جستجوی استاد راهنمای دانشگاهی

• Combinatorial Optimization
• Operations Research
• Artificial Intelligence
• +۳ مورد دیگر

Corinne LUCET-VASSEUR is a University Professor at Université de Picardie Jules Verne (UPJV), leading Research Unit UR 4290 (OCIA - Optimisation Combinatoire, Images et Applications). Her office (Room 302, Tel: 5900) serves as the hub for her research group focused on combinatorial optimization and artificial intelligence applications. Her research spans: Combinatorial Optimization : Developing metaheuristics for NP-hard problems Healthcare Logistics : Patient flow optimization, facility location, simulation training Logistics Engineering : Parcel distribution, vehicle routing with time windows Algorithm Design : Ant Colony Optimization, Adaptive Large Neighborhood Search, portfolio methods She applies these methodologies to solve complex real-world problems, particularly in healthcare systems where resource constraints and scheduling complexity demand innovative optimization approaches. Her work bridges theoretical advances with practical implementation through industrial partnerships. Current research projects include: SMILE PICK UP (CIFRE industrial partnership) Simusanté (healthcare simulation) LORH (logistics optimization) These projects secure ongoing funding and provide doctoral training opportunities through industry collaboration. Her publication record demonstrates consistent methodological innovation applied to healthcare and logistics challenges across multiple European conferences and journals. Professor Lucet-Vasseur actively mentors junior researchers through co-authorship on conference papers and journal articles. Her supervision style emphasizes practical problem-solving with industry relevance, preparing students for both academic and industrial careers in optimization. The OCIA research unit provides a collaborative environment for tackling complex combinatorial problems with real-world impact. The OCIA laboratory serves as UPJV's center for combinatorial optimization research, specializing in metaheuristic development for healthcare and logistics applications. The lab maintains strong industry connections through CIFRE contracts and applied projects, ensuring research relevance while providing students with exposure to real business challenges. Current focus areas include adaptive algorithm selection using reinforcement learning and fitness landscape analysis for optimization problems.

• Combinatorial Optimisation
• Explainable AI
• Metaheuristics
• +۷ مورد دیگر

Dr. Lee Christie is a Research Fellow at Robert Gordon University's School of Computing, Engineering & Technology, where he conducts research in optimization and artificial intelligence. He is affiliated with the Complex Optimisation Research Group and maintains connections with the National Subsea Centre through his research on net-zero operations. His educational background includes: BSc (Hons) in Computer Science from Robert Gordon University (2003-2007) MSc in Information Engineering (Distinction) from Robert Gordon University (2009-2011, part-time) PhD in Computational Intelligence from Robert Gordon University (2011-2016) Dr. Christie's research primarily focuses on combinatorial optimization, structure learning, and blockchain technologies. He investigates how to make non-deterministic solvers more transparent through trajectory mining and feature extraction. His work bridges theoretical optimization techniques with practical applications in transportation systems (particularly connected autonomous vehicles), renewable energy (wind farm optimization), and supply chain management. He has published extensively on explainable metaheuristics, with a growing emphasis on making optimization algorithms interpretable for end-users while maintaining effectiveness. His recent publications (2021-2025) demonstrate a clear research trajectory toward explainable AI for optimization algorithms, with applications spanning transportation systems, renewable energy infrastructure, and complex supply chains. These works showcase his ability to translate theoretical advances into practical solutions for real-world problems with societal impact. Dr. Christie has secured research funding for projects including the A.R.T. Forum NSR (2019-2022), which developed implementation roadmaps for automated road transport in the North Sea Region. He teaches programming for business analytics courses and actively contributes to the Aberdeen Python User Group as a steering committee member. His academic service includes supervision of PhD students, with Dr. Martin Fyvie recently completing a dissertation on 'Explainability of Non-Deterministic Solvers' under his guidance as second supervisor. Dr. Christie maintains active collaborations with researchers including John McCall, A.-C. Zăvoianu, and A.E.I. Brownlee, resulting in consistent publication output across reputable venues in evolutionary computation and artificial intelligence.

• Computational Intelligence
• Control Theory
• Fuzzy Logic
• +۷ مورد دیگر

Dr. Atakan Sahin is a researcher at Robert Gordon University's School of Computing, Engineering & Technology, affiliated with the Complex Optimisation Research Group. His work focuses on computational approaches to energy system optimization and industrial process control. His educational background includes a PhD in Pure and Applied Chemistry from University of Strathclyde (2016-2020), an MSc in Control and Automation Engineering from Istanbul Teknik Üniversitesi (2014-2016), and a Bachelor's degree in the same field from the same institution (2009-2014). His doctoral research addressed monitoring complex nonstationary industrial processes. Dr. Sahin's research spans Computational Intelligence, Control Theory, and Fuzzy Logic applications with emphasis on Statistical Process Control and Machine Learning. His current work through the D4NZ project optimizes energy grids for renewable integration, focusing on multi-objective criteria including cost and robustness in offshore wind farm infrastructure. His recent publication output demonstrates active contribution to optimization research, particularly in renewable energy systems where computational methods solve complex engineering challenges. The 2024 conference paper on wind farm cable layouts represents practical application of his optimization expertise. Dr. Sahin maintains active research funding through the Scottish Government's Energy Transition Fund and collaborates internationally, as evidenced by recent conference participation in Austria. His work bridges theoretical computational methods with practical energy infrastructure challenges, supporting the UK's net-zero emissions targets through advanced optimization techniques.

• Evolutionary Computation
• Multi-Objective Optimization
• Artificial Intelligence
• +۷ مورد دیگر

Dr. Ciprian Zavoianu is an academic researcher at Robert Gordon University (RGU) in the School of Computing, Engineering & Technology. He leads the Net Zero Operations research programme at the National Subsea Centre and is affiliated with the Complex Optimisation Research Group. His work focuses on applying artificial intelligence, particularly evolutionary computation algorithms, to solve complex real-world optimization problems with practical engineering applications. Dr. Zavoianu earned his academic qualifications from West University of Timisoara, Romania (BSc and MSc in Computer Science) and Johannes Kepler University Linz, Austria (PhD in Computer Science, 2015). His doctoral research focused on enhancing multi-objective evolutionary algorithms for computationally-intensive optimization problems. His primary research interests include: Evolutionary Computation Multi-Objective Optimization Data Mining & Machine Learning (particularly for surrogate modeling) Timetabling and Rostering Parallel/Distributed Computing Dr. Zavoianu's recent publications (2021-2025) demonstrate a strong focus on applying optimization techniques to transportation systems, electrical machine design, and sustainable energy solutions. His work consistently addresses the challenge of computationally expensive optimization through innovative surrogate modeling approaches, enabling practical applications of evolutionary algorithms to real-world engineering problems. He has secured multiple research grants including 'Data For Net Zero' and 'Ferry Passenger and Freight Modelling for Shetland,' demonstrating the practical relevance and industry applicability of his research. Dr. Zavoianu actively supervises five PhD/EngD students across diverse topics including predictive analytics for subsea installations, optimization of electrical machines, and operations optimization for harbor operations. His supervision approach emphasizes bridging theoretical algorithm development with practical implementation in engineering contexts. His laboratory work is centered around the National Subsea Centre, where he leads the Net Zero Operations research programme, focusing on sustainable solutions for the energy transition through advanced computational methods.

Izabela Lubowieckaمشاهده پروفایل

استاد

• Biomechanics
• Computational Mechanics
• Medical Device Optimization
• +۲ مورد دیگر

Prof. Izabela Lubowiecka serves as a Professor at the Department of Structural Mechanics within the Faculty of Civil and Environmental Engineering at Gdańsk University of Technology. Her office is located in the Main Building (room 467A) with contact details including email lubow@pg.edu.pl and phone (58) 348 64 08. She maintains an active research profile with current projects and recent publications through 2025. Her research spans computational biomechanics with specific focus on abdominal wall mechanics, hernia repair systems, and temporomandibular joint analysis. She integrates structural engineering principles with medical applications through advanced computational modeling, uncertainty quantification, and machine learning techniques. Key methodologies include Self-Organising Maps for biomechanical data clustering and digital image correlation for in vivo strain analysis, targeting improvements in medical device design and surgical outcomes. Recent publications (2023-2025) demonstrate consistent interdisciplinary work bridging engineering and clinical medicine. Core themes include mechanical compatibility optimization of hernia implants, failure analysis of surgical mesh systems, and machine learning applications for identifying biomechanically similar tissue regions. This research emphasizes patient-specific modeling through uncertainty quantification and sensitivity analysis to address clinical challenges like hernia recurrence. Prof. Lubowiecka secures significant research funding through national programs: Mechanics of anterior abdominal wall in optimisation of hernia treatment : OPUS project (UMO-2017/27/B/ST8/02518) since 2018 3D-JAW : TMJ modeling for dental applications (POIR.04.01.02-00-0029/17-00) since 2017 Geometric-strength analysis of historical carpentry joints : OPUS project (UMO-2015/17/B/ST8/03260) since 2016 She leads a research team collaborating with medical professionals on translating computational biomechanics into clinical solutions for hernia repair and dental prosthetics, with emphasis on practical implementation of research findings.

• Computational Fluid Dynamics
• Design Optimisation
• Material Selection

Dr Dani Harmanto is an Associate Professor in Aeronautical Engineering at the School of Engineering and Sustainable Development, De Montfort University, Leicester. He is a chartered engineer with over 20 years of experience in UK higher education. His educational background includes: PhD in Automotive Engineering from Coventry University, UK MSc in Automotive Engineering from Coventry University, UK Bachelor's degree in Mechanical Engineering from Institut Teknologi Malang, Indonesia Dr Harmanto's research focuses on multidisciplinary areas including Computational Fluid Dynamics, Design Optimisation, and Material Selection. He integrates material science, design optimization, and fluid dynamics to address engineering challenges in sustainable energy systems and aeronautics. His work emphasizes practical applications in thermal management and aerodynamic efficiency. He has been recognized as an Inspirational Lecturer by the School of Engineering and Sustainable Development at De Montfort University in 2023. Inspirational Lecturers 2023 | School of Engineering and Sustainable Development, De Montfort University Dr Harmanto actively supervises postgraduate research, currently guiding Teerapath Limboonruang's PhD on optimizing heat transfer in solar parabolic trough collectors. He maintains strong research collaborations with Indonesia and other Far East nations, leveraging his background to develop sustainable research ecosystems and facilitate international partnerships in engineering education. He contributes to the Institute of Energy and Sustainable Development (IESD), holds Chartered Engineer status, and is a member of the Institution of Engineering Designers. His administrative roles include service on the Teaching and Learning committee (IED).

Jaume Fitó-De-La-Cruzمشاهده پروفایل

دانشیار

• Energy efficiency
• Multi-source district heating and cooling systems
• Hybrid energy networks
• +۵ مورد دیگر

Dr. Jaume Fitó-De-La-Cruz is an Associate Professor at Université Savoie Mont Blanc, where he is affiliated with Polytech Annecy Chambéry engineering school and the LOCIE (Laboratory of Optimisation of Energy and Industrial Processes). He holds a position in CNU Section 62 - Energy, Process Engineering, and maintains an active research program focused on multi-source energy networks and sustainable energy systems. His research interests span energy efficiency, multi-source district heating and cooling systems, hybrid energy networks, energy management optimization, exergy and exergoeconomic analyses, thermodynamic processes, and waste heat recovery. Dr. Fitó-De-La-Cruz has developed innovative approaches for assessing the flexibility potential of interconnected energy networks and has pioneered multi-criteria assessment methods for projects involving multiple stakeholders. Analysis of his recent publication record (2020-2024) reveals a strong focus on district heating networks, waste heat recovery systems, and the integration of demand-side management strategies into energy system design. His work consistently applies comprehensive 4E (energy, exergy, economic, environmental) analysis frameworks to evaluate energy systems, with particular attention to multi-stakeholder projects where different parties have competing objectives. Dr. Fitó-De-La-Cruz teaches Applied Mechanics, Structural Mechanics, Climate Engineering, and Building Information Modeling at Polytech Annecy Chambéry. He has co-developed OMEGAlpes, an open-source optimization tool for district-scale energy planning, and has published extensively on topics related to energy transition and decarbonization strategies for urban energy systems. His research demonstrates how consideration of demand-side management during initial design phases can lead to more efficient system sizing and reduced investment costs. As a member of LOCIE, Dr. Fitó-De-La-Cruz contributes to research on energy system optimization, working closely with industrial partners and other academic institutions on projects related to waste heat valorization, renewable energy integration, and the development of more sustainable urban energy networks.

• Benefits Realisation in Project Management
• Value Generation in Projects
• Lean Manufacturing and Process Optimisation
• +۳ مورد دیگر

Dr. Stylianos Sapountzis serves as Programme Leader for the MSc in Project Management at Salford Business School, University of Salford, where he leads modules including Project Management Leadership and Skills (PG), Advanced Project and Logistic Management (PG), and Project Management (UG). With an industrial background in manufacturing management within the electronics sector, he brings practical expertise to his academic role, having previously worked as a production manager and process engineer focusing on production optimization and new product introduction. His educational background includes: PG Cert Academic Practice (2015, University of Salford) PhD in Project Management (2013, University of Salford) PgDip Advanced Manufacturing Systems (1998, University of Salford) BSc (Hons) Manufacturing with Languages (1997, Manchester Metropolitan University) Dr. Sapountzis specializes in benefits realization frameworks, particularly his BeReal process for healthcare infrastructure projects, with research spanning value generation in projects, lean manufacturing applications, and digital transformation in project management. His scholarly work demonstrates a clear trajectory from healthcare infrastructure research toward contemporary applications of AI in project management and supply chain optimization, with recent publications examining digital transformation challenges in UK higher education and AI applications in negotiation activities. His research portfolio shows strong interdisciplinary connections between traditional project management principles and emerging digital technologies, with significant contributions to understanding how lean thinking can be applied across diverse sectors including healthcare, construction, and pharmaceutical manufacturing. The publication record reveals consistent output with increasing focus on digital transformation and AI applications since 2020. As a key member of the Health and Care Infrastructure Research and Innovation Centre (HaCIRIC), Dr. Sapountzis has presented research to international audiences and national bodies including the Department of Health, NHS Trusts, and Manchester City Council. His teaching expertise encompasses project planning and delivery tools, stakeholder management, and the Lean Toolbox, bridging theoretical concepts with practical industry applications developed through his earlier manufacturing career.

Anastasios Kouvelasمشاهده پروفایل

مدرس

• Traffic flow theory
• System and control theory
• Optimization
• +۱۰ مورد دیگر

Dr. Anastasios Kouvelas is a Lecturer at ETH Zurich, where he serves as head of the Road Traffic Engineering research group at the Institute of Transport Planning and Systems (IVT), Department of Civil, Environmental and Geomatic Engineering. He has held this position since August 2018, succeeding Dr. Monica Menendez who moved to New York University in Abu Dhabi. Prior to joining ETH Zurich, he was a research associate at the Urban Transport Systems Laboratory (LUTS) at EPFL (2014-2018) and a postdoctoral fellow at Partners for Advanced Transportation Technology (PATH) at the University of California, Berkeley (2012-2014). Dr. Kouvelas' research focuses on modeling, simulation, optimization and traffic flow control. His work aims to develop real-time solutions based on control theory and operations research methods. The Road Traffic Engineering group develops algorithmic solutions that are components of intelligent transportation systems used in traffic control centers. Recent technological advances in autonomous vehicles have expanded their research topics as the industry seeks efficient operational solutions for autonomous mobility. They are particularly interested in extending their work to the design of advanced management strategies for urban networks that utilize connected vehicles to improve traffic operations and develop network-wide control strategies that minimize environmental impacts. His recent publications (2023-2025) demonstrate strong focus on traffic prediction using deep learning techniques, bike lane allocation impacts on urban networks, transit network resilience against disruptions, vehicle trajectory extraction from aerial recordings, and traffic control for mixed traffic systems with connected and autonomous vehicles. His work bridges theoretical developments in control theory with practical traffic engineering challenges. Scientific Awards No specific scientific awards were mentioned in the provided information. Advising and Grants Dr. Kouvelas supervises PhD and Master's students in traffic engineering and intelligent transportation systems. His research is supported by various grants including a grant from the Hong Kong Research Grant Council (Grant No. GRF 11216323) for research on traffic speed prediction. Laboratories and Teams Dr. Kouvelas leads the multidisciplinary Road Traffic Engineering research group at IVT, which consists of researchers with backgrounds in civil engineering, electrical engineering, mechanical engineering, computer science, control, and operations research. The group's work spans multiple areas including traffic flow theory, traffic operations, connected and automated vehicles, and intelligent transportation systems.

Jens Geislerمشاهده پروفایل

استاد

• Control Engineering
• Modeling and Simulation
• Wind Turbine Control
• +۳ مورد دیگر

Prof. Dr. Jens Geisler serves as Professor of Control Engineering, Modelling and Simulation at Flensburg University of Applied Sciences' Department of Energy and Biotechnology since March 2020. His career bridges academic research and industrial wind energy applications with expertise in multivariable control systems and dynamic modeling. His educational background includes: Dipl.-Ing. (FH) in Mechanical Engineering and Computer Science from Osnabrück University of Applied Sciences M.Sc. in Mechatronic Systems Engineering from Osnabrück University of Applied Sciences Geisler's research spans advanced control methodologies for renewable energy systems, specializing in wind turbine grid integration and elastic multibody dynamics . Core competencies include optimal control algorithms, real-time numerical simulation, and microcontroller implementation for industrial applications, with significant contributions to self-optimizing mechanical systems and rail vehicle guidance technologies. His 2022-2025 publications reveal a strategic research trajectory toward AI-enhanced state estimation and automated observer design, emphasizing practical validation with real-world measurements while simplifying complex aerodynamic models for control engineering applications in wind energy systems. No scientific awards were documented in the provided sources. Teaching responsibilities encompass Energy Sciences, Mechanical Engineering, and System Technology programs, with industry-focused curriculum development. No student advisement or grant information was disclosed in available materials. Geisler maintains active research collaborations through projects including the SFB614 'Self-optimising systems in mechanical engineering' and the RailCab initiative, alongside extensive industry experience developing grid-support control systems for wind turbines at Senvion GmbH and DEIF Wind Power.

Sarah Immanuelمشاهده پروفایل

مدرس ارشد

• Biomedical Signal Processing
• Sleep Disorder Diagnostics
• Machine Learning for Healthcare
• +۵ مورد دیگر

Sarah Immanuel is a Senior Lecturer in the Business and Hospitality vertical at Torrens University, specializing in Data Management and Data Analytics. She directs teaching, research, and subject coordination within the Centre for Artificial Intelligence Research and Optimisation (AIRO), leveraging her 23+ years of academic experience across Australian and international institutions. Her educational background includes: Bachelor of Electrical and Electronics Engineering from Bharathiar University Master of Applied Electronics Engineering from Bharathiar University PhD in Biomedical Engineering from The University of Adelaide (dissertation: Polysomnographic signal processing for advanced diagnostics of paediatric sleep disordered breathing) Immanuel's research focuses on biomedical signal processing applications for sleep disorders and clinical diagnostics. She develops machine learning models for disease prediction in sleep disorders, mental health, and cardiovascular conditions, while creating data analytics platforms for healthcare decision-making. Her work integrates Signal and Image Processing with AI to address Digitally Enhanced Living challenges, particularly for elderly populations through ARC Industry Transformation Research Hub projects at Flinders University. Analysis of her 27 research outputs reveals consistent focus on cardiorespiratory dynamics, with recent publications (2023-2024) emphasizing transvenous phrenic nerve stimulation for central sleep apnea, heart rate variability biomarkers for stress/cognitive decline, and machine learning applications for surgical candidate prediction. Her fingerprint shows dominant themes in Central Sleep Apnea (100%), Transvenous Phrenic Nerve Stimulation (100%), and Polysomnography (60%). As an active PhD supervisor, she mentors students in cardiorespiratory signal processing and machine learning for clinical applications. Her research has generated significant community impact through the ARC Hub project on elderly care technologies. Immanuel maintains active research collaborations through Flinders University's Academic status position and contributes to healthcare innovation via the AIRO center's data-driven platforms.