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Mary Elizabeth KurzView profile

Associate Professor

• Scheduling
• Metaheuristics
• Industrial Engineering
• +5 more

Mary Elizabeth Kurz is an Associate Professor in the Department of Industrial Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. Her research focuses on scheduling optimization, metaheuristics, and assembly line balancing for complex manufacturing systems. Education: B.S., Systems Engineering, University of Arizona (1995) M.S., Systems Engineering, University of Arizona (1997) Ph.D., Systems and Industrial Engineering, University of Arizona (2001) Research interests include: Development of heuristics and metaheuristics for scheduling Assembly line balancing with ergonomic constraints Flexible flowline scheduling with sequence-dependent setups Application of genetic algorithms and particle swarm optimization Recent work trends show applications in opioid crisis modeling, photolithography scheduling, and automotive configuration management. She has presented at INFORMS and IISE conferences, with special emphasis on multi-objective optimization and real-world industrial constraints. Scientific awards: Third Place Best Paper, ASME Manufacturing Engineering Division (2014) As an INFORMS member and Institute of Industrial Engineers Senior member, she has taught courses in operations research, decision support systems, and metaheuristics. Her work spans both theoretical and applied domains, with a strong focus on manufacturing system efficiency.

Raik StolletzView profile

Professor

• Operations Management
• Business Analytics
• Quantitative Decision Analysis
• +8 more

Prof. Dr. Raik Stolletz is a Professor of Production Management at the Business School of the University of Mannheim, leading the Chair of Production Management within the Area Operations Management. His research focuses on business analytics, quantitative decision support for manufacturing and service systems, and stochastic modeling for operations optimization. Area Operations Management, Business School, University of Mannheim Research Interests : Stolletz specializes in predictive and prescriptive business analytics, with applications in Industry 4.0, airport operations, automotive production, workforce planning, and distribution center management. His work emphasizes tools for decision-making in deterministic and stochastic environments. Research Trends : His recent publications address time-dependent queueing systems, buffer allocation in stochastic flow lines, assembly line balancing, and revenue management in production. Keywords span Operations Management, Supply Chain Analytics, and Industrial Engineering, with sub-fields including Stochastic Optimization, Dynamic Scheduling, and Service Systems. Grants & Collaborations : Projects are funded by industry partners, the European Union, and the German Science Foundation (DFG), focusing on automotive production networks, airport logistics, and manufacturing system optimization.

Erdal ErelView profile

Professor

• Production Operations Management
• Manufacturing Systems Design
• Assembly and Disassembly Line Balancing
• +4 more

Erdal Erel is a Professor of Operations Management (OM) and currently serves as the Vice Rector in charge of administrative and financial affairs at Bilkent University's Faculty of Business Administration. He holds a B.S. in Industrial Engineering from Istanbul Technical University (1981), an M.S. from Stanford University (1983), and a Ph.D. from Virginia Polytechnic Institute and State University (1987). His academic career has been dedicated to advancing research in Production Operations Management, focusing on manufacturing systems design, assembly/disassembly line balancing, scheduling, and project management. Erel's educational background includes: B.S. in Industrial Engineering, Istanbul Technical University (1981) M.S. in Industrial Engineering, Stanford University (1983) Ph.D. in Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University (1987) His research interests span several critical areas of operations management, including manufacturing systems design, assembly and disassembly line balancing, scheduling and sequencing methodologies, and project management. He has made significant contributions to robust optimization techniques applied to time-cost trade-offs and stochastic modeling in production systems. His work emphasizes practical solutions for complex operational challenges through advanced algorithms like ant colony optimization and beam search methods. Erel's publications reflect a focus on optimization in production systems, scheduling algorithms, and decision models under uncertainty. His research bridges theoretical advancements with real-world applications in manufacturing and service industries, addressing issues such as cost minimization, robust scheduling, and efficiency improvements in assembly line operations. Erel has contributed extensively to his field but no specific scientific awards are mentioned in the provided text. No specific information about advising students or grants is provided in the text. Erel's involvement in collaborative projects, including work with colleagues like I. Sabuncuoglu and J.B. Ghosh, highlights his role in interdisciplinary research teams focused on operational efficiency and advanced manufacturing technologies.

• Optimization
• Cryptography
• Artificial Intelligence
• +3 more

Rui Sá Shibasaki is a lecturer at the University of Picardie Jules Verne, specializing in Optimization and Cryptography within the AI - OCIA department. His research focuses on operational research and mathematical optimization, particularly in network design, assembly line balancing, and energy efficiency. Research Trends: His recent publications emphasize energy optimization in manufacturing processes, robust assembly line balancing under uncertainty, MaxSAT formulations for integer programming, and advanced decomposition methods in large-scale network design. Key themes include constraint programming, heuristic algorithms, and sustainability in industrial systems. Notable Contributions: He has developed Dantzig-Wolfe decomposition techniques for stability radius optimization and explored entropy-based sensor placement strategies. His work bridges theoretical optimization with practical applications in logistics and production planning.

• Pharmacology
• Chemotherapy
• Cytofluorimetry
• +3 more

Sabrina Pacor is an Associate Professor in Applied Biology (BIO/13) at the University of Trieste , where she teaches Pharmacology in the Pharmacy LM and STB BSc programs. With over 30 years of research experience in experimental oncology and host defense peptides, she has made significant contributions to studying antimicrobial peptides (AMPs) and their interactions with bacterial membranes. Her research focuses on: Direct antimicrobial activity of AMPs against Gram-positive and Gram-negative bacteria Indirect immunomodulatory effects of host defense peptides Development of drug delivery systems using nanomaterials (carbon nanotubes, gold nanoparticles) Mechanistic studies of ruthenium-based antimetastatic drugs She leads extensive cytofluorimetry research using flow cytometry platforms, particularly for evaluating: Cytotoxicity (necrosis/apoptosis, proliferation index) Modulation of host biological responses (chemotaxis, phagocytosis, ROS production) Peptide-bacterial membrane interactions through fluorescent labeling Her recent work demonstrates trends in: Proline-rich antimicrobial peptides against ESKAPE pathogens Hybrid antibiotic design (peptide-aminoglycoside conjugates) Structure-activity relationships in membranolytic peptides Evolutionary insights into defensin and cathelicidin families Prof. Pacor has co-authored over 100 peer-reviewed publications and actively mentors students, having supervised: 70 experimental/thesis reviews for Pharmacy/CTF Master's students 20 Bachelor's degree theses

• Ergonomics and Human Factors
• Risk Assessment and Management
• Multi-Criteria Decision Making
• +6 more

Prof. Dr. Gülin Feryal Ural is a Professor of Industrial Engineering at Baskent University's Faculty of Engineering. With a PhD in Industrial Engineering from Kocaeli University (2013), she has established herself as a prominent researcher in ergonomics, risk assessment, and multi-criteria decision making. Her academic journey includes a Master's in Business Administration (2006) and BSc in Industrial Engineering (2004), both from Kocaeli University. Dr. Ural's educational background is deeply rooted in Industrial Engineering, with a PhD from Kocaeli University in 2013, followed by a Master's degree in Business Administration in 2006 and her undergraduate degree in Industrial Engineering in 2004, all from the same institution. This strong foundation has enabled her to bridge theoretical knowledge with practical applications in her research and teaching. Her research interests span multiple domains within Industrial Engineering, with a strong focus on Ergonomics and Human Factors Management , Risk Assessment and Management , and Multi-Criteria Decision Making methodologies. Dr. Ural has pioneered approaches integrating various decision-making techniques like KEMIRA-M, DEMATEL, and Entropy methods to address complex problems in occupational safety, usability evaluation, and production systems. Her work often bridges theoretical frameworks with practical industrial applications, particularly in healthcare, manufacturing, and educational settings. Analysis of Dr. Ural's extensive publication record reveals a clear trajectory toward increasingly sophisticated risk assessment methodologies and ergonomics applications. She has consistently advanced the integration of multiple decision-making techniques to create holistic assessment frameworks. Her research shows particular strength in adapting these methods to specific industry contexts, from healthcare to manufacturing, and increasingly incorporating machine learning approaches for risk prediction. The interdisciplinary nature of her work is evident in publications spanning engineering, healthcare management, and educational research domains. Dr. Ural has actively contributed to academic service through editorial roles, including membership on the editorial board of the International Journal of Intelligent Computing and Cybernetics and serving as an editor for the International Journal of Lean Six Sigma since 2023. Her teaching portfolio is extensive and reflects her research expertise, covering courses such as Ergonomics and Human Factors Management, Work Study, Lean Production, Occupational Health and Safety, Risk Analysis and Risk Management, and Special Topics in Industrial Engineering. This comprehensive teaching approach ensures her students receive both theoretical foundations and practical applications of Industrial Engineering principles.

Simon TheveninView profile

Assistant Professor

• Production Management
• Optimization Methods
• Production Scheduling
• +4 more

Simon Thevenin is an Assistant Professor in the Automation, Production, and Computer Sciences Department at IMT Atlantique in France since 2018. He holds a Ph.D. from the University of Geneva (2015) and previously worked as a Postdoctoral researcher at HEC Montreal and an Algorithm Expert at Quintiq. His research focuses on optimization methods for production management, including scheduling, planning, and manufacturing line design. He leads projects such as the EU-funded ASSISTANT (2020-2023), ALICIA (2023-2025), and ACCURATE (2023-2026), advancing AI-driven solutions for sustainable manufacturing and supply chain resilience. His work integrates machine learning, robust optimization, and digital twin technologies to enhance production systems' adaptability and efficiency. Education: Ph.D. in Production Systems Scheduling, University of Geneva (2015) Teaching/Research Assistant, University of Geneva (2010-2015) Research Interests: His research emphasizes optimization under uncertainty, reconfigurable manufacturing systems, and AI applications in production. He explores topics like lot-sizing models, equipment lifecycle management, and circular manufacturing ecosystems. Grants/Projects: ASSISTANT (EU-funded, 2020-2023): AI for production digital twins ALICIA (EU-funded, 2023-2025): Circular production resource ecosystems ACCURATE (EU-funded, 2023-2026): Supply chain resilience against disruptions Labs/Teams: Part of the LS2N research lab (Modelis team) at IMT Atlantique, specializing in logistics and industrial optimization.

• Industrial Logistics
• Supply Chain Management
• Digitalization in Logistics
• +7 more

Fabio Sgarbossa is a Full Professor of Industrial Logistics at NTNU's Department of Mechanical and Industrial Engineering, Faculty of Engineering. He holds editorial roles in journals like the International Journal of Production Research and has authored over 150 publications. His research focuses on industrial logistics systems, supply chain resilience, and Industry 4.0 technologies, with a strong emphasis on human-centric design and digital transformation. Education: Master's in Management Engineering (2005) and PhD in Industrial Engineering (2010), both from the University of Padova, Italy. Research Interests: Design and management of industrial logistics; supply chain optimization; digitalization in manufacturing; human factors in production systems; autonomous mobile robots (AMRs); predictive maintenance; and circular economy integration. He leads NTNU's Logistics 4.0 Lab and collaborates on EU-funded projects. Key Contributions: Developed frameworks for Industry 4.0 adoption in logistics, decision support systems for additive manufacturing, and human-centric warehouse design. His work bridges operational efficiency with worker well-being. Grants & Collaborations: Active in EU and national projects focusing on smart manufacturing, resilient supply chains, and aging workforce challenges. Supervises graduate students in logistics systems and technology integration. Labs/Teams: Head of Logistics 4.0 Lab at NTNU, collaborating with industry partners on AMR implementations and digital twin applications.

• Automation Engineering
• Production Simulation
• Multi-Objective Optimization
• +7 more

Amos H.C. Ng is a Professor of Automation Engineering at the School of Engineering Science, University West (Högskolan i Skövde). His academic qualifications include BEng, MPhil, and PhD degrees, complemented by professional certifications such as Chartered Engineer (UK) and membership in the Institution of Engineering and Technology (UK). His research focuses on production simulation, multi-objective optimization, simulation-based innovization, and digital human modeling, with applications in manufacturing systems, Industry 4.0, and smart manufacturing. Ng has contributed to over 150 publications since 2000, spanning topics like decision support systems, maintenance optimization, and reconfigurable manufacturing. His work integrates simulation, data mining, and evolutionary algorithms to address challenges in production systems, including bottleneck analysis, energy efficiency, and human-robot collaboration. Notable projects include developing the Mimer knowledge discovery tool and frameworks for digital twin applications in production lines. His research emphasizes practical industry applications, collaborating with organizations to improve production processes through advanced methods like trend mining and cloud-based optimization. Ng also serves as a course coordinator and contributes to educational initiatives in automation engineering.

Valeria OlivaresView profile

Assistant Professor

• Observational Astrophysics
• Galaxy Clusters
• Galaxy Groups
• +11 more

Valeria Olivares is an Assistant Professor in the Department of Physics at Universidad de Santiago, Chile. She is an observational astrophysicist with a focus on galaxy clusters and groups, utilizing multi-wavelength data from facilities such as ALMA, MUSE, and Chandra. Previously, she was a NASA NPP Postdoctoral Fellow at NASA Ames Research Center and has held affiliations with the National Aeronautics and Space Administration (NASA) and Observatoire de Paris. Current Position: Assistant Professor, Universidad de Santiago Former Position: NASA NPP Postdoc Fellow, NASA Ames Research Focus: AGN feedback, galaxy evolution, intracluster medium Observational Tools: ALMA, MUSE, Chandra, VLT/SINFONI Her research centers on understanding the life cycle of gas in galaxy clusters and groups, particularly how AGN feedback regulates cooling flows and drives multiphase filament formation. She investigates the origins of cold and warm gas in brightest cluster and group galaxies (BCGs/BGGs), combining X-ray, optical, and sub-mm observations to constrain physical mechanisms such as uplift by radio bubbles, thermal instability, and turbulence. Her work also extends to sub-millimeter galaxies, where she studies extreme star formation triggered by galaxy mergers. The recent publications highlight a strong trend in analyzing AGN feedback through X-ray cavity dynamics, Hα–X-ray correlations in filaments, and gas condensation in group-dominant galaxies. These studies employ large, unbiased samples such as the Planck SZ-selected clusters, allowing robust statistical analysis of feedback cycles across cosmic time. Scientific recognition includes a NASA press release titled 'Black Holes Can Cook for Themselves' (2025), highlighting her discovery of an Hα–X-ray surface brightness correlation in cooling-flow cluster filaments. This work underscores the self-regulating nature of AGN feedback in maintaining thermal balance in clusters. She actively collaborates with international teams, utilizing archival and new observational data. Her research is supported by access to major telescopes and space observatories. While formal student advising is not detailed, her collaborative publications suggest mentorship roles in large astrophysical projects. Valeria Olivares leads an active research program in extragalactic astrophysics, with a focus on observational campaigns that integrate multi-wavelength datasets to unravel the complex physics of galaxy evolution and AGN feedback.

• Management Science
• Operations Research
• Optimization Algorithms
• +12 more

Professor Celia A. Glass is a Professor of Management Science at Bayes Business School, City St George's, University of London. She is affiliated with the Faculty of Actuarial Science and Insurance and has been a key figure in advancing research in operational research and optimization since joining the institution in 1999. She holds a PhD and BSc from King’s College London and has held visiting positions at Queen Mary University of London and Scottish and Southern Energy. PhD, King’s College London BSc, King’s College London Her research focuses on Operations Research, Management Science, and Optimization, with applications in healthcare, telecommunications, and manufacturing. Key areas include staff rostering, call centre analytics, frequency assignment, and combinatorial scheduling. She has led EPSRC-funded projects and industrial collaborations with OfCom, the NHS, and food safety laboratories. Her recent publications reflect a strong trend in periodic scheduling for wireless networks, staff rostering optimization, and combinatorial algorithms for graph and matrix problems. She has made significant contributions to both theoretical and applied optimization. Fellow, Operational Research Society Fellow, London Mathematical Society Fellow, Institute of Mathematics and its Applications Member, EPSRC College She has supervised multiple PhD students and has served as a referee for leading journals such as European Journal of Operational Research and Operations Research . Her industrial consultancy includes Whittington Hospital, OfCom, and the Registered Nursing Homes Association. She has co-organized workshops and served on accreditation panels, demonstrating leadership in the academic and professional community. Her research has been supported by EPSRC grants and industrial partnerships, focusing on real-world applications of optimization in healthcare and telecommunications. She leads the Nightglass Medical Rostering Ltd spin-out company, providing NHS rostering solutions.

Thomas RobbinsView profile

Associate Professor

• Management Science
• Operations Research
• Supply Chain Management
• +7 more

Thomas Robbins is an Associate Professor in the Department of Marketing & Supply Chain Management within the College of Business at East Carolina University , Greenville, North Carolina. He teaches courses including Management Science, Statistics, Operations and Supply Chain Management, Project Management, and has also delivered a Big Data & Analytics seminar in the ECU Honors College. Education: Ph.D. in Business Administration and Operations Research – The Pennsylvania State University, 2007 MBA – Weatherhead School of Management, Case Western Reserve University, 1989 B.S. in Electrical Engineering – The Pennsylvania State University, 1985 Research Interests: Dr. Robbins’ scholarship centers on applying rigorous quantitative models to real-world business and societal problems. His expertise spans simulation, linear, integer and stochastic programming, predictive analytics, sports analytics, service sciences, and innovative business education . Current themes include optimizing service operations, forecasting in sports and betting markets, and data-driven decision making in healthcare and quick-service industries. Publication Trends: Over the past fifteen years his work has appeared in leading journals such as European Journal of Operational Research, Service Science, Decision Sciences Journal of Innovative Education, International Journal of Operations & Quantitative Management, The Journal of Thoracic and Cardiovascular Surgery, and The Wiley Encyclopedia of OR/MS . A clear trajectory emerges from early stochastic call-center models and workforce cross-training studies (2010-2012), through healthcare learning-curve analyses (2011-2015), to contemporary topics in sports analytics, COVID-19 modeling, and pedagogical innovation (2017-2023). Previous Career: Before academia, Dr. Robbins accumulated 20 years of industry experience at IBM, Boston Market, Advanced Graphical Applications, General Electric, and—most prominently—as a Partner in the consulting practice of Ernst & Young, retiring from Cap Gemini in 2002 as a Vice President. Grants & Funding: Specific grant details are not provided in the source text. Labs & Teams: While no formal laboratory is named, his affiliation with the College of Business and ongoing research collaborations suggest active participation in the university’s analytics and operations communities.

Märt ReinveeView profile

Senior Lecturer

• Physical Ergonomics
• Industrial Engineering
• Occupational Health
• +3 more

Märt Reinvee is a Senior Lecturer in Physical Ergonomics at the Institute of Forestry and Engineering , Estonian University of Life Sciences. His research bridges occupational health , industrial engineering , and ergonomic technology , focusing on musculoskeletal risk assessment, low-cost sensor applications, and environmental factors affecting workplace safety. PhD in Engineering Sciences (2020), MSc in Ergonomics (2009), BSc in Engineering (2007) Current projects: Strengthening Farm Health and Safety (€302,853 funding) Key research trends: ergonomic assessment tools , noise exposure analysis , and cost-effective sensor validation Professional memberships: Human Factors and Ergonomics Society (since 2014), ErgoEst Estonian Ergonomics Society (since 2009)

Yuvin Adnarain ChinniahView profile

Professor

• Occupational Health and Safety
• Industrial Safety
• Machine Safety
• +5 more

Dr. Yuvin Adnarain Chinniah serves as a Full Professor and Department Director in the Department of Mathematical and Industrial Engineering at Polytechnique Montreal. His expertise spans occupational health and safety, industrial safety engineering, and machinery risk assessment. He actively contributes to the Research Group on Globalisation and Management of Technology (GMT) and Laboratoire Poly-Industries 4.0. Dr. Chinniah's research focuses on occupational health and safety with particular emphasis on machinery safety, risk assessment methodologies, human-robot collaboration, and safety standards implementation. His work bridges theoretical frameworks with practical applications in industrial settings, addressing critical issues like confined space safety, lockout/tagout procedures, and safety in Industry 4.0 environments. His research integrates ISO and CSA standards into practical safety solutions for industrial machinery. His recent publications demonstrate a clear trajectory from traditional machine safety toward advanced applications involving robotics, digital transformation, and human-robot collaboration. The research consistently addresses safety optimization in manufacturing processes, with increasing focus on cyber-physical systems, AI integration for hazard detection, and safety-driven production planning. His work maintains strong connections to industrial standards while pushing boundaries in collaborative robotics safety. Dr. Chinniah has successfully supervised 9 Ph.D. students and 10 Master's students, with thesis topics covering confined space safety, lockout/tagout procedures, human-robot collaboration safety, and machinery risk assessment. His teaching portfolio includes key courses in safety engineering, ergonomics, and maintenance engineering. He leads significant research projects related to occupational safety in industrial settings, with particular focus on machinery safety standards implementation and risk assessment methodologies.

David JamesView profile

Professor

• Bioprocess Engineering
• Biopharmaceutical Production
• Recombinant Protein Production
• +5 more

Professor David James is a distinguished academic at the University of Sheffield's School of Chemical, Materials and Biological Engineering, where he holds the position of Professor of Bioprocess Engineering and serves as Research Centre Director of the Advanced Biomanufacturing Centre. With a career spanning over three decades, Professor James has established himself as a leading expert in bioprocess engineering and biopharmaceutical production. His research interests focus on the production of high-value therapeutic recombinant protein biopharmaceuticals, systems biotechnology for rational bioprocess engineering, cell factory and gene vector engineering, and process analytical technology. Professor James has pioneered numerous innovations in CHO cell engineering, synthetic promoter design, and recombinant protein production systems. Analysis of his recent publications reveals a strong trajectory toward precision control of bioproduction processes, with emphasis on synthetic biology approaches for mammalian cell engineering. His work spans from fundamental cell biology to applied bioprocess development, with significant contributions to viral vector production, protein analytics, and pandemic-related research during the recent global health crisis. His notable scientific achievement includes the Royal Society Wolfson Research Merit Award received upon his appointment to Sheffield in 2006 for 'Research and Training in Biopharmaceutical Bioprocessing for UK Bioindustry'. Professor James actively contributes to academic training through courses such as CPE412 – Molecular Biotechnology, mentoring the next generation of bioprocess engineers while maintaining a robust research program with numerous industry collaborations.