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Jose PicheralView profile

Researcher

• Signal Processing
• Source Localization
• Spectral Analysis
• +3 more

Jose Picheral is an active researcher at the Signals and Systems Laboratory specializing in signal processing with expertise in source localization, spectral analysis, and vibration analysis. His work bridges theoretical methodologies with practical applications in aerospace engineering, acoustics, and mechanical systems monitoring. His primary research interests include: Signal Processing Source Localization Spectral Analysis Vibration Analysis Acoustic Imaging Array Signal Processing Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on sparse signal processing techniques applied to aircraft engine vibration monitoring through tip-timing analysis, high-resolution acoustic imaging methods, and non-uniform antenna array processing. Key trends include the development of OMP-based spectral analysis for blade vibration, manifold learning approaches for impulse response reconstruction, and robust super-resolution techniques for correlated source localization in noisy environments. No scientific awards were documented in the provided source material. The text contains no information regarding student advising activities or research grant funding. He operates within the Signals and Systems Laboratory framework, which concentrates on advanced signal processing solutions for engineering challenges, particularly in aerospace vibration analysis and acoustic source mapping through innovative sparse recovery and manifold-based methodologies.

Andre AmaralView profile

Lecturer

• Spatio-temporal Statistical Modelling
• Bayesian Modelling
• Machine Learning
• +2 more

Dr André V. Ribeiro Amaral is a Lecturer in Statistical Learning at the School of Mathematical Sciences, University of Southampton. His research focuses on spatio-temporal statistical methods for environmental and public health applications, including Bayesian computation and machine learning for infectious disease modeling. PhD in Statistics from KAUST (2023) MSc in Statistics from UFMG (2020) Previous Research Associate at Imperial College London (2024–2025) Key research themes include: Computationally tractable spatio-temporal models Bayesian inference for complex datasets Machine learning integration in statistical frameworks Applications to epidemiology and environmental science His methodological work spans data fusion, preferential sampling correction, and disease spread dynamics, with recent publications on dengue fever nowcasting and Antarctic krill abundance modeling. Teaching: Co-teaching Statistical Modelling II (MATH3091)

David MontwéView profile

Assistant Professor

• Sustainable Forest Management
• Silviculture
• Climate Change Adaptation
• +5 more

David Montwé is an Assistant Professor in Silviculture at the University of British Columbia's Faculty of Forestry, Department of Forest Resources Management. His research focuses on sustainable forest management through silvicultural interventions to enhance forest resilience to climatic extremes. He integrates methodologies from silviculture, growth and yield modeling, tree-ring science, and climate change adaptation to evaluate timber quality impacts and mitigate forest disturbances under climate change. Research Trends: Recent publications highlight his work in drought resilience, biomass estimation via remote sensing, climate-growth relationships, and physiological adaptations in temperate and boreal forests. Studies span experimental drought conditioning, genetic selection, silvicultural treatments, and advanced analytical techniques like deep learning data fusion of ALS and multispectral data.

Talel AbdessalemView profile

Professor

• Database Systems
• Data Mining
• Machine Learning
• +4 more

Talel Abdessalem is a Professor at Télécom Paris , where he has held leadership roles including Director of LTCI Research Laboratory (since 2017) and Dean of Research (since 2018). He currently serves as Deputy Vice-President for Research at Institut Polytechnique de Paris . PhD in Computer Science from Paris-Dauphine University Habilitation (HDR) from UPMC-Sorbonne University His research spans large-scale data management , recommender systems , social network analysis , and uncertain data modeling . He has participated in numerous national (ANR, FEDER) and European (FP7) research projects, with recent work focusing on stream-based learning , graph analytics , and privacy-preserving systems . His publications include diverse contributions to directed graph centrality algorithms (2021), stream recommender frameworks (River, Scikit-Multiflow), and geospatial recommendation models (ALGeoSPF). He has supervised 14 PhD students and collaborates with researchers in France, Brazil, and Indonesia. Co-leads DIG (Data, Intelligence and Graphs) research team Director of LTCI (Information Processing and Communication) laboratory

YUNG Kai-leungView profile

Professor

• Precision Engineering
• Space Instrument Design
• Deep Space Explorations
• +4 more

Ir Professor YUNG Kai-leung, BBS, holds multiple prestigious positions at The Hong Kong Polytechnic University including Sir Sze-yuen Chung Professor in Precision Engineering, Chair Professor of Precision Engineering, Associate Head of the Department of Industrial and Systems Engineering, and Director of the Research Centre for Deep Space Explorations. He is a globally recognized expert in precision engineering with decades of experience in space technology development. Professor Yung earned his MSc from Imperial College London and PhD from the University of Plymouth. His professional background includes positions at BOC Advanced Welding Co. Ltd., British Ever Ready Group, and Cranfield Unit for Precision Engineering before joining PolyU in 1986. His research focuses on: Advanced space instrumentation for lunar and planetary exploration Precision mechatronic systems for extraterrestrial applications Control systems for deep space missions Nanoscale fabrication techniques Logistical optimization for space operations His recent publications demonstrate strong interdisciplinary focus combining space technology with AI, blockchain, advanced materials, and autonomous systems. Research consistently addresses challenges in deep space exploration through innovative engineering solutions. Significant honors include: Bronze Bauhinia Star (BBS) - Hong Kong SAR Government (2015) 49th International Exhibition of Inventions Geneva - Bronze Medal (2024) 1010 Award for Innovation (2001) Editor's Choice Award from MDPI Machines (2022) As Director of the Research Centre for Deep Space Explorations, he leads teams developing critical instrumentation for China's space program including the Camera Pointing System for Chang'e-3/4 lunar missions, Surface Sampling Systems for Chang'e-5/6, and Mars Landing Surveillance Camera for Tianwen-1.

Carlos FilipeView profile

Professor

• Biosensors
• Functional Nucleic Acids
• Smart Food Packaging
• +3 more

Carlos Filipe is a Professor and Associate Dean at the Faculty of Engineering , McMaster University, specializing in biotechnology , biosensors , and smart food packaging . His work integrates functional nucleic acids , DNAzyme technology , and aptamer-based detection for pathogen monitoring in food and clinical contexts. Developed colorimetric biosensors for Salmonella and Escherichia coli Innovated lab-in-a-package systems for rapid, hands-free bacterial testing Created thermally stable sugar films for vaccine preservation and phage antimicrobials Research Interests : Focus on bioactive paper , point-of-care diagnostics , and integrated chemical-biomedical engineering . Key methodologies include microfluidics , surface immobilization , and environment-responsive materials . Recent Publications highlight advancements in phage-activated DNAzyme hydrogels (2025), smart packaging (2024), and universal SARS-CoV-2 aptamers (2022). Articles span Advanced Materials , Nature Communications , and Angewandte Chemie . Teaching Responsibilities : Instructs Chemical Engineering Principles II (CHEMENG 2F04) and co-ordinates Integrated Biomedical Capstone Design Projects across multiple engineering disciplines since 2018. Technical Contributions : Pioneered lab-on-a-chip systems, portable electrospinning , and pullulan-encapsulated bioassay tablets , with applications in water quality , viral diagnostics , and antibody purification .

• Biomedical Engineering
• Chemical Engineering
• Synthetic Biology
• +7 more

Dr. Vincent Leung is an Assistant Professor in the Department of Chemical Engineering at McMaster University , with a focus on interdisciplinary research at the intersection of chemical engineering, biomedical engineering, and synthetic biology. He has contributed to innovations in paper-based diagnostics , biomaterials , and vaccine stabilization technologies. Research Themes Thermal stabilization of viral vaccines using sugar films Evolved bacteriophages for antimicrobial applications Microfluidic paper-based assay development Encapsulation of labile biomolecules Biophysics of cellulose adhesion Teaching Courses in biomedical design, engineering economics, and technical communication Mentoring award-winning iGEM student teams Awards Silver Medal , iGEM (2022) for synthetic biology innovation Patent applications related to vaccine delivery systems Publications 15+ peer-reviewed articles across disciplines: Viruses , ACS Omega , Lab on a Chip , and more His work emphasizes practical solutions for low-resource settings and global health challenges , including portable diagnostics and affordable vaccine storage. Collaborations with McMaster's SynBio Team and industry partners demonstrate his commitment to translating research into real-world applications.

• Microfluidics
• Magnetic Particle Manipulation
• Cellular Engineering
• +3 more

Simon Dumas is a Postdoctoral Researcher affiliated with the Institut Curie in Paris, France. He is associated with the research team Macromolecules and Microsystems in Biology and Medicine (MMBM) under the Cell Physics and Cancer (UMR168) unit. His work focuses on the intersection of microfluidics, magnetic manipulation, and biomedical applications. His research interests include: Microfluidic device design for biomedical diagnostics Magnetic particle modeling and manipulation Droplet-based assays for single-cell and multiomic analysis 3D tissue engineering and cellular alignment Nanoparticle coatings for genomic targeting Tumor-on-a-chip modeling for precision therapy Simon has published extensively on magnetic microtools, including innovations in Magnetic Microtweezers for bioseparation and Multiomic Droplet-Based Assays for ultra-low input samples. His work spans theoretical modeling, device fabrication, and biological applications, particularly in cancer research and cellular engineering. Recent publications highlight advancements in: Remote magnetic actuation of 3D cellular structures Continuum modeling of particle flows in microfluidic suspensions Hybrid in silico and tumor-on-a-chip protein behavior analysis VEGF-functionalized beads for angiogenic disease treatment

Osman ErvanView profile

Researcher

• Autonomous Systems
• Robotics
• Control Theory and Applications
• +2 more

Osman Ervan is a Research Assistant at the Department of Control and Automation Engineering, Faculty of Electrical and Electronics Engineering, Istanbul Technical University. He has been actively contributing to academic research since 2017, with expertise in robotics, autonomous systems, and control theory. His research focuses on robotics and sensor data processing, particularly involving LiDAR systems, point cloud registration, and tensor voting methods. Recent projects include advanced sampling techniques for point cloud data, autonomous robotic imaging systems, and fuzzy logic-based obstacle avoidance algorithms. Key publication trends show a strong emphasis on 3D point cloud processing (2019-2023), sensor configuration optimization (2015-2016), and autonomous navigation systems (2021-2023). His work spans both theoretical and applied aspects of robotics. Dr. Ervan is based at ITU Ayazaga Campus, Istanbul, Turkey. He has published 8 research outputs since 2015, with active collaborations in multi-robot systems development and sensor integration research.

Thomas EngelhardtView profile

Researcher

• Real-Time Rendering
• Global Illumination
• 3D Graphics
• +4 more

Thomas Engelhardt is a Researcher and PhD student at the Computer Graphics Group of the Karlsruhe Institute of Technology (KIT) , Germany. His work focuses on real-time rendering techniques, including global illumination, participating media, and visibility culling. Research Interests: Interactive 3D graphics High-quality lighting simulation GPU-based rendering algorithms Occlusion culling and visibility optimization Participating media rendering Environment mapping techniques Publications demonstrate expertise in virtual point lights, epipolar sampling, hierarchical buffers, and scalable final gathering for global illumination.

Damion CorriganView profile

Professor

• Analytical Chemistry
• Electrochemical Sensing
• Biosensors
• +6 more

Damion Corrigan serves as Professor in the Department of Pure and Applied Chemistry within the Faculty of Science at the University of Strathclyde, holding the prestigious LGC Professorship in Measurement Science for Health. He leads the Centre for Advanced Measurement Science and Health Translation—a strategic partnership between the National Measurement Laboratory (NML) at LGC, University of Strathclyde, and NHS Lanarkshire—and holds fellowships including FRSC (Fellow of the Royal Society of Chemistry). His institutional roles extend to co-chairing CAMS-UK's Measurement Science Institute and serving on UKRI's Interdisciplinary Assessment College and NPL's Industrial Committee on Biosensors. Corrigan's research pioneers diagnostic solutions for drug-resistant bacterial infections, COVID-19, sepsis, cancer, and epilepsy through electrochemical sensing and analytical chemistry. His group specializes in device fabrication, surface functionalization, bioconjugation, and assay development across diverse platforms—from microfabricated arrays to wearable and resource-limited setting diagnostics. Translational impact drives his work, evidenced by founding Aureum Diagnostics (low-cost electrochemical platforms) and Microplate Dx (antibiotic selection technology), earning him the 2023 Academic Entrepreneur of the Year award. His recent publications demonstrate cutting-edge integration of microfluidics with electrochemical biosensors, emphasizing accessible fabrication methods and automated data processing to bridge laboratory innovation with real-world healthcare applications. This work consistently targets cost reduction and scalability for global diagnostic deployment. Key recognitions include: Academic Entrepreneur of the Year - Praxis Auril KE Awards (2023) Edinburgh Bioquarter Innovation Competition (2013) Corrigan actively mentors PhD students and manages 59 research projects (11 active, 47 completed) funded by BBSRC, Tenovus Scotland, and industry partners including GSK, AstraZeneca, and National Nuclear Laboratory. Current initiatives span Berger's Disease diagnostics and sustainable aquaculture health systems in Southeast Asia, reflecting his commitment to interdisciplinary grant acquisition and practical implementation. He directs the Centre for Advanced Measurement Science and Health Translation while leading R&D at Aureum Diagnostics and Microplate Dx. His collaborative ecosystem integrates clinicians, microbiologists, neuroscientists, and engineers to advance measurement science for healthcare, supported by specialized equipment including Autolab Potentiostats and robotic test platforms.

Helge Rørvik RøsjøView profile

Professor

• Cardiovascular biomarkers
• Heart failure
• Intelligent health
• +3 more

Helge Rørvik Røsjø is a Professor II at the University of Oslo and Director of Research and Innovation at Akershus University Hospital. His academic career spans cardiovascular biomarker research, heart failure, and precision medicine within the Department of Internal Medicine and Laboratory Sciences. His research focuses on cardiovascular biomarkers (particularly secretoneurin and cardiac troponins), translational cardiovascular research using population cohorts like the Akershus Cardiac Examination 1950 Study, and intelligent health applications for pragmatic clinical trials. His work bridges laboratory findings with clinical implementation through projects like Clinical Priority Setting (CLINPRI). Recent publications (2023-2025) demonstrate expertise in biomarker validation for arrhythmia prediction, cardiac imaging correlations using CMR, and population-based risk stratification for hypertension and heart failure. His research group frequently publishes in Heart , Clinical Chemistry , and JACC journals. Røsjø has received significant recognition through leadership roles including Head of Research (2013-2018) and current Director of Research and Innovation at Akershus University Hospital. His collaborative network spans Uppsala Clinical Research Center, CardiNor AS, and Spinchip. He mentors extensively as main supervisor for 6 PhD students and co-supervisor for another 6, with research grants supporting projects on cardiovascular biomarkers and pragmatic trials. His laboratory work focuses on secretoneurin assay development and high-throughput biomarker analysis within the Cardiovascular Research Group (CRG).

• Gout
• Rheumatoid Arthritis
• Rheumatic Diseases
• +3 more

Claus Rasmussen is affiliated with Aarhus University's Faculty of Health Sciences and North Jutland Regional Hospital, focusing on rheumatology and metabolic comorbidities. His roles include clinical research, advisory work, and committee memberships. Faculty of Health Sciences, Aarhus University North Jutland Regional Hospital Research interests center on gout epidemiology , rheumatoid arthritis heterogeneity, and immune-mediated rheumatic diseases . His work examines disease activity markers , genetic risk factors , and comorbidity patterns in diabetes and rheumatic conditions. Recent publications highlight gout-diabetes comorbidity , nurse-led urate-lowering strategies, and cross-national rheumatoid arthritis studies. Awards include multiple Danish Rheumatological Society prizes and the Quality Prize (2005). Danish Rheumatological Society Lecture Competition First Prize (2013) Danish Rheumatological Society Lecture Competition First Prize (2008) Best Poster in Congress (2007) Quality Prize from Lis Harriet and Hans Ulrik Hansen (2005) His clinical expertise extends to orthopedic infection diagnostics and multidisciplinary back clinic development . He has served on the Danish Health Authority assessment committee (2007–2010) and participated in the TURKBIO collaboration (2010–2011).

• Clinical Bioinformatics
• Antimicrobial Resistance
• Rapid Diagnostics
• +3 more

Rafi Ahmad is a Professor at UiT The Arctic University of Norway specializing in Clinical Bioinformatics, based in Tromsø. He leads translational research within the Clinical Bioinformatics Research Group, focusing on accelerating infectious disease diagnostics through novel sequencing technologies to transform clinical decision-making for sepsis and urinary tract infections. His research centers on antimicrobial resistance (AMR) profiling and rapid pathogen detection using culture-independent methods. Key innovations include nanopore sequencing workflows that reduce diagnostic turnaround times from days to 4-9 hours, enabling real-time treatment adjustments. He investigates microbiome dynamics in inflammatory conditions like ulcerative colitis and develops machine learning-enhanced biosensors (e.g., SERS nanowire chips) for strain-level bacterial identification. His work bridges clinical microbiology, bioinformatics, and One Health frameworks to address AMR globally. Analysis of his 2022-2025 publications reveals a consistent trajectory toward point-of-care diagnostic implementation , with emphasis on urine, blood, and tissue samples. Methodologies prioritize speed ( As an active member of the Clinical Bioinformatics Research Group (MH øst L9.105B), he collaborates internationally on projects like AMR-Educate, focusing on technology transfer from research to clinical practice. His lab specializes in optimizing sequencing protocols for real-world use, including sample preparation enhancements that bypass culture steps.

Matteo SantacesariaView profile

Associate Professor

• Inverse Problems
• Mathematical Analysis
• Medical Imaging
• +3 more

Matteo Santacesaria is an Associate Professor at the Department of Mathematics (DIMA) of the University of Genoa. His research focuses on inverse problems, mathematical analysis, and their applications in medical imaging and machine learning. He teaches courses such as Mathematics for Architectural Sciences, Mathematical Analysis I, and Company Internship for Mathematics students. His work bridges theoretical mathematics with practical applications, including compressed sensing, MRI and CT reconstruction, and deep learning techniques. Recent projects involve developing algorithms for artifact correction in medical imaging and sparsity-promoting regularizers for inverse problems. He actively contributes to international conferences like SSVM and collaborates on manifold learning and variational methods. His research emphasizes interdisciplinary solutions for imaging challenges and optimization in inverse problem frameworks.