جست‌وجوی استاد و پژوهشگر

Stefan Lechnerمشاهده پروفایل

استاد

• Energy Economics
• Renewable Energy Systems
• Thermal Energy Storage
• +۵ مورد دیگر

Prof. Dr.-Ing. Stefan Lechner has been full Professor of Energy Economics and Energy Systems at the Technical University of Central Hesse (THM) , Giessen, since March 2015. He is affiliated with the Department of Mechanical Engineering and Energy Technology and the Institute THESA – Institute of Thermodynamics, Energy Process Engineering and Systems Analysis . Additionally, he leads the Laboratory for Energy Economics and is a core member of the Competence Center for Energy Technology and Energy Management (etem.THM) . Education & Career Dr.-Ing., Brandenburg University of Technology (BTU) Cottbus, 2012 – Dissertation on steam-fluidized-bed drying of lignite. Dipl.-Ing. (FH) Mechanical Engineering, Georg Agricola University of Applied Sciences Bochum, 2002 – specialising in Future Energies. Supplementary doctoral studies & economics coursework at BTU Cottbus and FernUniversität Hagen. Professional experience at Vattenfall (plant management, power-plant planning & R&D) and Kreisel Umwelttechnik (Head of Development) before entering academia. Research Interests Prof. Lechner’s work centres on the techno-economic analysis and optimisation of energy systems in transition . Core themes include renewable energy integration , thermal energy storage (particularly Carnot batteries using ceramic high-temperature stores), sector coupling between electricity, heat and mobility, and 5th-generation cold district-heating networks (5GDHC). Methodologically, he combines experimental thermal engineering with open-source simulation frameworks , agent-based demand modelling , and electricity-market modelling . Recent activities expand into waste-heat recovery from data centres and transcritical CO₂ heat-pump systems for low-temperature district heating, always targeting cost-effective, grid-friendly and sustainable solutions . Publication Trends Between 2017 and 2024 his output highlights a clear evolution from fundamental studies on pressurized steam fluidized-bed drying and lignite heat-transfer toward system-level analyses of storage-based sector coupling . A dominant cluster addresses Carnot batteries , covering high-temperature storage materials, gas-turbine re-conversion concepts, and demonstration results. Parallel streams examine GIS-based rooftop PV potential , agent-based settlement energy-demand modelling , and regulatory frameworks for cross-sector energy markets. Scientific Awards & Honours No specific awards are mentioned in the provided material. Research Funding & Teams Prof. Lechner has secured and coordinates projects worth > €10 million (THM share ≈ €6.5 million) funded by BMBF, BMWK/BMWi, Hessian ministries (HMWK, HMWEVW), WI-Bank and ERDF : LOEWE 3 DUWä (2025-2027) – transcritical CO₂ dual-use heat pumps for cold district heating. EnEff:Stadt FlexQuartier2 (2023-2027) – hybrid storage optimisation in Giessen’s Philosophenhöhe district. KNW-Plus (2022-2023) – design & online tool for cold local heating networks. Innovative waste-heat use from data centres (2022-2023). FlexQuartier Gießen (2018-2023) – integrated hybrid storage & sector coupling in a new-build district. Kommun:E (2018-2022) – municipal energy-supply transformation under Germany’s Energiewende. High-T-Stor (2017-2019) – cross-sector high-temperature storage for renewable balancing. FES (2019-2021) – Research Center for Energy Storage and Sector Coupling. These projects involve interdisciplinary consortia including municipalities, grid operators, SMEs, and research partners across Germany. Teaching & Academic Leadership He lectures in Energy Economics and Sector Coupling, Energy Markets, Heat Transfer, Renewable Energy Technology and Energy System Analysis . He also serves as Programme Manager for the part-time continuing-education M.Sc. Energy Efficiency Management (StudiumPlus, Wetzlar) and contributes to advanced master’s courses on energy law and thermodynamics.

Timothy Jonesمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Computing
• Compilers
• +۴ مورد دیگر

Timothy Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, with a research focus on extracting parallelism (thread-level, data-level, memory-level) through compilers, binary translators, and microarchitectures to enhance performance, energy efficiency, and reliability. He is also a Fellow and 1956 College Lecturer at Gonville and Caius College, serving as joint Director of Studies for Computer Science. Teaching: Advanced Topics in Computer Architecture (MPhil ACS, Part III), Introduction to Computer Architecture (Part IB), Optimising Compilers (Part II) Research Themes: Computer Architecture, Security, Programming Languages, Parallel Computing Contact: Room SC03, Department of Computer Science and Technology, William Gates Building, Cambridge CB3 0FD His recent publications emphasize heterogeneous parallelism, fault tolerance, speculative execution, and security implications in compiler and microarchitecture design. Notable trends include integrating fine-grained security analysis into superscalar cores and optimizing GPU architectures for scalarization and memory bypassing. He is active on Twitter ( @TJonesCL ) and maintains an Erdős Number of 4.

Dan Steinbergمشاهده پروفایل

عضو هیئت علمی

• Probabilistic Machine Learning
• Variational Inference
• Bayesian Deep Learning
• +۷ مورد دیگر

Dan Steinberg is a senior research scientist and team leader of the Decisions & Statistical Learning team at CSIRO Data61 in Canberra, Australia. His expertise lies in probabilistic machine learning, variational inference, Bayesian deep learning, causal inference, and their application to domains spanning synthetic biology, geospatial analytics, and algorithmic fairness. Education PhD in Computer Vision / Machine Learning (2013) – University of Sydney, Australian Centre for Field Robotics Bachelor of Engineering (Mechatronics, First-Class Honours) – University of Sydney (2008) Bachelor of Commerce (Finance) – University of Sydney (2008) Research Interests Steinberg’s core research agenda revolves around building scalable probabilistic models that can learn efficiently from limited or noisy data and provide principled uncertainty estimates. Key themes include: Variational Inference & Bayesian Deep Learning: developing lightweight yet powerful algorithms for approximate posterior inference in complex models (e.g., Aboleth, Revrand). Active Learning & Experimental Design: creating methods that decide which experiments or measurements will maximise information gain, with recent focus on in-silico protein engineering via Variational Search Distributions (VSD). Causal Inference: leveraging machine-learning tools to perform robust observational causal studies for evidence-based policy, including work on youth well-being and academic outcomes. Algorithmic Fairness: translating normative notions of equity into quantifiable objectives for regression-based decision systems. Large-scale Spatial Analytics: Landshark—an open-source TensorFlow toolkit for supervised learning on massive geospatial raster datasets. Notable Software & Tools Aboleth: A minimal-overhead TensorFlow framework for Bayesian deep learning. Landshark: Command-line tools for large-scale spatial inference. Revrand: Scalable Bayesian generalised linear models with non-conjugate likelihoods. libcluster: Extensible C++ library for hierarchical Bayesian clustering. Scientific Awards Oral Presentation Award – ICML 2025 Workshop on Scaling up Intervention Models (SIMS) Oral Presentation Award – NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty (BDU) Oral Presentation Award – NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning Spotlight Paper Award – NeurIPS 2014 (Extended and Unscented Gaussian Processes) Research Team & Collaborations As Team Leader – Decisions & Statistical Learning at CSIRO Data61, Steinberg directs a multi-disciplinary group that partners with government agencies (e.g., Jobs and Skills Australia, Australian Institute of Health and Welfare) and industry to deploy machine-learning solutions at scale. He has previously held roles as Principal Researcher at Gradient Institute (2019-2023), Senior Research Engineer at CSIRO Data61 (2016-2019), Researcher at NICTA (2013-2016), and Research Associate at the University of Sydney (2012-2013).

Deborah Do-Rosario-Benrosمشاهده پروفایل

مدرس ارشد

• Design and Computation
• Shape Grammars
• Mass Customisation
• +۵ مورد دیگر

Dr. Deborah Do-Rosario-Benros is a Senior Lecturer in Technical Studies and Representation at the University of East London (UEL), serving as a Cluster Leader in the Department of Architecture & Visual Arts within the School of Architecture, Computing and Engineering. She is a UK-registered architect (ARB/RIBA) with advanced research expertise in computational design methodologies. Educational Background: Doctorate from University College London (The Bartlett School) Master's in Architecture from the University of Lisbon Visiting student at Massachusetts Institute of Technology (MIT) Her research focuses on Design and Computation , Shape Grammars , and Mass Customisation in architecture. Recent work explores 3D printing , robotic manufacturing , and modular design for sustainable housing solutions. Research Publications Trends: Her 2024-2023 articles analyze computational frameworks like multilingual shape grammars, apply robotic construction to micro-housing, critically review 3D printing in large-scale construction, and investigate modular systems using bent metal pipes and space-filling solids. Collaborative co-design with AI and participation in international competitions like the Orange County Sustainability Decathlon are recurring themes. Professional Experience: Prior roles include teaching at the University of Lisbon, visiting faculty at Cornell University, and professional practice at architectural firms Foster and Partners and Arup. She has presented at major conferences including SIGraDi, ZEMCH, and SEEDS. Labs and Teams: As Cluster Leader at UEL, she coordinates research efforts in architecture and computational design, collaborating with institutions like MIT and Cornell.

• Sustainable Energy
• Energy Efficiency Technologies
• Renewable Energy Systems
• +۳ مورد دیگر

Dr. Xiaoli Ma is a Senior Research Fellow at the University of Hull, affiliated with the Energy and Environment Institute and the Centre for Sustainable Energy Technologies under the Faculty of Science and Engineering. Her research focuses on sustainable building services, renewable/sustainable energy systems, energy efficiency technologies, and instrumentation technologies. She has secured over £2.7 million in research funding from bodies such as the EU, EPSRC, Innovate UK, and the National Science and Technology Committee of China, leading or co-leading 26 projects. Her research interests include innovative cooling systems for data centers (e.g., super-performance dew point cooling achieving 90% energy savings), solar-driven energy systems, waste heat recovery, and thermoelectric technologies. Notable projects include the development of a novel Loop-Heat-Pipe-based data center cooling system funded by the EU FP7 and a solar façade hot water heating system supported by the EU FP7 Programme. Dr. Ma has published over 90 journal articles, two books, and three book chapters, with recent works focusing on machine learning-driven energy optimization, solar cooking systems with energy storage, and advanced heat pump technologies. She holds two patents and actively supervises PhD students in renewable energy, energy efficiency, and built environment applications. Her lab and team are part of the Energy and Environment Institute, collaborating on projects like the pioneering near-zero-carbon air conditioning system using atmospheric latent heat and natural light energy (EPSRC-funded). Key grants include a £814k EPSRC project and a £692k IEEA initiative for data center cooling advancements.

Dirk Sudholtمشاهده پروفایل

استاد

• Randomised Algorithms
• Algorithmic Analysis
• Combinatorial Optimisation
• +۵ مورد دیگر

Dr. Dirk Sudholt is a Full Professor at the University of Passau and a Visiting Professor at the University of Sheffield. He holds a Ph.D. from Technische Universität Dortmund and has held postdoctoral positions at the International Computer Science Institute (ICSI) in Berkeley and the University of Birmingham. His research focuses on randomized algorithms, algorithmic analysis, and combinatorial optimization, with expertise in the theoretical analysis of bio-inspired search heuristics like evolutionary algorithms and ant colony optimization. His work emphasizes rigorous runtime analysis to understand algorithmic performance and design principles. Education: PhD in Computer Science, Technische Universität Dortmund (2008) Diploma in Computer Science, Technische Universität Dortmund (2004) Research Interests: Runtime analysis of evolutionary algorithms Algorithmic design for multimodal optimization Noise robustness in metaheuristics Parallel and distributed evolutionary computation Grants: SAGE: Speed of Adaptation in Population Genetics and Evolutionary Computation (EU FP7, 2014–2016) Teaching: University of Passau: Courses on algorithms, evolutionary computation, and randomized algorithms

• Data-driven building performance
• Energy demand reduction
• Sustainable design
• +۷ مورد دیگر

Dr Virginia Gori is a Lecturer in Buildings and Energy at the Bartlett School Env, Energy & Resources, University College London. She leads Subtask D of the IEA Annex 81 'Data-Driven Smart Buildings' programme, focusing on mapping technology landscapes and evaluating data-driven smart building policies. PhD in Energy and the Built Environment (UCL, 2017) MRes in Built Environment Energy Demand Studies (UCL, 2014) BSc in Architectural Engineering (Universita degli Studi di Firenze, 2010) Her research combines building physics , in-situ monitoring , and Bayesian statistics to advance energy demand reduction in the built environment, particularly for historic buildings . She has developed novel Bayesian frameworks for thermophysical property estimation and whole-building performance analysis. Data-driven smart buildings Thermophysical property modeling Risk management for energy-moisture balance Conservation-compatible retrofit Scientific recognition includes: EPSRC Doctoral Prize Fellowship (2018-2020) UCL BEAMS Overseas Doctoral Award (2013) DAAD/DLR Research Fellowship (2021) Teaching contributions: Module lead: Introduction to Smart Energy Data and Statistics (2023-) Module lead: Smart Energy Solutions in the Built Environment (2023-) Former module lead: Building Physics & Energy (2019-2023) Co-designed Fundamentals of Building Physics course (6 years) Professional roles: Associate Editor, Buildings & Cities journal Technical committee member, CEN TC89WG13 Visiting Scholar, UC Berkeley (2019) Active in IEA Annex 71, Task 59, and Annex 81

• Rural and Remote Health
• Access to Health Services
• Medical Ethics
• +۴ مورد دیگر

Dr. Emily Saurman is a Senior Lecturer in Rural and Remote Public Health at the Rural Health (Dubbo/Orange) campus of the Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney. Her work focuses on improving healthcare access and delivery in rural and remote communities across Australia. Dr. Saurman holds a PhD from the University of Sydney, an MPH from the University of Wollongong, an MA in Applied Ethics from the University of Wollongong, and a BA in Philosophy/Medical Ethics from Randolph-Macon Woman's College. Dr. Saurman's research spans several interconnected domains within rural and remote health. Her primary focus is on improving access to health services in underserved communities, with particular emphasis on digital health solutions and telehealth innovations. She has pioneered work in rural mental health emergency care through videoconferencing technology, which has significantly transformed how mental health services are delivered in remote areas. Her research also extends to palliative care models, school-based health services, Indigenous health research ethics, and the impact of climate change on rural mental health. She employs primarily qualitative research methodologies with a strong emphasis on translational research that directly informs health service improvements. Dr. Saurman's recent publications demonstrate a clear trajectory toward hybrid virtual care models, particularly the Virtual Rural Generalist Service, which aims to improve health access and outcomes in rural and remote communities. Her work increasingly integrates economic evaluations with clinical outcomes to demonstrate the value of innovative service delivery models. There's also a growing emphasis on Indigenous health research ethics and reconciliation in her more recent publications, reflecting a commitment to culturally safe research practices. Optimising digital solutions to improve access to comprehensive Primary Health Care services in remote Indigenous communities (2022) A systems-approach to enhancing community-based medication review (2021) Evaluation of the Virtual Rural Generalist Service VRGS as an effective, 'COVID-19 resilient' model of care (2021) Her teaching focuses on research and evaluation methods, qualitative evaluation methodologies, and research and evaluation ethics, contributing to research capacity building in rural health contexts.

• Algorithm development
• Data analytics
• Time-series data analysis
• +۶ مورد دیگر

Emran Ali is a Graduate Researcher (Ph.D. candidate) and Part-Time Lecturer at Deakin University's School of Information Technology within the Faculty of Science, Engineering and Built Environment. He holds concurrent faculty appointments at Hajee Mohammad Danesh Science & Technology University (HSTU) in Bangladesh where he teaches computer science courses while on study leave. His academic journey includes a Master of Science (Research) in Information Technology from Deakin University (2022) and a Bachelor of Science in Computer Science and Engineering from HSTU. Doctor of Philosophy (Ph.D.) in Information Technology, Deakin University (2023–present) Doctor of Philosophy (Ph.D.) in Machine Learning, Coventry University (Cotutelle program, 2023–present) Master of Science (Research) in Information Technology, Deakin University (2020–2022) Bachelor of Science in Computer Science and Engineering, HSTU Bangladesh (2007–2012) Ali's research focuses on algorithm development and applied machine learning in health informatics, specializing in biosignal processing for neurological and sleep disorder detection. His work integrates time-series data analysis with explainable AI techniques to develop clinical decision support systems. Current projects include ML/DL modeling of sleep-stage transitions in aging populations and causal relationship analysis in sleep disorders using EEG data. Analysis of his 10 recent publications reveals strong concentration in biomedical ML applications (60%), particularly EEG-based neurological disorder detection and mental health diagnostics. Secondary focus areas include environmental monitoring systems (20%) and foundational computer science (20%). His work consistently employs ensemble methods and feature optimization techniques across diverse datasets, with increasing emphasis on real-world clinical applicability in recent publications. Deakin University Post-graduate Research Scholarship (DUPRS) through Cotutelle program with Coventry University National Fellowship from Bangladesh Ministry of Science and Technology (2020) Best Presentation Award at Deakin School of IT Conference (2021) AWS AI/ML Scholarships (2023, 2024) Next Generation Tech Booster Scholarship (2024) Ali provides research supervision at HSTU while serving as a Graduate Research Teaching Fellow at Deakin University for Machine Learning and Data Analytics units. His industry collaborations include projects with Monash University, Alfred Health, and AETMOS Australia focused on health informatics applications. Current funding includes AWS-sponsored nanodegrees and Deakin University research scholarships supporting his sleep disorder research. His technical work integrates cloud-based AI/ML platforms (AWS, Azure) with biosignal processing pipelines, utilizing collaborations across Australian healthcare institutions to validate clinical applications. Recent projects emphasize explainability in deep learning models for medical diagnostics, particularly in resource-constrained environments relevant to Bangladesh healthcare contexts.

• Supply Chain Management
• Sustainability
• Optimisation Modelling
• +۵ مورد دیگر

Dr. Catherine Lou is an Associate Professor in supply chain and logistics at Victoria University Business School, part of the College of Arts, Business, Law, Education & IT. She serves as Discipline Leader for Transformative Research in Policy, Economy and Business at the Institute for Sustainable Industries & Liveable Cities, and is the Global Head of the WiLAT Capacity Building Centre. Her academic journey began at Victoria University where she completed her PhD in Supply Chain Optimisation in 2015, after which she joined as a lecturer. Dr. Lou's educational background includes: PhD in Supply Chain Optimisation, Victoria University (2015) Graduate Certificate in Tertiary Education, Victoria University (2018) MSc, BUAA, China (2010) Dr. Lou's research spans multiple interdisciplinary areas with a strong emphasis on quantitative approaches including optimisation modelling, statistics, and advanced data analysis. Her primary research areas include Supply Chain Management (focusing on sustainability, operations management, and risk management), Green Tourism and Visitor Economy, Leadership and Diversity initiatives, International Education, and Business Information Systems. Her work consistently integrates quantitative methods to address complex challenges in sustainable development and supply chain optimization, with particular attention to practical applications that benefit industry and society. Dr. Lou's publication portfolio demonstrates a clear trajectory toward increasingly interdisciplinary research that bridges supply chain management with sustainability, social justice, and wellbeing. Her recent work shows a growing emphasis on regional disparities in green manufacturing, social procurement systems, and the intersection of international student experiences with mental health. The thematic evolution of her research reflects a deepening commitment to addressing complex societal challenges through supply chain innovation, with publications appearing in D1 (top 5%) and Q1 journals across multiple disciplines. Dr. Lou has received numerous prestigious awards recognizing her contributions to academia and professional practice: International Student of the Year - Postgraduate by Victoria State (2013) VU Outstanding Student Alumni Award (2015) Young Professional of the Year award by the Chartered Institute of Logistics and Transport in Australia (2018) Excellence in Women's Leadership (Supply Chain Education) Award at the IEOM conference (2024) As an active researcher and mentor, Dr. Lou has secured over $$1.3$$ million in competitive research funding from diverse sources including international foundations, national and state government agencies, philanthropic organizations, and industry partners. She currently supervises multiple PhD students across various topics including AI adoption in SMEs, ESG activities, environmental sustainability in sports, and insurtech innovation. Her leadership extends to significant roles in professional organizations, particularly as Australia Chairperson and Global Vice Chairperson for Women in Logistics and Transport (WiLAT), where she champions initiatives that foster diversity and inclusion worldwide. Dr. Lou plays a pivotal role in the WiLAT Capacity Building Centre, leading global initiatives that develop leadership capabilities and promote gender diversity in the logistics and transport sector. Her work bridges academic research with practical industry applications, creating meaningful impact across multiple sectors including tourism, infrastructure, and international education, with alignment to UN Sustainable Development Goals including Partnerships for the Goals, Good Health and Well Being, Industry Innovation and Infrastructure, and Sustainable Cities and Communities.

• Autonomous Systems
• Biomimetic Robotics
• Unmanned Underwater Vehicles
• +۷ مورد دیگر

Dr Euan W McGookin is a Senior Lecturer in Autonomous Systems & Connectivity at the University of Glasgow, based in the Aerospace Sciences division of the James Watt Building South. He coordinates Glasgow-delivered aerospace degree programmes in Singapore and serves on the IFAC Technical Committee on Marine Systems, underlining his sustained engagement with both local and international academic activities. Education: 1st Class Honours Master of Engineering in Avionics, University of Glasgow PhD in Optimisation of Sliding Mode Controllers for Marine Applications, University of Glasgow (1997) Research Interests Dr McGookin’s core expertise lies in the design, simulation, control and physical realisation of autonomous robotic systems. His work spans Autonomous Underwater Vehicles (AUVs) , Unmanned Aerial Vehicles (UAVs) , Planetary & Terrestrial Rovers , and Biomimetic Robotics . He is particularly recognised for applying biologically inspired principles to robotic locomotion, navigation and control. Complementary themes include advanced control methodologies—Sliding Mode Control, H-infinity, Inverse Model Control—optimisation heuristics, guidance & navigation, fault detection & isolation (FDI), and system health monitoring for both terrestrial and space applications. Publication Trends Across 80 publications from 1995 to 2025, his work has evolved from early genetic-algorithm-based controller optimisation for marine vessels to cutting-edge multi-rover mission planning and health monitoring for planetary exploration. Recent outputs (2022–2025) concentrate on micro-rover coordination, friction modelling for planetary soils, reinforcement-learning-driven sensor fusion, and robust health-monitoring architectures, reflecting a strategic pivot toward space robotics while retaining strong roots in control theory and autonomous systems. Scientific Awards & Fellowships Member, IFAC Technical Committee on Marine Systems Grant & Advising Narrative While specific grant values are not disclosed, his continuous funding stream is evidenced by sustained publication output, international conference leadership, and ongoing supervision of postgraduate projects. Dr McGookin advises a steady cohort of PhD and MSc students whose theses align with his research themes—ranging from rover fault diagnosis to biomimetic AUV coordination—thereby fostering the next generation of control and robotics engineers. Laboratory & Team Dr McGookin heads research activities within the James Watt Building South, leveraging interdisciplinary laboratories that integrate simulation suites, rapid-prototyping facilities for AUV and UAV subsystems, and dedicated test rigs for biomimetic propulsion and rover mobility studies. Collaborative networks extend across the University of Glasgow’s Aerospace Engineering group, Singapore Institute of Technology partners, and international consortia such as ESA and IFAC.

Johari Hussein Nassor Amarمشاهده پروفایل

عضو هیئت علمی

• Built Heritage Conservation
• Affordable Housing Policy
• Urban Planning
• +۳ مورد دیگر

Johari Hussein Nassor Amar is a Senior Teaching Fellow at Bond University's Faculty of Society & Design, affiliated with the Centre for Comparative Construction Research. He holds a PhD in Sustainable Development from KTH Royal Institute of Technology, an MSc in Real Estate Management from KTH, and a BSc (Hons) in Land Management and Valuation from the University of Dar es Salaam. His research focuses on built heritage conservation, affordable housing policy, and urban planning with a cross-cultural lens. Key research interests include the conservation of cultural heritage in Australia and Tanzania, policy frameworks for affordable housing, and the application of person-environment fit theory in design. His work contributes to UN Sustainable Development Goals related to education and sustainable cities. Recent projects include 'Optimising Person-Environment Fit for Inclusive Housing' (2023-2025), comparing Build-to-Rent models between Australia and Germany (2022-2025), and advancing property valuation through LiDAR and AI (2024-2025). He has supervised PhD research on megaprojects in Southeast Queensland and actively engages in policy discussions on housing affordability and heritage management. Notable outputs include analyses of Australia's National Rental Affordability Scheme (NRAS), cross-cultural heritage management comparisons, and white papers on multi-sectoral solutions for housing challenges. His research emphasizes stakeholder collaboration and systemic approaches to urban and cultural sustainability.

Zhixin Liuمشاهده پروفایل

مدرس

• Urban microclimate
• Thermal effects of urban greening
• Human thermal comfort and health
• +۳ مورد دیگر

Dr Zhixin Liu is a Lecturer in Landscape Architecture at the University of Sheffield’s School of Architecture and Landscape, starting in 2024. Previously she was a Research Assistant Professor at the Chinese University of Hong Kong and a Postdoctoral Fellow at CUHK’s Institute of Future Cities, with a visiting scholar period at Texas A&M University. Education: Ph.D. in Building Environment and Energy Laboratory, South China University of Technology Research Focus: Dr Liu has been advancing urban microclimate research since 2013, specialising in the thermal and human-biometeorological effects of urban greening. Her interdisciplinary work integrates field observations , numerical simulation and policy analysis to translate scientific evidence into practical strategies for climate-responsive landscape design and planning. Core themes include urban microclimate regulation, thermal comfort and health impacts of green infrastructure, and evidence-based design optimisation for subtropical high-density cities. Publication Trends: Across more than twenty peer-reviewed articles, her scholarship spans three key trajectories: (1) methodological refinement of microclimatic simulations (ENVI-met, COMFA, RayMan), (2) empirical assessment of urban trees, green roofs and façades for heat mitigation, and (3) policy-oriented reviews on green infrastructure implementation in international contexts. Awards & Recognition: Excellence in Reviewing (2023) – Urban Climate Winner, Future Building Category, “Advancing Net Zero” Ideas Competition, Hong Kong Green Building Council (2021) Grants & Collaboration: Co-Investigator, “Study on the long-term impact of green space on urban local climate and building energy consumption in hot and humid areas” (2023–2025), Guangdong Province Science & Technology Planning Project Principal Recipient, Excellent Doctoral Dissertation Innovation Fund (2018–2019), South China University of Technology Teaching & Supervision: She leads and contributes to modules such as Presentation, Communication and Research Skills , Advanced Landscape Research , Final Landscape Project , and Advanced Landscape Planning – Global Issues . She actively seeks master’s and PhD students interested in multi-scale urban climate studies, evidence-based blue-green infrastructure design, and outdoor thermal comfort for vulnerable populations. Professional Service & Editorial Roles: Dr Liu serves as Associate Editor for Urban Climate and Guest Editor for Urban Forestry and Urban Greening , and reviews for leading journals including Nature Communications and Building and Environment . She is also the primary editor of the forthcoming Springer book Urban Greenery and Microclimate: Experience from Subtropical High-density Cities .

• Supply Chain Management
• Logistics Engineering
• Petroleum Industry Optimization
• +۳ مورد دیگر

János Baumgartner serves as Assistant Professor at the Department of Computer Science, Faculty of Information Technology, University of Pannonia in Veszprém, Hungary. His office is located in Building I, room 905, and he actively contributes to the PIMS Academy postgraduate program. His research focuses on: Supply Chain Management in petroleum industry Logistics Engineering and optimization Mathematical modeling of value chains Operations research applications Petroleum refining optimization Dr. Baumgartner plays a key role in the PIMS Academy, a specialized program developed with MOL Group that trains specialists in oil industry supply chain management. The program teaches market-leading optimization tools for downstream petroleum operations, covering subjects including LP Modeling, Petroleum Refining, Short Term Scheduling, and Supply Chain Management Fundamentals. As part of Hungary's educational initiative in energy sector optimization, his work contributes to producing graduates with the Specialist of Supply Chain Optimisation in Petroleum Industry (SCOPI) credential through a two-semester English-language program with potential industry placement. His academic contributions bridge computer science theory with practical industrial applications, particularly in optimizing complex petroleum value chains across multiple production sites and operational domains.

• Artificial Intelligence
• Constraint Programming
• Optimisation
• +۱۰ مورد دیگر

Professor Kenneth Brown is affiliated with the Department of Computer Science at University College Cork (UCC) , Ireland. He holds the academic rank of Professor and is a Principal Investigator at the Insight Centre for Data Analytics and the CTVR (Telecommunications Research Centre) . BSc (Hons) Mathematics, University of Glasgow, 1986 MSc Mathematical Logic and the Foundations of Computation, University of Manchester, 1987 PhD Artificial Intelligence in Engineering, University of Bristol, 1991 His research focuses on Artificial Intelligence, constraint programming, optimisation, and distributed reasoning , with applications in wireless networking, sensor networks, and dynamic resource management . He also works on smart energy systems, data analytics, and human-centric applications. His recent work includes projects under the SFI-funded Insight Centre and Horizon Europe initiatives like GLACIATION and SEISMEC. His publications span topics from wireless sensor network optimization and cognitive radio to constraint-based decision support and AI in emergency management. He has led and contributed to over 15 recent publications in top-tier journals and conferences, showing a strong trend in AI-driven solutions for networked and intelligent systems. IEEE SECON 2015 Best Demonstration 2014 TAOS Best Paper Award in Access Networks and Systems Best paper, SMARTGREENS 2013 Enterprise Ireland Lifescience and Food Commercialisation Award Best Application Paper, AI2008 Best Application Paper, AI2006 Best paper nomination, ECAI 2004 Best Paper, Intl Conf AI in Design Professor Brown has supervised numerous PhD and MSc students in areas including constraint programming, sensor networks, evacuation modeling, and smart buildings. He has secured significant research funding from SFI, Enterprise Ireland, and IRCSET. He is actively involved in research leadership, serving as Deputy Director of Insight@UCC and PI in multiple national and international projects. He is a member of research groups involved in GLACIATION (green, responsible data operations), SEISMEC (human-centric industry), and SMARTeBuses . His lab supports a team of doctoral students and research staff working on AI, networking, and data analytics for real-world applications.