. Kai-Uwe Bletzinger. She holds a Dr.-Ing. from the University of Stuttgart and has held postdoctoral positions at Harvard University (Bertoldi Lab) and TU Munich's Institute for Computational Mechanics. Her research focuses on biomimetic adaptive structures, biomechanics, and smart materials. Education M.Sc. in Civil Engineering (University of Stuttgart, 2014) – Thesis: "Isogeometric Contact Analysis of Thin-Walled Structures" B.Sc. in Civil Engineering (University of Stuttgart, 2011) – Thesis: "Elementary School Pavilion Structural Analysis" Study Abroad: École Spéciale des Travaux Publics (ESTP, France, 2012) Research Interests Her work integrates principles from biology and mechanics to design adaptive structures, including motion design, soft robotics, and active metamaterials. Notable projects include studying snapping mechanisms in plants (e.g., Venus flytrap) and developing bio-inspired systems like Flectofold shading devices. She also explores isogeometric analysis and structural optimization for thin-walled and slender structures. Grants & Awards Bertha Benz Prize 2022 (Daimler and Benz Foundation) Klaus Tschira Boost Fund Fellowship (€80,000 interdisciplinary grant) 3rd Place AVK-Prize for Innovations (2017, Flectofold Shading System) GAMM Juniors Fellowship (2020–2022) Teaching & Grants She teaches advanced finite element methods and nonlinear mechanics at TUM and has supervised projects in computational mechanics. Her grants include CareerDesign@TUM funding and the Klaus Tschira Fellowship for high-risk, interdisciplinary research. Labs & Teams Associated with the Chair of Structural Analysis at TUM, collaborating on projects like livMatS (Living Materials Systems) and the Harvard SEAS Bertoldi Lab. Involved in software development (e.g., Carat++, Kiwi!3d) and third-party initiatives (CoDA, FlexWing).

• Motion Design
• Active and Adaptive Structures
• Biomechanics
• +6 more

Ross Thyer is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at Rice University. He holds a BSc (Hons) from the University of Western Australia and a PhD from the Harry Perkins Institute of Medical Research under Drs. Rackham and Filipovska. His postdoctoral training at the University of Texas at Austin with Prof. Andrew Ellington focused on engineered biosynthesis pathways and non-canonical amino acids. He co-founded GRO Biosciences, a Boston-based biotech startup, and leads the Thyer Lab at Rice. His research bridges synthetic biology, protein engineering, and molecular programming to address global challenges. Key areas include expanding genetic codes for therapeutics, engineering biosynthetic pathways via genetic circuitry, and developing microbial systems for environmental bioremediation. Core technologies include deep learning for protein design, modular DNA assembly, and high-throughput selections. The lab also develops tools like MutCompute for enzyme engineering and domesticates non-model bacteria for bioproduction. His work emphasizes technology innovation, with recent advances in selenocysteine incorporation, L-DOPA sensing systems, and actinobacteria toolkits. The Thyer Lab actively collaborates on biocatalyst development and translational applications in healthcare and industry.

• Synthetic Biology
• Protein Engineering
• Genetic Code Expansion
• +6 more