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Daniel Vázquez VázquezView profile

Assistant Professor

• Inherent Safety Engineering
• Safety Index Engineering
• Multiobjective Optimization
• +6 more

Daniel Vázquez Vázquez is an Assistant Professor in the Chemical Engineering and Materials Science Department at IQS School of Engineering (Universitat Ramon Llull). He is an active member of the Grup d'Enginyeria i Simulació de Processos Ambientals (GESPA), where he contributes to research in process engineering and environmental systems. His work spans multiple areas of chemical engineering with a particular focus on sustainable process design and optimization. Research Interests Daniel's research primarily centers on Inherent Safety Engineering and Safety Index development, with significant contributions to Multiobjective Optimization methodologies for chemical process design. His work bridges theoretical developments in optimization techniques with practical applications in environmental engineering and sustainable chemical processes. He has developed novel approaches like the OFISI (Optimizable Fuzzy Inherent Safety Index) that integrate fuzzy logic with process safety assessment. His research portfolio demonstrates a strong trajectory toward addressing complex sustainability challenges, particularly in the areas of carbon management, renewable energy integration, and circular economy principles. Recent work shows an increasing focus on planetary boundaries and the development of methodologies that ensure chemical processes operate within environmental limits while maintaining economic viability. Publication Trends Analysis of Daniel's recent publications reveals a clear evolution in research focus from traditional chemical process optimization toward more comprehensive sustainability frameworks. Early work concentrated on inherent safety metrics and distillation sequence design, while more recent publications integrate machine learning techniques (particularly Bayesian symbolic regression) with process engineering to develop hybrid modeling approaches. There's a marked emphasis on carbon management, with multiple publications addressing carbon dioxide removal technologies, methanol production from renewable sources, and the integration of carbon capture with energy systems. Collaborations and Projects M-AD-NESS Project (2024-2027): As Principal Investigator, Daniel is leading research on Dual Anaerobic Bioelectrochemical Digesters for in-situ biomethane production from wastewater sludge. GESPA Project (2022-2025): As a researcher, he contributed to this group focused on Environmental Process Engineering and Simulation, funded by the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR). Daniel's research has gained significant attention, with his 2021 Nature Communications paper 'Delaying carbon dioxide removal in the European Union puts climate targets at risk' receiving 61 citations, policy references, and coverage in multiple news outlets. His work has been highlighted by 4 news outlets, blogged about, referenced in policy sources, and shared widely on social media platforms. Laboratory and Research Group Daniel is an active member of the Grup d'Enginyeria i Simulació de Processos Ambientals (GESPA), a research group dedicated to environmental process engineering and simulation. This group brings together multiple researchers from IQS to address challenges in sustainable chemical processes, waste management, and environmental protection through advanced modeling and optimization techniques.

• Operations Research
• Optimization
• Network Flows
• +3 more

Prof. Horst W. Hamacher is a Professor in the Department of Optimization at the University of Kaiserslautern's Faculty of Mathematics. His research focuses on optimization, operations research, and their applications in logistics, healthcare, and disaster management. Key areas include network flow optimization, evacuation planning models, radiation therapy treatment design, and hub location problems. He leads the Optimization Group (AG Optimierung), developing algorithms for complex systems. His work integrates theoretical advancements with practical solutions, such as minimizing beam-on time in radiation therapy and optimizing urban evacuation routes. He has authored/co-authored over 100 journal papers and book chapters, including seminal contributions to facility location theory and dynamic network flows. Collaborations span academic and industrial partners, addressing challenges in public transportation, medical engineering, and sustainable urban planning. Notable projects include the 'OptionS' initiative for sustainable water management optimization and the 'FlowLoc' framework for evacuation dynamics. He actively contributes to interdisciplinary education, bridging mathematics with real-world applications like robotic assembly and infrastructure design.

Shima MohebbiView profile

Assistant Professor

• Game Theory
• Agent-Based Simulation
• Stochastic Modeling
• +7 more

Shima Mohebbi is an Assistant Professor in the Department of Systems Engineering and Operations Research at George Mason University, with affiliate appointments in Computer Science and Civil Engineering. She leads the CARING research group and contributes to the Center for Resilient and Sustainable Communities (C-RASC). Academic Rank: Assistant Professor Departments: Systems Engineering & Operations Research (primary), Computer Science (affiliate), Civil Engineering (affiliate) School: College of Engineering and Computing Research Affiliation: C-RASC Her research focuses on developing scalable mathematical models and data analytics for cyber-physical systems , with applications in healthcare , infrastructure networks , and sustainable urban water systems . She employs game theory , agent-based simulation , and machine learning to study decision-making under uncertainty. Recent publications highlight advancements in: Hybrid simulation and reinforcement learning for resilient infrastructure scheduling Differential game models for water conservation incentives Graph-empowered simulations for interdependent systems Organizational resilience frameworks in socio-technical contexts Award highlights include: 2025 College of Engineering and Computing Faculty Excellence Award for Teaching 2024 Air Force Summer Faculty Fellowship 2023-2025 IISE Best Track Paper Awards NSF and AFRL grants for resilient systems research She actively mentors students in PhD Dissertations (Behnam Momeni, Pavithra Sripathanallur Murali) MSc Theses (Nischal Newar, Mark Herman Dsouza) Undergraduate research (Shakira Mangrio) Her lab collaborates across engineering, computer science, social sciences, and public policy domains to address grand challenges in smart cities and sustainable communities .

Mohamed Amine Ben AbdallahView profile

Lecturer

• Dynamic Modelling
• Robotic Systems
• Multibody Systems Optimization
• +3 more

Dr. Mohamed Amine Ben Abdallah is a Lecturer in Automotive Engineering and Dynamics at Sheffield Hallam University's Department of Engineering and Mathematics, part of the College of Business, Technology and Engineering. He holds MEng and PhD degrees from Tunisia's National Engineering School of Monastir (2013 and 2018) and has prior experience as a Lecturer at the Institute of Engineering Studies of Monastir, followed by postdoctoral research at the University of Surrey's Automotive Engineering Centre. His research focuses on dynamic modeling of compliant robotic systems, multibody systems optimization, electric vehicle engineering, and Industry 5.0 digital twin applications leveraging AI. Key research areas include mechanism synthesis using evolutionary algorithms, metaheuristic optimization for flexible systems, and AI-driven trajectory planning for autonomous systems. He contributes to sustainable design through energy-efficient disassembly optimization and recyclability analysis. Teaching spans automotive, aerospace, and mechanical engineering courses, including modules like Advanced Automotive Engineering and Sustainable Vehicle Technology. His publications emphasize optimization techniques in mechanical systems, robotic dynamics, and AI integration in engineering design. Participates in the Industry and Innovation Research Institute and has contributed to conferences such as the Design and Modeling of Mechanical Systems. Current projects explore AI-enhanced robotic learning and digital twin applications in Industry 5.0 contexts.

• Wireless Networking
• Mobile Computing
• Visible Light Communication
• +7 more

Chenren Xu is an Associate Professor in the Department of Computer Science at Peking University's School of Electronics Engineering and Computer Science. With a prolific publication record spanning from 2016 to 2025, Xu has established themselves as a leading researcher in wireless networking, mobile systems, and novel communication technologies. Their work frequently appears in top-tier conferences including SIGCOMM, MobiCom, NSDI, and SenSys, as well as leading journals such as IEEE Transactions on Mobile Computing and IEEE Journal on Selected Areas in Communications. Xu's research focuses on cutting-edge problems in wireless communications, with particular emphasis on visible light communication, backscatter networking, high-speed rail networking, and satellite-terrestrial integrated systems. Their work bridges theoretical innovation with practical implementation, often developing novel systems that address real-world networking challenges. Recent publications demonstrate growing leadership in the field, with Xu increasingly serving as first author on significant contributions. The research portfolio shows consistent evolution from foundational mobile networking concepts toward more specialized areas including acoustic sensing, visible light communication, and space-air-ground integrated networks. Xu's work demonstrates strong interdisciplinary connections between networking, systems, and hardware design, with practical applications spanning transportation systems, healthcare monitoring, and next-generation wireless infrastructure. Xu actively collaborates with researchers across institutions, maintaining particularly strong ties with Peking University colleagues including Daqing Zhang, Xuanzhe Liu, and Lingyang Song. Their research has practical implications for 5G/6G deployment, IoT systems, and future mobile networking architectures.

• Finance
• Banking
• Portfolio Optimization
• +2 more

Christos Staikouras is an Adjunct Assistant Professor of Economics at the Athens University of Economics and Business, School of Business Administration. His academic qualifications include a PhD in Banking from Cass Business School, an MBA from Imperial College London, and a BSc in Mechanical Engineering from the National Technical University of Athens. His research focuses on finance, banking, portfolio optimization, economic policy, and bank capital management. Recent publications explore financial crises, risk-adjusted returns in investments, and economic growth drivers in EU periphery nations. He has received multiple awards including a Best Paper Award at the European Applied Business Research Conference (2003) and an Athens Chamber of Commerce Award (1995). Research projects include EU-funded studies on cybersecurity economics and European banking efficiency.

Ying TangView profile

Professor

• Discrete Event Systems
• Sustainable Production and Service Automation
• Intelligent Game-based Learning Environments
• +7 more

Ying Tang is a Professor and Associate Chair in the Department of Electrical & Computer Engineering at Rowan University , where she also serves as Undergraduate Program Coordinator. Her academic journey includes a Ph.D. in Electrical Engineering from New Jersey Institute of Technology, an M.S. in Computer Engineering, and a B.S. in Electrical Engineering, both from Northeastern University. Research Interests focus on: Design, control, and optimization of Discrete Event Systems Intelligent systems for Health and Computational Health Sustainable Production Automation and Digital Engineering Machine Learning and Blockchain applications Energy-aware Manufacturing and AI-driven Education Recent Research Trends show emphasis on: Sustainable manufacturing optimization using harmony search algorithms Machining process modeling with energy consumption analysis AI-integrated educational games for personalized learning Error coupling prediction in precision gear manufacturing Human-machine interaction in industrial systems Scientific Contributions include: Co-inventor of U.S. Patent 9,626,568 for spatial structured light applications Founding chair of two IEEE Technical Committees Over 200 publications with 4420+ citations (h-index 37) Academic Leadership involves: Associate Editor roles in multiple IEEE journals Guest Editor for special issues on Cyber-physical Social Intelligence Editorial Board Member of International Journal of Remanufacturing Research Funding comes from NSF , EPA , DOT , private foundations, and industry partners. Major projects include: SPARC (Systematic Problem-solving & Algorithmic Reasoning for Children) PING (Personalized Instruction and Need-aware Gaming) E4SPA (Sustainable Production Automation Education) Collaborative VR Learning Environment

• Supply Chain Management (SCM)
• Generative Artificial Intelligence (GenAI)
• Quantum Computing in Logistics
• +3 more

Prof. Joachim Ehrenthal is a Professor of Business Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW), specializing in digital supply chain technologies. He holds a PhD from the University of St.Gallen and an MSc from Mannheim University. His research bridges generative AI, quantum computing, and real-world supply chain challenges, with a focus on educational integration and industry collaboration. Teaching activities include tech-centric courses in Digital Supply Chain Management at FHNW’s Bachelor and Master levels, enriched with industry co-developed case studies. He co-leads FHNW’s Competence Center Digital Supply Chain and collaborates with industry partners on GenAI and Quantum initiatives. Research highlights include integrating GenAI with the SCOR model for educational purposes and exploring quantum computing applications in logistics optimization. His work spans multi-agent systems, incident management, and digital twin implementations. He has published extensively in peer-reviewed journals and conferences since 2011, addressing topics like retail out-of-stocks, service-dominant logic, and supply chain resilience. Notable projects include a Swiss National Science Foundation (Innosuisse)-funded study on real-time railway resource disposition and digital transformation case studies in chocolate manufacturing and clinical trials. His expertise combines academic rigor with practical industry engagement, shaping next-generation supply chain practices through innovation.

Gregory J. McRaeView profile

Professor

• Environmental Science and Engineering
• Atmospheric Processes
• Chemical Transport and Transformations
• +5 more

Professor Gregory J. McRae is affiliated with the Department of Chemical Engineering at the Massachusetts Institute of Technology (MIT) . He holds a Ph.D. from California Institute of Technology (1981) and M.S. in Chemical Engineering from the same institution (1975), alongside a B.E. from Monash University (1971). Research Interests : Atmospheric oxidant formation, acid deposition, global climate modeling, chemical transport in multimedia environments, process modeling, numerical analysis, and computational neuroscience. Notable Awards : Presidential Young Investigator Award (NSF, 1984), George Tallman Ladd Research Prize (1985), Niccograph Scientific Visualization Prize (1991), and multiple honors for environmental and computational contributions. Leadership Roles : Member of U.S. EPA Review Panels, National Research Council committees, NAS Panel on Destruction of Chemical Warfare Agents, SANDIA Combustion Research Facility advisory board, and U.S. DoE Science Advisory Board for Advanced Scientific Computing. Academic Contributions : Advisor to interdisciplinary researchers like Chuang-Chung Lee, who developed mathematical models for amyloid fibrillation and synaptic plasticity under his guidance. Publications : Span climate science, chemical engineering, computational methods, and neurodegenerative disease modeling, reflecting his cross-disciplinary expertise.

• Aerospace Engineering
• Fluid Mechanics and Thermal Engineering
• Mechanical Engineering
• +7 more

Dr. Hideaki Ogawa is an Adjunct Associate Professor in the School of Engineering at RMIT University, Australia. His research focuses on aerospace propulsion systems, hypersonic flows, and multi-objective design optimization. He specializes in scramjet combustor dynamics, plasma thrusters, and aeroelastic systems, with applications in space transport and small satellite propulsion. Research interests include aerospace engineering, fluid mechanics, mechanical engineering, and communications engineering. His work addresses challenges in hypersonic combustion, cavity enhanced mixing, and structural nonlinearities. Teaching interests span high-speed aerodynamics, computational fluid dynamics, and evolutionary algorithms. Recent research highlights include optimization of cusped field thrusters for microsatellites, numerical investigations of scramjet combustion, and nonlinear signal processing for aeroelastic systems. His publications emphasize advanced propulsion systems and their integration into space missions. Dr. Ogawa supervises projects on topics such as transonic buffet control, upstream cavity flows, and cracked fuel mixing in scramjets. His collaborations involve multidisciplinary teams addressing challenges in access-to-space systems and space traffic management. He holds a strong focus on practical applications of computational methods and systems engineering approaches.

• Data Privacy
• Evolutionary Computing
• Recommendation Systems
• +5 more

Dr. Jinli Cao is a full-time Associate Professor in the Department of Computer Science and Information Technology at La Trobe University. She holds a BSc from Hebei University, China, and a PhD from the University of Southern Queensland, Australia (1997). Her research focuses on evolutionary computing, data privacy, deep learning for vulnerability assessment, and decision support systems. She has published over 150 papers in top venues such as VLDB and IEEE Transactions series. Dr. Cao leads an ARC-funded project on software vulnerability risk discovery and has secured three ARC grants. She has supervised 11 PhD, 2 Master’s, and 57 Honours students, many of whom work in academia and industries like Oracle and Commonwealth Bank. Teaching contributions include developing courses in databases, data warehouses, and artificial intelligence. Research Interests: Privacy-preserving data publishing and optimization Evolutionary algorithms for dynamic data partitioning Deep learning applications in cybersecurity and healthcare Graph-based machine learning for access control and anomaly detection Decision support systems and top-k query processing Her recent articles explore cutting-edge topics like privacy-preserving spatial crowdsourcing tasks, graph neural networks for traffic prediction, and cybersecurity frameworks for vulnerability prioritization. Awards include competitive ARC grants totaling $450,000 (2023-2025). She actively serves as an Associate Editor for Health Information Science and Systems and has examined over 100 PhD theses across Australian universities. Teaching highlights: Developed 20+ courses including Database Management Systems, Data Warehousing, and Artificial Intelligence. Coordinates units like Decision Support Systems and Intermediate Programming in Java.

• Applied Mathematics
• Electrochemical Systems
• Multiscale Porous Media Modeling
• +4 more

Professor Troy Farrell is the Executive Dean of the Faculty of Science at Queensland University of Technology (QUT). He holds a PhD (QUT) and B.Sc (Hons) from the University of Newcastle. His expertise lies in applied mathematics and physical chemistry, focusing on industrial systems like batteries, solar cells, and biomass processing. He leads major research projects in electrochemical nano-diodes, metal-air batteries, and coal seam gas modeling. Professor Farrell has secured over $2.8M in external funding and led national initiatives such as the Mathematics in Industry Study Group (MISG) and the ATN Industry Doctoral Training Centre. He is a Fellow of the Queensland Academy of Arts and Sciences and has received prestigious awards for his research and teaching. His teaching focuses on mathematical modeling, partial differential equations, and calculus, emphasizing student-centered pedagogy and innovation. Key achievements include developing multiphase models for food drying, phase-field models for lithium-ion batteries, and population balance models for biomass pretreatment. Research Projects: Mathematical modeling of biofuel production from cellulosic materials Electrochemical nano-diodes using Poisson-Nernst-Planck models Optimization of lithium-air batteries for secondary power Multiscale modeling of porous materials with hybrid continuum/particle methods Agrochemical uptake in plant cuticles Awards: ANZIAM Mid-Career Research Award (2015) QUT Vice-Chancellor's Award for Partnerships (2013) Australian Government Citation for Teaching Excellence (2006) Teaching & Leadership: Professor Farrell pioneered innovative teaching methods recognized by the Carrick Institute, coordinating undergraduate and postgraduate programs in Mathematical Sciences. He has mentored over 13 doctoral students and actively bridges academia-industry collaboration through leadership roles in MISG and the ATN IDTC. His work emphasizes translating mathematical models into real-world solutions for energy, agriculture, and environmental sectors. Labs & Teams: He oversees interdisciplinary teams at QUT specializing in electrochemical systems, porous media modeling, and industrial mathematics. Current collaborations include projects with sugar cane industries, battery manufacturers, and coal seam gas operators to address challenges like biomass storage safety and energy storage optimization.

• Risk Management
• Project Management
• Construction Management

Prof. Dr. Gül Polat Tatar is a Professor at the Department of Civil Engineering, Faculty of Civil Engineering at Istanbul Technical University. She holds a PhD in Structural Engineering from the same institution. Her research focuses on Risk Management, Project Management, and Construction Management. Key contributions include studies on machine learning applications in construction cost overrun analysis, subcontractor selection models, and construction 4.0 technology adoption barriers. She has received the Best Paper Award for Design and Risk Management in 2016. Her work spans over 150 peer-reviewed publications, with recent emphasis on optimization models, industry 4.0 technologies, and sustainable construction practices. She has advised numerous research projects and serves as an Education Coordinator at ITU. Education: Bachelor of Science in Civil Engineering, Istanbul Technical University (1993-1997) Master of Science in Building Management, Istanbul Technical University (1997-1999) Doctor of Philosophy in Structural Engineering, Istanbul Technical University (2000-2005) Research Trends: Recent publications emphasize AI-driven construction project management, sustainable practices, and subcontractor performance evaluation. She explores challenges in technology adoption and delay mitigation in developing countries. Awards: Highlighted by her 2016 Best Paper Award and consistent contributions to high-impact journals. Grants & Teams: Leads interdisciplinary teams on construction management innovation, collaborating with industry partners on projects funded by national and international grants. Labs/Teams: Active in ITU’s Construction Management Research Group, focusing on digital transformation and risk analytics.

Bryce MeredigView profile

Adjunct Professor

• Materials Science
• Artificial Intelligence
• Machine Learning
• +4 more

Bryce Meredig is an Adjunct Professor of Materials Science and Engineering at Northwestern University. His research focuses on AI-driven materials discovery, including machine learning methods, autonomous simulations, and materials data infrastructure. He co-founded Citrine Informatics in 2013, a leading enterprise materials informatics software company, serving as CEO and later Chief Science Officer. Education: PhD in Materials Science and Engineering, Northwestern University MBA, Stanford University Bachelor of Arts in Materials Science and Engineering & German Studies, Stanford University Research Interests: Machine learning for materials design Self-driving simulations and labs Materials databases and data infrastructure Automation in materials research His work bridges academia and industry, emphasizing practical applications of AI in accelerating materials innovation. Key Contributions: Developed AutoMat for automated electrochemical materials discovery Authored influential studies on closed-loop frameworks and machine learning validation Pioneered open quantum materials databases and data standardization Awards: AIME Robert Lansing Hardy Award Early Career Achievement Award (Northwestern University) Labs and Teams: Active in Northwestern's Materials Science department and collaborates with industry partners through Citrine Informatics.

Andrew EberhardView profile

Professor

• Optimization Theory
• Machine Learning
• Convex Analysis
• +7 more

Professor Andrew Eberhard holds the position of Deputy Head of Department (Research and Innovation) in the Department of Mathematical and Geospatial Sciences (MGS) at RMIT University's School of Science. He has also served as Deputy Director of the Australian Mathematical Sciences Institute (AMSI) and currently sits on its board. His academic journey includes visiting professorships at institutions such as the University of Perpignan (France), Dalhousie University (Canada), and Blaise Pascal University (France). He has contributed significantly to optimization theory and applications, including roles as Co-chair of the AustMS special interest group (MoCaO) from 2018–2024 and Program Leader of the Platform Technologies Research Institute (2012–2015). Professor Eberhard's research focuses on nonsmooth analysis, convex functions approximation, optimization algorithms, and their applications in control theory, signal processing, and economic modeling. He has applied his theoretical work to real-world challenges like utility function estimation, air traffic flow management, and blood inventory optimization. His recent work includes advancements in stochastic optimization with integer variables and machine learning integration for enhancing algorithm performance. He has been an invited speaker at prestigious events such as the International Conference on Applied Mathematics (2024, Vietnam), Variational and Nonsmooth Analysis (2024, Hong Kong Polytechnic University), and ANZIAM's plenary session (2012, Australia). His teaching interests emphasize nonsmooth analysis and its interdisciplinary applications. Professor Eberhard has supervised numerous research projects, including those on hyperparameter optimization in machine learning, MIMO signal processing, and asset protection routing. His grants include leadership roles in developing algorithms for stochastic integer programming and multi-criteria decision-making under uncertainty. He collaborates actively through the Platform Technologies Research Institute and is affiliated with multiple academic journals as an editor or reviewer.