جست‌وجوی استاد و پژوهشگر

• Computational Intelligence
• Optimization Algorithms
• Educational Technology
• +۳ مورد دیگر

Zervoudakis Konstantinos is a Researcher at the School of Production Engineering and Management, Technical University of Crete. His work focuses on computational intelligence, optimization algorithms, and their applications in education and product design. He holds a fixed-term research position and is based in Office G3.0.01, Building G3. Research Interests: His primary areas include developing nature-inspired optimization algorithms (e.g., flying fox, mayfly, and bees algorithms), applying computational methods to educational challenges like student psychological fitness assessment and group formation, and optimizing product line design using metaheuristics like Tabu Search and Differential Evolution. He also investigates the impact of ICT on education and special education teacher efficacy. Publications Trends: Recent works emphasize hybrid optimization algorithms for real-world problems (maintenance scheduling, product design), AI-driven educational tools for mental health assessment and learning grouping, and algorithmic solutions for multi-objective decision-making. His research bridges computational innovation with practical applications in education and engineering. Awards: None explicitly mentioned in the provided texts. Advising & Grants: No student advisees listed. No grants disclosed in the data.

• Optimization Algorithms
• Operational Research
• Logistics and Supply Chain Management
• +۳ مورد دیگر

Magda Marinaki is a Researcher at the Technical University of Crete, affiliated with the School of Production Engineering and Management. She is part of the Computational Engineering and Optimization Laboratory, focusing on optimization algorithms and their applications in logistics, transportation systems, and sustainability. Her work spans blockchain technology in maritime logistics, vehicle routing problems (VRP), swarm intelligence algorithms, and energy-efficient transportation solutions. Her research interests include optimization methodologies like genetic algorithms, particle swarm optimization, and grey wolf optimizers. Recent studies address challenges such as electric vehicle charging infrastructure, drone integration in logistics, and flow shop scheduling. She has contributed to both theoretical advancements in metaheuristics and practical applications in supply chain management and environmental engineering. Key Projects: Blockchain applications in port operations, energy-minimizing EV routing, and UAV path planning. Collaborations: Interdisciplinary work on sustainability and smart infrastructure. Marinaki’s publications highlight a focus on solving complex real-world problems through innovative algorithmic approaches, with a particular emphasis on environmental and efficiency metrics.

Bernard Gendronمشاهده پروفایل

استاد

• Combinatorial Optimization
• Logistics
• Transportation Networks
• +۵ مورد دیگر

Bernard Gendron is a Full Professor at the Department of Computer Science and Operational Research (DIRO) at the University of Montreal and a researcher at the Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation (CIRRELT). His research focuses on combinatorial optimization, including polyhedral theory, decomposition methods, metaheuristics, constraint programming, and applications in logistics, transportation, telecommunications, and healthcare. He has held leadership roles, such as Director of CIRRELT (2008–2015) and President of Canadian Operational Research Society (CORS) and INFORMS Transportation Science & Logistics section. He has received awards including CORS Practice (2004), Service (2006), and Merit (2010) Awards. Education: Not explicitly stated in texts, but extensive academic and professional experience implies doctoral-level qualifications. Research Interests: Combinatorial optimization, logistics networks, transportation systems, integer programming, and algorithm design. His work bridges theoretical developments and practical applications, particularly in network design and large-scale optimization problems. Publications: Over 50 peer-reviewed articles, with recent contributions on facility location, network design, and heuristic algorithms. Key areas include subgradient methods, Lagrangian relaxation, and metaheuristic approaches. Editorial & Leadership: Editor-in-Chief of INFOR, member of editorial boards for journals like EURO Journal on Transportation and Logistics. Active in program committees (e.g., Odysseus 2018). Taught courses on optimization, network flows, and mathematical programming. Labs/Teams: Associated with CIRRELT and DIRO research groups focused on transportation and logistics optimization.

Andreas Wittمشاهده پروفایل

استاد

• Operations Management
• Supply Chain Management
• Business Information Technology
• +۳ مورد دیگر

Andreas Witt is a Professor in the Department of Business at Fulda University of Applied Sciences since 2010. His work focuses on operations management, supply chain planning, and business IT, with a particular emphasis on SAP ERP/APO systems and quantitative planning methods. Education: Industrial engineering degree (1991–1997) and part-time doctoral studies (2000–2004) at Technische Universität Braunschweig, dissertation on production planning in the steel industry. His research addresses scheduling optimization, buffer constraints, and production planning in process industries, particularly the steel sector. Publications highlight hybrid flow shop scheduling, batching techniques, and ERP integration for real-world logistics challenges. Recent trends in his articles include algorithm design for constrained scheduling, resource allocation in multi-project environments, and mathematical modeling for production optimization in heavy industries.

• Topology Optimization
• Computational Mechanics
• Acoustics
• +۳ مورد دیگر

Eddie Wadbro is a Visiting Professor at the Department of Computing Science , Umeå University. His research spans computational mechanics, acoustics, and machine learning, focusing on topology optimization and its applications in industrial design, forestry, and electromagnetics. He actively collaborates across disciplines to solve complex engineering challenges. Key Research Areas: Topology optimization, acoustic wave control, machine learning for industrial systems, fluid dynamics Recent Trends: Alzheimer's disease classification via morphological analysis, deep reinforcement learning for autonomous machinery, multiscale material design Collaborations: Works with experts in forestry engineering, electromagnetics, and biomedical imaging.

Amal Abd El-Raoufمشاهده پروفایل

استاد

• Software Engineering
• Software Quality
• Big Data
• +۴ مورد دیگر

Dr. Amal Abd El-Raouf is a Full Time Professor in the Computer Science Department at Southern Connecticut State University, where she has served since 2005. She teaches undergraduate courses including Introduction to Programming, Data Structures, and Algorithms, along with graduate Software Engineering and Software Quality courses. As an active member of the Greater Hartford Association for Computing Machinery (ACM) Chapter, she contributes to the regional computing community. Her academic credentials include a PhD in Computer Science and Engineering from the University of Connecticut (2005) and Bachelor's and Master's degrees from Cairo University. This foundation supports her dual expertise in theoretical computer science and practical software development. Dr. Abd El-Raouf's research spans critical areas of modern computing: Software Engineering and Quality form the core of her work, extended into Big Data analytics, Real-time Systems, Parallel and Distributed Computing, and Object-Oriented Systems. Her investigations address fundamental challenges in software performance, maintenance, and reliability, with recent work bridging into bioinformatics and machine learning applications. Analysis of her 2008-2019 publications reveals an evolving research trajectory: beginning with foundational work in software restructuring and maintenance, she progressively incorporated Big Data techniques and machine learning. Notable trends include applying clustering algorithms to software architecture, optimizing distributed systems, and developing predictive models for sales and software reliability - demonstrating consistent innovation from theoretical frameworks to practical implementations. Her research program is substantially supported by diverse funding sources: NASA Connecticut Space Consortium grants for bioinformatics initiatives ($2,000, 2024-2025) Microsoft Azure Cloud Grant ($20,000, 2016-2017) CSU Research Grants for Big Data performance optimization ($3,000, 2018-2019) and software reliability prediction ($3,750, 2017-2018) NASA Space Grant for cloud-based gene expression analysis ($7,500, 2015-2016) While specific lab infrastructure isn't detailed in available materials, her collaborative publications with researchers like Hanafi and Fergany indicate active research partnerships across institutions. Her current work on the NASA-funded Women in Bioinformatics Workshop signals ongoing expansion into interdisciplinary computational biology applications.

Gang Liمشاهده پروفایل

دانشیار

• Supply Chain Management
• Operations Management
• Optimization
• +۱۲ مورد دیگر

Gang Li is an Associate Professor of Supply Chain and Operations Management at the Department of Management, Bentley University, with affiliate faculty status at Georgia State University. He holds two PhDs: one in Supply Chain and Operations Management from the University of Texas at Austin and another in Systems Engineering from the Beijing University of Aeronautics and Astronautics. Teaching Interests: Operations & Supply Chain Management, Decision Methods, Quality Management Research Interests: Service Process Optimization, Supply Chain Social Impact, Decision Support Systems His research focuses on model and algorithm development for service operations, with emphasis on sustainability integration and societal/environmental impact. Article trends include supply chain sustainability , optimization , service equity , and decision analytics . Award: ASQ Certified Six Sigma Black Belt

Dario Landa-Silvaمشاهده پروفایل

استاد

• Computational Optimization
• Operations Research
• Artificial Intelligence
• +۴ مورد دیگر

Dario Landa-Silva is a Professor of Computational Optimization at the University of Nottingham and a key member of the Computational Optimization and Learning (COL) Lab . He serves as Director of Teaching and Learning in the Faculty of Science and co-leads the Smart Systems and Operations initiative within the TMC Initiative . His academic journey began with a BEng and MSc from institutions in Mexico, followed by a PhD and PHCHE from the University of Nottingham. Education: BEng (Mexico) MSc (Mexico) PhD (University of Nottingham) PHCHE (University of Nottingham) Landa-Silva's research focuses on the intersection of computer science, operations research, and artificial intelligence , applying metaheuristics, hyper-heuristics, and machine learning to solve constrained combinatorial problems like vehicle routing, personnel scheduling, and space allocation. He has pioneered methods integrating optimization with data science, human computation, and computer simulation, particularly in logistics and healthcare applications. His recent publications highlight innovations in renewable energy forecasting , autonomous systems for oil exploration, and hybrid AI optimization techniques. Notable trends include multi-objective approaches , stochastic scenario bundling , and evolutionary algorithms for imbalanced data classification. Scientific Awards: Fellow of Advance Higher Education FHEA (Fellow of the Higher Education Academy) Landa-Silva has supervised numerous PhD students in topics such as workforce scheduling , nurse rostering , and logistics optimization . He has led over £1.2M in research grants from EPSRC , Innovate UK , and industry partners like Unilever , E.ON Energy , and Netacea Ltd . He is affiliated with the COL Lab and the Smart Systems and Operations team, emphasizing practical translation of research into business impact through Knowledge Transfer Partnerships and REF impact case studies .

Flavia Micotaمشاهده پروفایل

مدرس ارشد

• Optimization Algorithms
• Cloud Computing
• Evolutionary Computation
• +۳ مورد دیگر

Dr. Flavia Micota is a Senior Lecturer at the Faculty of Mathematics and Computer Science of the West University of Timisoara. Her academic work bridges theoretical computer science with practical applications in optimization and data analysis. University: West University of Timisoara Faculty: Faculty of Mathematics and Computer Science Her research focuses on: Optimization algorithms and metaheuristics Cloud computing resource allocation Evolutionary computation Medical data analysis using taxonomy-based measures Task scheduling in heterogeneous systems Algorithm design for static and dynamic environments Analysis of her publications reveals trends in applying hybrid optimization techniques to cloud computing challenges, refining metaheuristics for industrial scheduling, and developing taxonomy-driven similarity/dissimilarity measures for medical data classification. Common methodologies include differential evolution, symmetry breaking, and constraint satisfaction frameworks. No scientific awards are explicitly mentioned in the provided data.

• Mechanobiology
• Tissue Engineering
• Augmented Reality
• +۴ مورد دیگر

Antonio Boccaccio is an Associate Professor in the Department of Mechanics, Mathematics and Management at the Polytechnic University of Bari . His research focuses on mechanobiology, tissue engineering, and augmented reality applications. Academic rank: Associate Professor Department: Mechanics, Mathematics and Management Research areas: Scaffold design, Finite element modeling, Stem cell biomechanics His recent work includes: Optimizing lattice spring models for mechanobiology Designing porous scaffolds for bone regeneration Developing augmented reality tools for dental and STEM applications

Samira Shirzaei Nicholsمشاهده پروفایل

استادیار

• Operations Research
• Public Health
• Gender Equity
• +۴ مورد دیگر

Samira Shirzaei Nichols serves as an Assistant Professor in the Department of CISA (Computer Information Systems and Analytics) at the College of Business, University of Central Arkansas (UCA), with contact details including email sshirzaei@uca.edu, office COB 305D, and phone (501) 450-5331. Her academic role integrates quantitative analytics with real-world problem-solving across public health, social equity, and business operations. Her research spans Operations Research, Public Health, and Gender Equity, employing machine learning, statistical modeling, and simulation to address epidemiological forecasting (HIV/COVID-19), gender pay disparities in academia/business, and service system optimization. Key methodologies include ARIMA/SARIMA time-series analysis, RNN neural networks, mixed-methods approaches, and Society 5.0 simulation frameworks, demonstrating interdisciplinary rigor in translating theoretical models to societal challenges like refugee health access and grocery store operational efficiency. Analysis of her 15 publications (2014-2025) reveals an accelerating focus on public health crises since 2020, with 60% of recent work dedicated to pandemic response modeling and gender equity analysis. While early research centered on supply chain optimization (2014-2018), post-2020 outputs pivot toward urgent health applications—evidenced by 5 COVID-19 forecasting studies—and structural inequities, using comparative data (2018 vs. 2021) to quantify gender pay gaps across academic disciplines. Her work consistently bridges technical analytics with human-centric outcomes. No information is available regarding student advising, grant funding, laboratory facilities, or research teams from the provided sources, though her prolific publication record indicates active scholarly engagement.

Yelena Yeshaمشاهده پروفایل

استاد

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

Yelena Yesha serves as Professor and Knight Foundation Endowed Chair of Data Science and AI at the University of Miami's College of Arts and Sciences, with dual appointments in the Department of Computer Science and Department of Radiology. She holds several leadership positions including Innovation Officer at the Frost Institute for Data Science and Computing (IDSC), Director of IDSC AI + Machine Learning, Board Member and Senior Liaison for Industry Interaction at the Institute of the Mathematical Sciences of the Americas (IMSA), and Founding Director of NSF CARTA. Her research spans multiple interdisciplinary domains with strong emphasis on artificial intelligence and data science applications. She develops machine learning models for civil engineering problems like concrete strength prediction, creates blockchain solutions for IoT and government applications, and applies natural language processing to medical imaging and healthcare analytics. Her work demonstrates exceptional ability to bridge computer science with practical applications in engineering, healthcare, and public policy. Analysis of her recent publications reveals a strong trend toward practical AI implementations across diverse fields, with particular focus on healthcare applications (NLP for breast imaging, infectious disease monitoring) and engineering applications (3D-printed concrete, CFRP-confined structures). Her research increasingly incorporates explainable AI techniques like SHAP analysis and develops user-friendly interfaces for practical deployment of complex models. Knight Foundation Endowed Chair of Data Science and AI As Innovation Officer at IDSC and Director of multiple research initiatives, Dr. Yesha oversees significant research programs connecting academic work with industry applications. Her leadership in NSF CARTA indicates involvement in major federally funded research projects. She has served as principal investigator or key collaborator on numerous interdisciplinary grants spanning computer science, engineering, and healthcare domains. Dr. Yesha directs the IDSC AI + Machine Learning initiative and serves as Senior Liaison for Industry Interaction at IMSA, indicating leadership in research teams focused on data science applications. As Founding Director of NSF CARTA, she leads a consortium-level research effort connecting multiple institutions around data science and computing. Her work with IDIOMS demonstrates leadership in healthcare-focused research teams developing infectious disease monitoring systems.

• Operations Research
• Production Planning
• Scheduling
• +۳ مورد دیگر

Semra Tunalı is a Professor at İzmir University of Economics' Faculty of Economics and Administrative Sciences, Department of Business Administration since 2010. She holds a Ph.D. in Computer Sciences from Ege University and has held academic positions at Ege University, Dokuz Eylül University, and as Visiting Fellow at GINTIC Institute of Manufacturing Technology, Northwestern University, and Loyola University. B.Sc. in Industrial Engineering, Ege University (1978) M.Sc. in Applied Statistics, Ege University (1980) MBA, University of Missouri (1985) Ph.D. in Computer Sciences, Ege University (1991) Her research focuses on production optimization, with emphasis on: Buffer allocation in unreliable production lines Capacitated lot sizing with setup carryover Scheduling flexible mixed-model assembly lines Hybrid metaheuristics for manufacturing systems Simulation optimization in industrial applications Combinatorial optimization in production planning Her recent publications (2010-2019) demonstrate expertise in applying heuristic algorithms like genetic algorithms and tabu search to complex production problems, particularly in lot sizing and assembly line optimization. Common themes include: Integration of simulation and analytical modeling Hybrid algorithm development for manufacturing systems Capacity planning improvements through optimization Reliability analysis in production line design

Andreas Kloseمشاهده پروفایل

دانشیار

• Operations Research
• Combinatorial Optimization
• Integer Programming
• +۳ مورد دیگر

Andreas Klose is an Associate Professor at the Department of Mathematics, Aarhus University, Faculty of Science. His work focuses on combinatorial optimization and integer programming, particularly for logistics applications. Active in exact solution approaches for bi-objective and uncertain facility location problems Develops metaheuristics for fixed charge transportation challenges Teaches master courses on location planning, vehicle routing, and optimization methods Research Trends: Recent publications emphasize facility location under uncertainty, exact algorithms for capacitated problems, and metaheuristic approaches. Topics span both theoretical and applied operations research. Teaching: Offers courses on Multiple Criteria Optimization , Location Planning , Vehicle Routing , and Metaheuristics , alternating between fall and spring semesters. Collaborations: Frequently collaborates with researchers like Simon Gadegaard and Kim Jörnsten on facility location and transportation problem frameworks.

Michal Weiszerمشاهده پروفایل

مدرس

• Optimisation
• Metaheuristics
• Operational Research
• +۵ مورد دیگر

Dr. Michal Weiszer is a Teaching Fellow at the School of Engineering and Materials Science, Queen Mary University of London, specializing in optimization, metaheuristics, and operational research with applications in airport operations. His research has significantly contributed to the development of the Active Routing concept for airport ground movement, integrating aircraft engine performance and airframe dynamics with routing and scheduling to achieve greener operations. Dr. Weiszer's research interests focus on routing and scheduling, multi-objective optimisation, simulation, and intelligent transportation systems . His work bridges theoretical optimization techniques with practical aviation applications, particularly in airport ground movement. He has pioneered approaches that integrate aircraft performance models with routing algorithms to reduce emissions and improve efficiency in airport operations. His research spans both algorithmic development and practical implementation, with strong industry connections. Analysis of Dr. Weiszer's publication record shows a consistent focus on airport ground movement optimization using evolutionary algorithms and multi-objective approaches. His research has evolved from basic routing algorithms to more sophisticated integrated systems incorporating aircraft dynamics, emissions modeling, and uncertainty handling. Recent work has expanded into multimodal transportation and open-source simulation platforms, demonstrating the broadening impact of his research beyond traditional airport operations. Dr. Weiszer has received several notable awards and funding: QMUL Flexible Innovation Fund as Principal Investigator EPSRC sponsored TRANSIT project (EP/N029496/1) as Research Co-Investigator Impact Acceleration projects with Avisu as Co-Investigator Impact Acceleration projects with NATS (UK air traffic control) as Co-Investigator His grant portfolio demonstrates strong industry-academia collaboration, with projects translating theoretical research into practical applications. The funding from Royal Society, EPSRC, and industry partners highlights the recognition of his work's potential impact on sustainable aviation. Dr. Weiszer has successfully secured both early-stage innovation funding and larger collaborative projects, showing progression in his research career.