جست‌وجوی استاد و پژوهشگر

Czesław Smutnickiمشاهده پروفایل

استاد

• Manufacturing Systems
• Operations Research
• Optimization
• +۳ مورد دیگر

Prof. Czesław Smutnicki is the Dean and Head of the Department of Computer Engineering at the Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His research focuses on manufacturing systems, operations research, and optimization, with a particular emphasis on scheduling algorithms and metaheuristics. Current Position: Dean, Department of Computer Engineering Institution: Wrocław University of Science and Technology Research Areas: Cyclic scheduling, Lagrangian relaxation, quantum annealing, and multi-criteria optimization Recent publications show a trajectory from classical scheduling (1996-2018) to modern applications involving quantum computing and distributed systems. The articles cluster around three main themes: (1) quantum-enhanced scheduling optimization, (2) Lagrangian relaxation techniques for tardiness minimization, and (3) robust scheduling under uncertainty in multi-vehicle/worker environments. Contact: czeslaw.smutnicki@pwr.edu.pl

Samuli Aaltoمشاهده پروفایل

استاد مهمان

• Communication Engineering
• Queueing Theory
• Energy-Aware Systems
• +۲ مورد دیگر

Samuli Aalto is a Visiting Professor at the Department of Information and Communications Engineering, Aalto University School of Electrical Engineering. His research focuses on Communication Engineering , particularly in Queueing Theory , Stochastic Scheduling , and Energy-Aware Systems . He has contributed extensively to optimizing resource allocation in wireless networks and server farms. Academic Affiliation : Aalto University, School of Electrical Engineering Research Themes : Optimal scheduling in queueing systems, energy-efficient network management, and stochastic resource allocation Recent Publications highlight work in: Whittle index applications for multi-class queueing systems Energy-aware dispatching in heterogeneous networks Slowdown minimization in single-server queues Age-energy tradeoff models for wireless systems His research involves mathematical modeling of Markovian systems , processor sharing , and size-based scheduling . Projects include optimizing P2P video-on-demand systems, analyzing queue-specific job sizes , and developing energy-performance tradeoff frameworks for modern data centers and 5G networks.

Robbert Reijnenمشاهده پروفایل

پژوهشگر

• Multi-Objective Optimization
• Deep Reinforcement Learning
• Graph Neural Networks
• +۴ مورد دیگر

Robbert Reijnen is a Researcher at the Department of Information Systems within the Industrial Engineering and Innovation Sciences school at Eindhoven University of Technology . His work focuses on algorithmic approaches for complex optimization problems in industrial contexts. Research interests include: Deep Reinforcement Learning for dynamic systems Graph Neural Networks in scheduling optimization Adaptive parameter control in evolutionary algorithms Multi-objective optimization frameworks Recent publications highlight applications in job shop scheduling, vehicle routing, and differential evolution techniques. He has received recognition through scientific awards : Winner of MLVRP2023 GECCO competition (2023) Active in organizing academic workshops like EURO Meets NeurIPS 2022 Vehicle Routing Competition , and teaching Algorithmic programming for operations management . His work contributes to UN Sustainable Development Goals related to efficient resource management.

• Operations Research
• Logistics Optimization
• Heuristic Algorithms
• +۳ مورد دیگر

Dr. Kateryna Czerniachowska is a Lecturer at the Department of Process Management, Wrocław University of Economics. She specializes in logistics optimization, heuristic algorithms, and supply chain management. Her work focuses on solving complex problems such as order-picking efficiency, shelf space allocation, and inventory distribution in retail and warehouse systems. She is fluent in English, Polish, Russian, and Ukrainian. Her research emphasizes mathematical modeling for retail networks and warehouse layouts, incorporating innovative heuristics like Flower Cutting and Mushroom Picking algorithms. Recent studies address sequence-dependent constraints in conveyor systems and multi-axial product categorization. She actively collaborates with industry to apply these methods in practical settings. Her publications span optimization frameworks for space allocation, scheduling TV advertisements via genetic algorithms, and predicting public transportation delays using machine learning. She maintains active profiles on ResearchGate and ORCID. Consultations are available via Microsoft Teams upon prior arrangement via email. She contributes to pedagogical activities focused on operational research and logistics systems design.

Krzysztof Lutosławskiمشاهده پروفایل

پژوهشگر

• Operations Research
• Environmental Engineering
• Data Science
• +۳ مورد دیگر

Krzysztof Lutosławski is a Researcher affiliated with the Department of Process Management at Wrocław University of Economics. His work bridges operations research, environmental engineering, and data science, focusing on optimization challenges in retail logistics, biodegradation processes, and predictive modeling. Research Interests include: Optimization of supply chain operations through scheduling algorithms and shelf space allocation Environmental applications like aerobic biodegradation of industrial waste Data-driven approaches for customer behavior analysis and financial forecasting Development of novel food products through antioxidant-rich agricultural research Recent work emphasizes machine learning applications in e-commerce and LSTM networks for purchase prediction. His biotechnology research examines microbial degradation of organic waste products. Consultation hours are Tuesdays 11:30-13:00. Proficient in English and Polish, he actively supervises doctoral students and collaborates with socio-economic partners. Academic profiles available via ORCID and ResearchGate .

• Operating systems
• Distributed systems
• Computer Science
• +۳ مورد دیگر

Professor Willy Zwaenepoel is a distinguished academic and Dean of the Faculty of Engineering at the University of Sydney. He holds Fellowships from ACM, IEEE, and ATSE. His research focuses on distributed systems, operating systems, and experimental computer science. Previously, he spent two decades at Rice University and nine years as Dean of EPFL's School of Computer and Communication Sciences before joining Sydney in 2018. Education: BS/MS, Ghent University (1979) MS/PhD, Stanford University (1980/1984) Research Interests: His work emphasizes distributed systems and operating systems, with contributions to key-value stores, transactional systems, and large-scale graph processing. Recent projects include optimizing geo-replicated systems and improving datacenter scheduling efficiency. Articles Trends: Recent publications address OS scheduling (Nest), distributed graph mining (Tesseract), and transactional systems' performance limits. He explores hardware-software co-design for multicore systems and energy-efficient data centers. Awards: Fellow of ACM (2021) Fellow of IEEE (2020) Fellow of ATSE (2019) Grants & Advising: Active grants include adaptive key-value store research (2021) and large-graph processing systems (2018). He advises PhD students and postdocs on distributed systems and storage challenges. Labs/Teams: Leads the Sydney systems research group focusing on scalable distributed systems and cloud infrastructure.

Jingui Xieمشاهده پروفایل

دانشیار

• Business Analytics
• Healthcare Management
• Data-Driven Healthcare Optimization
• +۳ مورد دیگر

Prof. Dr. Jingui Xie is an Associate Professor of Business Analytics at the TUM School of Management (TUM Campus Heilbronn) and a core member of the Munich Data Science Institute. His research focuses on improving healthcare systems through data analytics, queueing models, and robust optimization frameworks. Key areas include ICU data analytics, healthcare resource planning, and the impact of air pollution/COVID-19 on medical systems. Previously, he held roles at Brunel University London, Cambridge Judge Business School, and the National University of Singapore. He earned his PhD from Tsinghua University and has received awards such as the POMS-HK Student Paper Competition (2018) and the Tsinghua Outstanding Dissertation Award (2010). Education: PhD in Operations Research, Tsinghua University Postdoctoral Research at National University of Singapore (2010–2011) Research Interests: Healthcare Data Analytics for ICU decision-making Joint estimation and robust optimization frameworks Applications of machine learning in healthcare operations Awards: First Prize, POMS-HK Student Paper Competition (2018) Junior Teaching Award, USTC (2016) Key Projects: COVID-19 Data Analytics: Linking environmental factors to infection rates ICU Data Analytics: Optimizing ventilator extubation decisions Bed Shortage Analytics: Coherent metrics for hospital resource planning

Johannes Oetschمشاهده پروفایل

پژوهشگر

• Answer Set Programming
• Neural-Symbolic Computation
• Visual Question Answering
• +۳ مورد دیگر

Johannes Oetsch is a researcher at TU Wien's Forschungsbereich Knowledge Based Systems within the Faculty of Informatics. His work focuses on Answer Set Programming (ASP) , neuro-symbolic computing , and visual question answering systems . He holds a Diplom-Ingenieur (Dipl.-Ing.) and a Doctor of Technical Sciences (Dr.techn.) in informatics. Key research areas include: Integration of large language models with symbolic reasoning frameworks Optimization techniques in ASP for scheduling problems Explainability mechanisms for neuro-symbolic systems Recent work emphasizes visual question answering using graph-based representations and contrastive explanation methods. He has contributed to the development of ALASPO , an adaptive optimization framework for ASP solvers. His research also explores applications in manufacturing scheduling and automated testing of logic programs. Notable contributions include: Neuro-symbolic pipelines combining ASP with vision-language models Lexicographical makespan optimization in parallel machine scheduling Large-neighbourhood search strategies for ASP-based optimization

Eric Pinsonمشاهده پروفایل

استاد

• Combinatorial Optimization
• Scheduling Theory
• Transport Logistics
• +۳ مورد دیگر

Eric Pinson is a Professor at the University of Angers (UCO) within the Faculty of Sciences. He holds an HDR (Accreditation to Supervise Research) from Université Pierre et Marie Curie (Paris VI) since 1994 and a PhD in Computer Science and Applied Mathematics from the same institution in 1988. He leads the LigéRO regional project (Loire Operational Research Group) and is an integrated member of LARIS (Angevin Research Laboratory in Systems Engineering), part of team EA-7315. Education: PhD in Computer Science and Applied Mathematics, Université Paris VI, 1988 HDR in Research Supervision, Université Paris VI, 1994 Research Interests: His work focuses on Combinatorial Optimization , particularly in scheduling theory and transport logistics. Key areas include algorithm development for scheduling problems (job-shop, flow-shop, maintenance planning), resource allocation in production systems, and optimization under constraints such as human resource limitations and energy considerations. His contributions span theoretical advancements and practical applications in renewable energy maintenance (e.g., wind turbines) and industrial logistics. Publications Trends: Recent work emphasizes algorithmic efficiency (O(n²) scheduling adjustments, energy function management) and industrial applications (wind farm maintenance, multi-skill project scheduling). Earlier publications established foundational scheduling algorithms and constraint-based optimization techniques. Scientific Awards: No specific awards listed, though his sustained contributions indicate significant recognition within the operations research community. Advising & Grants: Supervised at least one PhD student (Aurélien Froger, 2012–2016). Involved in collaborative projects including the DC-GNN program for real-world data clustering using graph neural networks. Labs & Teams: Primary affiliations include LARIS (Systems Engineering) and the LigéRO network, fostering regional operational research collaboration.

Zoé Ejebuمشاهده پروفایل

عضو هیئت علمی

• Applied Economics
• Nursing
• Health Workforce Retention
• +۳ مورد دیگر

Zoé Ejebu is a Senior Research Fellow at the University of Southampton, affiliated with the Health Workforce and Systems research group. She joined the university in 2020 and focuses on applied economics methods to study nurse retention, workforce performance, and healthcare resource allocation. Her work emphasizes analyzing large datasets and conducting discrete choice experiments to understand job preferences. Education: PGCAP (2024), University of Southampton FHEA (2023), Higher Education Academy PhD in Economics (2010–2014), University of Aberdeen MSc in Financial Economics (2009–2010), University of Glasgow MA in Economics (2008–2009), University of Aberdeen Licence Économique, Monnaie et Finance (2007–2008), Université Paris II, France Research Interests: Zoé’s work centers on applied economics in healthcare, including nurse retention strategies, workforce performance metrics, and the impact of working conditions. She explores topics such as shift patterns, burnout prevention, and cost-effectiveness of nurse staffing. Her recent studies address NHS nurse retention through discrete choice experiments and policy analysis. Articles Trends: Her publications focus on nurse staffing, shift work impacts, and healthcare workforce dynamics. Recent work highlights cost-benefit analysis of nurse deployment, frailty in adult populations, and frameworks for evidence-based staffing decisions. Awards: Dean’s List Award (2024) Dean’s List Award (2024) Teaching & Grants: She teaches 'Developing Research Skills: Practice-Based Learning' and 'Applied Quantitative Research Methods.' She leads the Evaluation of the N50k Programme and collaborates on projects like understanding NHS nurse retention factors. She accepts PhD students and has no listed grant details. Labs/Teams: Active in the Health Workforce and Systems research group, contributing to interdisciplinary projects on healthcare labor economics and policy.

Jian-Bo Yangمشاهده پروفایل

استاد

• Evidential Reasoning
• Probabilistic Inference
• Multiple Criteria Decision Analysis
• +۱۰ مورد دیگر

Jian-Bo Yang is Professor and Chair of Decision and System Sciences at the University of Manchester. With over £3.78m in secured research funding from 49 projects (including 17 EPSRC/ESRC grants), he leads research in decision sciences and analytics. He coordinates multiple courses including Quantitative Methods for Management and Decision Analysis for Business, while supervising PhD, MPhil, and MSc students. His research integrates evidential reasoning , probabilistic inference , and multi-criteria decision analysis to address complex problems in risk assessment, resource optimization, and intelligent systems. Recent publications demonstrate focus on: Theoretical advances in evidence-based decision frameworks Evolutionary algorithms for industrial optimization Uncertainty quantification in multi-source data fusion Yang has developed software systems like the Intelligent Decision System (IDS) and collaborates through the Data Science Institute and Decision and Cognitive Sciences Research Centre . His work supports UN Sustainable Development Goals through improved decision methodologies.

Yonah Wilamowskyمشاهده پروفایل

استاد

• Statistics
• Operations Research
• Quantitative Methods in Law
• +۳ مورد دیگر

Dr. Yonah Wilamowsky is a Professor of Computing and Decision Sciences at Seton Hall University, specializing in Statistics and Operations Management. He holds a PhD in Operations Research from New York University (1975), an MS in Operations Research (1970), and a BA in Mathematics (1968) from Brooklyn College. Dr. Wilamowsky teaches courses such as Business Statistics, Quantitative Methods in Business, and Database Management Systems. His research focuses on applying statistics and quantitative methods to law, business processes, biblical studies, and higher education. Notable contributions include work on pooled testing optimization, healthcare reimbursement auditing, and historical mathematical analysis. He has published in journals like European Journal of Business and Management Research , Naval Research Logistics , and Hakirah . Dr. Wilamowsky has received academic honors including Phi Beta Kappa, Pi Mu Epsilon, and Sigma Xi (all 1968). He has also contributed to professional development through consulting in statistics and operations research, and has presented at conferences like the Decision Sciences Institute Annual Meeting. His teaching spans both undergraduate and graduate levels, emphasizing practical applications of quantitative techniques. Current research interests include statistical methodologies for legal and biblical studies, as well as operational efficiency in higher education administration.

• Operations Management
• Management Science
• Supply Chain Management
• +۵ مورد دیگر

Dr. Omprakash Gupta is a Professor of Management at the University of Houston-Downtown's Marilyn Davies College of Business, where he has been teaching since 2011. His academic career spans over three decades with previous appointments at Prairie View A&M University, Nirma Institute of Management, and Purdue University. Education: Ph D in Operations Research from Purdue University MS in Mathematics from Purdue University MS in Mathematics from Gujarat University BS in Mathematics from Gujarat University with Supporting Areas of Emphasis in Physics Professor Gupta's research interests focus on operations management, management science, and the application of mathematical models to business and management. His scholarly work demonstrates a unique integration of quantitative methods with cultural and philosophical perspectives, particularly exploring Vedic principles in management. His research spans diverse domains including supply chain management, inventory modeling, quantitative decision-making, linguistic relativity in marketing, and Ramayana-based management principles. His recent publications (2015-2024) reveal a fascinating evolution from traditional operations research topics toward interdisciplinary studies connecting Eastern philosophy with business practices. While maintaining his expertise in quantitative methods and supply chain optimization, Gupta has increasingly explored the intersection of cultural values, linguistic frameworks, and business decision-making. His work on Ramayana-based management principles and linguistic relativity represents a distinctive contribution to management scholarship. Awards and Recognition: MDCOB Excellence in Research Award (September 2024) Marilyn Davies College of Business Excellence Award (September 2022) Professor Gupta has served in numerous leadership roles including Editor-in-Chief of AIMS International Journal of Management and President of AIMS International. His professional service extends to editorial boards, conference organization, and thesis evaluation. He has presented his research at international conferences worldwide and has made significant contributions to management education through case method teaching and faculty development initiatives. His current academic activities include teaching Operations & Supply Chain Management (MGT 3332) and Quantitative Methods in Business (GBA 5210) courses for both undergraduate and graduate students at the University of Houston-Downtown, with scheduled courses through Fall 2025.

Dong Daiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• High-Performance Computing
• +۵ مورد دیگر

Dong Dai is an Associate Professor at the University of Delaware in the Department of Computer and Information Sciences under the College of Engineering. He directs the Data Intelligence Research Lab (DIRLab) , focusing on optimizing intelligent infrastructure for high-performance, data-intensive systems using machine learning techniques. Research Interests : Artificial Intelligence, Machine Learning, High-Performance Computing, Storage Systems, Metadata Management, Graph Storage, Job Scheduling Education : PhD and BSc from the University of Science and Technology of China Grants : CCF-EAGER, CNS, CCF-Hybrid NVM, CCF-Parallel Graph-Based Paradigm, OAC-Provenance Collection Teaching : Courses include CISC 361 Operating Systems , CISC 360 Computer Architecture , ITCS 5145 Parallel Computing , and ITSC 3050 Undergraduate Research .

• Operations Research
• Discrete Event Simulation
• Deterministic Scheduling
• +۴ مورد دیگر

John Fowler is a Professor in the Department of Supply Chain Management at Arizona State University's W. P. Carey School of Business, holding the Motorola Professorship in International Management. He previously served as Department Chair (2011-2016) and Avnet Professor of Industrial Engineering at ASU. Education: Ph.D. in Industrial Engineering, Texas A&M University (1990) M.S. in Industrial Engineering, Texas A&M University (1986) B.S. in Industrial Engineering, Texas A&M University (1982) Research Interests focus on discrete event simulation , deterministic scheduling , and multi-criteria decision making , particularly in semiconductor manufacturing systems and healthcare operations. His work bridges operations research with applications in pandemic preparedness, supply chain design, and energy-efficient scheduling. Recent Publications demonstrate expertise in simulation modeling for pandemic response, semiconductor supply chain optimization, and healthcare systems analysis. He has developed decision support frameworks for push-pull supply chains and hybrid scheduling approaches for batch processing in semiconductor manufacturing. Scientific Awards Fellow of the Institute of Industrial and Systems Engineers Outstanding Paper Award, International Journal of Lean Six Sigma (2013) Editorial Service includes Editor-in-Chief of IIE Transactions on Healthcare Systems Engineering (2011-2016) and ongoing roles at Journal of Simulation and IEEE Transactions on Semiconductor Manufacturing . He has held leadership positions in academic societies and served on editorial boards for multiple journals. Grants and Industry Collaboration include NSF funding for healthcare delivery systems, Intel-sponsored semiconductor research, and Mayo Foundation partnerships. His work has addressed pandemic influenza preparedness through simulation models and developed capacity allocation solvers for high-tech industries. Laboratory Leadership encompassed directing the Modeling and Analysis of Semiconductor Manufacturing Laboratory at ASU from 1996 to 2009, where he pioneered simulation frameworks and scheduling methodologies for complex manufacturing systems.