جست‌وجوی استاد و پژوهشگر

• Computer Engineering
• IoT Systems
• Machine Learning
• +۴ مورد دیگر

Dijana Stojić is an Assistant at the Department of Computer and Software Engineering, Faculty of Technical Sciences in Čačak, University of Kragujevac. She has held this position since January 2018 while pursuing her doctoral studies in Electrical and Computer Engineering with a specialization in Computer Engineering, which she began in 2021. Her academic journey began with excellent results at the 'Vuk Karadžić' elementary school in Čačak, followed by the Technical School in Čačak where she majored in computer electrical engineering. She earned her Bachelor's degree in Computer Engineering in 2011 (average grade 9.37) and Master's degree in 2012 (perfect average grade 10.00) from the Faculty of Technology in Čačak. Her Master's thesis, 'Software Support for Active RFID Localization,' was supervised by Prof. Dr. Siniša Ranđić. Dijana's research spans multiple domains within computer engineering, with recent publications focusing on practical applications of technology in diverse fields. Her work demonstrates strong expertise in IoT systems, machine learning applications, blockchain technology, and human-computer interaction. She has published extensively on topics including earthquake detection using mobile phones, predictive models for identifying students with difficulties in online learning, medical applications like ECG monitoring with Arduino, agricultural engineering applications, and infrastructure monitoring systems. Award for best first-year student at Faculty of Technology in Čačak Award for best second-year student at Faculty of Technology in Čačak Her professional activities include serving as Student Vice-Dean at the Technical Faculty in Čačak from December 2010 to September 2012, participating in the TEMPUS SIGMUS project, and completing an internship at D.O.O. DOCUS from June 2013 to June 2014. She was a scholarship holder of the Ministry of Education, Science and Technological Development from April 2013 to March 2017 and has been involved in significant research projects including 'Development and modeling of energy efficient, adaptable, multiprocessor and multisensory electronic low-power systems' (TR 32043) and the 'German-Serbian Collocation Dictionary for German Language and Teaching' (DeSKoll).

Jaime Barrancoمشاهده پروفایل

پژوهشگر

• Biomedical Image Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Jaime Barranco is a Researcher at the Computational Neuroanatomy & Fetal Imaging Section of the Center for Biomedical Imaging (CIBM SP CHUV-UNIL), supervised by Prof. Meritxel Bach Cuadra. His work integrates biomedical image processing, deep learning, and web/software engineering. Education: MSc in Telecommunication Engineering (2020) from Universidad Politécnica de Madrid, specializing in machine learning and multimedia data science. His research includes the A-eye project, funded by the Gelbert Foundation, which develops AI systems for MRI assessment of the eye to advance disease degeneration studies and personalized surgical planning. Collaborators include experts from Rostock University Medical Center and the ARTORG Center. Scientific Awards: Certified Widevine Implementation Partner (CWIP) from Google Jaime combines technical expertise in software engineering (Unity, DRM systems) with biomedical applications, leveraging his background in video streaming technology to innovate in medical imaging.

Boris Tolgمشاهده پروفایل

استاد

• Medical Simulation
• Virtual Reality Applications
• Mass Casualty Incident Training
• +۲ مورد دیگر

Boris Tolg is a Professor of Informatics and Mathematics at the Hamburg University of Applied Sciences , affiliated with the Faculty of Life Sciences and the Department of Biomedical Engineering. He leads the SIMLab and the Research and Transfer Centre for Medicine, Health, and Technology (FTZ MGT), while serving as Pro-Dean for Research and Digitalization. Research Focus: Simulation and virtual reality applications for mass casualty incident (MANV) training and medical education. Expertise: Digital monitoring systems, motion analysis in simulations, and combating simulator sickness. His recent work explores VR-based training tools for emergency response coordination, spine posture analysis sensors, and health impact assessments in urban planning. Publications emphasize scalable solutions for food safety control and digital transformation in healthcare education. Leadership: Chairs the Commission for Safeguarding Good Scientific Practice and contributes to organizations like the ARGH and GI.

Albert Parkمشاهده پروفایل

استادیار

• Social computing
• Group-health informatics
• Human-centered design
• +۷ مورد دیگر

Albert Park is an Assistant Professor in the Department of Software and Information Systems at the University of North Carolina-Charlotte's College of Computing and Informatics. His research bridges computational methods with health informatics applications. Education: BS/MS in Computer Science (Virginia Tech), PhD in Biomedical and Health Informatics (University of Washington) Prior affiliation: NIH-NLM Post-Doctoral Fellow at University of Utah Research focuses on computational analysis of social networks in health contexts, human-centered design of health technologies, and machine learning applications for patient-provider interactions and peer support systems. His lab develops novel methodologies for analyzing social computing platforms and health-related discussions. Recent publications examine Reddit-based mental health communities, vocabulary homophily in online health forums, and NLP tool reliability for analyzing social health data. Key methodologies include text mining, visualization, and longitudinal behavioral analysis. Awards: NIH-NLM Post-Doctoral Fellowship Actively recruiting Ph.D. students with technical expertise in social computing or machine learning and interdisciplinary understanding of social/behavioral sciences.

Mark Stevensonمشاهده پروفایل

مدرس ارشد

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۸ مورد دیگر

Mark Stevenson is a Senior Lecturer in the School of Computer Science at the University of Sheffield, UK. He leads undergraduate programs and serves as a key member of the Natural Language Processing research group , focusing on knowledge extraction from text and user information access solutions. Research Interests : Natural Language Processing Information Retrieval Machine Learning Biomedical Text Disambiguation Lexical Semantics Exploratory Search Systems Scientific Awards : EPSRC Advanced Research Fellowship (2006-2011) Best Paper Award at CLEF 2004 Grants & Projects : He has secured significant funding including the EU FP7 PATHS project (£709,407), EPSRC grants for biomedical disambiguation (£239,920) and Lexical Adaptation (£30,000), and NIHR funding for public health research access systems.

Farshad Firouziمشاهده پروفایل

استادیار مدعو

• Edge Computing
• Internet of Things (IoT)
• Artificial Intelligence
• +۴ مورد دیگر

Farshad Firouzi serves as an Adjunct Assistant Professor in the Department of Electrical and Computer Engineering at Duke University, where he teaches EGR 393: Research Projects in Engineering. His academic work bridges hardware and software domains with a strong emphasis on practical applications in critical systems. His research spans Edge Computing, Internet of Things (IoT), Artificial Intelligence, Machine Learning, Healthcare Systems, Chip Design, and Reliability Engineering. This interdisciplinary focus manifests in projects ranging from Parkinson's disease monitoring using edge devices to LLM-enhanced chip design and security-hardened neural networks. His work consistently addresses real-world challenges in system dependability, particularly in healthcare and biomedical contexts where failure is not an option. Analysis of his 2024-2025 publications reveals three dominant research thrusts: (1) LLM applications in hardware design (ChipMnd, Spiced), (2) Edge-based healthcare monitoring systems (freezing of gait recognition, blood glucose prediction), and (3) Security and reliability in AI/ML systems (gradient inversion defense, silent data corruption mitigation). His work demonstrates a clear trajectory toward integrating cutting-edge AI techniques with hardware-aware solutions for mission-critical applications. No scientific awards were mentioned in the source materials. The absence of student listings or grant information suggests his current role may be primarily research-focused without formal advising responsibilities. Similarly, no dedicated labs or research teams were referenced in the available documentation.

Thomas Boudierمشاهده پروفایل

دانشیار

• Image Processing
• Biomedical Imaging
• Computer Vision
• +۳ مورد دیگر

Thomas Boudier is an Associate Professor at Centrale Méditerranée with additional affiliation as Professor Associate at Sorbonne University's Institute of Biology Paris-Seine (IBPS). His research focuses on bioimage informatics, bridging computer science and biological imaging to develop advanced tools for analyzing complex biological structures. His educational background includes: PhD in Bioimage Informatics from Sorbonne University (1994-1997) Master's in Computer Vision from Nice Sophia Antipolis University (1992-1993) Undergraduate studies in Mathematics from Paris Diderot University (1990-1992) Dr. Boudier's research spans the intersection of computer science and biological imaging, with particular expertise in 3D image analysis and processing. His work has significantly contributed to developing computational methods for analyzing complex biological structures across multiple scales. He has pioneered approaches for electron microscopy image segmentation, 3D reconstruction of cellular structures, and quantitative analysis of tissue organization. His research has important applications in neuroscience, cancer biology, and regenerative medicine, where precise quantification of cellular and subcellular structures is critical. His extensive publication record demonstrates consistent innovation in bioimage analysis, with recent work focusing on deep learning applications for electron microscopy, 3D analysis of neuronal structures, and computational modeling of cardiac cells. His development of specialized software tools like TAPAS, Spot Spine, and CardioVinci has provided the research community with valuable resources for automated image analysis. Throughout his career, Dr. Boudier has maintained strong collaborations across international institutions, including work at Academia Sinica in Taiwan and The Walter and Eliza Hall Institute of Medical Research in Australia. His research laboratory is affiliated with INRIA - National Institute for Research in Digital Science and Technology, where he contributes to advancing computational methods for biological imaging.

• Statistics
• Epidemiology
• Genetics
• +۷ مورد دیگر

Maria De Iorio is a Professor at the Yong Loo Lin School of Medicine and holds a joint appointment at the Faculty of Science , both at the National University of Singapore. Her work bridges statistics, epidemiology, and clinical sciences through advanced Bayesian modeling and computational methods. Key research areas: Statistics, Epidemiology, Genetics, Clinical sciences, Medical biochemistry Primary affiliations: Paediatrics department (YLLSoM) and interdisciplinary projects in Science faculty Recent publications focus on extreme value theory, digital numismatics, metabolomic simulations, and maternal-child health Her statistical innovations include: Repulsive mixture models for interpretable clustering Bayesian semi-parametric approaches for longitudinal studies Novel prior distributions for graphical models Application domains span: Pediatric oncology (ALL treatment response modeling) Metabolic syndrome analysis (obesity, diabetes, bone health) Digital humanities (coin distribution patterns, ceramic artifact analysis) Financial forecasting (discrete survival methods for invoice prediction)

Alva O. Ferdinandمشاهده پروفایل

دانشیار

• Public Health Law
• Health Policy
• Rural Health Disparities
• +۵ مورد دیگر

Alva O. Ferdinand, DrPH, JD, is an Associate Professor in the Department of Health Policy & Management at the Texas A&M University Health Science Center, School of Public Health. As Director of the Southwest Rural Health Research Center, they focus on public health law, rural health disparities, and health policy analysis. Their work bridges legal frameworks with health outcomes, addressing critical issues in diabetes care, emergency department utilization, and health equity. Education: DrPH in Health Care Organization and Policy (University of Alabama at Birmingham, 2013), MPH (2008), JD (Michigan State University, 2006), BA in International Studies (Oakwood University, 2003) Their research explores the intersection of law, health policy, and rural health outcomes, including studies on diabetes-related hospitalizations, emergency care disparities, and the impact of public policies on vulnerable populations. Recent publications analyze maternal health policy, telehealth regulations, and neighborhood effects on pediatric asthma. Key publication trends include rural health disparities (2015-2025), diabetes outcomes (2014-2024), emergency care utilization (2012-2024), and policy evaluations (2013-2024). Subfields span climate epidemiology, health equity, and digital privacy. Teaching interests center on Public Health Law & Ethics. Affiliation with the Southwest Rural Health Research Center drives their focus on regional health challenges.

• Combinatorial optimization
• Heuristic algorithms
• Scheduling
• +۳ مورد دیگر

Marco Ghirardi is an Associate Professor in the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino. His academic work focuses on Operations Research within the broader field of Mathematical and Computer Sciences. His research interests include: Combinatorial optimization Heuristic algorithms Scheduling Professor Ghirardi's work spans multiple domains including industrial automation, traffic systems, and robotics. His research applies mathematical optimization techniques to solve complex real-world problems in manufacturing, transportation, and rehabilitation engineering. His expertise in combinatorial optimization and heuristic algorithms has led to significant contributions in scheduling problems, network optimization, and control systems. His recent publications demonstrate a strong focus on applying operations research to diverse fields: Developing algorithms for fuel treatment scheduling Solving graph theory problems like the maximum happy vertices problem Creating robust traffic assignment models under uncertainty Designing control systems for rehabilitation robotics Professor Ghirardi actively participates in multiple research projects including: NOUS - A catalyst for EuropeaN ClOUd Services (2024-2026) as Research Group Member ESOPO - Exoskeleton for rehabilitation of lower limbs (since 2009) as Scientific Director Design of planning algorithms for production scheduling for SMEs (2022-2023) as Scientific Manager He teaches various courses across different degree programs including: Software architecture for automation Optimization for problem solving Operations Research Industrial Automation Laboratory Heuristics and Metaheuristics for Problem Solving at PhD level

Arndt von Haeselerمشاهده پروفایل

استاد

• Phylogenetic inference
• Phylogenomics
• Neural Networks
• +۴ مورد دیگر

Arndt von Haeseler is a Full Professor for Bioinformatics at the Center for Molecular Biology and Department for Computer Sciences at the University of Vienna, as well as at the Department for Medical Biochemistry at the Medical University of Vienna. He serves as the Scientific Director of the Center for Integrative Bioinformatics Vienna (CIBIV) and was previously Dean of the Center of Molecular Biology at the University of Vienna and Head of the Center for Medical Biochemistry at the Medical University of Vienna from 2017-2020. His research focuses on phylogenetic inference, phylogenomics, neural networks, sequence evolution, and complex patterns of evolution. With expertise spanning mathematics, biology, and computer science, he has made significant contributions to computational biology through the development of algorithms and software tools for phylogenetic analysis. His work bridges theoretical approaches with biological applications, particularly in evolutionary biology and genomics. Dr. von Haeseler's recent publications demonstrate a strong trend toward integrating machine learning approaches with traditional phylogenetic methods, while expanding into single-cell RNA sequencing analysis and organoid modeling. His research spans computational methodology development, evolutionary analysis, and biomedical applications, with a consistent focus on improving analytical frameworks for biological sequence data. Visiting Professor at Division of theoretical Genetics, National Institute of Genetics, Mishima, Japan (since 2012) WWTF Science Chair Award, Vienna, Austria (2005) Honorary Professor for Theoretical Biology, University of Leipzig, Germany (since 1999) PhD scholarship, Studienstiftung des Deutschen Volkes, Germany (1985-1988) He mentors numerous PhD students and researchers, including Heiko A. Schmidt, Alina Leuchtenberger, and Cassius Manuel. His laboratory develops computational methods that have found widespread application in evolutionary biology and genomics research. The Center for Integrative Bioinformatics Vienna (CIBIV), which he directs, serves as a hub for interdisciplinary research bridging computational approaches with biological questions.

Kevin Nolanمشاهده پروفایل

پژوهشگر

• Fluid Dynamics
• Aerosol Transmission
• Medical Engineering
• +۵ مورد دیگر

Dr Kevin Nolan is a Researcher at the UCD School of Mechanical and Materials Engineering , University College Dublin, specializing in fluid dynamics , aerosol transmission , and medical engineering . His work spans surgical safety , renewable energy systems , and microfluidic technologies , with a focus on real-world applications like infection control and wind turbine aerodynamics . Recent research includes modeling surgical smoke leakage , developing standards for face coverings , and analyzing wind turbine blade erosion using advanced fluid dynamic techniques. Collaborations with Mater Hospital , Cisco Systems , and NUI Galway highlight the interdisciplinary impact of his work. Key contributions: Schlieren optical technique for visualizing airflow, European standard development for community face coverings Current projects involve IoT-based air quality monitoring , 3D facial mapping for mask design , and reducing dead spots in air purification Publications address gas leaks in laparoscopy , reusable cloth mask efficacy , and flow friction dynamics , with a strong emphasis on computational fluid dynamics (CFD) and practical mitigation strategies across medical and engineering domains.

• Computational Fluid Dynamics
• Chemical Engineering
• Porous Media
• +۷ مورد دیگر

Gianluca Boccardo is an Associate Professor at the Department of Applied Science and Technology (DISAT) at Polytechnic University of Turin, where he conducts research at the intersection of computational fluid dynamics, deep learning, and porous media applications. His work bridges theoretical chemical process development with practical industrial applications in energy systems and sustainable engineering. His research interests span multiple domains of engineering and computational science: Computational Fluid Dynamics for complex engineering systems Deep learning applications in chemical process modeling Multiscale modeling of transport phenomena in porous media Energy processes engineering and sustainable technologies Fluid mechanics applications in industrial contexts Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional computational methods to solve challenging problems in chemical engineering. His work particularly focuses on applying these hybrid approaches to porous media systems, pharmaceutical processes, and energy storage technologies, demonstrating a commitment to both theoretical advancement and practical industrial application. Professor Boccardo actively supervises numerous PhD students working on cutting-edge research topics and leads significant research initiatives including the MULTIPHASE Erasmus Mundus Joint Master program and the BATCAT Battery Cell Assembly Twin project. His research group receives funding from both competitive EU grants and commercial contracts with industry partners. He is an active member of the Molecular Engineering Lab (MolE) and the Multiscale Modeling research group at DISAT, where his team develops innovative approaches to modeling complex chemical processes and developing sustainable engineering solutions.

Jan Sijbersمشاهده پروفایل

استاد

• Image Reconstruction
• Medical Imaging
• Quantitative MRI
• +۳ مورد دیگر

Jan Sijbers is a Full Professor at the University of Antwerp , affiliated with the Department of Physics . He serves as Spokesperson of the imec-Vision Lab and is a co-founder of spin-offs IcoMetrix and Deltaray . His academic role includes a 10% position as Research Director at imec. Research Interests: Quantitative Magnetic Resonance Imaging (MRI), Tomographic Image Reconstruction, Medical Imaging Algorithms Editorial Roles: Senior Area Editor (IEEE Transactions on Image Processing), Associated Editor (IEEE Transactions on Computational Imaging) Teaching: Courses in Physics, Mathematics, Signal/Image Processing, and X-ray Microtomography Research Trends: His 2025 publications focus on X-ray phase contrast imaging, zebrafish models for bone disease, mesh-based CT reconstruction, and AI-driven biomedical imaging. Earlier works emphasize statistical signal processing in MRI and discrete tomography algorithms. PhD Advisees: He has supervised 68 PhD theses since 2004, with recent topics spanning edge illumination X-ray imaging, 3D knee morphology, and advanced MRI relaxometry. Laboratory Leadership: As head of imec-Vision Lab, he leads research in computational imaging, with applications in medical diagnostics and industrial X-ray systems.

Michael Kochمشاهده پروفایل

استاد

• Robotics
• Additive Manufacturing
• Materials Science
• +۳ مورد دیگر

Prof. Michael Koch is a Professor at Technische Hochschule Nürnberg, specializing in interdisciplinary research at the intersection of robotics, materials science, and industrial engineering. His work focuses on advancing additive manufacturing, robotics integration, and computational simulation in manufacturing processes. He holds a Dr.-Ing. and Dipl.-Wirt.-Ing., reflecting his expertise in engineering and applied sciences. Research interests include 3D printing optimization, cyber-physical systems, and safety analysis of materials under mechanical stress. He has contributed to innovations in robotics programming via augmented reality and developed frameworks for automated manufacturing processes. His studies on biomedical applications, such as ovarian cancer modeling, demonstrate a cross-disciplinary approach. Key projects involve robot-guided CT scanning for automotive industry 4.0, part orientation evaluation for additive manufacturing (Poeam), and safety protocols for explosives (PBX). His work emphasizes integrating real-world geometry data into simulations to improve accuracy and efficiency. Prof. Koch’s publications span over three decades, with a focus on manufacturing, robotics, and materials science. He has pioneered methods for energy-efficient CO2 capture systems and explored microstructural changes in materials under dynamic loading.