جست‌وجوی استاد و پژوهشگر

• Echocardiography
• Congestive Heart Failure
• Left Ventricular Assist Device
• +۶ مورد دیگر

Mihai Strachinaru is a Researcher at Erasmus MC's Department of Cardiology, focusing on advanced imaging techniques and cardiovascular research. His work integrates echocardiography, particle image velocimetry, and MRI to study heart failure mechanisms and coronary microcirculation. He collaborates internationally on topics such as left ventricular function validation and burn wound infection management. Research interests include echocardiography applications in cardiovascular diseases, thermal burn infection control, and prognostic markers for heart failure. His recent studies explore high-frame-rate imaging modalities and multi-modal image validation techniques. Professional activities include peer-reviewed publications in Ultrasound in Medicine and Biology and Clinical Research in Cardiology .

Jérôme Jacquinمشاهده پروفایل

پژوهشگر

• Pragmatics
• Enunciative Linguistics
• Interactional Linguistics
• +۷ مورد دیگر

Jérôme Jacquin is a researcher (MER 1) in the Section of Language and Information Sciences at the Faculty of Arts, University of Lausanne, a position he has held since 2017. He previously served as a graduate assistant (2007–2012) and senior lecturer (2012–2017) in general and French linguistics at the same institution. His academic work is deeply embedded in linguistic pragmatics, with a particular focus on argumentation and epistemic positioning in spoken interaction. His research interests center on the pragmatics of language, especially in enunciative and interactional frameworks. He investigates how individuals express and negotiate knowledge—epistemic positioning—through linguistic and multimodal means in contexts such as political debates, business meetings, and medical interviews. His work integrates multimodal analysis, examining how gesture, gaze, and other nonverbal cues contribute to argumentative practices. He also contributes to methodological reflection on corpus construction and digital processing in linguistics, particularly through projects like IMPACT and POSEPI. His recent publications reflect a strong trend toward empirical, corpus-based studies of epistemic and evidential markers in French, with increasing attention to multimodal dynamics in argumentation. These works span political discourse, workplace communication, and digital environments, demonstrating a consistent focus on how language constructs knowledge and identity in interaction. Scientific Awards: Early Postdoc.Mobility grant from the Swiss National Science Foundation (2014–2015) Ambizione grant from the Swiss National Science Foundation (2016) Through these grants, he conducted research at Victoria University of Wellington and ENS-Lyon’s ICAR laboratory, focusing on argumentation in professional settings and multimodal interaction. He has been actively involved in interdisciplinary collaborations, contributing to pedagogical tools like IMPACT for oral data transcription and analysis. While no formal advisees are listed, his leadership in research projects suggests an advisory role in training emerging scholars. His work continues to advance the integration of digital methods and multimodal analysis in linguistic pragmatics. Laboratories and Projects: Language in the Workplace Project (Victoria University of Wellington) ICAR Laboratory (ENS-Lyon) POSEPI Project (Corpus on Epistemic Positioning) IMPACT Tool (Transcription and commentary platform for oral data)

• Network Science
• Cybersecurity
• Data Analysis
• +۳ مورد دیگر

Matthew Roughan is a Professor and Interim Director of the Teletraffic Research Centre at the University of Adelaide. His research focuses on network science, cybersecurity, data analysis, and statistical modeling. He is affiliated with the University's academic community and contributes to both theoretical and applied research in these domains. His work spans diverse areas including satellite maneuver analysis, causal network discovery, entropy rate estimation, and protocol reverse-engineering. Recent projects highlight advancements in machine learning applications for space surveillance, robust causal network development, and optimization algorithms for multi-modal systems. Roughan's articles reflect a commitment to interdisciplinary approaches, blending mathematics, computer science, and domain-specific knowledge. Notably, his contributions to entropy theory, cybersecurity tool development, and space technology analysis underscore his impact in both academic and practical contexts. His work in Teletraffic Research Centre involves managing interdisciplinary projects and fostering innovation in network and data analysis methodologies.

Niko Suenderhaufمشاهده پروفایل

استاد

• Robotic Vision
• Computer Vision
• Machine Learning
• +۷ مورد دیگر

Professor Niko Suenderhauf is a leading researcher in robotic vision and AI at Queensland University of Technology (QUT). He focuses on enabling robots to understand and interact with their environment through advancements in SLAM, scene understanding, and semantic mapping. His work bridges robotics, computer vision, and machine learning, aiming to create reliable, relatable, and sustainable robotic systems that collaborate with humans to address societal challenges like climate change and aging populations. His key achievements include pioneering graph-based SLAM methods integrated into the ROS ecosystem, developing object-based semantic SLAM systems, and demonstrating the efficacy of deep learning for place recognition. Collaborations with institutions like DeepMind and Amazon reflect his interdisciplinary approach. Awards include recognition for groundbreaking SLAM research and highly cited publications. Research interests emphasize open-world navigation, privacy-preserving vision, and embodied AI, with a focus on practical applications in construction, environmental monitoring, and domestic robotics. His work on uncertainty quantification and robust perception ensures systems operate safely in unpredictable environments. Professor Suenderhauf actively engages in education, mentoring students across undergraduate and postgraduate levels, and emphasizes the societal impact of technology through collaborations with neuroscience, law, and design experts.

• Formal Semantics
• Pragmatics
• Syntax-Semantics Interface
• +۳ مورد دیگر

Wataru Uegaki is a Reader (Associate Professor) and UKRI Future Leaders Fellow at the University of Edinburgh’s Department of Linguistics and English Language, part of the School of Philosophy, Psychology and Language Sciences. He holds a PhD from MIT (2015) and previously taught at Leiden University. His research focuses on formal semantics and pragmatics, exploring how word meanings interact with grammatical structures across languages. He leads two major projects: the UKRI-funded Logic in Semantic Universals (2022-2025) and the AHRC/DFG MECORE project (2021-2024), investigating clausal embedding restrictions and cross-linguistic modal generalizations. Uegaki teaches semantics and pragmatics at undergraduate and graduate levels, emphasizing empirical and theoretical approaches. He has supervised over 20 students, including PhD candidates James Engels and Fred Whibley. His work combines experimental methods with theoretical frameworks, contributing to semantic universals and evolutionary linguistics. Collaborators include institutions in Edinburgh, Konstanz, Amsterdam, and beyond. He maintains active research profiles on his website and Google Scholar .

Yuko Asano-Cavanaghمشاهده پروفایل

مدرس ارشد

• Semantics
• Pragmatics
• Cross-cultural Communication
• +۳ مورد دیگر

Dr. Yuko Asano-Cavanagh is a Senior Lecturer in Japanese within the School of Education at Curtin University, part of the Faculty of Humanities. Her academic work focuses on semantics, pragmatics of Japanese, and cross-cultural communication. She teaches Japanese language and studies, emphasizing cultural nuances and linguistic structures. Education: PhD (ANU) MA (ANU) GradDip (ANU) MEd (Tokyo Gakugei) BA (Tokyo Woman's Christian University) Research Interests: Dr. Asano-Cavanagh explores semantic frameworks like Natural Semantic Metalanguage, analyzing Japanese expressions such as 'kawaii' (cute), 'jishuku' (self-discipline), and cultural pragmatics of danger. Her work bridges semantic theory with sociocultural contexts, examining gender reinforcement, emotional language, and modern societal constructs like 'shukatsu' (job hunting) and 'konkatsu' (marriage partner hunting). Recent studies highlight pandemic-related keywords and cross-linguistic nostalgia analysis. Publications: Her research spans pragmatics, cultural keywords, and language education, with notable contributions to journals like Gender and Language and Philology . Her 2024 publications explore pandemic-era linguistic shifts in Japan, while earlier works analyze 'kawaii' discourse and Japanese evidential markers. Affiliations: She is affiliated with the Australian Linguistic Society, Society for Teaching Japanese as a Foreign Language, and the International Pragmatics Association. Grants & Advising: Though specific grants aren't detailed, her extensive publications indicate sustained research engagement. No advisee list is provided. Labs/Teams: No dedicated lab mentioned, but collaborations with co-authors like R. Cavanagh and G. Farese suggest interdisciplinary teamwork in linguistic analysis.

Shahram Karamiمشاهده پروفایل

پژوهشگر ارشد

• Fluid Flow Instability
• Turbulent flows
• Combustion
• +۴ مورد دیگر

Shahram Karami is a Research Fellow at the Lab for Turbulence Research in Aerospace & Combustion (LTRAC) , Department of Mechanical & Aerospace Engineering, Monash University. His research focuses on high-fidelity simulations (DNS/LES) of turbulent/reacting flows, aeroacoustics, and hydrodynamic instabilities in supersonic impinging jets. He joined Monash in June 2016 under Prof. Julio Soria's supervision. Previously, he completed his PhD (2012-2015) at the University of Melbourne's Combustion Research Group, where he conducted groundbreaking DNS of lifted flames under Prof. Evatt Hawkes and Dr. Mohsen Talei. His PhD work produced influential studies on flame stabilization and edge-flame structures in Combustion and Flame (2016) and JFM (2014). Research Interests: Fluid flow instabilities, turbulent flows, combustion physics, heat transfer, and aeroacoustics. His work contributes to UN Sustainable Development Goals related to clean energy and climate action. Peer Review Activities: Since 2014, he has reviewed for leading journals including International Journal of Heat and Mass Transfer , Combustion and Flame , Physics of Fluids , Aerospace Science and Technology , and Proceedings of the Combustion Institute . Labs/Teams: Active member of LTRAC, collaborating internationally on fluid dynamics and supersonic jet instabilities. His research has been cited over 200+ times, with key contributions to understanding jet noise mechanisms and combustion dynamics.

• Computational Linguistics
• Natural Language Processing
• Text Technology
• +۳ مورد دیگر

Yu Wang is a Lecturer at Bielefeld University's Faculty of Linguistics and Literary Studies, affiliated with the Computational Linguistics department. He is associated with the research project Monitoring the understanding of explanations under Prof. Dr. Hendrik Buschmeier, focusing on digital linguistics and text technology. While his institutional affiliation highlights computational linguistics, his Google Scholar publications reveal interdisciplinary work in optimization algorithms, graph neural networks, and machine learning applications. Research Interests: Yu Wang's work bridges computational linguistics with advanced algorithmic techniques. His publications explore Multi-objective optimization Graph neural network architectures Swarm intelligence applications Evolutionary computation methods Sparse learning systems Biologically-inspired algorithms Labs & Projects: Yu Wang contributes to the Digital Linguistics Group at Bielefeld University, specifically working on explainability monitoring in explanatory processes. His technical publications suggest collaborations with researchers in optimization and machine learning domains.

Emil Alstrup Jensenمشاهده پروفایل

پژوهشگر

• Raman Spectroscopy
• Flow Cytometry
• Biomedical Engineering
• +۴ مورد دیگر

Emil Alstrup Jensen is a PhD student at the Department of Applied Mathematics and Computer Science , Technical University of Denmark. His research focuses on integrating Raman spectroscopy , machine learning , and microfluidic platforms for biomedical applications, including blood typing and flow cytometry innovations. Current projects include Raman spectroscopy and Multi-Modal Machine Learning Models (2024–2027), supervised by L. K. H. Clemmensen, A. Kristensen, and L. E. Pedersen. Collaborations span microfluidics , biomedical engineering , and applied data analysis . His publications highlight advancements in high-throughput Raman spectroscopy , label-free blood analysis , and viscoelastic fluid-based cytometry , often utilizing optical fiber coupling and particle suspension dynamics to improve diagnostic accuracy and efficiency. Project details: Raman spectroscopy and Multi-Modal Machine Learning Models (Active PhD project, 2024–2027) Supervisors: Lars Kai Hansen (Main Supervisor) Anders Kristensen Lars Erik Pedersen Research trends: Combining Raman spectroscopy with artificial intelligence for clinical diagnostics Designing microfluidic platforms for capillary flow cytometry using viscoelastic fluids Optimizing non-transparent solution analysis via flow cell engineering Contact: ealje@dtu.dk

Lisa Fenkمشاهده پروفایل

پژوهشگر

• Visual Neuroscience
• Sensory Processing
• Active Sensing
• +۳ مورد دیگر

Lisa Fenk serves as a Lise Meitner Research Group Leader at the Max Planck Institute for Biological Intelligence in Martinsried, Germany, where she leads the Active Sensing research group. Her position represents a prestigious independent research leadership role within the Max Planck Society's framework for early-career scientists. Dr. Fenk's research focuses on the neural mechanisms of active sensing, particularly investigating how visual systems differentiate between self-generated and external sensory inputs. Her groundbreaking work revealed that fruit flies move their retinas via tiny muscles in ways surprisingly similar to vertebrate eye movements. She leverages Drosophila's advanced genetic, physiological, and behavioral methods to understand how small brains form predictions that inform perception and behavior. Her research spans visual neuroscience, sensory processing, and comparative neuroethology with particular expertise in eye movement systems across species. Analysis of Dr. Fenk's publication record reveals a strong trajectory in visual neuroscience with emphasis on active sensing mechanisms. Her work demonstrates consistent innovation in understanding how organisms extract relevant visual features through purposeful eye movements. The research spans multiple model systems including Drosophila, spiders, and comparative analyses of visual processing across species, with increasing focus on neural circuit mechanisms in recent years. Dr. Fenk maintains an active research program with recent publications in high-impact journals including Science (2024), Nature (2022), and Current Biology (2021). Her work demonstrates strong international collaboration across neuroscience institutions in Europe and North America. As a Lise Meitner Group Leader, Dr. Fenk directs her own research laboratory investigating the fundamental mechanisms of active vision. Her team employs genetic, physiological, and behavioral approaches in Drosophila to uncover how brains differentiate between sensory inputs generated by self-movement versus external events, with broader implications for understanding predictive processing in neural systems.

• Fluid Mechanics
• Microfluidics
• Inkjet Technology
• +۴ مورد دیگر

Balestra Gioele is a Full Professor at the Fribourg School of Engineering and Architecture (HES-SO) and Co-Head of the iPrint Institute. His primary affiliations include the BSc HES-SO in Mechanical Engineering, where he teaches CFD simulation and Fluid Mechanics. He leads the ComplexFluidPrint project (since 2019), developing advanced inkjet technologies for complex fluids. His research focuses on fluid mechanics, microfluidics, and rheology, with recent projects addressing micro-manipulation via liquid plugs and composite materials for IoT applications. Research interests include thin film instabilities, droplet dynamics, and industrial applications of inkjet technology. Notable projects include the experimental validation of liquid plug-based micro-manipulation (2020-2022), funded by HEIA-FR, and a collaborative effort on multifunctional composite materials with COMATEC (2019-2021), yielding 250'000 CHF in funding. His work bridges theoretical models, numerical simulations, and experimental validation. Publications span topics like machine learning for inkjet behavior prediction (2023), karst drapery morphogenesis (2021), and instability mechanisms in curved substrates (2018-2020). Current research emphasizes inertial microfluidics, airflow visualization for inkjet systems, and advanced nozzle plate manufacturing (2024). Grants: HES-SO, HEIA-FR, COMATEC Team Collaborations: Over 20 researchers across projects, including Domae Yoshinori, Maturo Jonas, and Gallaire François Labs/Teams: iPrint Institute, ComplexFluidPrint team

• German Language Studies
• Applied Linguistics
• Translation Studies
• +۳ مورد دیگر

Anelia Lambova is an Assistant Professor of German Language and Culture at New Bulgarian University (Sofia), affiliated with the Department of Foreign Languages and Cultures. She holds a degree in German Philology and Bulgarian Language/Literature from Sofia University. Her career spans over three decades, including roles as Head of Program for 'Foreign Languages and Cultures' and 'German Studies', and membership in the Faculty Council. Her research focuses on German language pedagogy, translation studies, sociolinguistics, and intercultural communication. Notable contributions include works on modal particles in German, business German, and the role of technology in language learning. She has authored/co-authored textbooks like Business Deutsch and participated in international conferences across Europe. Lambova actively engages with academic communities via organizations like IVG and the Bulgarian Association of Germanists. She contributed to Erasmus teacher exchange programs and served on national committees for German language Olympiads.

Yijin Liuمشاهده پروفایل

دانشیار

• Energy Storage
• Materials Science
• Battery Technology
• +۴ مورد دیگر

Associate Professor Yijin Liu is affiliated with the Walker Department of Mechanical Engineering at the University of Texas at Austin. Prior to this role, he served as a Lead Scientist (2020), Staff Scientist (2015), and Associate Staff Scientist (2012) at the SLAC National Accelerator Laboratory, Stanford University. His academic background includes a B.S. (2004) and Ph.D. (2009) in Optics from the University of Science & Technology of China (USTC), followed by postdoctoral research at Stanford. **Research Focus**: Dr. Liu specializes in energy storage materials, particularly leveraging X-ray characterization methods combined with machine learning and data mining. His work addresses challenges in battery manufacturing, safety, degradation, and failure analysis. Key areas include high-throughput experimental methods for battery cathodes, chemomechanical interactions, and in-situ visualization of material dynamics. **Key Technical Contributions**: He pioneered techniques such as operando microscopy for studying particle network dynamics in composite cathodes and developed machine learning frameworks for analyzing material defects and cathode detachment. His methodologies have advanced understanding of oxygen redox mechanisms in layered oxides and thermal-healing processes in battery materials. **Awards**: No specific awards are listed, but his impactful contributions to battery science are reflected in his extensive publication record and leadership in national lab research programs. His work bridges fundamental material science with industrial applications, informing both academic and industrial battery development. **Labs/Teams**: The Liu Group at UT Austin focuses on interdisciplinary approaches to energy storage, integrating advanced imaging, computational modeling, and experimental innovations. Visit his group website for ongoing projects and collaborations.

Pietro Borghesaniمشاهده پروفایل

دانشیار

• Asset Health Monitoring
• Vibration Sensing
• Signal Processing
• +۶ مورد دیگر

Associate Professor Pietro Borghesani is affiliated with the School of Engineering and the Department of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW). He holds an Associate Professor rank and focuses on asset health monitoring, vibration sensing, signal processing, and machine learning applications in mechanical systems. His research spans aerospace and rail industries, emphasizing condition-based maintenance optimization and fault diagnostics. Education: PhD in Mechanical Engineering (2013, Politecnico di Milano), postdoctoral work at Politecnico di Milano, and prior experience at McKinsey & Co. as a business analyst consultant. Research interests include: Health monitoring of rotating machinery Signal processing for diagnostics Machine learning in condition assessment Wear mechanisms in gears and bearings Integration of physics-based models with AI Publications highlight advancements in neural network explainability, vibration-based diagnostics, and cepstral analysis. His work bridges signal processing with tribology and mechanical systems. Grants include projects on railway track geometry monitoring (LP200100382), sugar industry maintenance (LP150100545), and aero-engine bearing health (LP180101161). He is an Editorial Board Member for Mechanical Systems and Signal Processing and a member of the International Society for Engineering Asset Management (ISEAM). Labs/Teams: Collaborations with Australian/international companies in aerospace and rail sectors; involvement in experimental setups for vibration and acoustic emission studies.

• Dynamical Systems
• Control Theory
• Machine Learning
• +۳ مورد دیگر

Mario Sinani is a Researcher and Teaching Assistant in the Department of Aeronautics at Imperial College London's Faculty of Engineering. His research focuses on dynamical systems, control theory, and machine learning applied to nonlinear systems and fluid-solid interactions. He develops data-driven models for nonlinear control of flexible structures interacting with fluid flows under supervision of Dr. Andrew Wynn (Flow Control Group) and Prof. Rafael Palacios (Load Control and Aeroelastics Lab). Education includes a PhD in Data-Driven Modelling and Nonlinear Control from Imperial College London, and MSc/BSc in Mechanical Engineering with a focus on Control Theory and Robotics from National Technical University of Athens. Prior to Imperial, he worked at CERN on particle detector technologies and as an R&D engineer in Zurich developing dynamic light control systems. Teaching responsibilities include Control Systems for MSc students, Flight Dynamics and Control for MEng Aeronautical Engineering, and Applied Aerodynamics courses. His research integrates advanced mathematical analysis with cutting-edge machine learning techniques to address complex fluid-structure interaction challenges in aerospace systems.