Find Academic Supervisors

• Machine Learning
• Computer Vision
• Bioinformatics
• +4 more

Adriana Birlutiu is a Lecturer in the Computer Science Department at 1 December 1918 University of Alba Iulia , Romania. Her expertise lies in machine learning, computer vision, bioinformatics, and transfer learning, with a recent focus on porcelain-industry optimisation. Education Ph.D., Radboud University Nijmegen, Netherlands (2011) M.Sc., Babeș-Bolyai University of Cluj-Napoca & University of Lorraine (Erasmus), 2005 B.Sc., Babeș-Bolyai University of Cluj-Napoca, 2004 Research Interests Adriana's research spans machine learning , deep learning , computer vision , and bioinformatics . She has contributed to preference learning, domain adaptation, protein–protein interaction prediction, and automated quality control in porcelain manufacturing. Her recent projects integrate deep neural networks with industrial computer-vision systems to detect defects and recognise characters on ceramic surfaces. Publication Trends Across 15 recent publications (2010-2019), Adriana has consistently explored transfer learning , multi-task learning , and Bayesian methods . Articles cluster around two major axes: biomedical applications (protein networks, cancer relapse prediction, respiratory-motion modelling for radiotherapy) and industrial AI (porcelain defect detection, character recognition). The work shows a clear evolution from theoretical machine-learning foundations to practical, domain-specific implementations. Grants & Projects SIVAP (2016-2018): Intelligent ML & computer-vision system for porcelain manufacturing optimisation, UEFISCDI PN-III-P2-2.1-BG-2016-0333. CMRCC (2017-2018): Computational Models for Reproducing Ceramics Colors, UEFISCDI PN-III-P2-2.1-PED-2016-1835. Student Supervision & Mentoring Adriana has supervised more than 25 undergraduate and master’s theses. Her students have won multiple awards at national conferences such as In-Extenso and SCCSS-IEECC , covering topics from automated defect detection to web applications for academic scheduling. Teaching Responsibilities She teaches courses including Machine Learning , Mathematical Software , Fundamental Algorithms , Object-Oriented Databases , and Modelling and Simulation at both undergraduate and master levels.

Solomon BrownView profile

Professor

• Mathematical Modelling
• Process Analysis
• Optimisation
• +9 more

Professor Solomon Brown is a faculty member in the Department of Chemical and Biological Engineering at the University of Sheffield, School of Chemical, Materials and Biological Engineering. His research focuses on mathematical modelling, process analysis, and optimization of clean energy systems, particularly in energy storage, techno-economic analysis, and uncertainty quantification using Gaussian processes. PhD in Modelling Fluid Flow and Ductile Fractures (UCL, 2011) MSci in Mathematics (King’s College London, 2007) Research Interests: • Mathematical Modelling of Energy Systems • Techno-Economic Analysis of Storage Technologies • Uncertainty Quantification and Gaussian Processes • Agent-Based Models for Technology Adoption • Scheduling and Supply Chain Analysis Scientific Awards: IChemE Frank Lees Medal (for CO2 pipelines safety research during PhD) Publications Trends: Recent work spans energy storage systems (e.g., Li-ion batteries, solid oxide cells), climate policy under uncertainty, run-of-river hydropower optimization, and CO2 transport in carbon capture projects. His studies often integrate computational models with real-world data to address clean energy challenges. Contact: Email: s.f.brown@sheffield.ac.uk

• Computational Fluid Dynamics
• Chemical Engineering
• Optimisation
• +4 more

Nausheen Basha is a Researcher in the Department of Chemical Engineering at Imperial College London, part of the Faculty of Engineering. Previously, she held a Research Assistant position at City, University of London. She earned her PhD in Chemical Engineering from City, University of London (2017–2021) and an MSc in Aerospace Engineering from the University of Manchester (2013–2014). Education: PhD in Chemical Engineering, City, University of London (2017–2021) MSc in Aerospace Engineering, University of Manchester (2013–2014) Research Interests: Nausheen’s work focuses on integrating machine learning and computational fluid dynamics (CFD) to enhance engineering design and optimization. Her research spans computational fluid dynamics, chemical engineering optimization, and the application of machine learning techniques such as deep learning and Bayesian optimization. She explores multiphase systems, reactor design, and the development of surrogate models to improve simulation efficiency and accuracy in fluid dynamics and mechanical engineering contexts. Research Trends: Her recent work emphasizes multi-fidelity methods, Bayesian optimization, and machine learning-driven approaches to solve complex fluid dynamics problems. She has contributed to advancements in flow reactor design, laminar mixing systems, and the analysis of dispersed oil-water flows, often leveraging CFD simulations combined with data-driven frameworks. Advising & Grants: No formal advisees or grant information is listed in the provided text. Her contributions are primarily through research publications and academic positions.

• Autonomous Robotics
• Computational Intelligence
• Human-machine Interaction
• +3 more

Dr. Wai-keung Fung is a Senior Lecturer in Electronics, Robotics & Control Engineering at Cardiff Metropolitan University's Cardiff School of Technologies. He holds a PhD in Mechanical and Automation Engineering from the Chinese University of Hong Kong (2001) and has held academic roles at the University of Manitoba (Canada) and Robert Gordon University (UK). He is Programme Director for the BEng/MEng in Electronics and Computer Systems Engineering and co-leads the EUREKA Robotics Centre. He is a Fellow of the Higher Education Academy (FHEA), IEEE Senior Member, and IET member. His research focuses on Autonomous Robotics , Computational Intelligence , and Human-machine Interaction , with recent work spanning gender bias in speech processing, underwater communication systems, and medical diagnostics via EEG analysis. His interdisciplinary contributions bridge robotics, machine learning, and engineering applications. Awards: Fellow of the Higher Education Academy (FHEA) since 2015 IEEE Senior Member since 2009 IET Member since 2017 Labs & Affiliations: EUREKA Robotics Centre (Cardiff School of Technologies) His research has been published in IEEE conferences and journals, addressing challenges in robotics, medical AI, and pipeline monitoring. He continues to advance applied technologies with industry and academic collaborations.

Berç RustemView profile

Professor

• Operations Research
• Optimization Algorithms
• Robust Optimization
• +7 more

Professor Berç Rustem is a distinguished academic in the Department of Computing at Imperial College London. He holds the position of Professor of Computational Methods in Operations Research and leads research groups including the Computational Optimisation Group (COG), Quantitative Analysis & Decision Science (QUADS), and Analysis, Engineering, Simulation & Optimization of Performance (AESOP). His research focuses on optimality, sensitivity, robustness, and the development of algorithms for optimization under uncertainty, with applications in engineering, economics, finance, and defense. His expertise spans linear/nonlinear/integer programming, game theory, stochastic systems, and risk management. He has edited journals like Computational Management Science and Optimization Methods & Software , and served as President of the Society for Computational Economics (2001-2003). His work emphasizes robust optimization techniques, portfolio strategies, and decision-making frameworks in uncertain environments. Professor Rustem has collaborated extensively with colleagues and advised numerous research students, contributing to advancements in global optimization, bilevel programming, and computational economics. His recent papers address topics like robust portfolio optimization, correlated equilibria, and algorithmic solutions for complex systems.

• Digital Twins
• AI in Construction
• Robotic Automation
• +2 more

Dr. Yiping Meng is a Lecturer in Construction Management at Teesside University's School of Computing, Engineering and Digital Technologies. She holds a PhD in Multi-objective Optimisation from the University of Sheffield and has postdoctoral research experience at Loughborough University and University of Cambridge. Her research integrates digital twins, AI, and robotic automation for sustainable construction. Key areas include dynamic digital twin systems for building performance tracking, multi-criteria decision support for automation construction, and computer-aided design of complex architectural geometries. She currently leads research on RECONSTRUCT: A Territorial Construction System for Circular Low-Carbon Environments. Publications demonstrate cross-disciplinary approaches combining computational optimization, material science, and building information modeling. Recent work emphasizes machine learning applications in energy management and robotic fabrication. Dr. Meng collaborates with national and international partners on circular economy frameworks and net-zero construction initiatives. She teaches digital technologies in construction and mentors students in sustainable design principles.

Elham HosseinzadehView profile

Lecturer

• Energy Storage
• Thermal Management
• Electrified Transport Systems
• +3 more

Elham Hosseinzadeh is a Lecturer in Energy Storage and Conversion at the University of York, affiliated with the Department of Electronic Engineering in the School of Physics, Engineering and Technology. Her research focuses on energy storage systems (batteries and fuel cells), thermal management, and electrified transport. She holds a Ph.D. from the Technical University of Denmark (2013) in mechanical engineering, specializing in PEM fuel cell modeling. Prior roles include Research Fellow at WMG, University of Warwick, and Lead Engineer at Dyson, where she addressed real-world battery manufacturing challenges. Her expertise spans fuel cell system optimization (e.g., for forklift trucks), battery thermal management for electric vehicles, and computational modeling of energy systems. She teaches courses like Renewable Power Generation and Fuel Cell and Battery Technologies. Research grants include EPSRC and HVM Catapult-JLR projects. Her work emphasizes interdisciplinary approaches, combining experimental analysis, numerical simulations, and multi-domain modeling to enhance energy storage efficiency and safety. She leads research on battery lifecycle management, novel cooling materials, and multi-objective optimization in automotive applications.

Ibuki KusanoView profile

Associate Professor

• Probabilistic Optimisation of Structures
• Aerodynamics of Suspension Bridges
• Optimisation Based on Surrogate Models
• +7 more

Ibuki Kusano is an Associate Professor in the Department of Industrial Engineering at IQS School of Engineering, Universitat Ramon Llull. His research is centered on structural and aerodynamic optimization of civil infrastructure, particularly long-span bridges, with a strong emphasis on probabilistic and reliability-based design methodologies. His research interests include: Probabilistic Optimisation of Structures Aerodynamics of Suspension Bridges Optimisation Based on Surrogate Models Co-Kriging Computational Fluid Dynamics (CFD) Reliability-Based Design Optimization His recent publications demonstrate a consistent focus on integrating advanced computational techniques—such as machine learning, surrogate modeling, and CFD—with structural engineering to improve the safety, efficiency, and performance of bridge systems. The research trends highlight a shift toward data-driven and probabilistic frameworks for predicting wind-induced responses, flutter stability, and energy generation in offshore wind farms. His scientific contributions have been supported by research grants from AGAUR (Agència de Gestió d'Ajuts Universitaris i de Recerca) through the GEPI research group. He is actively involved in interdisciplinary projects such as offshore wind farm data analysis using machine learning for energy prediction. While no formal awards are listed, his h-index of 7 and 325 citations reflect a solid research impact. Kusano contributes to academic training through the Master’s and Bachelor’s programs in Industrial Engineering at IQS, and his work is conducted within the GEPI – Industrial Products Engineering Group, which focuses on additive manufacturing, reverse engineering, and material characterization.

• Acoustics
• Active noise and vibration control
• Architectural acoustics
• +6 more

Winthrop Professor Jie Pan is affiliated with the School of Engineering and the Department of Mechanical Engineering at The University of Western Australia, and is a member of the UWA Defence and Security Institute. His research focuses on acoustics, active noise and vibration control, architectural acoustics, control engineering, industrial noise reduction, and structural dynamics. His work contributes to UN Sustainable Development Goals related to sustainable cities and communities, and responsible consumption and production. Research Interests: Acoustics and vibration control in mechanical systems Active and passive noise mitigation strategies Structural dynamics and finite element analysis Applications in industrial engineering and transformer systems Remote sensing for environmental monitoring Recent Articles Trends: Prof. Pan's recent publications emphasize advanced analytical techniques, experimental validation, and numerical modeling in vibration and acoustics. Key themes include the effects of hydrostatic loading on clamped plates, piezoelectric actuator performance, and the use of UAV-based hyperspectral imaging for disease detection. His work bridges mechanical engineering with environmental and biomedical applications. Grants and Supervision: He has led 30 research projects, including major grants from ARC Australian Research Council and Woodside R2D3. Examples include the Integrated Passive and Active Control of Humming Noise from Haul Trucks and Smart Acoustical Surfaces collaborations. He has supervised 9 doctoral/master's students, though specific advisee names are not listed here.

Michal WeiszerView profile

Lecturer

• Optimisation
• Metaheuristics
• Operational Research
• +5 more

Dr. Michal Weiszer is a Teaching Fellow at the School of Engineering and Materials Science, Queen Mary University of London, specializing in optimization, metaheuristics, and operational research with applications in airport operations. His research has significantly contributed to the development of the Active Routing concept for airport ground movement, integrating aircraft engine performance and airframe dynamics with routing and scheduling to achieve greener operations. Dr. Weiszer's research interests focus on routing and scheduling, multi-objective optimisation, simulation, and intelligent transportation systems . His work bridges theoretical optimization techniques with practical aviation applications, particularly in airport ground movement. He has pioneered approaches that integrate aircraft performance models with routing algorithms to reduce emissions and improve efficiency in airport operations. His research spans both algorithmic development and practical implementation, with strong industry connections. Analysis of Dr. Weiszer's publication record shows a consistent focus on airport ground movement optimization using evolutionary algorithms and multi-objective approaches. His research has evolved from basic routing algorithms to more sophisticated integrated systems incorporating aircraft dynamics, emissions modeling, and uncertainty handling. Recent work has expanded into multimodal transportation and open-source simulation platforms, demonstrating the broadening impact of his research beyond traditional airport operations. Dr. Weiszer has received several notable awards and funding: QMUL Flexible Innovation Fund as Principal Investigator EPSRC sponsored TRANSIT project (EP/N029496/1) as Research Co-Investigator Impact Acceleration projects with Avisu as Co-Investigator Impact Acceleration projects with NATS (UK air traffic control) as Co-Investigator His grant portfolio demonstrates strong industry-academia collaboration, with projects translating theoretical research into practical applications. The funding from Royal Society, EPSRC, and industry partners highlights the recognition of his work's potential impact on sustainable aviation. Dr. Weiszer has successfully secured both early-stage innovation funding and larger collaborative projects, showing progression in his research career.

• Mechanism analysis and damage modelling for composites
• Additive manufacturing/3D printing of continuous fibre reinforced composites
• Topology optimisation and structural design of composites
• +3 more

Dr. Yuan Chen serves as an Assistant Professor at Southern University of Science and Technology in the School of System Design and Intelligent Manufacturing. He obtained his PhD in Aerospace Engineering from the University of Sydney in 2019 and completed postdoctoral research there before joining SUSTech in 2022. Education: PhD in Aerospace Engineering, University of Sydney (2015-2019) ME in Mechanical Engineering, Hunan University (2012-2015) Dr. Chen's research focuses on composite materials and advanced manufacturing. His work spans multiple interconnected areas including: Mechanism analysis and damage modeling for composites Additive manufacturing of continuous fiber reinforced composites Topology optimization and structural design of composites Multiscale modeling and experimental techniques Design and intelligent manufacturing of innovative metacomposites Non-destructive testing methods for composite structures His recent publications demonstrate a strong focus on 3D printing of carbon fiber composites, mechanical metamaterials, and structural optimization. The research shows progression from fundamental mechanical analysis of composite structures toward advanced manufacturing techniques and innovative material designs with specialized properties like negative Poisson's ratios and thermal-dimensional stability. Scientific Awards: Best Oral Presentation, 6th International Conference on Material Strength and Applied Mechanics (2023) Pengcheng Peacock Plan, Shenzhen Government (2022) Travel Award, Multidisciplinary Digital Publishing Institute (2022) Best Oral Presentation, 4th International Conference on Material Strength and Applied Mechanics (2021) Young Scientist Medal, International Association of Advanced Materials (2021) World's Top 2% Scientists (2024) Dr. Chen serves as Editor-in-Chief for Advanced Manufacturing: Polymer & Composites Science and is on the editorial boards of several other journals. He has been supported by multiple prestigious grants including the National Natural Science Foundation of China, National Key Research & Development Program of China, and Guangdong University Key-Area Special Program. He is actively involved in mentoring students and has established the Chen Garden research group focusing on advanced composite materials. Dr. Chen maintains strong international collaborations with researchers in Australia, the UK, Germany, and other countries, and is a member of several professional societies including the Royal Aeronautical Society and the European Materials Research Society.

• Software Engineering
• Artificial Intelligence
• Genetic Programming
• +4 more

Dr. Anthony Ventresque is a Visiting Associate Professor at the University College Dublin, School of Computer Science , with a PhD in Computer Science from the University of Nantes & INRIA France (2008). He is also the Director of the TCD Complex Software Lab and a Senior Investigator with Lero, the SFI Irish Software Research Centre. MSc in Philosophy and Logic from the University of Nantes PhD in Computer Science from the University of Nantes & INRIA France His research focuses on Software Engineering , Genetic Programming , and Multi-objective Optimization , with applications to Autonomous Systems , Cloud Computing , and Sports Analytics . Recent publications highlight his work on grammar-obeying program synthesis using large language models, mutation testing for software quality, and domain adaptation for object detection in rugby data. His scientific awards include a Teaching Award from the UCD School of Computer Science in 2020. He has contributed to grants like Mutation Testing at Scale and Advancing Computational Archaeology , and his teaching activities encompass modules such as Big Data Programming and Operating Systems over multiple years. He leads the TCD Complex Software Lab , fostering interdisciplinary research and innovation.

Gokhan SerhatView profile

Assistant Professor

• Computational Mechanics
• Numerical Methods
• Design Optimization
• +7 more

Gokhan Serhat is a tenure-track Assistant Professor at the Department of Mechanical Engineering , KU Leuven, stationed at the Bruges Campus. He conducts research within the Mecha(tro)nic Systems Dynamics Group and the M-Group and maintains a guest-scientist affiliation with the Max Planck Institute for Intelligent Systems. Education: Ph.D. in Mechanical Engineering, Koç University, 2018 (Marie Curie Fellow) M.Sc. in Computational Mechanics, Technical University of Munich, 2013 B.Sc. in Mechanical Engineering, Middle East Technical University, 2011 Research interests span computational mechanics, numerical methods, design & topology optimization, structural dynamics, composite materials, fiber-path optimisation, functionally graded structures, and bio-mechanical/haptic modelling. His work integrates high-fidelity simulation, laminate-parameter techniques, and additive-manufacturing constraints to create lightweight, variable-stiffness composite structures and tactile/biomechanical devices. Recent articles (2022-2025) reveal a strong trajectory in composite optimisation (anisotropic topology, lamination parameters, manufacturability) alongside interdisciplinary forays into biomechanics & haptics (fingertip dynamics, tactile displays, skin simulation). The portfolio is evenly split between computational-method development and application-oriented studies in aerospace, automotive, and human-interaction domains. Scientific recognition: Marie Curie Early-Stage Research Fellow (doctoral training grant) Research funding & leadership: Promoter, Flemish project “Fiber path and topology optimization of 3D printed composites” (2023-2027) Promoter, FWO/Flemish project “Concurrent fiber path and topology optimization of 3D printed composites” (2022-2024) He teaches three courses at KU Leuven Bruges: Structural Dynamics , Aerospace Structures & Lightweight Design and Mechatronic Design , and is an active member of the Faculty Council and the Department Council.

Hao ChengView profile

Assistant Professor

• Artificial Intelligence for Geo-Science
• Computer Vision
• Autonomous Driving
• +4 more

Dr Hao Cheng is an Assistant Professor (from 1 Oct 2024) in the Department of Earth Observation Science, ITC Faculty, University of Twente, the Netherlands. He currently holds a Marie Skłodowska-Curie European Postdoctoral Fellowship focused on vehicle-vulnerable road user interactions for safer intelligent transportation and autonomous driving systems. Education: Ph.D. (with distinction) in Civil Engineering & Geodetic Science, Leibniz Universität Hannover, Germany, 2021 M.Sc. (with distinction) in Internet Technologies & Information Systems, joint programme of TU Braunschweig, Leibniz Universität Hannover, TU Clausthal & University of Göttingen, Germany, 2017 Research interests lie at the intersection of Artificial Intelligence and Geo-Information Science , with principal themes: Deep learning & computer vision for road-user behaviour modelling Trajectory prediction and motion forecasting for autonomous driving Interaction & safety analysis between vehicles and vulnerable road users (pedestrians, cyclists) Ethical, explainable and accessible AI for geospatial applications Graph neural networks, diffusion models and transformer architectures applied to dynamic scene understanding His recent publication portfolio (2018-2025) demonstrates a strong methodological core in deep learning and computer vision deployed across transportation safety , 3D mapping , remote sensing and human-machine interaction . A notable trend is the migration from early LSTM-based traffic modelling toward contemporary transformer, graph and diffusion frameworks that deliver diverse, controllable and interpretable predictions for real-world autonomous-driving scenes. Scientific recognition: Marie Skłodowska-Curie Actions European Postdoctoral Fellowship (MSCA) – VeVuSafety project Grants & projects: Cheng is principal investigator of the MSCA-funded VeVuSafety project (Grant 101062870) which develops learning-based models of vehicle-VRU interactions to enable safer intelligent transport systems. Labs & teams: From October 2024 he will lead research activities within the Department of Earth Observation Science at ITC, University of Twente, collaborating with the broader ITC AI-for-Geo groups and transportation-safety institutes across Europe.

Pedram AsefView profile

Lecturer

• Electrical Machines
• Electric Propulsion Systems
• Electric Vehicles
• +8 more

Dr. Pedram Asef is a Lecturer (Assistant Professor) of Advanced Electrical Machines at the Department of Mechanical Engineering, Faculty of Engineering Sciences, University College London. He serves as the Director of the UCL e-Motion Laboratory and is a member of the Advanced Propulsion Laboratory at UCL. Additionally, he participates in the Computing Committee within the Mechanical Engineering Department. His professional activities span academia, industry, and research funding bodies, where he serves as a Panel Member for the Royal Society, UK Research and Innovation, and the British Council for Grant Application Assessment. Dr. Asef earned his PhD in Electrical Engineering from the Polytechnic University of Catalonia (UPC) with Cum Laude distinction in 2019, where his thesis was nominated for the Best Thesis Award. His academic journey includes previous positions as a Lecturer in Electric Propulsion Systems at the University of Bath (2022-2023), Senior Lecturer in Automotive Engineering at the University of Hertfordshire (2020-2022), and Post Doctoral Research Fellow at the University of Surrey (2019-2020). Dr. Asef's research focuses on the design, optimization, and control of advanced electrical machines, electric propulsion systems, and electric drives for next-generation electric vehicles across ground, maritime, and aerospace applications. His interdisciplinary approach integrates applied mathematics, particularly optimization and machine learning methods, to enhance the performance, efficiency, and sustainability of electric drives and energy systems. His work addresses critical challenges in electrified transport innovation, with a strong emphasis on practical implementation and commercialization. His research portfolio includes leading and contributing to high-impact, multi-institutional projects funded by prestigious bodies including the EPSRC, ESA, European Commission, Innovate UK, and the Great Britain Sasakawa Foundation. Notable projects include FEMMHUB (exploring novel manufacturing techniques for electrical machines), AutoTrust (focusing on autonomous system reliability), EM-TECH (developing innovative e-motor technologies), OBELICS, AutoPower, and the UK-Japan-xEV collaboration. Dr. Asef has received several prestigious recognitions including: Fellow of the Higher Education Academy (FHEA) Chartered Engineer (CEng) registered by the Engineering Council Endorsed Researcher by the Royal Academy of Engineering IEEE Senior Member Star Reviewer of IEEE Power and Energy Society Shanghai Jiao Tong University Fellowship As an academic leader, Dr. Asef serves as an Associate Editor for IET The Journal of Engineering and has held various editorial roles for other journals. He actively participates in international conferences as a Technical Track Chair, Steering Committee member, and Technical Committee member. He has led research and industrial projects worth over £6 million in recent years, with funding from diverse sources including EPSRC, ESA, European Commission, and Innovate UK. Dr. Asef directs the UCL e-Motion Laboratory, which focuses on advanced electrical machines and propulsion systems research. He is also a member of the Advanced Propulsion Laboratory at UCL, where interdisciplinary teams work on sustainable mobility solutions. His laboratory environment fosters innovation in electric vehicle technologies, collaborating with industry partners and international research institutions to translate theoretical advances into practical applications.