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Mark A. ArnoldView profile

Professor

• Analytical Chemistry
• Near Infrared Spectroscopy
• Noninvasive Sensing
• +4 more

Mark A. Arnold is the Edwin B. Green Professor in Laser Chemistry and Director of the Center for Biocatalysis and Bioprocessing at the University of Iowa. He holds a PhD from the University of Delaware and a BS from Indiana University-Purdue University Indianapolis. His primary affiliation is with the Department of Chemistry within the College of Liberal Arts and Sciences. His research focuses on developing spectroscopic chemical sensors for real-time, noninvasive monitoring of analytes in complex biological and environmental matrices. Key areas include noninvasive blood glucose sensing for diabetes management, terahertz spectroscopy for gaseous analytes, and near-infrared monitoring of bioprocesses. Innovations include the Kromoscopy technique for high-signal-to-noise measurements and radioluminescent sensors for long-term stability. Publications highlight advancements in bioprocess optimization (e.g., Pichia pastoris antibody production), material characterization via terahertz spectroscopy, and instrumental innovations like Hadamard transform-based chemical imaging. Collaborations with the Fraternal Order of Eagles Diabetes Research Center extend his work to clinical applications. Awards and grants are not explicitly listed in the provided materials. His advisory role involves directing interdisciplinary teams at the Arnold Research Group and the Center for Biocatalysis, focusing on biocatalytic processes, sensor development, and translational research. Infrastructure includes access to advanced facilities like the Iowa Advanced Technology Laboratories.

Scott HamshawView profile

Adjunct Assistant Professor

• Water Resources
• Machine Learning
• Environmental Sensing
• +4 more

Scott Hamshaw is an Adjunct Assistant Professor in the Department of Civil and Environmental Engineering at the University of Vermont (UVM) and a Machine Learning Specialist with the U.S. Geological Survey (USGS) Water Mission Area. His research focuses on applying machine learning to water resources, environmental sensing, and geomatics, with a particular emphasis on sediment dynamics, hydrological modeling, and remote sensing techniques. He holds a dual bachelor’s degree from UVM and St. Michael's College, followed by M.S. and Ph.D. degrees in engineering from UVM. Scott is a licensed professional engineer in Vermont and teaches courses in geomatics and stormwater engineering. Education: B.S., Civil Engineering, University of Vermont B.A., St. Michael's College M.S., Civil Engineering, University of Vermont Ph.D., Civil Engineering, University of Vermont Research Interests: Scott’s work integrates machine learning with environmental data to address challenges in water resource management, including streambank erosion monitoring, sediment transport analysis, and drought prediction. His methods leverage high-frequency sensor data, LiDAR, and UAS (unmanned aircraft systems) to quantify geomorphic changes and model hydrological processes. Recent projects include forecasting turbidity in drinking water basins and developing tools for hydrological drought prediction across CONUS. Publications Trends: His recent work emphasizes machine learning applications in hydrology, with a focus on predicting sediment dynamics, water quality parameters, and drought conditions. He has also explored spatial techniques like LiDAR and UAS photogrammetry for erosion monitoring and geomorphic change detection. Awards and Grants: No specific awards or grants are listed in the provided text. Advising and Labs: Scott has not listed advisees, but his teaching includes courses on geomatics and stormwater engineering. His work at USGS and UVM suggests involvement in collaborative research teams focused on water and environmental systems.

Francesc J. FerriView profile

Professor

• Computer Vision
• Pattern Recognition
• Machine Learning
• +7 more

Francesc J. Ferri is a Professor in the Department of Computer Science at the University of Valencia since 2008. He holds a Licenciado in Physics (1987) and a Ph.D. in Pattern Recognition (1993) from the same university. His research focuses on Computer Vision, Pattern Recognition, and Machine Learning, with contributions to subspace learning, metric learning, and kernel methods. He has authored/co-authored ~140 papers (h-index=11 as of 2011), with notable work on feature selection and large-scale classification. Education: Licenciado in Physics (1987), Ph.D. in Pattern Recognition (1993), both from University of Valencia. Affiliations: Member of AERFAI, IAPR, ACM, IEEE. Teaching includes courses on Automata Theory, Algorithms, Computer Vision, and Pattern Recognition at undergraduate and graduate levels. He has advised multiple Ph.D. and MSc students, including Adrian Perez-Suay (metric learning) and Katerine Diaz-Chito (subspace-based image recognition). Research projects include sabbaticals at Surrey University (1993) and Michigan State (2005), and collaborations on audio event detection, bioinformatics, and e-learning systems. His recent work addresses explainable AI, edge computing for safety systems, and multidataset HRTF analysis.

Raymond C. RumpfView profile

Professor

• Electromagnetics
• Photonics
• 3D Printing
• +7 more

Professor Raymond C. Rumpf is a faculty member in the Electrical and Computer Engineering department at the University of Texas at El Paso (UTEP), where he pioneered research in electromagnetics, photonics, and 3D printing since founding the EMLab in 2010. His work has produced groundbreaking technologies such as the world’s first 3D volumetric circuit, tightest optical beam bend, and thinnest all-dielectric antenna. Research Interests Electromagnetics and photonics 3D printing and additive manufacturing Metamaterials and photonic crystals Computational electromagnetic modeling Hybrid 3D printing for RF and optical devices Dynamic material response Awards Senior Member of the National Academy of Inventors (2024) Fellow of the International Society for Optics and Photonics (SPIE) $5M Department of Energy grant for nuclear security workforce training $100K NSF grant for electromagnetic simulation algorithms His lab focuses on hybrid 3D printing, computational methods (e.g., finite-difference frequency-domain), and developing disruptive technologies like invisibility cloaks and ultra-broadband filters. The EMLab has been recognized globally, with publications in top journals and book authorship.

• Quantum Computing
• Trapped Ions
• Quantum Sensing
• +3 more

Associate Professor Erik Streed is Director of the Queensland Quantum and Advanced Technologies Research Institute at Griffith University. An experimental quantum physicist with PhD from MIT (Nobel laureate W. Ketterle group), his research spans trapped ion quantum computing, integrated photonics, quantum sensing, and applications in biosensing and materials science. Research foci: Trapped ion quantum networking over optical fibers Quantum sensing with 3C-SiC/Si heterojunctions Ultrafast coherent control of ytterbium ions Quantum optomechanics for communication Nanoscale biosensing using functionalized cantilevers Pioneered lighthouse-inspired segmented optics for trapped ion systems, enabling first imaging of a single atom's shadow. Leads ARC and defence-funded projects including 'Quantum Atom Optic Chip Sensors' ($300K) and 'Nano optoelectronic coupling' ($631K). Recipient of Queensland Young Tall Poppy Science Award (2011) and Best Paper Award for single-atom imaging (2013). Mentors doctoral candidates in quantum technologies and serves as Australian National Fabrication Facility Queensland Node Director.

• Hardware-Software Co-design
• Deep Learning Security
• Intellectual Property Protection
• +5 more

Huili Chen is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California San Diego's Jacobs School of Engineering. Her research spans the intersection of hardware security, deep learning, and human-robot interaction, with a particular focus on intellectual property protection for AI systems and socially interactive robotics for education and family settings. Her research interests focus on hardware-software co-design for secure and robust deep learning systems, with specific expertise in neural network watermarking, hardware Trojan detection, and privacy-preserving AI. She has made significant contributions to federated learning security, developing frameworks like GALU for logic unlocking and AdaTest for hardware Trojan detection. In human-robot interaction, she investigates long-term multi-person interactions, particularly in home environments with children and parents, exploring how robots can enhance engagement and learning through adaptive role-playing. Her publication trends reveal a dual research trajectory: one branch focused on deep learning security and hardware co-design (accounting for approximately 60% of her recent work), and another dedicated to socially assistive robotics and human-robot interaction (40%). The security research often involves innovative approaches combining reinforcement learning with hardware constraints, while her HRI work emphasizes longitudinal studies of robot-child-parent dynamics in naturalistic settings. Dr. Chen actively collaborates with leading researchers including Farinaz Koushanfar at UC San Diego and Cynthia Breazeal at MIT Media Lab. Her work has been published in top-tier venues including IEEE Transactions on Affective Computing, ACM Transactions on Embedded Computing Systems, International Conference on Computer Vision (ICCV), and the ACM/IEEE International Conference on Human-Robot Interaction (HRI). She is a key contributor to the DAMI-P2C project, which has developed datasets and models for analyzing parent-child multimodal interactions, and leads research on hardware security frameworks for deep neural networks. Her laboratory combines expertise in computer architecture, machine learning, and social robotics to develop systems that are both technically secure and socially effective.

Stefan HinzView profile

Professor

• Remote Sensing
• Photogrammetry
• InSAR
• +5 more

Prof. Dr.-Ing. Stefan Hinz is a Professor at the Karlsruhe Institute of Technology (KIT), serving as Spokesperson for the Topic Data Science in Climate and Environmental Research within the KIT Climate and Environment Center. He is based at the Institute for Photogrammetry and Remote Sensing (IPF) in Karlsruhe, Germany, where his work bridges advanced remote sensing methodologies with critical environmental and climate challenges. His research spans Remote Sensing , Photogrammetry , and Environmental Monitoring , with specialized expertise in InSAR, GNSS, and deep learning applications. Key focus areas include land subsidence analysis (particularly in the Mekong Delta), infrastructure safety monitoring for dams and bridges, atmospheric dust density estimation, and climate adaptation strategies through spatial planning. His interdisciplinary approach integrates geospatial data science with practical environmental solutions. Recent publications reveal a pronounced shift toward AI-driven remote sensing, with deep learning techniques enhancing traditional methods like SAR interferometry. His work emphasizes real-world applications in geohazard monitoring, environmental protection, and climate resilience, often targeting vulnerable regions like the Mekong Delta. This trend reflects a broader movement toward computational innovation in earth observation science. Prof. Hinz leads strategic initiatives within the KIT Climate and Environment Center, coordinating data science efforts for climate research and environmental protection. His role involves fostering cross-disciplinary collaboration to address sustainability challenges through advanced remote sensing technologies and spatial data analysis.

• Plasma Physics
• Laser Technology
• Extreme Ultraviolet (EUV) Radiation
• +3 more

Oscar Versolato is a Research Professor and Group Leader of the EUV Plasma Processes group at the Amsterdam Center for Nanolithography (ARCNL). He leads the Source Department, focusing on advanced plasma-based EUV light sources for semiconductor applications. His expertise spans plasma physics, laser technology, and spectroscopy of highly charged ions. He holds a PhD cum laude from the University of Groningen (2016 NWO Vidi Grant recipient) and conducted postdoctoral research at the Max Planck Institute and Aarhus University. His work addresses tin plasma dynamics, droplet deformation, and EUV radiation generation. Key achievements include ERC Starting (2018) and ERC Consolidator (2022) grants. Research interests include optimizing EUV sources via laser-driven tin plasmas and understanding plasma kinetics. Education: PhD in Laser Spectroscopy (University of Groningen) Research Focus: EUV plasma dynamics and optimization Laser-driven tin microdroplet systems Spectroscopic analysis of high-charge-state ions Plasma source efficiency and scalability Awards: NWO Vidi Research Grant (2016) ERC Starting Grant (2018) ERC Consolidator Grant (2022) Grants & Projects: Leadership in EUV source development, including the TI-REX tunable infrared laser system for nanolithography applications. Labs/Teams: Head of ARCNL's Source Department, coordinating interdisciplinary efforts in plasma physics and nanolithography.

• Quantum Photonics
• Quantum Optics
• Solid-State Physics
• +3 more

Dr. Lothaire Ulrich is a Postdoctoral Researcher at ICFO - The Institute of Photonic Sciences, working in the Quantum Photonics with Solids and Atoms research group. He holds a PhD in Physics from Université PSL Paris (FR). His research focuses on quantum photonics, rare-earth ion physics, and optical systems for quantum technologies. Key areas include quantum control, optical signal processing, and advanced material characterization. His work bridges quantum engineering and solid-state physics to develop high-performance photonic devices for quantum applications. Education: PhD in Physics, Université PSL Paris (FR). Research Interests: Quantum photonics systems, rare-earth ion-doped crystals, optical waveform generation, high-bandwidth laser systems, and photonic RF signal processing techniques. His studies emphasize quantum control architectures and spectral engineering for quantum communication and analog signal processing. Selected Research Trends: His articles highlight advancements in quantum emitters manipulation, wideband signal processing via spectro-spatial architectures, and high-rejection photonic filters using rare earth materials. Ongoing work explores integration of quantum processors with analog RF systems. Scientific Awards: None explicitly mentioned. Lab/Team Affiliation: Quantum Photonics with Solids and Atoms group at ICFO.

Alessio MaliziaView profile

Professor

• Human-Centred Systems
• Ubiquitous Interactive Systems
• End-User Development
• +3 more

Alessio Malizia is a Professor at the Faculty of Logistics, Molde University College (HiMolde), and concurrently holds a Professorship in User Experience Design at the University of Hertfordshire. His academic career spans roles at institutions like the University Carlos III of Madrid, Brunel University London, and Sapienza University of Rome. He is an ACM Distinguished Speaker and has research interests in Human-Centred Systems, Ubiquitous Interactive Systems, and hybrid physical-digital environments. His work integrates interdisciplinary collaboration and end-user development methodologies. Malizia’s research focuses on advancing technologies that blend digital and physical worlds, with contributions to wavelet transforms, signal processing, and image denoising. He has authored influential books and chapters, including works on time-frequency representations and sonar image processing. His industry experience includes roles at IBM and Silicon Graphics, alongside visiting research at Xerox PARC, where he explored neural networks and collaborative technologies. Key grants include projects with the European Space Agency (ESA) on sonar image fusion and ocean laboratory systems. His teaching spans Java programming, digital service design, and advanced signal processing techniques. Malizia has advised five doctoral students and currently mentors two, producing notable alumni like Prof. Corina Naforniță and Sorin Moga. His administrative roles include serving as Deputy Dean at Politehnica University Timișoara and Department Director at the University of Hertfordshire. Awards: ACM Distinguished Speaker Grants: ESA-funded projects on sonar imaging (2014–2016), IMFUSING (2014–2017) Labs/Teams: Active in interdisciplinary teams focusing on hybrid systems and end-user development

Matthew OliverView profile

Professor

• Phytoplankton oceanography
• Biogeography
• Remote sensing
• +5 more

Matthew Oliver is the Patricia and Charles Robertson Distinguished Professor of Marine Science and Policy at the University of Delaware. He holds appointments in the School of Marine Science & Policy and the Department of Geography and Spatial Sciences within the College of Earth, Ocean & Environment. His research focuses on phytoplankton oceanography, biogeography, remote sensing, and polar marine ecosystems. He leads the Ocean Exploration, Remote Sensing, and Biogeography (ORB) Lab, which develops technologies like robotic systems and satellite data to study marine organisms' distributions and ecosystem dynamics. Oliver earned a Ph.D. in Oceanography from Rutgers University (2006), an M.S. in Biology from Cal Poly (2001), a B.S. in Ecology from Cal Poly (1999), and an A.A. in Natural Sciences from Cerritos College (1996). His work emphasizes understanding how physical ocean processes influence biological systems, with applications to conservation and fisheries management. His research interests span satellite-driven ecological forecasting, marine predator behavior, and Antarctic ecosystem studies. The ORB Lab's innovations include real-time ocean data platforms (e.g., Atlantic Sturgeon risk maps) and partnerships with agencies like NOAA and Delaware Sea Grant. Oliver's publications highlight interdisciplinary approaches linking oceanography with ecology, with recent work exploring submesoscale transport, Lagrangian coherent structures, and the role of eddies in biological hotspots. Advising focuses on students with quantitative skills, particularly in spatial analysis and programming. His lab actively collaborates with international teams on projects like Project CONVERGE (Antarctic ecosystem dynamics) and robotic ocean glider deployments. Current initiatives include advancing dynamic ocean management tools and integrating animal telemetry with remote sensing data. Labs/Teams: ORB Lab (lead), Robotic Discovery Laboratories. Key projects involve developing seascapes frameworks for marine conservation and improving ecological forecasting models for climate-sensitive species.

David RoonView profile

Researcher

• Aquatic Ecology
• Riparian Forests
• Aquatic-Terrestrial Linkages
• +5 more

David Roon is a Researcher in the Department of Forest Ecosystems & Society at Oregon State University's College of Forestry. His work focuses on aquatic-terrestrial linkages, particularly how forest disturbances like wildfires and insect outbreaks affect stream ecosystems. He holds a PhD in Fisheries Science from Oregon State (2021), an MS in Biology from the University of Alaska Fairbanks (2011), and a BA in Environmental Studies from Lewis & Clark College (2005). Roon's research emphasizes whole-ecosystem approaches to understand food web dynamics and disturbance impacts. Current projects investigate wildfire effects on Pacific Northwest aquatic systems, including thermal regime changes, fish habitat vulnerability, and post-fire recovery mechanisms in the Hinkle Creek watershed. He applies system dynamics models and GIS mapping to quantify ecological responses to environmental changes. His work bridges applied science and natural resource management, addressing questions like how riparian thinning affects stream temperatures and food webs in redwood forests. He has published extensively on topics ranging from invasive species impacts to disturbance ecology, with a focus on linking ecological processes across spatial and temporal scales.

Guido DolmansView profile

Professor

• Wireless Systems
• Radar Technology
• Biomedical Engineering
• +3 more

Guido Dolmans is a Full Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), concurrently serving as Scientific Director and R&D Manager at IMEC Netherlands since 2006. He holds an MSc and PhD in Electrical Engineering from TU/e (1992 and 1997). His research focuses on wireless systems, radar solutions, localization, and emerging technologies like AI and data analytics. He contributes to UN Sustainable Development Goals through innovations in energy-efficient IoT systems and biomedical applications. Academic roles include leadership in TU/e’s Electronic Systems group and IMEC Netherlands. His work spans radar architectures, ingestible device localization, and sustainable IoT frameworks. Notable collaborations include projects on brain-computer interfaces and transdural telemetry. Guido’s research portfolio includes 128 publications, with recent emphasis on 2D indoor tracking via FMCW radar and energy-efficient biomedical sensor networks. He leads initiatives like the SUPERIOT project to advance sustainable IoT technologies.

Newton ArmstrongView profile

Professor

• Instrumental and Electronic Composition
• Electronic and Digital Performance
• Sound Art
• +5 more

Professor Newton Armstrong at City St George's, University of London is a composer, performer, and electronic musical instrument designer whose work bridges instrumental and electronic music with focus on human-technology-environment interactions. Ph.D., Princeton University (2006) M.F.A., Princeton University (2003) M.Mus., University of Melbourne (1996) B.Mus. (Hons), University of Melbourne (1991) His research explores: Instrumental and Electronic Composition through hybrid acoustic-electronic systems Digital Performance via custom software/hardware development Sound Art with environmental acoustics and psychoacoustic phenomena Machine Learning applications in rhythm perception and generation Experimental Music Aesthetics in 20th/21st century contexts From his 15 most recent works, key trends emerge in: Neural network models for expressive timing Spatialized sound installation design Instrument development for enactive performance Contemporary chamber music with extended techniques Temporal structure analysis through mathematical frameworks Urban acoustic ecology applications

Josip ŽubrinićView profile

Assistant Professor

• Applied Mathematics
• Homogenization Theory
• Elasticity and Materials Science
• +3 more

Dr. Josip Žubrinić is an Assistant Professor in the Department of Applied Mathematics at the Faculty of Electrical Engineering and Computing (FER), University of Zagreb. His research focuses on applied mathematics, homogenization theory, elasticity, and interdisciplinary applications in materials science and quantum systems. He is affiliated with FER's applied mathematics group and actively contributes to the Bibliography (CROSBI) research repository. Dr. Žubrinić's work spans theoretical and applied domains, including: Homogenization of PDEs in heterogeneous media Statistical mechanics models (e.g., Rydberg atoms, Flory polymer models) Combinatorial optimization for settlement planning Mathematical analysis of elastic structures and poroelastic plates Recent research highlights include studies on critical-contrast PDEs, quantum lattice systems, and multiscale modeling of composite materials. His articles demonstrate a strong emphasis on interdisciplinary methods bridging pure mathematics and real-world engineering problems. No scientific awards or grants are explicitly listed in the provided materials. His teaching includes specialized topics like complexity functions in jammed systems and combinatorial models.