جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Data Processing
• Decision Algorithms
• +۶ مورد دیگر

Dr. NAIT CHABANE Ahmed is a Researcher-Lecturer at CESI Saint-Nazaire Campus, specializing in Engineering and Numerical Tools. His research focuses on Artificial Intelligence, Data Processing, Decision Algorithms, and Industry 4.0/5.0 applications. He holds a Ph.D. in Computer Science from University of Western Brittany (UBO Brest) & ENSTA Bretagne (2013). Research Highlights: Developed neural network-based solutions for sonar image segmentation and seabed classification Pioneered multi-objective optimization frameworks for human-robot collaboration in aerospace manufacturing Advanced fatigue evaluation methodologies for manual task scheduling Specializes in LSTM networks for production systems forecasting Awards: Recipient of the IEEE 2nd Student Competition Poster Prize (2013). Supervision: Completed thesis: Guillaume Morin-Duponchelle (2022) Ongoing theses: Pierre Hémono (eXcent), Houssein Olleik (Pilgrim Technology) Supervised international internships (University of Jaipur) Key Labs/Teams: Member of CESI LINEACT research group focusing on engineering and numerical tools development.

• Combinatorial optimization
• Predictive maintenance
• Multi-objective scheduling
• +۵ مورد دیگر

BENCHEIKH Ghita is a Researcher-Lecturer at CESI LINEACT, specializing in Engineering and Numerical Tools. She holds a PhD in Industrial Engineering and Computer Science from the National Engineering School of Tarbes and National Polytechnic Institute of Toulouse (2020) and a Master’s in Operational Research and Decision-Making from the University of Bordeaux (2016). Her research focuses on combinatorial optimization, predictive maintenance, multi-objective scheduling, and metaheuristics, with applications in production planning and maintenance systems. She teaches Computer Science, Operational Research, and Mathematics at the 4th and 5th-year engineering curriculum and master’s level. Her work integrates advanced methodologies such as multi-agent systems, genetic algorithms, and machine learning to address challenges in manufacturing efficiency, predictive maintenance, and logistics optimization. Key contributions include pioneering approaches for joint scheduling of production and maintenance activities, leveraging health assessment of technical resources. She has published extensively in top-tier journals and conferences, including Journal of Manufacturing Systems and IEEE ETFA . Her research has explored topics like vehicle routing problems, flow network optimization, and data-driven predictive analysis for equipment reliability. She is affiliated with the Engineering and Numerical Tools research team at CESI LINEACT, contributing to cutting-edge projects in sustainable development and smart manufacturing systems.

Benjamin Moseleyمشاهده پروفایل

دانشیار

• Operations Research
• Theoretical Computer Science
• Machine Learning
• +۵ مورد دیگر

Benjamin Moseley is the Carnegie Bosch Associate Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University (CMU), with a courtesy appointment in the School of Computer Science's Machine Learning Department. He is also a consulting professor at the start-up Relational AI. Education: PhD in Computer Science from the University of Illinois, advised by Chandra Chekuri. Prior roles include Assistant Professor at Washington University in St. Louis (2014–2017), Research Assistant Professor at Toyota Technological Institute at Chicago (2012–2014), and visiting positions at Sandia National Laboratories and Yahoo Labs. Notable affiliations include the NSF-funded Algorithms, Combinatorics, and Optimization (ACO) PhD program. Research focuses on algorithm design, analysis, and evaluation, with emphasis on operations research, theoretical computer science, and machine learning. Current projects include algorithmic foundations of machine learning, distributed algorithm design, and scheduling/logistics optimization. His work bridges theoretical rigor and practical applications, addressing challenges in big data analysis, streaming algorithms, and approximation techniques. Recognition includes multiple best paper awards (IPDPS 2015, SPAA 2013, SODA 2010), top-tier NeurIPS presentations, and prestigious grants from NSF, ONR, Google, Bosch, and others. His research has been supported by a NSF CAREER Award, Google Faculty Research Awards, and the Carnegie-Bosch Chair. Teaching contributions include developing the Business Analytics and Optimization undergraduate minor at Tepper, courses for UBA/MBA/MSBA programs, and被评为“Top 50 Undergraduate Business School Professor” by Poets and Quants. He emphasizes pedagogy integrating advanced algorithms with business applications. Labs/Teams: Active in Relational AI collaborations and affiliated with CMU's machine learning and operations research research groups. His work frequently intersects with industrial partners like Google, Yahoo, and Bosch.

• Cyber-Physical Systems
• Smart Grids
• Swarm Intelligence
• +۵ مورد دیگر

Prof. Wilfried Elmenreich is a Professor at the Department of Networked and Embedded Systems at Alpen-Adria-Universität Klagenfurt. He serves as a Member of the Senate and Member of the Works Council for Academic Staff. His research focuses on Cyber-Physical Systems, Smart Grids, Swarm Intelligence, and Sustainability Technologies. He leads projects involving swarm robotics, decentralized energy management, and educational technology. Key research areas include: Design of swarm-based algorithms for production scheduling and robotics Development of frameworks like SwarmFabSim for bottom-up optimization Non-Intrusive Load Monitoring (NILM) using neural networks and edge computing Integration of federated learning into smart grid systems Sustainability education and pandemic-related behavioral studies His work combines theoretical contributions with practical implementations, such as the CPSwarm project for swarm system design and the Yomopie energy monitoring tool. Recent publications emphasize interdisciplinary approaches, blending robotics, machine learning, and electrical engineering to address challenges in energy systems and autonomous systems.

Yossiri Adulyasakمشاهده پروفایل

استاد

• Supply Chain Analytics
• Optimization under Uncertainty
• Large-Scale Optimization
• +۴ مورد دیگر

Yossiri Adulyasak is a Full Professor in the Department of Logistics and Operations Management at HEC Montréal, holding the Canada Research Chair in Supply Chain Analytics. He is also an Adjunct Professor at the University of Montreal's Department of Computer Science and Operations Research and a scientific advisor at IVADO Labs. His research focuses on supply chain optimization, data-driven decision-making, and robust optimization under uncertainty, with applications in retail, transportation, and humanitarian logistics. Education: PhD in Operations and Logistics Management (HEC Montréal), Master of Civil Engineering in Transportation Engineering (Chulalongkorn University). Research Interests : Supply chain analytics, large-scale optimization algorithms, stochastic programming, machine learning integration, and resilient supply chain design. His work emphasizes practical applications in logistics networks, inventory management, and dynamic resource allocation under uncertainty. Recent Articles : Focus on AI-driven retail analytics, robust optimization for lot-sizing and facility location, and humanitarian logistics. Key topics include pandemic response strategies, electric vehicle routing, and drone delivery systems. Awards : Recipient of the 2021 Prix de recherche Chenelière Éducation/Gaëtan Morin for excellence in scientific publications. Supervision : Directed 3 PhD dissertations and over 40 master’s and project supervisions, collaborating with companies like Bombardier, Pratt & Whitney Canada, and JDA. Active in industrial partnerships for supply chain optimization solutions. Lab/Teams : Member of GERAD (Group for Research in Decision Analysis) and IVADO Labs, contributing to cross-disciplinary AI and operations research initiatives.

Sonia Cafieriمشاهده پروفایل

استاد

• Nonlinear Optimization
• Global Optimization
• Combinatorial Optimization
• +۳ مورد دیگر

Sonia Cafieri is a Professor at the École Nationale de l'Aviation Civile (ENAC) in Toulouse, part of the Université de Toulouse. She leads the Mathematics of Optimization and Operations Research (MORO) group within the OPTIM research team. Her roles include membership in the Managing Board of EUROPT and the Nonlinear Mathematical Programming group of GdR-ROD. She chairs the Program Committee of EUROPT 2021 and serves on ENAC's Research and Doctoral Councils. Education: HDR in Applied Mathematics (2012, Université Paul Sabatier), PhD (2006, University of Naples), and Laurea in Mathematics (2001, Second University of Naples). Research focuses on Nonlinear Optimization, Global Optimization, Combinatorial Optimization (network clustering), and Operations Research applications in air transportation and engineering. Recent work addresses air traffic management, trajectory optimization, and stochastic programming for robust scheduling. Publications span optimization methodologies and applications, with a focus on aircraft conflict resolution, drone trajectory planning, and robust cyclic scheduling. Software contributions include ROSE (reformulation engine) and COUENNE (MINLP solver). Teaching includes courses on Numerical Analysis, Combinatorial Optimization, and Operations Research for Air Transportation at ENAC and other institutions.

Dalila Fontesمشاهده پروفایل

استاد

• Operational Research
• Artificial Intelligence
• Logistics and Transportation
• +۳ مورد دیگر

Dalila Fontes is a Full Professor at the Faculty of Economics of the University of Porto (FEP) and a board member of LIAAD (Laboratório de Inteligência Artificial e de Apoio à Decisão), a unit of INESC TEC since 2007. She holds a Ph.D. in Management Science from Imperial College London (2000), an MSc in Operational Research from the London School of Economics (1994), and a 5-year degree in Electrical Engineering and Computer Science from the University of Porto (1993). She has served as a Visiting Professor at the University of Florida (2007/08) and Texas A&M University (2015–16). Her research focuses on applying Operational Research and Artificial Intelligence techniques to solve complex management problems in production, logistics, transportation, and services, emphasizing combinatorial optimization. She has authored over 60 publications and coordinates research projects in these areas. She is an Associate Editor for the Journal of Combinatorial Optimization and Operations Research Forum (Springer). At FEP, she teaches Operational Research, Logistics, and Optimization courses in English to undergraduates, masters, and Ph.D. students. She has held administrative roles including Vice-Dean at FEP and currently directs ISFEP (FEP’s Research and Services Institute). Her work bridges academia and industry, addressing sustainable production systems and energy-efficient scheduling strategies.

• Answer Set Programming
• Artificial Intelligence
• Cybersecurity
• +۱۲ مورد دیگر

Prof. Martin Gebser is a University Professor and Deputy Director at the Institute for Artificial Intelligence and Cybersecurity, University of Klagenfurt. His work bridges theoretical advancements in Answer Set Programming (ASP) with practical applications in industrial scheduling, semiconductor manufacturing, and explainable AI systems. Institute for Artificial Intelligence and Cybersecurity, University of Klagenfurt His research focuses on Answer Set Programming and its extensions for complex scheduling problems, particularly in semiconductor production. Key areas include: Multi-shot ASP solving for job-shop decomposition Hybrid AI systems integrating reinforcement learning and logic programming Explainable AI for battery health monitoring and semiconductor dispatching Recent publications emphasize temporal planning, constraint learning, and real-world data integration. He has developed customizable simulators and optimization frameworks for industrial applications.

• Project Management
• Operations Research
• Healthcare Logistics
• +۴ مورد دیگر

Professor Oya Tukel is a faculty member at the MT School of Management, New Jersey Institute of Technology (NJIT). Her research focuses on project scheduling optimization, resource allocation strategies, and operations research applications in healthcare and manufacturing. She has contributed extensively to understanding knowledge management in R&D projects and disaster preparedness logistics. Her work bridges theoretical scheduling models with real-world challenges in supply chain management and organizational innovation. Notable contributions include frameworks for minimizing costs in epidemic response planning and applying customer lifetime value models in manufacturing systems. She has also explored buffer sizing techniques in critical chain scheduling and knowledge transfer practices in dormant projects. Media Highlights: Recognized in 'Education Power 50' listings (2023-2024), recipient of accolades for 'Enterprising Women in Commerce', and featured in NJIT's Sports Data Analytics program initiatives. Research Impact: 1737 citations and an h-index of 13, with publications in journals like International Journal of Managing Projects in Business and Project Management Journal . Her articles demonstrate a focus on interdisciplinary solutions for project management challenges, integrating financial metrics, organizational learning, and operational efficiency. Recent work emphasizes public health preparedness and sustainable R&D practices.

Kelley Waltonمشاهده پروفایل

دانشیار

• Human Resources Management
• Diversity, Equity & Inclusion
• Sport Law
• +۳ مورد دیگر

Kelley Walton serves as an Associate Professor of Instruction in the Department of Sports Administration within Ohio University's College of Business, concurrently directing the Online Master of Sports Administration (OMSA) program. Leveraging over a decade of legal and human resources expertise from her tenure with the Columbus Blue Jackets (NHL), she bridges academic theory with industry practice in sport management education. Her educational foundation includes a Juris Doctor from Capital University Law School and a Bachelor of Science in Interpersonal Communication from Eastern Michigan University, forming the basis for her dual expertise in law and sport administration. Walton's research critically examines Human Resources Management systems in sports organizations, with pioneering work on Diversity, Equity & Inclusion implementation, Sport Law compliance frameworks, and Legal Issues in interscholastic athletics. Her scholarship extends to Career Counseling methodologies for sports industry entry and Youth Sports governance models, consistently emphasizing practical application through case studies and industry partnerships. Her publication trajectory from 2013-2021 reveals evolving expertise from foundational career preparation guides toward sophisticated analyses of sports governance and event management. Key thematic threads include legal risk mitigation in contracts, human capital optimization for mega-events, and educational frameworks addressing systemic inequities in sport professions. As OMSA Director, Walton architects curriculum integrating real-world HR challenges from her NHL experience, emphasizing immigration compliance, workforce management for seasonal events, and inclusive hiring practices. Her industry consulting through K Walton Consulting directly informs program development, ensuring graduates master operational realities of sports organizations. She leads the OMSA instructional team in delivering asynchronous and cohort-based learning experiences, with particular innovation in virtual career preparation modules and industry mentorship networks connecting students with sports executives globally.

William Youngمشاهده پروفایل

استاد

• Operations Management
• Operations Research
• Predictive Analytics
• +۷ مورد دیگر

Dr. William A. Young II is the Charles G. O’Bleness Full Professor of Business Analytics at Ohio University’s College of Business, specializing in the Department of Analytics and Information Systems. He holds a Ph.D. (2010), M.S. (2005), and B.S. (2002) in Electrical and Systems Engineering from Ohio University. His research focuses on operations management, predictive analytics, and decision support systems, with notable work in supply chain optimization, healthcare analytics, and educational technology. Education: Ph.D., Mechanical and Systems Engineering, Ohio University (2010) M.S., Electrical Engineering, Ohio University (2005) B.S., Electrical Engineering, Ohio University (2002) Research Interests: Dr. Young’s work bridges operations research and business analytics, emphasizing practical applications in logistics, healthcare, and education. His studies often employ artificial neural networks and optimization algorithms to address real-world challenges such as inventory management, energy efficiency, and student success prediction. Recent projects include viral marketing incentive models and pandemic risk mitigation in warehouse operations. Publications: His 100+ articles span journals like *European Journal of Operational Research*, *Applied Soft Computing*, and *Expert Systems with Applications*. Key themes include multi-objective optimization, predictive modeling, and decision support systems for complex systems. Awards: 2023 Faculty Excellence Award for Teaching and Learning 2020 University Professor Award Multiple College of Business Research Awards (2017, 2018) 2015 Cincinnati-Dayton Outstanding Young OR/MS Award Grants & Collaborations: He has secured funding from organizations like the National Science Foundation and General Electric Aviation. His interdisciplinary teams address challenges in manufacturing, environmental systems, and educational technologies. Labs & Initiatives: Leads Ohio University’s analytics research efforts, collaborating with industry partners to develop innovative solutions in supply chain, healthcare, and education. His work often integrates artificial intelligence with domain-specific knowledge extraction techniques.

Magdalene Marinakiمشاهده پروفایل

پژوهشگر

• Optimization
• Optimal Control
• Nature Inspired Algorithms
• +۵ مورد دیگر

Magdalene Marinaki serves as a Researcher and permanent laboratory teaching personnel at the Technical University of Crete (TUC), School of Production Engineering and Management. She also teaches in the Hellenic Open University's Social Sciences Graduate Program. Her expertise lies in optimization methodologies, optimal control systems, and nature-inspired algorithms applied to logistics and manufacturing. She holds a Diploma, MSc, and PhD from TUC, specializing in Production Engineering and Management. Her research focuses on computational optimization, metaheuristics, vehicle routing problems (VRP), energy-efficient transportation systems, and structural control. She has authored 4 books and over 50 journal articles, with additional contributions to conference proceedings. Notable projects involve EU-funded research on blockchain applications in maritime logistics, electric vehicle routing, and unmanned aerial vehicle (UAV) path optimization. Her recent work emphasizes sustainable transportation solutions, including EV charging infrastructure planning and drone-integrated delivery networks. She has developed algorithms like teaching-learning-based optimization and hybrid swarm intelligence techniques, addressing real-world challenges in supply chain management and smart manufacturing systems.

• Operations Research
• Optimization
• Logistics
• +۵ مورد دیگر

Reinhard Bürgy is a Part-Time Lecturer at the Department of Computer Science, Lucerne School of Computer Science and Information Technology, Hochschule Luzern (Lucerne University of Applied Sciences and Arts), Switzerland. He concurrently serves as a Solution Architect for Decision Support & Operations Research at Polypoint AG. His academic background includes roles as Senior Assistant and Postdoctoral Researcher at the University of Freiburg and Polytechnique Montréal. Education: PhD in Economics (Operations Research focus) from University of Freiburg (2014), Master in Business Informatics from University of Freiburg (2009). Research focuses on quantitative decision support systems for industry and services, exact/heuristic optimization methods, combinatorial optimization, integer programming, algorithms & data structures, and operations/service management. Key application areas include production planning, sustainable logistics systems, and workforce scheduling in retail and healthcare. His publications emphasize scheduling optimization (job shop, employee scheduling), logistics network design, and infrastructure resilience. Notable work includes convex cost job shop scheduling and decomposition heuristics for large-scale employee scheduling problems. Advising and grants: No specific students or grants mentioned. Active in industry-academia collaboration through Polypoint AG and prior academic roles.

• Labor Law
• Public Law
• Data Protection Law
• +۵ مورد دیگر

Bettina Hübscher is a Lecturer at the Lucerne School of Business (Lucerne University of Applied Sciences and Arts), affiliated with the Institute of Business and Regional Economics (IBR) CC Management and Law. She holds a Master's in Risk Management and a law degree from the University of Lucerne. Her professional roles include Project Leader and Program Director at HSLU, co-founder of RECHT VERNETZT GmbH, and various public sector legal roles. She has held board memberships in organizations like the Raiffeisenbank Obwalden and Lake Lucerne Navigation Company. Her research focuses on labor law, public law, data protection, risk management, and governance. Notable projects include studies on AI and copyright law, energy transition policies, and integral risk management in public administration. She actively explores digitalization trends in workforce management, including hybrid work models and crowdworking platforms. Publications span labor law challenges, digital recruitment strategies, and crisis management frameworks. She engages in policy discussions about vocational training attractiveness and demographic impacts on wage-productivity systems. Her work bridges legal compliance with organizational resilience, emphasizing practical solutions for modern challenges in governance and workforce dynamics. Her advisory contributions include leading risk management projects for public institutions and publishing extensively on governance tools like GRC frameworks. She collaborates on interdisciplinary initiatives addressing digital transformation and legal implications of emerging technologies in business and public sectors.

• Multi-Agent Systems
• Human-Robot Interaction
• Game Theory
• +۷ مورد دیگر

Katia Sycara is a Research Professor at Carnegie Mellon University's Robotics Institute, part of the School of Computer Science. She also holds the Sixth Century Chair (part-time) in Computing Science at the University of Aberdeen, UK. Her research focuses on multi-agent systems, human-robot interaction, game theory, and adversarial reasoning. She leads the Advanced Agent-Robotics Technology Lab and has developed frameworks like the RETSINA multiagent infrastructure. Education: B.S. in Applied Mathematics (Brown University), M.S. Electrical Engineering (University of Wisconsin), Ph.D. Computer Science (Georgia Tech), Honorary Doctorate (University of the Aegean, 2004). Research interests include semantic web services, agent interoperability, crisis response systems, and negotiation support. She has pioneered work on the DAML-S language for semantic web services and contributed to the OASIS UDDI standard. Notable awards include the 2002 ACM SIGART Agents Research Award and AAAI Fellowship. She has led multimillion-dollar projects funded by DARPA, NASA, AFOSR, and ONR, focusing on applications like autonomous robotics, urban search and rescue, and enterprise integration. Awards: ACM SIGART Autonomous Agents Research Award (2002) AAAI Fellow (2002) IEEE Fellow (2013) Outstanding Alumnus (University of Wisconsin, 2005) Grants and Projects: Command and Control of Multi-Robot Teams (ONR) Games on Graphs (MURI/ONR) Urban Search and Rescue (NASA) Labs/Teams: Director of Advanced Agent-Robotics Technology Lab and contributor to the Semantic Web Science Association.