جست‌وجوی استاد و پژوهشگر

Ronald Aartsمشاهده پروفایل

استاد

• Ambulatory Monitoring
• Signal Processing
• Biomedical Engineering
• +۶ مورد دیگر

Ronald Aarts is a Full Professor (part-time) at Eindhoven University of Technology (TU/e) in the Department of Signal Processing Systems, affiliated with the EAISI institute. His research focuses on ambulatory and unobtrusive monitoring systems, integrating engineering with medicine and biology. He holds dual roles as a part-time professor and a long-term researcher at Philips Research since 1977. His expertise spans electromagnetism, acoustics, signal processing, and sensor technology. Education: BSc and PhD in Electrical Engineering and Physics from Delft University of Technology. Research Interests: Sensors for biomedical applications, sleep and cardiology monitoring, epilepsy detection, and wearable health technologies. Awards: Gilles Holst Award (1999), Philips Gold Invention Award (2012), IEEE Fellowship (2007), AES Silver Medal (2010). He has supervised over 19 PhD students and holds >250 patents. Key contributions include advancements in EEG-fMRI artifact suppression, non-invasive circulatory monitoring, and sleep state classification in preterm infants.

Ricard Marxerمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Unsupervised Learning
• +۷ مورد دیگر

Ricard Marxer is a Full Professor at the Université de Toulon and a researcher at LIS UMR CNRS 7020. He serves as the founding director of the Erasmus Mundus Joint Master’s Degree in Marine and Maritime Intelligent Robotics (MIR) and leads the DYNamics of Information (DYNI) research team. His work bridges machine learning, artificial intelligence, and bioacoustics with applications in marine robotics, biodiversity analysis, and responsible AI. Key research interests include unsupervised learning, speech and language processing, music technology, and AI safety. Recent work focuses on bioacoustic signal analysis, deep-sea imaging, and scaling speech models. He co-organized the EUSIPCO’24 special session on signal analysis for biodiversity and published a landmark survey on machine learning in bioacoustics. No formal student advisees are listed in the provided texts. His current research infrastructure includes the DYNI team and the MIR program, emphasizing interdisciplinary collaboration between computer science and ecological applications.

Kate Macfarlaneمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Cybersecurity
• Natural Language Processing
• +۷ مورد دیگر

Dr. Kate Macfarlane is a Senior Lecturer in Artificial Intelligence at the Department of Computing and Mathematics, Manchester Metropolitan University. Her work focuses on applying AI and automation to solve societal challenges, particularly in ensuring safe online interactions for vulnerable users. She holds a PhD in Multi-Agent Systems for Online Safety, a BSc in Computer Systems Engineering, and a PGCE. Her professional affiliations include Senior Fellow of the Higher Education Academy (SFHEA) and Member of the British Computer Society (MBCS). Research & Projects Current Project: SafeChat, developing emotion detection systems for safer online communication. Innovate UK Project: Predictive financial models for SMEs with Proforecast Ltd., rated 'Very Good' by Innovate UK. Google DNI Fund's SMART tool: Analyzing social media abuse metrics for journalists. Cyber Eyes Wide Open: Bridging cybersecurity with creative industries through collaborative projects. Technological Family Report: Exploring future technologies' impact on families and connected homes. Key Research Areas Her interdisciplinary research spans AI ethics, distributed systems, game technologies, and cybersecurity. Notable contributions include multi-agent systems for child safety online and VR adoption challenges. She frequently speaks at conferences such as the Great Northern AI Summit and Dynamo 20 Collaborating for Success. Grants & Collaborations Principal Investigator for Innovate UK's Proforecast project. Collaborations with Amazon Web Services (AWS) and Sunderland University's Creative Fuse team. Teaching & Engagement Committed to education innovation, she designs human-centered AI curricula and mentors students in applied research projects.

Felix Schneiderمشاهده پروفایل

پژوهشگر

• Structural Dynamics
• Uncertainty Quantification
• Bayesian Methods
• +۳ مورد دیگر

Felix Schneider is a Researcher at the Chair of Structural Mechanics at Technical University of Munich since 2018. He holds an M.Sc. in Civil Engineering from TU Munich (2018) and completed a semester abroad at the Norwegian University of Science and Technology. His research focuses on uncertainty analysis in structural and acoustic models, Bayesian updating techniques, and stochastic reduction methods in the frequency domain. He has contributed to advancements in rational polynomial chaos expansions and sparse Bayesian learning for structural dynamics applications. Education: 2011-2018: Study of Civil Engineering at Technical University of Munich 2018: Master of Science (M.Sc.) in Civil Engineering 2016: Semester abroad at Norwegian University of Science and Technology 2009: Abitur at Humboldtgymnasium Solingen Research emphasizes computational methods for structural dynamics, including: Bayesian parameter estimation for linear systems Rational surrogate models for uncertainty quantification Frequency-domain stochastic reduction techniques Applications in seismic risk assessment and vibroacoustic simulations Key contributions include a Maurer Söhne Prize for his Master's thesis and a published MATLAB toolbox for rational polynomial chaos expansions on the LRZ Git repository. Teaching responsibilities include courses on random vibrations, structural dynamics, and continuum mechanics. He has participated in research stays at ETH Zurich (2023) and collaborates with international institutions on uncertainty quantification projects.

Wangzhong Muمشاهده پروفایل

مدرس ارشد

• Sustainable Metallurgy
• Microstructure Physics
• Alloy Design
• +۳ مورد دیگر

Prof. Wangzhong Mu is a Senior Lecturer (Docent) in the Department of Materials Science and Engineering at KTH Royal Institute of Technology, Stockholm. His research focuses on sustainable metallurgy, microstructure physics, and alloy design. He leads the thermo-physical property analysis section in the Hultgren Lab and is affiliated with Digital Futures at KTH. Educations: PhD in Materials Science, KTH Royal Institute of Technology (2015) MSc/Bachelor's in Materials Science, Northeastern University, China Research Interests: Inclusion engineering and microstructure-property correlations in steels High-entropy alloy design using digital tools (AI/thermodynamic modeling) In-situ characterization via confocal microscopy and multiscale analysis Recycling-oriented steel production and CO2 reduction strategies Grants/Projects (selected): SSF Strategic Mobility Grant (2023-2024): Clean steel for sustainable future VINNOVA Mobility Grant (2022-2024): Hydrogen-based metallurgy STINT Project (2022-2023): Inclusion engineering for green steel EIT RawMaterials (ENDUREIT, 2019-2021): Durable steels at intermediate temperatures Labs/Teams: Hultgren Lab (materials characterization), Digital Futures (AI-driven metallurgy), and international collaborations with Hanyang University (South Korea), IIT Bombay (India), and Tohoku University (Japan).

• Human-Computer Interaction (HCI)
• Multimodal Interaction
• Visual Analytics
• +۵ مورد دیگر

Denis Lalanne is a full Professor in the Department of Informatics at the University of Fribourg, leading the 'human-building interaction' group at the Smart Living Lab and directing the Human-IST institute . He specializes in Human-Computer Interaction (HCI), focusing on multimodal interaction, visual analytics, and Human-Building Interaction (HBI). His work bridges computer science with architecture and urban design to improve building occupants' comfort and accessibility. His research spans topics such as assistive technologies for visually impaired individuals, energy-efficient lighting systems, and predictive models for indoor environmental quality. He has led projects like the Human-IST Lab and SWICE (Sustainable Well-being in Energy Transition), emphasizing interdisciplinary collaboration between academia, industry, and public institutions. Key contributions include the development of frameworks for human-centric lighting, wearable sensors for urban comfort analysis, and empathic systems to enhance HCI. His work is published in top venues like ACM Transactions on Accessible Computing , IEEE , and CHI . Education and career highlights include a PhD from EPFL (Swiss Federal Institute of Technology), postdoctoral research at IBM’s USER Group, and prior teaching roles at the University of Avignon. He is a Swiss representative at IFIP TC13 and has organized major conferences like IHM 2016.

• Energy Storage Systems
• Materials Science
• Electrochemistry
• +۳ مورد دیگر

Rohit Bhagat is a Professor and Centre Director at the Centre for E-Mobility and Clean Growth. His research focuses on advancing energy storage technologies, particularly lithium-ion batteries, through material science innovations and real-time monitoring systems. Key areas of interest include battery degradation mechanisms, sensor integration for diagnostics, and environmental impact assessments of battery production. Research highlights include developing predictive models for lithium plating detection using machine learning, investigating electrolyte degradation under elevated temperatures, and optimizing cathode materials for zinc-ion batteries. He has led projects such as the British Council MRes scholars initiative in STEM, emphasizing interdisciplinary collaboration. Bhagat’s work spans experimental design methodologies for battery modeling, thermal management strategies, and life cycle assessments. His contributions address critical challenges in battery safety, longevity, and sustainability, with applications in electric vehicles and renewable energy systems.

Francisco Ruizمشاهده پروفایل

دانشیار

• Fuel Atomization
• Internal Combustion Engines
• Regenerative Thermodynamic Cycles
• +۲ مورد دیگر

Dr. Francisco Ruiz is Associate Professor of Mechanical and Aerospace Engineering at Illinois Institute of Technology's Armour College of Engineering, specializing in thermal sciences and energy systems. Education: Ph.D. in Mechanical Engineering from Carnegie Mellon University (1987) M.S. in Mechanical Engineering from Carnegie Mellon University (1985) B.S. in Aerospace Engineering from Universidad Politécnica de Madrid (1983) His research investigates fundamental mechanisms of fuel atomization, cavitation effects in injection systems, and advanced internal combustion concepts including regenerative cycles and natural gas engines. He pioneers computational modeling approaches for combustion optimization and has developed innovative curriculum frameworks for engineering innovation. Publications demonstrate enduring focus on adaptive thermodynamic cycles, combustion stability, and fluid atomization physics. Recent work examines novel engine architectures and combustion modeling techniques for efficiency improvement. Awards recognize research and educational innovation: Tanasawa Award for atomization research (1988) SAE Teetor Award (1990) Chicago Tribune All-Professor Team (1993) He leads the Invention Center pedagogy initiative transforming engineering education through design thinking methodologies. Professional memberships include SAE, Tau Beta Pi, and Pi Tau Sigma.

Jiong Tangمشاهده پروفایل

استاد

• System Dynamics
• Control
• Sensing and Automation
• +۷ مورد دیگر

Jiong Tang is a Pratt & Whitney Chair Professor in Design and Manufacturing at the University of Connecticut , where he also serves as Co-Director of the Management and Engineering for Manufacturing Program . He received his B.S. and M.S. in Applied Mechanics from Fudan University, China (1989 and 1992), and his Ph.D. in Mechanical Engineering from Pennsylvania State University (2001). Prior to joining UConn, he worked at the GE Research Center as a research engineer. Research Interests : System dynamics, control theory, smart materials, vibration suppression, uncertainty propagation, computational intelligence, and multi-physics system modeling. Current Projects : Digital twin development for aerospace materials, physics-informed machine learning in manufacturing, adaptive metasurface design, and optimization of cooperative robotics. Methodological Focus : Combines Bayesian deep learning , Gaussian process metamodeling , transformer-based architectures , and multi-fidelity data fusion for industrial applications. His work emphasizes smart sensing , electromechanical integration , and uncertainty-robust inverse analysis . Collaboration : Research funded by federal agencies and industrial partners , with particular emphasis on aerospace and manufacturing technologies. His recent publications highlight generative adversarial networks for defect detection , piezoelectric metamaterials , and physics-guided neural network architectures across mechanical, structural, and composite systems.

Andrew Hoeghمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Statistical Ecology
• Spatiotemporal Modeling
• +۴ مورد دیگر

Dr. Andrew Hoegh is an Associate Professor of Statistics at Montana State University (MSU), affiliated with the Department of Mathematical Sciences within the College of Letters & Science. He leads the Bozeman Environmental and Ecological Statistics (BEES) research group, focusing on Bayesian computation, spatiotemporal modeling, and ecological applications. His work bridges statistical theory and practical problems in environmental science, epidemiology, and sports analytics. Education: Ph.D. (2016) Virginia Tech; M.S. (2008) Colorado School of Mines; B.A. (2006) Luther College. Research Interests: Bayesian statistics, statistical ecology, computational methods for complex data, and pathogen dynamics in wildlife. His group addresses challenges like bat ecology, zoonotic spillover, and aquatic invasive species using advanced statistical techniques. Awards: Kopriva Faculty Lectureship (2021), multiple nominations for research and advising awards, and grants from institutions like Cornell University and the USGS. Teaching: Courses include Bayesian Statistics, Spatial Data Analysis, and Statistical Computing. Current projects involve bat monitoring, virus spillover modeling, and agent-based movement simulations. Labs/Groups: BEES group meets biweekly, collaborating with USGS scientists. Active projects include bat acoustic data analysis, zebra mussel detection, and radar-based animal movement tracking.

• Ethnomusicology
• Musicology
• Alpine Music Traditions
• +۳ مورد دیگر

Yannick Wey is a Lecturer at the Competence Center for Music Education Research (CC MER) within the Lucerne School of Music at Lucerne University of Applied Sciences and Arts (HSLU). His roles include academic teaching, research coordination, and interdisciplinary collaboration in musicology and ethnomusicology. He holds a PhD from the University of Innsbruck, an MA and BA in Trumpet Performance from Zurich University of the Arts, and has conducted extensive research on Alpine music traditions. Education: PhD in Musicology, University of Innsbruck (2019) MA and BA in Trumpet Performance, Zurich University of the Arts His research focuses on Swiss folk music traditions , including yodeling, alphorn performance, and the cultural history of instruments like the Büchel. He examines musical transcription practices, cognitive aspects of folk music learning, and the intersection of music education with digitalization. Current projects explore Amazonian sound collaboration, KI applications in Alpine music, and safeguarding musical heritage archives. Notable contributions include studies on alphorn tonal reconstruction, dulcimer cultural development, and machine learning classification of yodel styles. His work appears in journals like Music & Science , Journal of Music Research Online , and Anthropos . Awards: SEMPRE 50th Anniversary Commemorative Collection recognition (2022) Nominated for Preis der deutschen Schallplattenkritik (2022) He actively organizes academic events like the Performing, Engaging, Knowing conference and chairs the ICTM Study Group on Multipart Music. His research integrates fieldwork, archival studies, and cross-cultural analysis to preserve and reinterpret Alpine musical heritage.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Sio Kei Im is an active researcher with a focus on computer science, machine learning, and human-computer interaction. His recent work spans multiple domains including image processing, quantum computing, and virtual reality. Publications address advanced data augmentation (LogicMix), multi-modal quantum watermarking (MMQW), and efficient neural decoding algorithms (TRHyper). Research interests include time series optimization, dialogue summarization, and haptics in VR environments. Collaborations with experts in linguistics, electrical engineering, and software development indicate interdisciplinary expertise. Key contributions involve adaptive algorithms for AI model protection, speaker recognition systems, and real-time 3D rendering techniques.

Nori Jacobyمشاهده پروفایل

استادیار

• Cognitive Psychology
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Nori Jacoby is an Assistant Professor in the Department of Psychology at Cornell University and a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt. Her research bridges cognitive science, neuroscience, and machine learning to explore how internal representations shape sensory and cognitive abilities, with a focus on universality/diversity in perception and collective behavior. Education: PhD from Hebrew University of Jerusalem (ELSC), postdocs at MIT, UC Berkeley, and Columbia University Lab: Directs the CoCoCo Lab (Cornell Computational Cognition Lab) Funding: NSF-funded postdoctoral program collaborating with UC Davis, CUNY, and Princeton Research interests include: High-dimensional perceptual spaces using adaptive sampling (e.g., Gibbs sampling with people) Cross-cultural studies of music and perception via global experiments Human-AI hybrid systems for collective creativity and decision-making Recent work explores mechanisms of cultural diversity in urban populations, neural correlates of rhythm in stroke patients, and LLM alignment with human sensory judgments. Current projects include large-scale music evolution experiments and NSF-funded studies on collective intelligence. Recruitment: Actively hiring postdocs and PhD students for interdisciplinary work.

• Aerospace Engineering
• Fluid Dynamics
• Aerodynamics
• +۳ مورد دیگر

Dimitrios Rozakis is an Assistant Professor of Mechanical and Aerospace Engineering. He is actively engaged in research and teaching at the College of Engineering, where he leads the Aerodynamics & Propulsion Laboratory . Education PhD in Aerospace Engineering, National Technical University of Athens (2012) MSc in Fluid Mechanics, University of Manchester (2008) Diploma in Mechanical Engineering, Aristotle University of Thessaloniki (2006) Research Interests His research spans computational and experimental aerodynamics , with particular emphasis on: Transonic and supersonic flows Flow control using plasma actuators Hypersonic boundary-layer transition Reduced-order modelling and machine-learning techniques Turbomachinery aerodynamics Recent work has focused on high-fidelity simulations of buffet phenomena, experimental investigations of plasma-based separation control, and the development of data-driven surrogate models for unsteady aerodynamic loads. Selected Scientific Awards ASME Best Paper Award (2020) European Research Council Starting Grant (2018) AIAA Young Investigator Award (2016) Students, Grants & Funding He currently supervises three PhD students—Maria Koutsogianni, Panagiotis Giannakakis, and Eleni Christoforou—working on projects funded by the ERC, Horizon Europe, and the Greek Secretariat for Research & Technology. Active grants include an ERC Starting Grant on “Physics-informed machine learning for unsteady aerodynamics” (€1.5 M) and a Horizon Europe project on “Green regional aircraft technologies” (€4.2 M). Laboratory & Collaborations He directs the Aerodynamics & Propulsion Laboratory , which houses low-speed and transonic wind tunnels, a Ludwieg-tube facility for short-duration hypersonic experiments, and a high-performance computing cluster (>2 000 CPU cores). Ongoing collaborations include the von Karman Institute, DLR, and ONERA.

• Additive Manufacturing
• 3D Printing
• Manufacturing Technologies
• +۴ مورد دیگر

Irene Buj Corral is a Professor in the Department of Mechanical Engineering at the Polytechnic University of Catalonia (UPC). She is affiliated with the TECNOFAB Research Group (Technologies of Fabrication) and the DigiFACT network, focusing on advanced manufacturing processes, 3D printing, and materials science. Her research emphasizes additive manufacturing techniques, surface finishing, and industrial applications of materials like ceramics and polymers. She contributes to projects such as the development of multi-material 3D printers and bio-compatible prosthetic materials. Key areas of expertise include: Additive Manufacturing, 3D Printing, Surface Engineering, Materials Science, and Industrial Process Optimization. She collaborates on initiatives like the PROHIPP project for high-pressure fluid-power products and has expertise in honing processes, Fused Filament Fabrication (FFF), and Direct Ink Writing (DIW). Her work spans academic contributions, including 422 documented activities (publications, projects, etc.), with a focus on innovation in digital manufacturing and sustainable technologies. She leads research in hybrid 3D printing systems, medical applications of 3D models for surgical planning, and circular economy practices in industrial processes.