جست‌وجوی استاد و پژوهشگر

• Physics
• Thermal Analysis
• Alternative Fuels
• +۵ مورد دیگر

Dr. Vlasta Vozárová serves as an Associate Professor at the Department of Physics within the Faculty of Engineering at Slovak University of Agriculture. She holds the administrative position of Vice-dean at the Faculty of Engineering and is affiliated with the Institute of Electrical Engineering, Automation, Informatics and Physics. Her educational background includes physics and engineering disciplines, as reflected in her academic position and research supervision. While specific educational details aren't provided in the source material, her expertise is evident through her extensive supervision of student research. Dr. Vozárová's research interests primarily focus on physical properties of materials , thermal analysis , alternative fuels , and biomass energy . Her work demonstrates a strong emphasis on applying physics principles to engineering problems, particularly in renewable energy applications. She has extensively utilized Differential Scanning Calorimetry (DSC) and other physical methods for material characterization. Analysis of her supervised theses reveals consistent research themes in temperature effects on material properties, characterization of alternative lubricants and biofuels, and applications of physics in engineering education. Her recent publications indicate continued focus on thermal stability analysis of biofuels and physical properties characterization of sustainable materials. Her academic service includes significant mentorship, having supervised over 90 theses across bachelor, diploma, and dissertation levels. The breadth of topics she supervises demonstrates her interdisciplinary expertise connecting physics with practical engineering applications. Dr. Vozárová maintains active engagement in engineering education, particularly in developing electronic teaching support systems for physics instruction. Her office is located at IEEAIF FE, Tr. A. Hlinku 2, Nitra, with contact information publicly available through the university directory.

• Combinatorial Optimization
• Operations Research
• Artificial Intelligence
• +۳ مورد دیگر

Corinne LUCET-VASSEUR is a University Professor at Université de Picardie Jules Verne (UPJV), leading Research Unit UR 4290 (OCIA - Optimisation Combinatoire, Images et Applications). Her office (Room 302, Tel: 5900) serves as the hub for her research group focused on combinatorial optimization and artificial intelligence applications. Her research spans: Combinatorial Optimization : Developing metaheuristics for NP-hard problems Healthcare Logistics : Patient flow optimization, facility location, simulation training Logistics Engineering : Parcel distribution, vehicle routing with time windows Algorithm Design : Ant Colony Optimization, Adaptive Large Neighborhood Search, portfolio methods She applies these methodologies to solve complex real-world problems, particularly in healthcare systems where resource constraints and scheduling complexity demand innovative optimization approaches. Her work bridges theoretical advances with practical implementation through industrial partnerships. Current research projects include: SMILE PICK UP (CIFRE industrial partnership) Simusanté (healthcare simulation) LORH (logistics optimization) These projects secure ongoing funding and provide doctoral training opportunities through industry collaboration. Her publication record demonstrates consistent methodological innovation applied to healthcare and logistics challenges across multiple European conferences and journals. Professor Lucet-Vasseur actively mentors junior researchers through co-authorship on conference papers and journal articles. Her supervision style emphasizes practical problem-solving with industry relevance, preparing students for both academic and industrial careers in optimization. The OCIA research unit provides a collaborative environment for tackling complex combinatorial problems with real-world impact. The OCIA laboratory serves as UPJV's center for combinatorial optimization research, specializing in metaheuristic development for healthcare and logistics applications. The lab maintains strong industry connections through CIFRE contracts and applied projects, ensuring research relevance while providing students with exposure to real business challenges. Current focus areas include adaptive algorithm selection using reinforcement learning and fitness landscape analysis for optimization problems.

• Intelligent Transportation Systems
• Control Theory
• Optimization
• +۳ مورد دیگر

Abdelkader EL KAMEL serves as a Lecturer at Centrale Lille, affiliated with the OSL research team within the CRIStAL laboratory. His office is located in room C339 at the Scientific City campus. His research centers on intelligent transportation systems and control engineering, with specific expertise in vehicle routing optimization, trajectory planning for autonomous vehicles, aperiodic sampling in nonlinear systems, and deep learning applications for mobility modeling. This work bridges theoretical control frameworks with real-world transport challenges. Dr. EL KAMEL has supervised seven doctoral theses: Bing Liu: Control and optimization of intelligent transport systems in the vicinity of intersections (Supported September 9, 2016) Yihan Liu: Optimization of home service vehicle routing problem (Supported June 27, 2017) Qing Shi: Trajectory planning and optimization for an active obstacle avoidance system for intelligent vehicles (Defended January 19, 2021) Qi Sun: Contribution to the control of nonlinear systems under aperiodic sampling (Defended December 15, 2016) Chen Xia: Control and optimization of intelligent transport systems in the vicinity of intersections (Supported November 24, 2015) Jian Zhang: Deep learning vehicle mobility model in intelligent transportation systems (Supported December 7, 2018) DIARY: Thesis details pending institutional notification (All dates subject to event updates) He conducts research within the OSL (Optimization and Systems Laboratory) team at CRIStAL, focusing on algorithmic solutions for intelligent mobility systems.

Sandjai Bhulaiمشاهده پروفایل

پژوهشگر

• Machine Learning
• Artificial Intelligence
• Optimization
• +۴ مورد دیگر

Dr. Sandjai Bhulai is a Researcher at Centrum Wiskunde & Informatica (CWI) in Amsterdam, The Netherlands, and affiliated with Vrije Universiteit Amsterdam. He works in the Stochastics department within the Faculty of Science, focusing on applying machine learning and optimization techniques to solve complex real-world problems across diverse domains including telecommunications, mental health crisis intervention, and operations research. His research spans multiple critical areas of applied mathematics and computer science: Development of novel machine learning evaluation frameworks (Dutch Draw, Dutch Scaler) Optimization algorithms for facility location and supply chain problems Telecommunications signal processing using deep learning Mental health applications, particularly suicide prevention helpline analysis Natural language processing for conversation analysis in crisis intervention Dr. Bhulai's recent work demonstrates exceptional interdisciplinary impact. His Dutch Draw framework provides a universal baseline for binary classification problems that has been adopted across multiple research communities. His mental health research has directly influenced suicide prevention practices through machine learning analysis of helpline conversations, identifying specific counselor interventions that improve outcomes. In telecommunications, he's developed neural network approaches that simultaneously handle multiple modulation schemes, improving efficiency in wireless communications. His scientific contributions appear in leading venues including: Computers and Operations Research Journal of Classification IEEE Open Journal of the Communications Society JMIR Mental Health Journal of Applied Probability Dr. Bhulai maintains strong collaborative relationships with researchers across institutions, particularly with Rob van der Mei at CWI. He has secured funding for impactful projects including the collaboration between Stichting 113 Suicide Prevention and CWI, which applies machine learning to improve crisis intervention services. His work exemplifies how theoretical advances in machine learning can address critical societal challenges.

Jean-François Côtéمشاهده پروفایل

استاد

• Combinatorial optimization
• Stochastic programming
• Mathematical programming
• +۵ مورد دیگر

Jean-François Côté is a Full Professor at the Department of Operations and Decision Systems within the Faculty of Business Administration at Laval University. His research focuses on combinatorial optimization, stochastic programming, and mathematical programming with applications in vehicle routing, cutting and loading problems, and logistics optimization. Dr. Côté holds a Doctorate in Computer Science, Operations Research from the University of Montreal, along with Master's and Bachelor's degrees in the same field from the same institution. His academic credentials provide a strong foundation for his interdisciplinary research at the intersection of computer science and operations research. His research spans several key areas in operations research including: Combinatorial optimization techniques for complex routing problems Stochastic programming approaches for handling uncertainty in logistics Mathematical programming models for integrated decision making Vehicle routing and delivery optimization in various contexts Cutting and loading problems in transportation and manufacturing Professor Côté's recent publication record demonstrates a strong focus on solving complex logistics and transportation problems with mathematical rigor. His work addresses challenging real-world problems including same-day delivery optimization, bike sharing systems, home healthcare routing, and automotive manufacturing sequencing. His methodological contributions include novel algorithmic approaches such as logic-based Benders decomposition, disaggregated integer L-shaped methods, and branch-and-regret algorithms. Dr. Côté has published extensively in top-tier operations research journals including: INFORMS Journal on Computing European Journal of Operational Research Transportation Science Computers & Operations Research Operations Research He actively collaborates with researchers across North America and Europe through the CIRRELT research center. His work addresses practical problems faced by industries including transportation, healthcare, manufacturing, and e-commerce. Professor Côté supervises graduate students working on cutting-edge optimization problems and contributes to advancing both theoretical and applied aspects of operations research. His laboratory, part of the broader research ecosystem at Laval University, focuses on developing innovative mathematical models and algorithms to solve complex decision-making problems in logistics and supply chain management.

• Mathematical Optimization
• Conic Optimization
• Smart Grids
• +۷ مورد دیگر

Miguel Anjos is Professor and Chair of Operational Research at the School of Mathematics, University of Edinburgh. He serves as Deputy Head of School and leads the Data and Decisions research theme. His professional roles extend to Chair of the Mathematical Optimization Society (2023–2025) and Vice-President (International Activities) of INFORMS. He holds Fellowships from the Humboldt Foundation, EUROPT, and the Canadian Academy of Engineering. Research Focus: Mathematical optimization for large-scale nonlinear problems in engineering applications, particularly conic optimization in facility layout and power grid optimization. Collaborations: National Grid ESO, Hydro-Québec, Schneider Electric, Rio Tinto, EDF, and Yeji Data Lab. Datasets: Maintains QAPLIB, FLPLIB, and Jones Benchmark for optimization research. His work addresses smart grid challenges: maximizing grid efficiency, integrating renewables, optimizing energy storage, and enabling customer participation. Former students have secured positions at universities (University of Tennessee, Western Ontario) and tech companies (Amazon, Shopify). Scientific Awards: Fellow of the Humboldt Foundation Fellow of EUROPT Fellow of the Canadian Academy of Engineering He has supervised PhD researchers including Elspeth Adams (2014 MOPTA runner-up), Christian Bingane (2019 CORS Student Paper Competition winner), and Mathieu Tanneau (2018–2021 FRQNT Merit Scholar). His postdocs have contributed to bilevel attacks in AI, energy storage scheduling, and electric vehicle infrastructure planning.

Miodrag Brzakovićمشاهده پروفایل

استاد

• Computer Science
• Quality Management
• Integrated Management Systems
• +۵ مورد دیگر

Miodrag Brzaković is a Full Professor and President of the Council at the Faculty of Applied Management, Economics and Finance, University of Economics and Business in Novi Sad, where he has taught since 2010. His academic leadership spans informatics and general management disciplines within Serbia's higher education sector. His educational background includes: Doctorate in Security Sciences (University of Belgrade, 2009) Master's in Electrical Engineering (University of Belgrade, 1988) Diploma in Telecommunications Engineering (Military Technical Academy Zagreb, 1977) Brzaković's research focuses on the intersection of computer science and management systems, with emphasis on information security standards (ISO 27000), quality management (ISO 9001), and sustainable development applications. His work bridges theoretical frameworks with practical implementations in logistics, healthcare, and tourism sectors, often utilizing multi-criteria decision-making methodologies like EDAS. He actively contributes to standardization through Serbia's Commission KS I1224 for IT security and financial services. Analysis of his 15 most recent publications (2015-2019) reveals consistent application of decision science to real-world problems: tourism site selection, mining safety, urban planning, and personnel management. A dominant theme is adapting international standards (ISO, SERVQUAL) to Serbian industry contexts while addressing ecological and social sustainability. His professional certifications include: Lead Auditor for SRPS ISO/IEC 27001:2013 (Information Security) Lead Auditor for SRPS ISO 9001:2008 (Quality Management) With extensive pre-academic experience directing military telecommunications (1988-1997) and defense IT systems (1997-2006), Brzaković brings operational expertise to his academic role. He has led projects implementing integrated management systems for business information, health information, and sports facilities, often collaborating with Serbian Standardization Institute on security protocols. His current work emphasizes sustainable development frameworks for rural tourism and smart city planning.

Robert Honkeمشاهده پروفایل

استاد

• Materials Science
• Structural Mechanics
• Computational Fluid Dynamics
• +۶ مورد دیگر

Prof. Dr. Robert Honke serves as Research Group Leader for System Simulation at the Institute for Hydrogen and Energy Technology (iwe) and sits on the Advisory Board of the Institute for Circular Economy of Bio:Polymers (ibp) at Hof University of Applied Sciences. His office is located in Building C, Room C117, with Wednesday office hours from 13:00-14:00. With over two decades of academic service since 2003, he bridges theoretical physics and practical engineering applications. Education: Physics studies at University of Regensburg Doctorate in Theoretical Physics (University of Regensburg) focusing on ab initio calculations of nonlinear vibrations on semiconductor surfaces Research Interests: Prof. Honke's work spans sustainable materials engineering and advanced simulation techniques. His primary focus areas include construction materials derived from biogenic residues, efficient thermal storage systems, control mechanisms for building energy management, and lightning strike damage simulation on composite structures. His research integrates computational physics with practical engineering challenges, particularly in aerospace and sustainable energy systems. The consistent thread through his career—from semiconductor surface physics to modern composite materials—demonstrates deep expertise in applying simulation methodologies to real-world structural and energy problems. Publication Trends: His recent publications (2015-2022) emphasize lightning protection for composite aerospace materials, thermal energy storage solutions, and biomass conversion technologies. Earlier works (1996-2002) established foundational contributions to surface physics, semiconductor vibrations, and satellite mirror design. Collectively, his research shows a strategic evolution from fundamental surface physics toward applied sustainable engineering, with computational modeling as the unifying methodology across all periods. Scientific Awards: No scientific awards were documented in the provided materials. Advising and Grants: Prof. Honke teaches core subjects in Master's programs for Composite Materials (structural mechanics) and Mechanical Engineering (CFD/FEM/Mathematics), maintaining strong industry connections from his prior Daimler Group experience. While specific student names and grant details aren't listed, his research group leadership indicates active supervision of graduate projects in simulation-based engineering. Labs and Teams: He directs the System Simulation research group at iwe, focusing on hydrogen technology applications, while contributing strategic guidance to ibp's circular economy initiatives for bio-polymers. These dual roles position him at the intersection of sustainable energy systems and advanced materials research within the university's engineering ecosystem.

• Artificial Intelligence
• Machine Learning
• Data Science
• +۵ مورد دیگر

Professor Kristina Schädler is a faculty member at the West Coast University of Applied Sciences (FH Westküste), where she serves as Professor of Data Processing within the School of Technology. She has been with the university since 2005 and also served as Dean of the Department of Technology. Her academic background includes a PhD in machine learning from TU Berlin, where she was awarded the Chorafas Research Prize for young scientists. West Coast University of Applied Sciences (since 2005) TU Berlin, Institute of Computer Science (1994-1999) Martin Luther University Halle/Wittenberg (1990-1994) Professor Schädler's research focuses on artificial intelligence and machine learning applications, particularly in image processing and data analysis. Her work spans multiple domains including industrial automation, agricultural technology, renewable energy, and animal husbandry. She has led numerous research projects that bridge academic theory with practical industrial applications, with particular emphasis on developing robust image processing systems that can be deployed in real-world settings. Her research portfolio demonstrates a consistent pattern of applying advanced machine learning techniques to solve practical problems across diverse industries. The ANIMET project, which developed facial recognition for horses, and the MaviSeg system for multichannel image segmentation represent her innovative approach to adapting computer vision technologies for specialized applications. Her work often involves close collaboration with industry partners to ensure practical relevance and implementation. Chorafas Research Prize for young scientists Innovationspreis at Equitana (2013) for the ANIMET project Professor Schädler has supervised numerous student theses that have resulted in practical applications across various domains. Her research group has secured funding from multiple sources including the European Commission, BMBF, and regional development agencies. She has established the CICAD project as a sustainable competence center for industrial image processing, which has trained multiple doctoral students through cooperative programs with the University of Lübeck. Her work demonstrates strong industry connections with companies like HIT Hinrichs Innovation + Technik, MBJ Solutions, and Fischer und Tausche Kondensatoren. Her research laboratory focuses on industrial image processing applications, with specialized equipment for 2D/3D imaging, spectral analysis, and machine learning implementation. The CICAD project established a dedicated competence center that continues to develop new applications of image processing technology across multiple industries.

Juan Manuel Corchado Rodríguezمشاهده پروفایل

استاد

• Artificial Intelligence
• Multi-agent Systems
• Wireless Sensor Networks
• +۶ مورد دیگر

Juan Manuel Corchado Rodríguez is a Full Professor with Chair at the University of Salamanca, Spain, where he has held numerous leadership positions including Vice President for Research and Technology Transfer (2013-2017), Director of the Science Park, Director of the Doctoral School, and Dean of the Faculty of Science (elected twice). He belongs to the Department of Computer Science and Automation and leads the BISITE Research Group focused on Bioinformatics, Intelligent Computing Systems and Educational Technology. His educational background includes a PhD in Computer Sciences from the University of Salamanca (1998) with thesis titled "Multi-agent systems based on hybrid artificial intelligence algorithms for real-time predictions and complex series" supervised by Dr. José Rafael García-Bermejo Giner, and a second PhD in Artificial Intelligence from the University of the West of Scotland. Corchado's research spans multiple cutting-edge domains in computer science, with primary focus on multi-agent systems, artificial intelligence, and ambient intelligence. His work integrates these technologies to solve real-world problems in smart cities, healthcare monitoring, energy management, and accessibility. He has pioneered approaches that combine wireless sensor networks with intelligent agents to create context-aware systems that can adapt to user needs and environmental conditions. His research particularly emphasizes practical implementations that bridge theoretical advances with tangible applications. Analysis of his recent publications reveals a consistent trajectory toward increasingly integrated intelligent systems. His work has evolved from foundational multi-agent architectures like PANGEA to sophisticated applications in smart territories, energy management, and healthcare. A notable trend is the convergence of multiple AI techniques (neural networks, case-based reasoning, organizational models) within single frameworks. His research increasingly addresses societal challenges through technological solutions, particularly in sustainable urban development and assistive technologies for vulnerable populations. Corchado directs the BISITE Research Group (Bioinformatics, Intelligent Computing Systems and Educational Technology), which operates within multiple university institutes including the University Research Institute in Animation Art and Technology, the University Institute for Science and Technology Studies, and the Biomedical Research Institute of Salamanca. His team develops practical applications of AI and multi-agent systems across various domains, with particular emphasis on creating technologies that improve quality of life and operational efficiency.

Alfonso González Brionesمشاهده پروفایل

دانشیار

• Ubiquitous Computing
• Ambient Intelligence
• Smart Cities
• +۸ مورد دیگر

Dr. Alfonso González Briones is an Associate Professor in the Department of Computer Science and Automation at the University of Salamanca, where he conducts cutting-edge research in intelligent systems and their applications. He is a prominent member of the BISITE Research Group and has also worked with the GRASIA Research Group at Complutense University of Madrid as a 'Juan De La Cierva' postdoc. His academic journey at the University of Salamanca includes a Bachelor of Technical Engineering in Computer Engineering (2012), a Bachelor's Degree in Computer Engineering (2013), a Master's Degree in Intelligent Systems (2014), and a PhD in Computer Engineering (2018). His research focuses on Ubiquitous Computing and Ambient Intelligence for developing smarter, more energy-efficient cities that improve social welfare and promote sustainable development. His work spans Multiple Agent Systems (MAS), energy optimization, smart cities infrastructure, Industry 4.0 applications, and machine learning techniques for various domains including social networks, transportation, and agricultural systems. Dr. González Briones has published extensively with over 30 journal articles and 60 conference proceedings publications, demonstrating consistent productivity across multiple domains of computer science and artificial intelligence. His research trends show a clear progression from foundational work in multi-agent systems toward increasingly sophisticated applications in smart cities, energy management, and Industry 4.0 contexts, with a growing emphasis on practical implementations that address real-world challenges. 2nd place in 1st SENSORS+CIRTI Award for best national thesis in Smart Cities (CAEPIA 2018) Juan de la Cierva State Program Grant in ICT - Information and Communication Technologies (2018) Member of scientific committees for Advances in Distributed Computing and Artificial Intelligence Journal (ADCAIJ) and British Journal of Applied Science and Technology (BJAST) Reviewer for prestigious journals including Supercomputing Journal, Journal of King Saud University, Energies, Sensors, Electronics, and Applied Sciences As an active researcher, Dr. González Briones has participated in 10 international research projects and served on technical committees for prestigious international conferences including AIPES, HAIS, FODERTICS, PAAMS, and KDIR. His work bridges academic research with practical industry applications, particularly in energy optimization systems, IoT, and Machine Learning solutions for real-world problems. He has also collaborated with private research centers including Virtual Power Solutions in Portugal and AIR Institute, where he worked as Project Manager in Industry 4.0 and IoT projects. His research infrastructure includes work with the BISITE Research Group, where he develops and implements multi-agent architectures for optimizing energy consumption and other complex systems. His laboratory work spans smart home energy management, intelligent transportation systems, semantic analysis for Industry 4.0, and social network analysis applications.