جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Evolutionary Computation
• Multiobjective Optimization
• +۱۰ مورد دیگر

Professor Xiaodong Li is a faculty member at RMIT University's School of Computing Technologies, serving as Assistant Associate Dean for Data Science & Artificial Intelligence. He holds a Ph.D. in Artificial Intelligence from the University of Otago, New Zealand. His research focuses on machine learning, evolutionary computation, swarm intelligence, and optimization techniques with applications in blockchain security, renewable energy, and logistics. He has received prestigious awards including the 2013 ACM SIGEVO Impact Award and the 2017 IEEE Transactions on Evolutionary Computation Outstanding Paper Award, and is an IEEE Fellow. His academic contributions include editorial roles at IEEE Transactions on Evolutionary Computation and leadership in IEEE Task Forces on Swarm Intelligence and Multi-modal Optimization. Current research interests span automated code generation, quantum AI-driven logistics, and anomaly detection. Supervision projects highlight interdisciplinary applications in AI ethics, solar energy monitoring, and fraud detection. Education: Ph.D. in Artificial Intelligence, University of Otago, New Zealand Key Roles: IEEE Fellow, ARC College of Experts (2023–2025) Publications: Over 280 peer-reviewed articles, including works on niching methods and evolutionary algorithms. Research trends show strong emphasis on hybrid optimization techniques, blockchain security, and AI-driven solutions for sustainability challenges. Recent articles explore dynamic environments, quantum rerouting strategies, and explainable machine learning systems. Awards: ACM SIGEVO Impact Award, IEEE Fellow, ARC College Membership Grants/Projects: Multiple industry-collaborative grants in smart logistics and energy systems. He leads the Data Science & AI team at RMIT, fostering innovation in large-scale optimization and metaheuristics. Active in international conferences like GECCO and IEEE CEC, he promotes open-source benchmark datasets for algorithm testing.

Andrew Pomfretمشاهده پروفایل

مدرس ارشد

• Intelligent Systems
• Robotics
• Flight Control
• +۴ مورد دیگر

Dr. Andrew Pomfret is a Senior Lecturer in the Department of Electronic Engineering at the University of York. His research focuses on intelligent systems and robotics, with expertise in avionics, cognitive networking, and control engineering. He actively supervises PhD students in areas like fault-tolerant systems and multi-agent systems. His work spans robotics, control systems, and interdisciplinary applications in aerospace and environmental science. Education & Affiliations: Electronic Engineering (Lecturer, University of York) Research Interests: Flight control, evolutionary algorithms, structural reconfiguration, image processing, and robotics. His recent work emphasizes robotic swarm intelligence, cooperative transport systems, and eigenstructure assignment in control systems. Publications: His research explores topics like error diversity in robotic swarms, cooperative robotic communication, and helicopter handling qualities. Key areas include swarm task partitioning, multi-agent coordination, and control system optimization. Grants & Projects: Upscaling of greenhouse gas emissions from freshwater wetlands (NERC-funded, 2017–2019) SkyGas: Development of a new technique for determining watershed/airshed gas fluxes (NERC-funded, 2012–2013) Labs/Teams: Collaborates with research groups in robotics and control systems at the University of York, focusing on interdisciplinary projects involving autonomous systems and environmental monitoring.

Zhang Shixuanمشاهده پروفایل

استادیار

• Mathematical Optimization
• Operations Research
• Data Science
• +۵ مورد دیگر

Zhang Shixuan is an Assistant Professor in the Department of Industrial & Systems Engineering at Texas A&M University. His research focuses on mathematical optimization theory and its applications to data science, operations research, and systems engineering. Education: Ph.D. in Operations Research from Georgia Institute of Technology Postdoctoral: Institute for Computational and Experimental Research in Mathematics (ICERM), Brown University His primary research areas include: Polynomial Optimization Integer Optimization Stochastic Optimization Robust Optimization His recent publications explore advances in distributionally robust optimization, security-constrained power flow algorithms, and theoretical aspects of multistage stochastic programming. Key trends in his work emphasize computational efficiency, algorithm design for nonconvex problems, and applications to energy systems and convex geometry. Doctoral Advisees: Jiamin Chen and Qi Xiao.

Peter Roslevمشاهده پروفایل

دانشیار

• Environmental Science
• Environmental Toxicology
• Water Quality
• +۷ مورد دیگر

Peter Roslev is an Associate Professor at the Department of Chemistry and Bioscience, Aalborg University, affiliated with the Faculty of Engineering and Science. He holds a PhD in Microbiology from the University of Maine (1994). His research focuses on environmental science, water treatment technologies, microbial processes, and ecotoxicology. Key areas include methane emission control, UV-based water purification, antimicrobial packaging, and pesticide impacts on wildlife. He leads projects like the Methane Scrubber and IN2AQUAS initiatives, aiming to address water quality, sustainable aquaculture, and environmental remediation. Education: PhD in Microbiology (University of Maine, 1994). Research Interests: Environmental toxicology, water treatment innovation (UV and membrane technologies), microbial ecology, and mitigation of pollutants in aquatic ecosystems. His work aligns with UN Sustainable Development Goals, particularly clean water and climate action. Grants & Projects: Principal Investigator for projects such as Methane Scrubber (2025), IN2AQUAS (2023–2027), and Development of Antimicrobial Films (2022–2025). Collaborates on EU-funded networks and Danish environmental initiatives. Labs/Teams: Active in cross-disciplinary teams addressing water quality, microbial communities, and eco-toxicological assessments. Engages in national and international research networks, including the Danish Environment Agency.

Ivar Lyhneمشاهده پروفایل

دانشیار

• Environmental Assessment
• Sustainability
• Climate Change
• +۴ مورد دیگر

Ivar Lyhne is an Associate Professor at the Department of Sustainability and Planning, Aalborg University's Technical Faculty of IT and Design. His work focuses on environmental assessment, sustainability strategies, and governance of renewable energy systems, particularly through projects like AAU BLUE – Marine & Maritime Research and the DREAMS initiative. He actively collaborates with institutions across Scandinavia and serves as a Senior Consultant at Ramboll Foundation since 2021. Academic Affiliation: Aalborg University (Technical Faculty of IT and Design, Department of Sustainability and Planning) Core Research Areas: Environmental Assessment, Climate Technology, Renewable Energy Governance, Systems Thinking, and Public Participation Lyhne's research explores the integration of Sustainable Development Goals (SDGs) into environmental assessment frameworks, digitalization of assessment tools, and community dynamics in energy infrastructure projects. Recent work emphasizes AI applications in environmental evaluation and creating structured datasets for generative AI training. His publications demonstrate expertise in CCUS (Carbon Capture, Utilization, and Storage) system integration, industrial symbiosis facilitation, and policy innovation. Selected works include studies on obstruction light impacts for wind turbines, transboundary stakeholder engagement, and quality control mechanisms in environmental appraisal. Notable recognition includes the 2022 Best Paper of the Year in the International Association for Impact Assessment Journal, shared with colleagues. He regularly contributes to conferences, peer reviews, and educational programs like the 2025 'Efteruddannelse i Miljøvurdering' series. Lyhne advises on projects related to offshore wind energy (EUopSTART), energy-positive districts (FLEXPOSTS), and Nordic environmental governance. His work bridges academic research with practical implementation, often involving interdisciplinary networks and digital tool development.

• Artificial Intelligence
• Machine Learning
• Data Science
• +۷ مورد دیگر

Dr. Alireza Moayedikia is a Lecturer in Information Systems at the School of Business, Law and Entrepreneurship, Swinburne University of Technology. His research focuses on Artificial Intelligence, Machine Learning, and Data Science, with expertise in social network analysis, natural language processing, and back-end software development. He has over ten years of professional experience in AI and ML, emphasizing data preparation for machine learning tasks. Research Interests: Dr. Moayedikia’s work spans optimization algorithms for crowdsourcing, microtask management, and feature selection. His recent contributions include advancements in matrix factorization, dynamic payment systems for microtask platforms, and community detection in attributed networks. His methodologies often integrate swarm intelligence (e.g., bee colony optimization) and probabilistic models. Publications: His 19 publications reflect a strong focus on AI-driven solutions, including contributions to data-driven healthcare systems and green logistics. His articles address challenges in sparse data handling, worker reliability estimation, and multi-criteria decision-making frameworks. Grants: He contributed to the SCOPE 3 research contract (2020–2021), developing prototypes for tracking Green House Gas emissions in last-mile delivery systems. Labs/Teams: Collaborates within interdisciplinary teams at Swinburne, focusing on applied AI and sustainable logistics solutions.

Sandy Brownleeمشاهده پروفایل

مدرس ارشد

• Optimization
• Artificial Intelligence
• Metaheuristics
• +۷ مورد دیگر

Dr Sandy Brownlee is a Senior Lecturer in Computing Science and Mathematics at the University of Stirling, affiliated with the School of Natural Sciences. He leads the Data Science and Intelligent Systems research group and co-leads the AI Theme for SICSA. He is also a Visiting Fellow in Civil and Building Engineering at Loughborough University. His work focuses on explainable optimization techniques, metaheuristics (including evolutionary algorithms and estimation of distribution algorithms), fitness modeling, constraint handling, and decision support systems. Applications span civil engineering, healthcare, software engineering, and art. Education: BSc (Hons) in Computer Science (2005) and PhD in Multivariate Markov Networks for Fitness Modelling (2009), both from Robert Gordon University. Post-PhD roles included research at Loughborough University and industry experience in energy sector software engineering before joining Stirling in 2013. Research interests emphasize bridging optimization theory and real-world applications, with a focus on algorithm transparency and value-added insights. He has over 100 publications, including work on surrogate models, genetic improvement (GI), and XAI in evolutionary computation. Current roles include MSc program director for Artificial Intelligence and Big Data. His Erdos-Bacon number (8) reflects interdisciplinary reach, combining academic collaboration (3) with minor media appearances (5). He actively contributes to conferences, workshops, and public lectures on AI and optimization.

Daniel Bochslerمشاهده پروفایل

مدرس

• Entrepreneurial Marketing
• Entrepreneurial Strategy
• Systems Engineering in Business
• +۵ مورد دیگر

Daniel Bochsler is a Lecturer in the Department of Management at the Naveen Jindal School of Management, University of Texas at Dallas. He holds an MBA from the University of Houston (1989) and a B.S. in Computer Science from Oregon State University (1979). His research focuses on applying systems engineering principles to entrepreneurial business strategies, particularly in commercial space industries and alternative energy sectors. He has held leadership roles in innovation commercialization, including Director at UTD and Board Chair of the North Texas Regional Center for Innovation and Commercialization. Bochsler has extensive industry experience, including roles as CEO of Natural Resource Recovery Inc. and Global Account Manager at Xiotech Corp. His research interests span entrepreneurial marketing, technology forecasting, and sustainable resource management. Key publications include works on commercial space value chains, waste-to-energy systems, and fuzzy logic in telecommunications. He has received multiple awards for technical excellence and leadership, including NASA Group Achievement Awards and the Tech Success Award. Bochsler actively participates in academic committees, such as the Distance Learning Faculty Senate Committee, and has contributed to curriculum development in entrepreneurship and technology management. His professional affiliations include INCOSE and the American Management Association.

Chris Connorمشاهده پروفایل

استادیار

• Additive Manufacturing
• Engineering Design
• Manufacturing Management
• +۵ مورد دیگر

Chris Connor is an Assistant Professor at Northumbria University in the Department of Mechanical and Construction Engineering. He is an experienced mechanical engineer with a focus on applied research and industrial impact. PhD in Mechanical Engineering (2009) MSc in Manufacturing Systems (1995) His research interests include additive manufacturing, engineering design, manufacturing management (e.g., Six Sigma), and renewable energy. He has contributed to the UN Sustainable Development Goals through his work. His recent publications span topics in additive manufacturing, renewable energy policies, biomedical engineering, and design education. These works reflect interdisciplinary research bridging materials science, industrial practices, and educational pedagogy. Chris has supervised PhD and MSc students, though individual names are not listed. His work has been cited 135 times, indicating a growing academic network and influence in engineering and sustainable practices.

• Sustainable Energy Systems
• Numerical Optimization
• Deep Learning
• +۳ مورد دیگر

Dr. Manuel Dahmen is the Head of Department at the Institute of Climate and Energy Systems (ICE-1) within the Research Center Jülich. His research focuses on designing sustainable and cost-efficient energy systems through advanced techniques like numerical optimization and deep learning. Key areas include renewable energy integration, process network analysis, and machine learning-driven system design. His work addresses challenges in decarbonizing industries, optimizing energy systems, and developing tailor-made fuels for high-efficiency engines. Dahmen leads interdisciplinary projects combining computational methods with practical engineering solutions, emphasizing robust design under uncertainty. He contributes to open-source tools like COMANDO for energy systems optimization and explores innovations in graph neural networks for molecular property prediction. Research trends reflected in his publications highlight optimization algorithms (e.g., semi-infinite programming), demand response strategies for industrial processes, and physics-informed machine learning for dynamic systems. Dahmen’s contributions bridge theoretical advancements with real-world applications, aiming to accelerate the transition to sustainable energy systems.

Martins Obiمشاهده پروفایل

مدرس

• Additive Manufacturing
• Design for Additive Manufacturing (DfAM)
• Sustainable Manufacturing
• +۴ مورد دیگر

Martins Obi is a Lecturer in Engineering Systems & Supply Chain Management at the College of Engineering and Physical Sciences, Aston University. He specializes in Additive Manufacturing, Sustainable Production Systems, and Supply Chain Optimization. His research focuses on Agent-Based Systems, Circular Manufacturing, and Net Zero transitions. Education: BSc in Mechanical Engineering from Federal University of Technology Minna PG Cert (qualification not specified) MSc in Engineering and Management of Manufacturing Systems from Cranfield University PhD in Design for Additive Manufacturing from Loughborough University Research Interests: Obi’s work bridges advanced manufacturing technologies with sustainability goals. Key areas include: Design for Additive Manufacturing (DfAM) Circular Economy applications in polymer recycling Agent-based systems for dynamic production optimization Net Zero transition strategies for UK manufacturing sectors PhD Supervision: Currently recruiting candidates in: Agent-Based Systems in Centralised Systems Circular Manufacturing Ecosystems Supply Chain Ecosystems

• Marine Engineering
• Shipping Decarbonization
• Alternative Fuels
• +۴ مورد دیگر

Ömer Berkehan İnal is a Researcher in the Department of Marine Engineering at Istanbul Technical University. His work focuses on decarbonization of shipping, alternative fuels, hybrid propulsion systems, and sustainable maritime technologies. He contributes to UN Sustainable Development Goals related to affordable and clean energy, and climate action. Key research areas include hydrogen fuel cell applications, waste heat utilization, and legislative frameworks for maritime sustainability. His research explores innovative solutions for reducing greenhouse gas emissions in shipping through electrification, hybridization, and novel energy systems. Notable contributions include case studies on cargo ships using hydrogen fuel cells and waste heat recovery systems in ships. He also emphasizes educational frameworks for integrating mechatronics and decarbonization strategies into marine engineering curricula. Collaboration networks span international institutions, with active research in Turkey and Europe. His publications address technical challenges in maritime decarbonization, legislative barriers for alternative fuels, and system design for zero-emission vessels.

Kara Marsdenمشاهده پروفایل

مدرس

• Sustainable Food Production
• Nitrogen Cycling in Agroecosystems
• Soil Gaseous Emissions (N₂O, N₂)
• +۳ مورد دیگر

Dr. Kara Marsden is a Teaching and Research Lecturer in Soil Science at Bangor University's School of Environmental and Natural Sciences. She holds a BSc and PhD in Environmental and Soil Science from Bangor University, and completed a Marie Skłodowska-Curie Global Fellowship at the University of Melbourne and Bangor. Her research focuses on sustainable food production, nitrogen cycling, gaseous emissions (N₂O/N₂), and plant-microbe interactions. She has published over 30 peer-reviewed papers, with an h-index of 16 and 1000+ citations. Her current work addresses agricultural emission mitigation strategies, soil microbial dynamics, and livestock nitrogen management. She leads modules on environmental science and pollution, and contributes to field courses in Tenerife. Active in professional bodies, she chairs the Welsh Regional Soils Discussion Group and serves on the EDI Committee. Her recent projects include studying emission hotspots and climate-smart agriculture practices. Key research trends include optimizing nitrogen use efficiency, quantifying soil-plant-animal interactions, and evaluating microplastic impacts on soil biology. She collaborates on interdisciplinary projects, linking field observations with lab-based analyses to inform sustainable land management. Grants and projects include an ongoing study on lower plant roles in temperate rainforest carbon budgets (2025–2026). No scientific awards are listed, but her work has significant policy implications for UK agricultural emissions targets.

• Rock mechanics
• Acoustic emissions
• Rock physics
• +۵ مورد دیگر

Carl Sondergeld is a Professor and Curtis Mewbourne Chair at the University of Oklahoma's Mewbourne School of Petroleum and Geological Engineering. He holds a Ph.D. in Geophysics from Cornell University (1977) and prior degrees from Queens College, CUNY. With 19 years at Amoco Production Company's Tulsa Research Center, he pioneered petrophysical research, sonic logging tools, and wellsite core analysis systems. He has 14 U.S. patents and has taught courses on petrophysics, seismic reservoir modeling, and unconventional resources for 17 years at OU. His research focuses on shale reservoirs, including microstructural characterization, anisotropy, hydraulic fracturing, NMR applications, and diffusion mechanisms. He leads the 'Experimental Rock Physics' and 'Unconventional Shale Consortium' industrial consortia. Awards include two Brandon Griffin Awards and four SPE Student Chapter Professor of the Year recognitions. Key technical expertise spans rock mechanics, acoustic emissions, and reservoir simulation. Education: B.A., Geology, Queens College, 1969 M.A., Geology, Queens College, 1973 Ph.D., Geophysics, Cornell University, 1977 Awards: Brandon Griffin Award (2014, 2017) SPE Professor of the Year (2010, 2013, 2016, 2020) Research Consortia: Experimental Rock Physics Consortium Unconventional Shale Consortium His recent work emphasizes diffusion-driven EOR mechanisms, CO2 sequestration, and shale microstructure using machine learning. Over 150 publications span hydraulic fracturing mechanics, NMR applications in reservoirs, and shale petrophysics innovations.

• Optimization Algorithms
• Additive Manufacturing
• Superconductivity
• +۳ مورد دیگر

Di Wu is a Research Fellow at the Department of Automation Technology and Mechanical Engineering , part of the Faculty of Engineering and Natural Sciences at Tampere University. Their work focuses on advanced manufacturing technologies, optimization algorithms, and materials science, with significant contributions to thermal modeling in additive manufacturing and superconductivity research. Affiliations : Tampere University (since 2019) Research Interests : Specializes in multi-objective optimization using AI methods, additive manufacturing process modeling, thermal field prediction in metal AM, and superconductivity applications. Their work integrates knowledge-based systems and causal modeling to enhance engineering design processes. Key Research Trends : Recent publications emphasize real-time thermal management in thin-wall metal additive manufacturing, ANN-based optimization for HTS solenoids, and AI-driven approaches to superconductivity research. They also explore functional modeling and dimensional analysis in welding and micro-turbine systems. Collaborations : Active in international collaborations with institutions like American Society of Mechanical Engineers and Springer, focusing on advanced manufacturing and material science challenges.