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Hien NguyenView profile

Associate Professor

• Machine Learning
• Artificial Intelligence
• Biomedical Image Analysis
• +9 more

Hien Nguyen is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Houston's College of Engineering. His research focuses on machine learning, artificial intelligence, and their applications in biomedical image analysis, computational medicine, and drug discovery. He specializes in developing AI systems to enhance radiology workflows, improve diagnostic accuracy, and model radiologists' cognitive processes. His work spans domains like medical imaging segmentation, domain adaptation, and interpretable AI for clinical trust. Nguyen's research integrates multimodal data from LIDAR, satellite imagery, and histopathology slides to address challenges in urban mapping, kidney disease classification, and cellular analysis. He has contributed to frameworks like MIRAM for breast lesion risk prediction and ItpCtrl-AI for radiologist intent modeling. His team explores meta-learning, self-supervised learning, and diffusion models for tasks ranging from apoptosis forecasting to seismic data interpolation. Key technical strengths include domain invariant learning, medical dataset synthesis (e.g., MorphSet), and explainable AI systems. His work bridges human expertise with machine intelligence, emphasizing clinical adoption through collaboration between radiologists and AI algorithms.

Adam SmithView profile

Research Fellow

• Climate Change Science
• Climate Change Mitigation
• Climate Change Adaptation
• +5 more

Adam Smith is a Senior Research Associate at the University of East Anglia's School of Environmental Sciences, where he contributes to climate change research through multiple roles. He is an active member of both the Tyndall Centre for Climate Change Research and ClimateUEA, focusing on making climate science actionable for decision-makers at various levels. Smith's research interests center on climate change mitigation and adaptation, with specific expertise in greenhouse gas emissions, climate resilience, climate risk assessment, and fire-climate interactions. His work bridges scientific research with practical applications, emphasizing how stakeholders use climate data to inform their decisions and strengthen adaptive capacity. His recent publications demonstrate a strong focus on translating climate science into actionable insights, particularly through projects like OpenLAND, OpenCLIM, and the MACC Hub. Smith's research trajectory shows increasing emphasis on place-based climate risk assessment, stakeholder engagement in climate adaptation, and the integration of local knowledge with scientific data. As project manager for multiple significant climate initiatives, Smith has developed expertise in rapid evidence assessment, project management, and knowledge exchange. His work on the confinement index during the COVID-19 pandemic, which contributed to Global Carbon Budget estimates, highlights his ability to respond to emerging global challenges with innovative methodological approaches. Smith is actively involved in the Tyndall Centre for Climate Change Research, contributing to their mission of providing evidence-based solutions to climate change challenges. His current projects, including the Maximising UK Adaptation to Climate Change Hub (running through 2027), indicate his leadership in developing practical tools and frameworks for local climate risk management and adaptation planning across the UK.

• Sustainable Agriculture
• Agroforestry
• Climate Change Mitigation
• +4 more

Paul Burgess is a Professor of Sustainable Agriculture and Agroforestry at Cranfield University, affiliated with the School of Water, Energy and Environment. His career includes a BSc (Hons) in Agriculture from the University of Reading, an MSc in Land and Water Management from Cranfield University, and a PhD in tea agronomy from Cranfield. He joined Cranfield in 1995 and has held roles from Lecturer to Senior Lecturer (2008), Reader (2014), and Professor (2021). His expertise spans agrifood systems, agroforestry, and climate-smart agriculture. Burgess has authored over 100 peer-reviewed papers and led major projects such as the EU AGFORWARD initiative (2014–2018), the UKRI Land Use for Net Zero project, and the BBSRC tea production partnership with Liptons. His research focuses on agroforestry economics, climate resilience, and sustainable land systems. He contributed to the DEFRA agroecology study and carbon sequestration projects with the Ministry of Defence. His awards include a Fellowship of the Higher Education Academy since 2007. He collaborates globally, with fieldwork in China, India, and East Africa. Current projects include digital tools for agroforestry (DigitAF) and regenerative tea production systems.

Michael RiveraView profile

Assistant Professor

• Human-Computer Interaction
• Digital Fabrication
• Computational Design
• +4 more

Michael Rivera is an Assistant Professor of Computer Science at the ATLAS Institute, University of Colorado Boulder. He directs the Utility Research Lab—a highly interdisciplinary group that invents and investigates digital manufacturing technology by combining materials science, computational fabrication, and sustainable design practices. His research has been published in premier human-computer interaction venues including ACM CHI, UIST, DIS, and IMWUT, and featured in national media outlets such as NPR's All Things Considered, Ars Technica, and CBS News. Dr. Rivera earned his Ph.D. and M.S. in Human-Computer Interaction from Carnegie Mellon University's Human-Computer Interaction Institute, where he was advised by Scott Hudson. Prior to CMU, he completed a M.S.E in Computer Graphics and Game Technology and a B.S.E in Digital Media Design at the University of Pennsylvania, and worked as a software engineer at Facebook. Michael Rivera's research focuses on sustainable digital fabrication techniques that democratize access to manufacturing tools while addressing environmental concerns. His work explores bio-based materials, computational recycling approaches, and low-cost fabrication methods. The Utility Research Lab has developed innovative projects including the Desktop Biofiber Spinning Machine for Smart Textiles Design and techniques for 3D Printing with Spent Coffee Grounds. His research bridges materials science, computational design, and human-centered approaches to create more accessible and environmentally responsible fabrication technologies. Rivera's publication record shows a clear trajectory toward increasingly sophisticated computational approaches to sustainable manufacturing. His recent work emphasizes material recycling processes, biofiber development, and computational design pipelines that enable disassembly and reuse of fabricated objects. This research direction reflects a commitment to addressing the environmental impact of digital fabrication while expanding its accessibility to diverse users and contexts. CRA/CCC Computing Innovation Fellowship Google CMD-IT Dissertation Fellowship Carnegie Mellon University Sansom Endowed Presidential Fellowship Adobe Research Fellowship Honorable Mention Xerox Technical Minority Scholarship Dr. Rivera is actively recruiting PhD students to join the Utility Research Lab, demonstrating his commitment to mentoring the next generation of researchers in human-computer interaction and digital fabrication. His research has been supported by prestigious fellowships including the NSF/CRA Computing Innovation Fellowship. He collaborates extensively with researchers across institutions, as evidenced by his co-authorship with scholars from various universities. The Utility Research Lab, directed by Dr. Rivera, serves as a hub for interdisciplinary innovation in digital fabrication. The lab has developed several notable projects that reflect its mission to advance science and engineering while positively impacting people, society, and the environment through sustainable design practices. Current work focuses on computational approaches to material recycling, biofiber design, and novel animation techniques that make fabrication more accessible and environmentally responsible.

Dani OrView profile

Professor

• Soil Physics
• Environmental Engineering
• Porous Media Transport
• +5 more

Dani Or is the Nevada Engineering Distinguished Professor in the Department of Civil & Environmental Engineering at the University of Nevada, Reno. His research focuses on mass and energy transport in porous media, landslide mechanics, evaporation dynamics from porous surfaces, and biophysical processes in soil. He has held roles such as Editor-in-Chief of the Vadose Zone Journal and chairs major conferences like the Gordon Research Conference on Flow and Transport (2008). Dr. Or’s work bridges soil physics, environmental engineering, and geophysics, with a strong emphasis on global-scale applications such as ecosystem water limitation and wildfire impacts. His contributions include pioneering studies on soil hydraulic conductivity, evaporation suppression technologies, and the integration of machine learning for soil moisture prediction. Awards: John Dalton Medal (2017), National Academy of Engineering (2022), Caltech Moore Scholar (2023). Grants & Advising: Leads interdisciplinary projects on soil structure dynamics, wildfire modeling, and geothermal engineering. No specific advisee list is provided in the text. Labs/Teams: Collaborates with global teams on soil parameterization databases (e.g., GSHP) and wildfire-soil interaction frameworks.

George CaridakisView profile

Associate Professor

• Cultural Informatics
• Digital Culture
• HCI
• +4 more

Associate Professor George Caridakis holds a faculty position at the Department of Cultural Technology and Communication, University of the Aegean, where he founded the Intelligent Interaction Research Group (ii.aegean.gr). He also serves as an Adjunct Professor at Athena Research Center (Athena RC) and a Senior Researcher at the National Technical University of Athens' Intelligent Systems, Content and Interaction Laboratory. His research spans Cultural Informatics, AI-driven Interaction, IoT, Mixed Reality, and Semantic Web technologies, with over 75 publications and an h-index of 20. Caridakis has led or contributed to over 20 European/National projects, focusing on cultural heritage preservation, digital twin technologies, and AI applications in education and tourism. He actively supervises graduate theses and teaches at both undergraduate and postgraduate levels. His work emphasizes participatory methods, context-aware systems, and cross-disciplinary collaboration in cultural spaces. Education details are not explicitly provided in the text, but his academic trajectory is evident through his roles and projects. Research interests include affective computing, embodied interaction, and heritage digitization. His methodologies often integrate semantic technologies and IoT to solve challenges in cultural preservation and visitor experience optimization. Recent work explores large language models (LLMs) for museum recommendations and robotics in education. Publications reflect a strong focus on cultural heritage management (e.g., digital twins, crowdsourcing, AR), user-centric design (recommender systems, sentiment analysis), and smart systems (IoT in heritage spaces). His projects like CAnTi and CHEKG demonstrate innovation in collaborative methodologies and modular knowledge graphs. Caridakis has served as a journal/conference reviewer and evaluator for funding bodies, contributing to the advancement of interdisciplinary research standards. He leads the OpenLab for Cultural Heritage Conservation, integrating VR/AR for site preservation. Collaborations span academia and industry, emphasizing applied research with practical societal impact. Current initiatives include advancing accessibility through regional digital infrastructures and enhancing citizen engagement via participatory frameworks.

• Cognitive Neuroscience
• Neurology
• Interoception
• +4 more

Marta Gerosa is a doctoral researcher at the Berlin School of Mind and Brain, affiliated with Humboldt-Universität zu Berlin and the Department of Neurology at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) in Leipzig, Germany. She is a stipend-holder of the DAAD Research Scholarship and a member of the Mind-Body-Emotion research group. Academic Education: Doctoral candidate (2022–present), Berlin School of Mind and Brain (Humboldt-Universität zu Berlin & Charité – Universitätsmedizin Berlin) 2nd Level Degree in Biomedical Sciences (2019–2022), University School for Advanced Studies IUSS, Pavia, Italy M.Sc. in Psychology, Neuroscience and Human Sciences (2019–2021), University of Pavia & IUSS B.Sc. in Psychological Sciences (2016–2019), University of Pavia, Italy Her research focuses on bodily self-awareness, brain-body interactions, interoception, multisensory integration, sense of agency, decision-making, and post-stroke body representation disorders. She investigates how cardiorespiratory signals influence voluntary action and agency, methodological variability in interoception tasks, and neural mechanisms of emotion regulation and body ownership. Recent publications highlight her work in psychophysiology, methodological innovation, and clinical applications. She has contributed to systematic reviews on fear conditioning and meta-methods analyses of heartbeat counting tasks, alongside studies on neural asymmetry and graphic perseveration. Scientific Awards: DAAD Research Scholarship Marta also served as an academic tutor in Cognitive Neuroscience at the University of Pavia, Italy (2020–2022), teaching Basic Anatomy and Physiology of the Nervous System and Clinical Neuropsychology. She has participated in multiple research projects, including training at the Cognitive and Forensic Neuropsychology Lab, ASST Niguarda Hospital, Milan, and the ICoN Center in Pavia.

Yi-Chang James TsaiView profile

Professor

• Smart Cities Infrastructure
• Transportation Systems Engineering
• Pavement Preservation and Management
• +5 more

Dr. Yi-Chang James Tsai is a Professor and CISE Group Leader at Georgia Institute of Technology's School of Civil and Environmental Engineering. He specializes in smart cities infrastructure, transportation systems engineering, and pavement preservation using advanced sensing technologies. His work has significantly impacted Georgia’s pavement management systems, including the development of a GIS-based pavement preservation system for GDOT. He holds the prestigious Chinese Chang Jiang Scholar title (2009) and received an innovation award for GIS-enabled ship recognition (2007). His research integrates emerging technologies like 3D laser, LiDAR, and AI to enhance infrastructure resiliency, roadway safety, and asset management. Key projects include predictive safety modeling, autonomous vehicle integration, and sustainability of transportation networks. Dr. Tsai leads the Smart City Infrastructure (SCI) Lab, focusing on infrastructure condition assessment, deterioration analysis, and optimization strategies. Education: Doctorate in Civil Engineering (prior to Georgia Tech faculty role) Grants: Multiple GDOT-funded projects on pavement preservation, HFST implementation, and sensor-based safety systems Dr. Tsai’s work emphasizes data-driven decision-making, cost-effective maintenance, and innovation in transportation infrastructure. His lab has pioneered technologies for automated sign detection, pavement crack analysis, and real-time safety scoring. Key Achievements: Developed GDOT’s pavement preservation system managing 18,000 miles of highways Advanced AI-based crack detection and 3D imaging techniques Leader in roadway safety audits and curve sign optimization The Smart City Infrastructure Lab collaborates with industry partners to address challenges in infrastructure sustainability, resiliency, and smart mobility solutions for aging populations and energy efficiency.

• Cognitive Psychology
• Neuroscience
• Embodied Cognition
• +5 more

Alejandro Gálvez Pol is a Professor in the Psychology Department at the University of the Balearic Islands, where he teaches courses including Memory and Cognition, Cognition and Brain, and Social Cognition and Brain across undergraduate and Master's programs in Psychology, Cognition and Human Evolution, and Cognition and Society. His research focuses on embodied cognition , exploring how humans actively sense and interact with their environment through movement and bodily states. As Principal Investigator of the Active Cognition, Embodiment & Environment Lab (ACE²Lab) , he employs electrophysiological methods to investigate the relationship between interoception (internal bodily awareness) and active sensing (using movement to gather information). Recent work examines cardiac, respiratory, and gastric rhythms within ecological paradigms using mobile neuroscience approaches. His laboratory has recently expanded with a mobile research van enabling field studies in natural environments, and he co-launched the new Master's program in Cognition & Society in May 2025. Current PhD students are participating in international summer schools like the Adriatica Summer School. Principal Investigator: Cognition Activa, Cuerpo y Ambiente (ACE²Lab) Member: Evolución y Cognición Humana (EvoCog) research group Thesis Director: PhD program in Cognition and Human Evolution Specialties: Neurosciences, Neurophysiology, Human Physiology His teaching spans multiple psychology programs, with recent courses including Memory and Cognition for undergraduate Psychology students, Cognition and Brain for the Master's in Cognition and Human Evolution, and Social Cognition and Brain for the new Master's in Cognition and Society. He supervises both Master's and undergraduate thesis projects across these programs.

Joseph KasprzykView profile

Associate Professor

• Water Resources Planning
• Decision Making Under Uncertainty
• Multiobjective Evolutionary Algorithms
• +3 more

Joseph Kasprzyk is an Associate Professor and Associate Chair for Graduate Education in the Department of Civil, Environmental and Architectural Engineering at the University of Colorado. He specializes in hydrology, water resources, and environmental fluid mechanics. His research focuses on decision making under uncertainty, multiobjective optimization, and scientific visualization in water systems planning. He holds a PhD (2013), MS (2009), and BS (2007) in Civil Engineering from Penn State University. Education: PhD in Civil Engineering, Penn State University, 2013 MS in Civil Engineering, Penn State University, 2009 BS in Civil Engineering with Honors, Penn State University, 2007 Research Interests: Optimization of water resources systems Climate change adaptation strategies Participatory decision support frameworks Multiobjective evolutionary algorithms Model diagnostics and visualization Key Contributions: Developed the Many Objective Robust Decision Making (MORDM) framework Pioneered participatory tools like ParFAIT for decision support Advances in linking water-energy systems through optimization Scientific Awards and Recognition: EPA STAR Graduate Fellowship (2010-2013) Outstanding Reviewer for ASCE Journal of Water Resources Planning and Management Invited presenter at SIAM Computational Science conferences Professional Engagement: Member of ASCE Environmental Water Resources Institute Reviewer for major journals including Environmental Modelling and Software Active in curriculum development for water systems analysis Labs and Teams: Involved in interdisciplinary water resources research groups, including collaborations with organizations like NOAA and the NSF-funded projects on robust decision making in infrastructure systems.

• Artificial Intelligence
• Machine Learning
• Edge Computing
• +7 more

Huan Liu is a Professor at Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, with research spanning artificial intelligence, edge computing, and interdisciplinary applications. His work bridges theoretical advances with real-world implementations across healthcare, transportation, and environmental systems. His primary research interests include: Artificial Intelligence and Machine Learning for complex system optimization Edge-Cloud Computing architectures for IoT and vehicular networks Medical image analysis and clinical decision support systems Graph neural networks and multimodal learning Privacy-preserving federated learning frameworks Recent publications demonstrate strong emphasis on applied AI, with 15+ 2025 papers addressing UAV swarm intelligence, medical diagnostics, and sustainable transportation through novel algorithmic approaches. Publication trends reveal consistent leadership in: Developing efficient edge computing solutions for dynamic environments Creating medical AI tools with clinical validation Innovating in graph-based and multimodal learning Applying optimization techniques to logistics and environmental challenges His work frequently appears in top venues including IEEE Transactions, Bioinformatics, and AAAI.

• Irrigation
• Agricultural Water Management
• Sub-Saharan Africa
• +7 more

Charlotte de Fraiture is a Professor in Water Resources Management, affiliated as an external employee. Her research focuses on sustainable irrigation systems, agricultural water management in Sub-Saharan Africa, and Ethiopia. She explores topics like rainwater harvesting, sedimentation reduction in canals, and livestock-irrigation interactions. Recent work emphasizes adaptive strategies in uncertain environments, such as smallholder farming investments and policy approaches. Her publications analyze case studies in climate change adaptation, hydrodynamic modeling, and participatory design of irrigation systems. She supervises PhD candidates in projects like financing modalities for smallholder farmers and GIS applications in water management. Projects include remote sensing for crop yield estimation and policy frameworks for farmer-led irrigation along sand rivers. No scientific awards are listed, but her work contributes to environmental science and agricultural engineering. Her research integrates engineering, policy, and socio-economic factors to enhance water resource sustainability in developing regions.

• Statistical Genetics
• Graphical Models
• Genomics
• +5 more

Pariya Behrouzi is an Assistant Professor in the Department of Mathematical and Statistical Methods - Biometris at Wageningen University & Research. She specializes in developing statistical methodologies with applications in genetics, genomics, and nutrition science. Her research focuses on graphical models, copula theory, and Bayesian approaches to analyze complex biological systems. Behrouzi leads or collaborates on projects such as SignAphy (plant signaling dynamics) and Sensing Age (epigenetic aging studies). She co-developed the netgwas R package for network-based genome-wide association studies. Her work bridges statistical theory with practical applications in agriculture, nutrition, and computational biology. Education: PhD in Statistics (as indicated by title) Key Research Tools: Copula graphical models, spatial statistics, and Bayesian networks Current Projects: Multi-omics network reconstruction, resilience in lettuce crops, and microbiota systems analysis Her recent publications explore topics like meat analogue texture optimization, telomere length dietary correlations, and plant disease resistance mechanisms. Behrouzi advises four PhD candidates and collaborates with international teams on interdisciplinary research.

• Virtual Reality
• Augmented Reality
• Human-Computer Interaction
• +7 more

Professor Yi-Ping Hung is a distinguished faculty member in the Department of Computer Science and Information Engineering at National Taiwan University's College of Electrical Engineering and Computer Science. With a prolific publication record spanning over three decades from 1988 to 2025, Professor Hung leads research at the intersection of virtual reality, human-computer interaction, and computer vision. Their work bridges theoretical innovation with practical applications in health monitoring, biomechanics, and immersive technologies. Professor Hung's research interests focus on creating novel interaction paradigms for virtual and augmented reality environments, with particular emphasis on multisensory feedback systems. Their lab has pioneered approaches for haptic feedback, gaze-based interaction, and physiological response integration in immersive environments. Recent work explores breathing-integrated relaxation techniques, wind simulation for VR, and personalized biofeedback systems that demonstrate the translational impact of their research. Analysis of publication trends reveals a consistent focus on making virtual experiences more natural and embodied, with increasing integration of machine learning techniques in recent years. Professor Hung's team has developed innovative systems for Tai Chi training, archaeological simulation, and mental wellness applications that showcase practical implementations of their research. Professor Hung has mentored numerous graduate students who have become first authors on significant publications, including Ping-Hsuan Han, Yang-Sheng Chen, and Kuan-Wei Tseng. The research group maintains strong collaborations across disciplines and has secured funding for projects spanning VR hardware development, health monitoring systems, and cultural heritage applications. Current research directions include blockchain applications for environmental stewardship, advanced avatar creation techniques using generative models, and sophisticated sensor fusion approaches for precise indoor localization. The lab continues to push boundaries in creating more immersive, natural, and beneficial human-computer interaction experiences.

Christoph TremmelView profile

Research Fellow

• Brain-Computer-Interfaces
• Electroencephalography
• Biomedical Engineering
• +1 more

Dr. Christoph Tremmel is a Research Fellow in Wellbeing Technology at the University of Southampton. His research focuses on Brain-Computer-Interfaces (BCIs), Electroencephalography (EEG), Biomedical Engineering, and Human-Computer Interaction. He investigates applications such as cognitive workload estimation using commercial in-ear EEG headsets and enhancing virtual communication through synthesized co-presence. His work spans interdisciplinary projects funded by EPSRC, including collaborations on wearable biosensors and low-cost non-contact detection systems. Key research projects include the EPSRC Core Equipment Award 2022/23 collaboration and the 'Enhancing the effectiveness of virtual communication' initiative. Tremmel has published extensively on EEG signal processing, decision confidence prediction, and neural correlates of perceptual tasks. His research integrates machine learning, neurophysiology, and engineering principles to advance human-centric technologies. While no awards are listed, his contributions to wellbeing technology and virtual reality applications highlight his innovative approach to bridging neuroscience and computational systems. Collaborations with colleagues like Prof. M.C. Schraefel and Prof. Mark Spearing reflect his commitment to multidisciplinary problem-solving.