جست‌وجوی استاد و پژوهشگر

• Numerical Geophysics
• Groundwater Modelling
• Mantle Convection
• +۳ مورد دیگر

Dr. Sia Ghelichkhan is a Tenure-Track Lecturer at the Research School of Earth Sciences (RSES) and member of the Institute for Water Futures at ANU. She holds a PhD in Geophysics from Ludwig Maximilian University of Munich (2019). Her expertise lies in numerical geophysics, particularly in developing large-scale models for groundwater systems, mantle convection, and glacio-isostatic adjustment. As co-lead of the Geoscientific Adjoint Optimisation Platform (G-ADOPT), she integrates advanced numerical methods to address Earth system dynamics. Her research combines adjoint data assimilation techniques with observational data to constrain mantle flow and geodynamic processes. Research interests focus on continental-scale groundwater modelling, mantle rheology, and dynamic topography. She leads projects on mantle convection retrodictions (e.g., early Cenozoic Atlantic region) and collaborates on global geodynamic models. Supervised student: Ruby Turner. Affiliations include the Environmental Geodesy Research Group and Climate & Ocean Geoscience Department. Active in high-resolution mantle flow simulations and exascale computing initiatives (e.g., TerraNeo). Awards: Not explicitly listed in provided texts. Grants include ANU Futures Scheme 2.0 and projects on sea-level modelling, geodynamic inversion, and mantle flow reconstructions. Laboratory involvement through G-ADOPT platform development.

Xiaojun Zengمشاهده پروفایل

استاد

• Machine Learning
• Computational Intelligence
• Decision Support Systems
• +۵ مورد دیگر

Prof. Xiaojun Zeng is a Professor of Machine Learning and Optimisation at the Department of Computer Science, University of Manchester. He holds a B.Sc. in Mathematics from Xiamen University and a Ph.D. in Computation from the University of Manchester. His research focuses on computational intelligence, machine learning, decision support systems, computational finance, health informatics, and data mining. He has published over 200 papers and contributed to projects like the EU-funded IoTRAIN initiative, aiming to modernize IoT education in Iran and Iraq. He has received prestigious awards, including the Microsoft European Retail Application Developer Award (2003) and the European IST Award (1999). His work spans academic leadership roles, including serving as an Associate Editor for IEEE Transactions on Fuzzy Systems and involvement in international conferences. Prof. Zeng’s research also addresses energy demand management and sustainable development goals, reflecting a commitment to interdisciplinary innovation. Education: B.Sc. in Mathematics, Xiamen University M.Sc. in Control Theory and Operations Research, Xiamen University Ph.D. in Computation, University of Manchester Research Interests: Computational intelligence, machine learning applications in healthcare and finance, decision support systems, and IoT integration in engineering education. His work bridges theoretical advancements with practical solutions in retail pricing, energy systems, and smart grids. Key Projects: IoTRAIN (2020–2023): EU project enhancing IoT education in Iran/Iraq. EPSRC and EU Framework projects on pricing, QoS, and cloud computing. Awards: Microsoft European Retail Application Developer Award (2003) European IST Award (1999) Grants & Advising: Supervised 40+ students and contributed to funded projects like the UK EPSRC pricing decision support initiative and EU H2020 Big Data in Finance. His research also impacts industrial collaborations in petroleum pricing and retail revenue management. Labs & Affiliations: Member of the Data Science Institute, Machine Learning and Optimisation group, and Christabel Pankhurst Institute at the University of Manchester.

• Machine Learning
• Ensemble Learning
• Feature Selection
• +۴ مورد دیگر

Gavin Brown is a Professor of Computer Science at the University of Manchester, affiliated with the Data Science Institute and the Machine Learning and Optimisation group. His research focuses on machine learning theory, ensemble methods, feature selection, and hardware-accelerated learning. He holds roles in interdisciplinary initiatives like the Centre for Digital Trust and Society, EnnCore project (privacy-preserving neural architectures), and the Robotics and Artificial Intelligence Centre. Education: PhD in Computer Science from the University of Birmingham (2003), with a thesis on 'Diversity in Neural Network Ensembles'. Research interests span theoretical foundations of machine learning, including bias-variance decomposition, ensemble diversity, and algorithmic stability. Applications include healthcare (e.g., outlier detection in vital signs), robotics (low-cost prediction hardware), and ethical AI (conceptual guarding of neural networks). He has pioneered work on feature selection for resource-constrained systems and neuromorphic computing. Recent articles emphasize unifying ensemble theory, hardware-efficient learning (FPGA-based feature selection), and clinical applications of machine learning. Projects include EnnCore (privacy-preserving AI), RAI Centre (robot-AI ethics), and Data Visualisation for clinical trials. He leads or co-leads 8 major projects, including £multi-million initiatives in digital trust, robotics, and AI. Supervised 24 doctoral students, with a focus on interdisciplinary work combining theory and applied machine learning.

Maximilien Gadouleauمشاهده پروفایل

دانشیار

• Coding theory
• Network coding
• Information theory
• +۱۳ مورد دیگر

Dr. Maximilien Gadouleau is an Associate Professor in the Department of Computer Science at Durham University, where he has been working since January 2012. He is a member of the Algorithms and Complexity research group, with secondary affiliations in Networks Engineering Science and Theory and Scientific Computing. Dr. Gadouleau received his MSc and PhD in Computer Engineering from Lehigh University in December 2005 and May 2009, respectively. After graduation, he held postdoctoral research positions at Université de Reims Champagne-Ardenne (until May 2010) and Queen Mary, University of London (until December 2011). Dr. Gadouleau's research spans multiple areas of theoretical computer science and discrete mathematics. His work focuses on the intersection of coding theory, network coding, and information theory with various branches of mathematics including combinatorics, graph theory, discrete optimization, matroid theory, logic, and group theory. He also investigates applications to network design, data storage, cryptography, data compression, and computation models. His recent work has particularly emphasized Boolean networks, finite dynamical systems, and semigroup theory. Dr. Gadouleau's extensive publication record demonstrates consistent contributions to theoretical computer science, with recent work showing a growing emphasis on the connections between discrete mathematics, dynamical systems, and coding theory. His research often bridges theoretical foundations with practical applications in network communication and data processing. Carnegie Trust for the Universities of Scotland: Research Assessor (2018) EPSRC Peer Review College member (2017) Dr. Gadouleau has successfully supervised PhD students including Izzy Friedlander (graduated July 2024) and Karl Southern (graduated July 2023). He was awarded an EPSRC first grant titled "Memoryless computation and network coding" which started on October 1, 2013. This grant supported research on computational models without memory and their applications to network coding problems. Dr. Gadouleau is an active member of the academic community, serving on editorial boards for journals including "Design, Codes, and Cryptography," "AIMS Mathematics," and "Mathematics and Systems Science." He regularly participates in international conferences and workshops, particularly in the areas of cellular automata, Boolean networks, and coding theory.

• Civil Engineering
• Environmental Engineering
• Physical Geography and Environmental Geoscience
• +۷ مورد دیگر

Barnaby Dobson is a Research Fellow at Imperial College London's Department of Civil and Environmental Engineering, part of the Faculty of Engineering. His research focuses on integrated water infrastructure modeling, emphasizing holistic evaluation of water systems' impacts on river quality. He developed the WSIMOD software to simulate interactions between water systems and management practices, with recent work exploring sewage spills' effects on river biodiversity through machine learning. Education and Background: 2023–current: Imperial College London, Research Fellow (Fluids Section) 2019–2023: Imperial College London, Research Associate (Environmental and Water Resources Engineering Section, CAMELLIA Project) 2018–2019: University of Oxford, Research Associate (Geography Department, Marius Project) 2014–2018: University of Bristol, PhD (Water Resource Systems Modelling, supervised by Dr. Francesca Pianosi and Prof. Thorsten Wagener) Research Themes: Integrated water system modeling Uncertainty quantification in socio-physical systems Optimisation for water resource control Linking wastewater systems to ecological impacts Key Projects: WSIMOD: Novel software for simulating water system interactions CAMELLIA Project: Integrated water systems modeling Marius Project: National water supply modeling for England and Wales

Wolfram Wiesemannمشاهده پروفایل

استاد

• Decision-making under uncertainty
• Supply chain management
• Healthcare optimization
• +۱ مورد دیگر

Wolfram Wiesemann is Professor of Analytics & Operations and Head of the Analytics, Marketing & Operations Department at Imperial College Business School. His research focuses on decision-making under uncertainty with applications in supply chain management, healthcare, and energy. Research Focus: Development of tractable approximation schemes for decision-making under uncertainty with rigorous error bounds. Applications span operations management, energy systems, and financial engineering. Teaching: BA1803 (Optimisation and Decision Models) and BA1806 (Introduction to Machine Learning) for MSc programs. Received Imperial College Business School Dean's Teaching Awards and nominations for Student Academic Choice Awards. Editorial Roles: Editor-in-Chief of Operations Research Letters and department co-editor for Management Science. Previously served on editorial boards of multiple leading journals. Research Impact: COVID-19 research on hospital care prioritization featured in Financial Times, Daily Mail, and France24.

• Spacecraft Systems Engineering
• Orbital Aerodynamics
• Space Debris Mitigation
• +۳ مورد دیگر

Dr. Peter Roberts is a Reader in Spacecraft Engineering at The University of Manchester's Mechanical and Aerospace Engineering department. His work focuses on orbital aerodynamics, spacecraft systems, and sustainable space technologies. He leads projects like the EU-funded DISCOVERER initiative, advancing Very Low Earth Orbit (VLEO) missions. Key achievements include the Icarus drag sail on TechDemoSat and the SOAR mission demonstrating drag-reducing materials. Roberts has secured grants from ESA, UKSA, and DARPA, coordinating large consortia. His research addresses space debris mitigation, aerodynamic materials, and atmospheric interactions. He advises on sustainable space practices, contributing to UN SDGs related to environmental protection. Notable awards include the 2022 Engineer's C2I Aerospace Award for DISCOVERER. Roberts collaborates internationally, including with Stuttgart University, and mentors over 15 postgraduate researchers. His labs and teams focus on experimental gas physics, spacecraft design, and VLEO mission systems.

• Computational Fluid Dynamics
• Multiobjective Optimisation
• Active Noise Control
• +۶ مورد دیگر

Sergey Utyuzhnikov is a Professor of Computational Mathematics and Reader in Mechanical and Aerospace Engineering at The University of Manchester since 2016. He holds a DSc (Habilitation) in Computational Mathematics from Moscow Institute of Physics & Technology (1997) and was certified as a Full Professor in Computational Mathematics by the Ministry of Education of Russia (1999). He has held academic roles at Moscow Institute of Physics & Technology (1986–2004) and Cranfield University (2004–2005), before joining the University of Manchester in 2005 as a School Senior Research Fellow. Educations: BSc, MSc, Moscow Institute of Physics & Technology (1977–1983) PhD (Candidate of Science) in Computational Mathematics (1986) DSc (Habilitation) in Computational Mathematics (1997) Research Interests: Focus on computational fluid dynamics, multiobjective optimization, active noise control, turbulence modeling, hypersonic flows, and geophysics. His work addresses challenges in boundary equations, nonlocal boundary conditions, and combustion modeling. He actively contributes to UN Sustainable Development Goals through aerospace engineering research. Key Projects: Leading the Aerospace Engineering research theme at the University of Manchester Co-investigator on projects like 'Development of advanced techniques for aerodynamic assessment of blunt bodies in hypersonic flow' Awards and Memberships: Fellow of the Institute of Mathematics & Applications (FIMA) since 2007 Membership in the Russian Academy of Sciences Academic expert for the Engineering & Physical Sciences Research Council (EPSRC) Labs & Collaborations: Part of the Aerospace Research Institute and collaborates internationally on topics like domain decomposition methods and turbulence modeling.

• Biotechnology
• Enzymology
• Microbial Biotechnology
• +۸ مورد دیگر

Salvatore Fusco is an Associate Professor and Group Leader in the Department of Biotechnology at the University of Verona. His research focuses on microbial enzymes for biomass and plastic valorization, microbial biotechnology, enzyme immobilization, and bioactive peptide characterization. He is affiliated with the Biochemistry and Industrial Biotechnology (BIB) research group and leads the PRIN 2022 project 'BioCat4BioPol'. Teaching includes modules such as Industrial Enzymology (6 credits), Molecular Biophysics (3 credits), and New Frontiers in Biocatalysis (6 credits) across undergraduate and master's programs. He advises on Protein Engineering for Enzyme Optimisation in the Biotechnology PhD program. Research interests span enzyme discovery, microbial isolation for industrial applications, and viral protein structural-functional studies. His work integrates computational methods for enzyme mining and experimental approaches for biocatalyst optimization. Administrative roles include membership in the PhD Boards of Biotechnology and Molecular Biotechnologies, and the Biotechnology Teaching Committee. He coordinates the 'Communication' role for departmental initiatives.

• Nanomaterials
• Luminescent lanthanide ions
• Hybrid organic-inorganic nanostructures
• +۷ مورد دیگر

Adolfo Speghini is a Full Professor in the Department of Biotechnology at the University of Verona. His academic sector is CHEM-03/A - General and Inorganic Chemistry. His research focuses on nanomaterials and luminescent properties, with particular emphasis on applications in biotechnology and nanomedicine. He serves as the PhD coordinator for the Faculty Board of PhD in Nanoscience and Advanced Technologies. Professor Speghini's research interests include: Nanomaterials activated with luminescent lanthanide ions Hybrid organic-inorganic nanostructures Multifunctional nanomaterials for Biotechnology, Green Chemistry and Nanomedicine Optical nanothermometry Surface functionalization of inorganic nanoparticles Nanoparticle-biomolecule interactions Colloidal Chemistry Nanostructures for drug delivery His recent publications demonstrate a strong focus on luminescent nanomaterials, particularly those doped with rare earth elements for various applications including bioimaging, nanothermometry, and energy conversion. The research spans from fundamental material synthesis to practical biomedical applications, showing a consistent thread of innovation in nanomaterial design and characterization. His work often involves interdisciplinary approaches combining chemistry, physics, and biomedical engineering. Professor Speghini has received research funding for numerous projects including: Nanocompositi polimerici a base di Quantum Dots luminescenti per pannelli fotovoltaici ad alta efficienza (2024) PRIN 2022 PNRR - Optical NanoThermometry using Luminescence and Raman Spectroscopies - OPTIMISE (2023) Celle fotovoltaiche ad elevato rendimento funzionalizzate con Quantum Dots luminescenti (2020) Smart fabrics: tessuti integrati con nanocompositi piezolettrici flessibili per la produzione di energia elettrica da energia meccanica (2020) He teaches several courses including: Basis of physical chemistry (2025/2026) General and Inorganic Chemistry (2025/2026) Nanomaterials for Biotechnology and Green Chemistry (2025/2026) Luminescent Nanomaterials for theranostics (2024/2025)

Matthias Kraumeمشاهده پروفایل

استاد

• CFD simulation
• Transport phenomena
• Membrane bioreactors
• +۵ مورد دیگر

Prof. Matthias Kraume is a Professor at the Technical University of Berlin (TU Berlin), affiliated with Faculty III - Process Sciences and the Institute of Process Engineering , specifically leading the FG Verfahrenstechnik research group. His research focuses on CFD simulation, multiphase processes, membrane bioreactors, and reactor design, with contributions to the Collaborative Research Centre InPROMPT (2009). He served as a former member of the UniCat Executive Board (2012–2017), contributing to Research Fields D1/D2 (2012–2017) and C2/C3/C4 (2007–2011). His work spans projects like multiphase processes, biological systems, and renewable resources optimization. Notably, he coordinated the InPROMPT project on integrated fluid multiphase systems. Publications emphasize CFD-DEM coupling, reactor optimization, and biocatalyst screening. His group’s work has been recognized through awards for students like Gregor Wehinger, who became a junior professor under his mentorship. Kraume’s team collaborates on energy-efficient biogas systems, viscoelastic fluid dynamics, and automated process control in stirred reactors. Current research includes advanced CFD modeling for fluidized beds, bioreactor design, and sustainable process intensification. He oversees lab activities at TU Berlin’s FG Verfahrenstechnik , with affiliations to industry partnerships for biogas and catalytic technologies.

Supriya Supriyaمشاهده پروفایل

مدرس

• Health Informatics
• Machine Learning
• Artificial Intelligence
• +۷ مورد دیگر

Supriya Supriya is a Lecturer in the Department of Design and Creative Technology at Torrens University Australia, affiliated with the Centre for Artificial Intelligence Research and Optimisation (AIRO). She holds a Ph.D. in Information and Mathematical Science from Victoria University Melbourne (2020) and master's and bachelor's degrees in Computer Science and Information Technology from Punjab Technical University, India (2014 and 2010). Her research focuses on health informatics, biomedical signal analysis (particularly EEG signals), machine learning, and artificial intelligence. Key areas include癫痫 detection, sleep stage classification, and the application of complex networks and graph-based techniques for medical diagnostics. She has also contributed to deep web data extraction and classification. Supriya has published extensively in reputable journals like IEEE Transactions and conferences, with notable works on EEG-based epilepsy detection and complex network frameworks. Her research aligns with UN Sustainable Development Goals related to education and innovation. She currently supervises PhD students in real-time biomedical signal analysis systems. Her technical expertise includes programming in MATLAB, C++, C#, and Python, and she emphasizes empowering women in STEM fields.

Ammar Alazabمشاهده پروفایل

مدرس

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۸ مورد دیگر

Dr. Ammar Alazab is a senior Cybersecurity Lecturer at Torrens University Australia, affiliated with the Design and Creative Technology College and the Centre for Artificial Intelligence Research and Optimisation (AIRO). He is actively accepting PhD students in areas such as Enhancing Cyber Threat Detection via Machine Learning and Federated Learning for Secure Cyber Threat Intelligence Sharing. With over 60 research publications and 50+ academic/industry talks, his work bridges AI and cybersecurity, focusing on malware analysis, IoT security, and cybercrime prevention. Education: PhD (Computer Science), Deakin University (2010–2014) Master (Computer Networking), Amman Arab University (2002–2004) Bachelor (Information Technology), Al-Balqa Applied University (1997–2001) Research Interests: Data Science (Hyper-heuristics, Evolutionary Computation), AI for Cybersecurity, IoT Security, Malware Analysis, Blockchain, VR/AR Applications. His work contributes to UN Sustainable Development Goals related to education and innovation. Advising/Grants: Supervises PhD projects in AI-driven cybersecurity and privacy-preserving analytics. No grants explicitly listed in the provided text. Labs/Teams: Leads research within the AIRO Centre, collaborating on topics like prompt attack taxonomy and federated learning defense strategies.

Hannah Wechkunanukulمشاهده پروفایل

دانشیار

• Culturally and Linguistically Diverse Populations
• Health Inequities
• Digital Health Innovation
• +۷ مورد دیگر

Associate Professor Hannah Wechkunanukul is a senior academic educator in the Public Health Department at Torrens University and a researcher at the Centre for Healthy Sustainable Development (CHSD). She holds an adjunct academic position at Flinders University (2014–2021) and serves on the Research Committee of the Public Health and Environmental Policy in Southeast Asia Research Unit (PHEP-SEA). Her research focuses on health inequities among culturally and linguistically diverse (CALD) populations, digital health innovation, and climate change impacts on health. She leads multidisciplinary projects like the DatCALD and DRIVE-CALD initiatives, aiming to improve healthcare accessibility through co-design and data-driven approaches. Education: PhD in Nursing and Midwifery (Flinders University, 2016) Graduate Diploma in Primary Health Care (Flinders University, 2011) Masters in Health Administration (Flinders University, 2009) Masters in Pharmacy (Naresuan University, 2003) Bachelor of Pharmacy (Mahidol University, 1993) Research Interests: Her work addresses health disparities in CALD populations, digital health interventions, pharmacy practices, and environmental health. She employs mixed-methods and systematic reviews to study topics like delayed medical care among ethnic groups and climate change's health impacts. Her recent studies on cardiac symptom delays in migrants have influenced cultural competency initiatives in healthcare systems. Grants & Collaborations: She leads the 2024–2028 project "Optimising the Detection and Multidisciplinary Management of Multimorbid Heart Failure in Primary Care," funded by a Competitive Research Grant. She collaborates with PHIDU on data mapping tools linking clinical and population health data. Labs/Teams: Works with multidisciplinary teams including industry partners and consumers on projects like the TAL-Co initiative to mitigate climate change's health effects.

• Women in Academia
• Remote Work
• Research Methodologies
• +۳ مورد دیگر

Eleni Tzouramani is a Senior Lecturer in the School of Business and Creative Industries, focusing on transformative educational practices and organizational dynamics. Her work bridges academic research with practical policy implications, particularly in crisis management among women academics and remote work frameworks. She co-led the Digital Maieutic Project, integrating AI and Universal Design for Learning principles, for which her team received the UKAIS Teaching Innovation Grant (2024). Her research interests span spirituality's role in organizational cultures, leadership development, and multimodal learning strategies. She actively contributes to parliamentary policy discussions, submitting evidence on home-based working for the UK House of Lords. Tzouramani has presented at international forums on topics like AI ethics in education and leadership navigation during transitional phases. She currently oversees a Knowledge Transfer Partnership in leadership development and collaborates with institutions to design inclusive educational frameworks.