Find Academic Supervisors

• Reliability Engineering
• Maintenance Optimisation
• Predictive Control
• +8 more

Michael E. Cholette is an Associate Professor in the School of Mechanical, Medical & Process Engineering at Queensland University of Technology's Faculty of Engineering. With expertise spanning multiple engineering disciplines related to dynamic systems, reliability, and applied optimization, his work focuses on practical applications across various industries and infrastructure systems. Dr. Cholette earned his B.S. from the University of Michigan in 2007 and completed his Ph.D. at the University of Texas at Austin in 2012, where his research centered on fault detection and diagnosis for complex systems with applications in automotive systems and semiconductor manufacturing. Following his doctoral studies, he worked as a postdoctoral research fellow with the CRC for Infrastructure and Engineering Asset Management in Brisbane, Australia, focusing on reliability modeling and asset management before joining QUT as a Lecturer in 2013. He was promoted to Associate Professor in 2021. His primary research interests include asset management, reliability modeling, Condition-Based Maintenance (CBM), and maintenance optimization. Additional research areas encompass condition monitoring, control systems, autonomous vehicles, and building optimization. Dr. Cholette has successfully secured research funding from various industrial and government bodies including Queensland Rail, Wilmar Sugar, the Australian Research Council, the Australian Renewable Energy Agency, and the US Department of Energy. His recent publications reveal a strong focus on renewable energy systems, particularly concentrated solar power plants, with significant contributions to solar field design, heliostat soiling management, and thermal storage optimization. His transportation-related research shows expertise in railway infrastructure maintenance, track geometry monitoring, and predictive maintenance approaches. The interdisciplinary nature of his work bridges mechanical engineering, control theory, and operations research to solve practical engineering challenges. Fellow of the International Society of Engineering Asset Management Co-chair of the Scientific Committee for the 2017 World Congress on Engineering Asset Management Member of Engineers Australia Dr. Cholette has supervised numerous doctoral students whose research spans solar energy systems, autonomous vehicle control, building energy optimization, and maintenance planning. His teaching includes courses in Engineering Asset Management and Maintenance, Vibration & Control, and Advanced Dynamics. He actively participates in multiple academic and professional societies and maintains strong industry connections that inform both his research and teaching practices.

Davide BarilariView profile

Professor

• Sub-Riemannian Geometry
• Curvature
• Geometric Control Theory
• +4 more

Davide Barilari is a Full Professor at the Department of Mathematics "Tullio Levi-Civita" of the University of Padua. His research focuses on Sub-Riemannian Geometry, Curvature, Geometric Control Theory, Hypoelliptic PDEs, and Optimal Transport. He has contributed to curvature analysis, geometric measure theory, and spectral theory in non-Euclidean settings. Research Highlights: Unified synthetic curvature bounds for Riemannian/sub-Riemannian structures, Steiner formulae in 3D contact manifolds, stochastic processes on sub-Riemannian surfaces He serves as Associate Editor for ESAIM: Control, Optimisation and Calculus of Variations and Journal of Dynamical and Control Systems . Recent grants include STARS@UNIPD (2021) and PRIN 2022 as project coordinator. Organized Conferences: Dispersion and Geometry in Padova (2024), PaPa sub-Riemannian seminars, Hypoelliptic Operators in Geometry (2023), Final Conference of ANR Project SRGI (2020)

Seyedali MirjaliliView profile

Professor

• Optimization
• Swarm Intelligence
• Evolutionary Algorithms
• +6 more

Seyedali Mirjalili is a Professor of Artificial Intelligence and Director of the Centre for Artificial Intelligence Research and Optimization (AIRO) at Torrens University Australia. He holds distinguished professorships at VSB Technical University of Ostrava, Óbuda University, and De La Salle University, and is an adjunct researcher at Griffith University and Yonsei University. His research focuses on optimization algorithms, swarm intelligence, evolutionary computation, and machine learning. Education: PhD in Computer Science (Griffith University, 2016). Research interests include optimization techniques, swarm intelligence algorithms (e.g., Grey Wolf Optimizer, Whale Optimization Algorithm), machine learning applications, and robust optimization frameworks. He has published over 600 papers with an H-index of 110 and is among the most cited researchers in optimization fields globally. Awards include the Pro-Vice Chancellor Research Special Award (2019) and recognition as a top 1% highly cited researcher (since 2019). He serves as an associate editor for journals like Neurocomputing and Applied Soft Computing. Labs/Teams: Leads the AIRO Centre at Torrens University, focusing on AI-driven solutions for complex optimization problems.

David Truong TonView profile

Lecturer

• Logistics and Supply Chain Management
• Analytical and Optimisation
• Supply Chain Contract
• +4 more

Dr. David Truong-Ton is a Lecturer in Logistics and Supply Chain Management at RMIT University's School of Accounting, Information Systems and Supply Chain. With over 20 years of experience, he specializes in teaching, research, and consulting in logistics, supply chain optimization, and analytical methodologies. His industry projects include the Australia-Vietnam Policy Institute Agri-business Trade Pilot (funded by DFAT, 2021-2023) and grants such as the POST-COVID-19 Vietnam-Australia Supply Chain Collaboration Platform (Australia-ASEAN Council, 2021-2022). He is actively involved in supervising Masters and PhD research in supply chain resilience and competitive advantage. Research Focus: Supply Chain Contracts, Disruption Management, E-Market Adoption Industry Collaboration: Projects in Vietnam, Australia-Korea supply chain resilience, and disaster relief coordination platforms Dr. Truong-Ton has published peer-reviewed work in logistics and new product design, emphasizing practical applications in global supply networks.

• Aerospace Design and Optimisation
• Aerodynamics
• Dynamics and Control
• +5 more

Professor Cees Bil is a Professor in the School of Engineering at RMIT University, specializing in Aerospace Engineering. His academic career includes roles as Associate Professor (1998–present) and Senior Lecturer (1995–1998) at RMIT, and prior positions at Delft University of Technology in the Netherlands. He leads research in Aerospace Design and Optimization , Aerodynamics , Computer-Aided Engineering , and Simulation and Modelling . His research spans unmanned systems , hybrid-electric propulsion , digital twin technology , and sustainable aerospace systems . Recent projects include AI-driven drone simulations, air traffic optimization, and bi-modal unmanned systems. Over 400+ publications demonstrate expertise in aerospace innovation, robotics, and aviation safety. Professor Bil’s work integrates transdisciplinary approaches, addressing challenges in Industry 4.0 , healthcare logistics (e.g., air mobile stroke units), and environmental sustainability via life cycle assessments. He supervises PhD/Master’s research in advanced propulsion, autonomous systems, and aviation safety. Key contributions include the Air Mobile Stroke Unit concept, bi-modal UAV systems , and expert systems for aviation incident analysis . His research bridges academia and industry, fostering solutions for aerospace, robotics, and smart transportation.

K.P. SandeepView profile

Professor

• Food-process engineering
• Thermal and aseptic processing
• Microwave sterilisation of particulate foods
• +5 more

K.P. Sandeep is Professor and Department Head in the Department of Food, Bioprocessing & Nutrition Sciences at North Carolina State University’s College of Agriculture and Life Sciences. He leads a multidisciplinary programme that integrates food engineering, advanced thermal processing, sensor technology and sustainable packaging to assure microbiologically safe, high-quality food products. Education: Ph.D. Agricultural & Biological Engineering, Pennsylvania State University, 1996 M.S. Agricultural & Biological Engineering, Pennsylvania State University, 1993 B.S. Agricultural Engineering, Indian Institute of Technology, 1991 Research focus: Sandeep’s group mathematically models velocity and temperature fields during conventional and microwave thermal processing of particulate foods, develops novel in-line sensors for real-time process monitoring, and creates biodegradable packaging materials via extrusion and nanotechnology. A central aim is microbiological validation that guarantees commercial sterility while optimising product quality. Teaching & outreach: He teaches undergraduate and graduate courses (Principles of Food and Bioprocess Engineering, Thermal Processing, Food Packaging) and regularly delivers industry workshops on HTST dairy systems, heat-exchanger design, and continuous-flow microwave processing. As site director for NSF’s Center for Advanced Processing and Packaging Studies (CAPPS), he fosters university-industry collaboration and runs a Thermal Analysis Service Center that measures thermo-physical and dielectric properties for food companies. Honours: His microwave-processing team has been recognised with the IFT Industrial Achievement Award, USDA Technology Transfer Award, and inclusion in NSF’s technology-breakthrough compendium; commercialisation efforts have created roughly 230 jobs via Yamco LLC and Wright Foods.

Hongjie MaView profile

Academic

• Artificial Intelligence
• Embedded Systems
• Operational Research
• +7 more

Dr. Hongjie Ma is a Senior Research Fellow at the University of Portsmouth , affiliated with the School of Electrical and Mechanical Engineering and the Centre for Operational Research and Logistics . With over a decade of experience, his work bridges Artificial Intelligence and Embedded Systems , focusing on smart industrial applications and energy optimization. His research interests include: AI-based abnormal detection AI-based decision optimisation Embedded systems for machine learning Smart industrial sensors Operational Research Logistics Recent publications span combustion engineering , fuel cell technology , and autonomous driving frameworks . His work has garnered over 500 citations and includes contributions to REF 2021 impact case studies. Key scientific awards include the IEEE Leadership Award . He supervises PhD students and has secured grants from Innovate UK , EPSRC , and Horizon Europe . He chairs the IEEE Smart World Congress and serves as guest editor for journals like the Journal of Marine Science and Engineering .

Spyridon PougkakiotisView profile

Lecturer

• Continuous Optimization
• Stochastic Optimization
• Risk-Aware Decision-Making
• +3 more

Spyridon Pougkakiotis is a Lecturer in Optimization at King’s College London’s Department of Mathematics, part of the Faculty of Natural, Mathematical & Engineering Sciences. He previously held positions as Lecturer in Mathematics at the University of Dundee (2023–2024) and as a postdoctoral research associate at Yale University (2022–2023). His research focuses on continuous optimization, stochastic optimization, and risk-aware decision-making, with applications in operational research, engineering, and data science. He has developed efficient algorithms for large-scale optimization problems and contributed to preconditioning techniques in interior point methods. Education: BSc in Informatics and Telecommunications, National and Kapodistrian University of Athens (2012–2016) MSc in Operational Research with Computational Optimisation, University of Edinburgh (2016–2017) PhD in Optimization, University of Edinburgh (2017–2022) His research interests emphasize nonlinear optimization (including non-smooth, stochastic, and black-box problems) and algorithm development. He has been recognized with the 2022 OR Society Doctoral Award and was a finalist for the 2024 Euro Doctoral Dissertation Award. Teaching includes undergraduate courses on numerical methods with Python and an MSc module on machine learning. He is involved in King’s Financial Mathematics group and organized events like the “Afternoon of Stochastic Optimisation” workshop in 2025. Awards: 2022 OR Society Doctoral Award (Most Distinguished Doctoral Research in Operational Research) 2024 Euro Doctoral Dissertation Award Finalist Current research projects include a 50/50 Haleon Industry Studentship (2025–2028), focusing on optimization applications in industry.

Yang XiaotangView profile

Assistant Professor

• Data Science & Analytics
• Operations Management
• Optimisation & Decision Science
• +7 more

Yang Xiaotang is an Assistant Professor in the Engineering Systems and Design (ESD) pillar at Singapore University of Technology and Design (SUTD). Previously, she was a Postdoctoral Fellow at the Rotman School of Management, University of Toronto, and a Visiting Scholar at the University of Michigan's Department of Industrial and Operations Engineering. She holds a PhD in Industrial and Systems Engineering from the University of Minnesota Twin Cities and a Bachelor of Engineering in Industrial Engineering from Chongqing University. Her research focuses on innovative technologies and business models within on-demand service platforms, smart mobility, digital economy, and healthcare systems. Key interests include automation's impact on labor, ride-hailing systems, and strategic vendor competition in on-demand markets. Selected publications include work on tele-driver integration in ride-hailing (Management Science, 2024) and automation's labor dynamics (under review in Manufacturing & Service Operations Management). Awards include Second Place in the Initiative on the Sharing Economy Student Competition (2023). She has presented at conferences such as INFORMS, MSOM, and POMS, and delivered seminars at institutions like Penn State University, University of Science and Technology of China, and the Hong Kong University of Science and Technology. Her work bridges operations research, transportation economics, and technological innovation.

• Operational Research
• Combinatorial Optimisation
• Mathematical Programming
• +7 more

Greet Vanden Berghe is a full professor at the Faculty of Engineering Technology of KU Leuven. She leads the Subdivision Combinatorial Optimisation and Decision Support at Ghent and Aalst Campuses, and contributes to research networks like Leuven.AI and LIM. Her work focuses on industrial combinatorial optimization problems through mathematical programming, heuristics, and decomposition approaches. Affiliations: Numerical Analysis and Applied Mathematics (NUMA), Leuven.AI, LIM Institute Research: Logistics optimization, personnel scheduling, vehicle routing, and algorithm development for industrial decision support Projects: MoVeRS (Modular Vehicle Routing Solver), Trustworthy Algorithms for Industrial Decisions, Fairness in Allocation Problems, and Electric Vehicle Charging Station Optimization Her research emphasizes bridging theoretical advancements with real-world industrial challenges, particularly in maritime logistics, healthcare scheduling, and production planning. She has developed scalable solvers and integrated legal constraints into routing algorithms.

Lukas SchirrenView profile

Research Fellow

• Open-source energy system modelling
• Deep decarbonisation
• Energy resilience
• +9 more

Lukas Schirren is a Research Fellow at the Department of Chemical Engineering, Imperial College London, affiliated with the Faculty of Engineering. He collaborates with the University of Oxford, UCL, and TUM on energy systems research. Supervised by Professor Adam Hawkes, his work focuses on open-source energy system modeling, deep decarbonisation, and energy resilience. BSc in Industrial Engineering, Technical University of Berlin (2018–2022) Exchange Semester, INSA Lyon (2021) MSc in Sustainable Energy Futures, Imperial College London (2023–2024, with distinction) His research leverages uncertainty quantification, geospatial analysis, and machine learning to address energy challenges. Key projects include: Industrial Decarbonisation in Ukraine: Modeling green hydrogen integration for ammonia/steel production using PyPSA-Eur (SHIELD project) Machine Learning for Energy Systems: Predictive models for solar PV generation losses Geospatial Analysis of Commodity Production Costs: Assessing hydrogen potential in Laos and Nepal (CCG project) He develops open-source tools like GeoH2-Laos and Slope-Exclusion, with technical expertise in Python, Jupyter Notebook, and GoLang databases. Distinction: Completed MSc with distinction (2024)

Marjia HaqueView profile

Researcher

• Transportation
• Logistics
• Supply Chains
• +3 more

Dr Marjia Haque is a researcher affiliated with the School of Engineering and IT at the University of New South Wales (UNSW) in Canberra. Her research focuses on critical areas including transportation, logistics, supply chain management, optimisation techniques, and systems engineering. Her academic credentials include a PhD in Computer Science from UNSW, an M.Sc. in Industrial & Production Engineering from Bangladesh University of Engineering and Technology (BUET), and a B.Sc. in the same field from BUET. She has contributed to the academic community through publications in book chapters, journal articles, and conference papers, though specific titles are not detailed in the provided data. Dr Haque teaches advanced courses such as Option Analysis (ZEIT8403) and Evidence-Based Decision Making (ZEIT8402) . Her work bridges theoretical research with practical applications, particularly in managing decentralised supply chain systems and reducing bullwhip effects through fuzzy genetic algorithms.

• Civil Engineering
• Optimisation
• Applied Mathematics
• +3 more

Aly-Joy Ulusoy is an Imperial College Research Fellow in the Department of Civil and Environmental Engineering at Imperial College London, affiliated with the Faculty of Engineering and the Grantham Institute. Her research focuses on optimisation methods for the design and control of water distribution networks, integrating adaptive systems, hydraulic modeling, and resilience analysis. She holds a Ph.D. (2021) and M.Sc. (2016) from Imperial College London, and an M.Sc. from École Supérieure d’Électricité, France (2016). Previously, she worked as a postdoctoral researcher in Dr. Ivan Stoianov's InfraSense Labs. Education: Ph.D. in Civil and Environmental Engineering, Imperial College London (2021) M.Sc. in Civil and Environmental Engineering, Imperial College London (2016) M.Sc., École Supérieure d’Électricité, France (2016) Her research interests span optimisation algorithms for water network control, adaptive hydraulic systems, data-driven hydraulic modeling, and resilient infrastructure design. Recent work emphasizes dynamically adaptive networks for pressure management, fault localization, and integration of AI for demand forecasting. She explores multi-objective optimization techniques to balance operational efficiency and resilience in water distribution systems. Key research trends include: (1) distributed optimization for real-time control under time-coupling constraints, (2) interpretable AI for water demand prediction, and (3) principled approaches for model maintenance using principal component analysis. Her work bridges theoretical optimisation with practical water infrastructure challenges. Advising and grants: No specific advisees or grants listed. Affiliated with InfraSense Labs, focusing on smart infrastructure and sensor networks. Active in developing methodologies for network resilience under uncertainty. Ongoing projects include adaptive MPC strategies for burst incident management and design-for-control frameworks for dynamically adaptive systems.

Nuno BimboView profile

Associate Professor

• Adsorption and porous materials
• Gas Storage and Separations
• Hydrogen technologies
• +3 more

Nuno Bimbo is an Associate Professor in Chemical Engineering at the University of Southampton, serving as the undergraduate Admissions Tutor for Chemical Engineering programs and a member of the FIMS research group. He holds a Master's from the University of Coimbra (2009) and a PhD from the University of Bath (2013). His research focuses on porous materials for energy storage, gas separations, and plasma gasification, particularly MXenes and their applications in batteries, fuel cells, and air purification. He has led projects funded by EPSRC and industry partners like NanoSUN and Smart Separations Ltd. Nuno is a Chartered Chemical Engineer (IChemE), a Fellow of the Higher Education Academy, and recipient of the 2018 Dean’s Award for Early Career Teaching Excellence. Teaching responsibilities include module coordination for Unit Operations, Reaction Engineering, and Process Optimisation. He has supervised numerous postgraduate and undergraduate research projects across Chemical Engineering, Chemistry, and Space Systems Engineering. His research group actively explores MXene synthesis, hydrogen storage in porous materials, and microwave-induced plasma processes for waste-to-energy conversion. Awards include the Dean’s Early Career Teaching Award (2018) and recognition for excellence in engineering accreditation (Ordem dos Engenheiros, 2014). Current projects involve KTP collaborations for hydrogen purification and Innovate UK-funded plasma gasification optimization.

Johan WesselooView profile

Professor

• Mining geotechnical engineering
• Mining induced seismicity
• Rock Mechanics
• +6 more

Johan Wesseloo is a Professor at The University of Western Australia, affiliated with the School of Engineering and the Australian Centre for Geomechanics. His academic credentials include a BE, ME, and PhD from the University of Pretoria. His research focuses on critical aspects of mining geomechanics with emphasis on safety and optimization in mining operations. Professor Wesseloo's research interests span mining geotechnical engineering, mining-induced seismicity, rock mechanics, rock engineering, and ground support systems. His work particularly addresses mine-induced seismicity and rockburst behaviour, risk-based geotechnical design, and both open pit and underground geomechanics. His research integrates theoretical modeling with practical applications to solve complex mining challenges. His publication portfolio demonstrates a strong focus on seismic risk assessment, rock failure mechanisms, and optimization of mining operations. Recent work shows increasing attention to probabilistic approaches in geomechanical design and the integration of numerical modeling with field observations to improve mining safety and efficiency. SAIMM Gold Medal (2020) SAIMM Gold Medal (2017) SAIMM Silver Medal (2015) SAIMM Gold Medal (2006) Professor Wesseloo leads an extensive research program with significant industry funding, currently managing multiple active projects through 2028 with major mining companies including Gold Fields, OZ Minerals, Newmont, Agnico Eagle Mines, and Alamos Gold Inc. His research group focuses on mining-induced seismicity and rockburst risk management in hard rock mines. He has also contributed substantially to academic discourse through editorial roles for major conferences including Ground Support 2023, the Second International Conference on Underground Mining Technology, the 1st International Conference on Mining Geomechanical Risk, and the 8th International Conference on Deep and High Stress Mining. The Australian Centre for Geomechanics serves as the primary research hub for Professor Wesseloo's work, where he leads the mXrap development project, Ground Support Systems Optimisation (GSSO), probabilistic stope support design initiatives, and physical and numerical modeling of caving geomechanics. His team collaborates extensively with industry partners to translate research findings into practical mining applications.