جست‌وجوی استاد و پژوهشگر

Andrew Martin Pownukمشاهده پروفایل

دانشیار

• Modeling of Uncertainty
• Unsupervised Learning
• Autonomous Computational Methods
• +۵ مورد دیگر

Dr. Andrew Martin Pownuk is an Associate Professor at the Department of Mathematical Sciences, The University of Texas at El Paso. His work bridges computational science, uncertainty modeling, and fuzzy logic, with a focus on engineering applications. He holds dual PhDs in Computational Science (2017) and Computational Methods in Engineering (2001), and has taught at UTEP since 2006. Ph.D. Computational Science, The University of Texas at El Paso (2017) Ph.D. Computational Methods in Engineering, Silesian University of Technology, Poland (2001) M.S. Mathematics and Computational Science, The University of Texas at El Paso His research centers on combining interval and probabilistic uncertainty for engineering problems, unsupervised learning, and computational mechanics. Recent work explores quantum computing's potential for uncertainty propagation and HyFlex teaching methodologies. Dr. Pownuk has received multiple accolades, including the 2018 NAFIPS Best Thesis Award and multiple Academic and Research Excellence awards. He contributed to projects with Chevron Corporation, Army Research Laboratory, and international collaborations like the COCONUT Project. 2018 NAFIPS Best Thesis Award 2017/2014 UTEP Academic and Research Excellence 2000 Silesian University Scientific Achievement Award

• Hydrology
• Water Management
• Climate Change Impacts
• +۳ مورد دیگر

Thomas Pulka is a researcher at the Institute of Hydrology and Water Management within the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU). His work focuses on high-alpine hydrological processes, particularly precipitation correction modeling, snow dynamics, and climate change impacts on water cycles. Education: Master of Science in Environment and Bioresources Management (2018–2021), Technical Management with Environmental Engineering specialization (2012–2015), Bachelor in High Tech Manufacturing with Social Systems management (2011–2012) His research emphasizes improving runoff forecasts for hydropower generation through snow cover modeling and addressing water level fluctuations in Kenyan Rift Valley lakes. Current projects include spatiotemporal precipitation analysis and glacier melt contributions to runoff. Key collaborations include work with VERBUND Trading GmbH and the European Geosciences Union (EGU). His publications highlight applications of conceptual hydrological models and snow depth pattern analysis in high-alpine catchments. Location: Muthgasse 18, 1190 Wien Email: thomas.pulka@boku.ac.at ORCID: 0000-0003-1916-3603

• Quantum Networks
• Quantum Machine Learning
• Quantum Synchronization
• +۳ مورد دیگر

Roberta Zambrini is a Research Professor at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), a joint institute of the Spanish National Research Council (CSIC) and the University of the Balearic Islands (UIB). She obtained her PhD in Physics from UIB in 2003, following a degree from the University of Milan. Her research focuses on quantum complex systems , including quantum networks, quantum synchronization, open quantum systems, and quantum machine learning. She teaches master's courses in Physics of Complex Systems and advises multiple PhD and Master's students. Her research spans quantum computing, quantum optics, and machine learning, with recent work emphasizing quantum reservoir computing , dissipative quantum systems, and quantum neural networks. Publications show a consistent focus on leveraging quantum phenomena for computational advantages and exploring non-equilibrium dynamics in quantum systems. Awards and Honors: Ramon y Cajal Fellowship Maria de Maeztu Unit of Excellence Award (2018–2022) Grants and Projects: She leads multiple projects, including QuaResC (quantum machine learning), QuProCS (quantum probes for complex systems), and initiatives funded by AEI, MINECO, and the EU. She also coordinates gender equity activities at IFISC. Editorial and Service: Serves as Divisional Associate Editor for Physical Review Letters and on boards for Proceedings A and Journal of Physics Communications . She is also a 'Gestora' at the Spanish Research Agency (AEI).

• Seismicity analysis
• Stress field
• Crustal structure
• +۶ مورد دیگر

Raffaella De Matteis is an Associate Professor in the Department of Science and Technology at the University of Sannio, Italy, specializing in Solid Earth Geophysics (GEO/10). Her research focuses on seismic tomography, crustal structure analysis, and earthquake source characterization, with particular emphasis on volcanic and geothermal regions in Italy. Her research interests span seismicity analysis, stress field determination, crustal structure using tomographic techniques, seismic wave propagation in heterogeneous media, seismic source parameters analysis, and ground motion predictive equations for early-warning applications. Dr. De Matteis has extensively studied Italian volcanic systems including Mt. Vesuvius, Ischia island, and Campi Flegrei caldera, as well as geothermal fields like Larderello in Tuscany and Nesjavellir in Iceland. Her publication record reveals strong expertise in 3D seismic tomography, with methodological contributions to velocity model development, earthquake relocation techniques, and ground-shaking mapping. Her work often addresses the practical applications of seismic research for hazard assessment and early warning systems, with a particular focus on how advanced tomographic methods improve our understanding of seismic hazards in complex geological settings. Dr. De Matteis has collaborated extensively with researchers across Italy and internationally, particularly on projects involving seismic monitoring of volcanic and geothermal areas. Her recent work has increasingly focused on the relationship between pore fluid pressure and earthquake triggering mechanisms, reflecting a growing interest in the connections between geothermal systems and seismic activity.

CARINA DA CONCEIÇÃO MENDES DE ALMEIDAمشاهده پروفایل

عضو هیئت علمی

• Water Management
• Climate Change
• River Basin Management
• +۶ مورد دیگر

Carina da Conceição Mendes de Almeida is an Assistant Professor at the Faculty of Engineering of Universidade Lusófona (ULHT) and holds a Visiting Assistant Professor position at ISA, University of Lisbon. Her career spans over a decade as a numerical modeling researcher at IST (University of Lisbon) and participation in multinational projects across Europe, Africa, Asia, and South America. PhD in Environmental Engineering (IST, University of Lisbon, 2019) MSc in Environmental Engineering - Water Management (ISA, University of Lisbon, 2008) Her research focuses on climate change adaptation , integrated water resource modeling , and resilient reservoir design , contributing to UN Sustainable Development Goals. Recent work explores Mediterranean reservoir dynamics, Bayesian ecological modeling, and decision-support tools for water quality management. Active in international collaborations, she has worked with institutions in Mozambique, Swaziland, India, Pakistan, Brazil, and São Tomé e Príncipe. Her 2024 article introduces a resilience-enhanced algorithm for reservoir design. Member, IWA River Basin Management Specialist Group Member, APRH Specialized Commission for Water Quality Ambassador, European Climate Pact

Paul M.J. Van den Hofمشاهده پروفایل

استاد

• Data-driven modeling
• Control systems
• Dynamic networks
• +۶ مورد دیگر

Paul M.J. Van den Hof is a Full Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e), specializing in data-driven modeling and control of dynamic systems. He leads the Control Systems Group and is affiliated with multiple research centers, including EAISI High Tech Systems, Mobility, and Foundational, as well as the EIRES Research initiative. Research Interests: His work focuses on developing fundamental techniques for dynamic network modeling, closed-loop identification, data analytics, experimental design, and model-based control. Applications span industrial process control, oil reservoir engineering, high-tech mechatronic systems, and cyber-physical systems. Recent projects include SYSDYNET (dynamic network identification), NAPAS (nanometer-accurate actuation), and CADUSY (data-driven modeling using symbolic methods). Scientific Contributions: Van den Hof has authored over 250 research outputs, including foundational work on identifiability in dynamic networks, frequency domain identification, and distributed control algorithms. His 2024-2025 publications address challenges in fault detection, Bayesian network topology identification, and multi-step least squares methods. He emphasizes practical implementation through tools like the SYSDYNET MATLAB toolbox. ERC Advanced Research Grant (2015) Honorary Member, Hungarian Academy of Sciences (2016) IEEE Fellow (2007) and IEEE Life Fellow (2023) IFAC Advisor (2020)

• Machine Learning
• Process-Based Modeling
• Environmental Science
• +۲ مورد دیگر

Yucong Hu is a Doctoral Researcher at the Max Planck Institute for Biogeochemistry in the Biogeochemical Integration Department . Affiliated with the IMPRS-gBGC graduate school , his work focuses on integrating process-based models with machine learning to address challenges in environmental data analysis. Current projects include upscaling scarce datasets, modeling unmeasurable natural processes, and optimizing hydrological simulations through advanced neural network architectures. Education 2020-2024: MS in Ecology, University of Chinese Academy of Sciences 2018-2020: BEng in Computer Science and Technology, China Agricultural University 2016-2020: BEng in Agricultural Biological Environmental and Energy Engineering, China Agricultural University His research leverages LSTM networks for streamflow and water quality prediction, as well as storm event-based pollutant delivery process analysis. Despite limited publication visibility, his work contributes to environmental data science and hydrological modeling.

Guodong Wangمشاهده پروفایل

پژوهشگر

• Machine Learning
• Industrial Data Processing
• Cyber-Physical Systems
• +۵ مورد دیگر

Dr. Guodong Wang is a researcher affiliated with the Forschungsbereich Cyber-Physical Systems at TU Wien. His work focuses on machine learning applications in industrial data processing, fault diagnosis, and health monitoring systems. He has collaborated extensively with Prof. Radu Grosu and other researchers on projects involving neural networks, Bayesian methods, and sensor data analysis. Education: PhD in Technical Sciences (Dr.techn.) MSc in Engineering His research interests bridge theoretical machine learning with practical industrial challenges, including: Development of generative neural network models for quality prediction in manufacturing Fault prognostics for semiconductor and marine machinery systems Integration of Bayesian networks and evidential reasoning for multi-sensor data fusion Key contributions include: Proposing the ZIZO algorithm for Echo-State Networks optimization Advancing wear condition prediction in milling tools Creating machine learning frameworks for cyber-physical systems diagnostics His work often addresses real-world applications in manufacturing, marine engineering, and medical diagnostics.

Alex K. Shalekمشاهده پروفایل

استاد

• Immunology
• Genomics
• Infectious Disease
• +۵ مورد دیگر

Alex K. Shalek is the J. W. Kieckhefer Professor in the Institute for Medical Engineering and Science and Department of Chemistry at MIT. He serves as Director of the Health Innovation Hub at MIT, Director of the Institute for Medical Engineering and Science, and holds extramural roles at The Koch Institute, Ragon Institute, and Broad Institute. His research focuses on developing and applying cutting-edge technologies to understand cellular and molecular mechanisms underlying human health and disease, particularly in immune responses, infection, cancer, and inflammation. The Shalek Lab creates tools like Seq-Well and CellLENS for single-cell and spatial omics analysis, enabling high-resolution studies of complex biological systems. Research interests include host-pathogen interactions, tumor microenvironment dynamics, and inflammatory memory in barrier tissues. Collaborations span global institutions to address challenges in tuberculosis, HIV, and cancer. The lab integrates genomics, chemical biology, and nanotechnology to profile and control multicellular systems, with applications in drug screening and disease modeling. Recent work highlights discoveries in tuberculosis granuloma biology, pancreatic cancer metastasis, and SARS-CoV-2 pathogenesis. The lab's computational frameworks like MESA and CellLENS advance spatial omics to map tissue complexity. Students and lab members (e.g., Aleth Gaillard, Carly Ziegler) contribute to projects in immunology, genomics, and technology development. Awards and grants are not explicitly listed here, but his work is supported by major institutions. Labs and teams include the Shalek Lab, with collaborations across MIT, Harvard, and industry partners.

Sergey Ishutovمشاهده پروفایل

استادیار

• Energy Efficiency
• 3D Printing
• Geoinformatics
• +۱ مورد دیگر

Sergey Ishutov is an Assistant Professor at the Faculty of Science , Concordia University of Edmonton , specializing in the Department of Environmental & Physical Sciences . He serves as Program Coordinator for the Sustainable Earth Resources and Geoscience program. PhD, Geology, Iowa State University of Science & Technology MSc, Geology, California State University BSc, Geology-Petroleum Geology, University of Aberdeen Research Focus: Dr. Ishutov's work bridges 3D printing and geoscience , concentrating on creating accurate rock analogs for experimental studies in petrophysics, rock mechanics, and reservoir engineering. His interests also extend to Energy Efficiency and Geoinformatics , particularly in sedimentary rock microstructure analysis and sustainable resource applications. Publication Trends: His recent publications (2018–2022) focus on 3D printing applications in replicating carbonate reservoir pores, analyzing mechanical behavior of printed rock analogs, and enhancing geoscience education through tactile models. Collaborative works with interdisciplinary teams highlight his expertise in integrating advanced fabrication techniques with traditional geological research. Teaching Contributions: Dr. Ishutov teaches foundational courses in physical earth science, environmental earth science, and environmental policy, emphasizing innovative pedagogical approaches and cross-disciplinary applications. Collaborative Networks: His post-doctoral affiliation with the Reservoir Geomechanics Research Group at the University of Alberta underscores his industry-academic partnerships in petroleum geoscience and computational modeling.

• Carbon Capture
• Molecular Simulation
• Direct Air Capture
• +۵ مورد دیگر

Jiajun He is a Teaching Assistant Professor at the University of Illinois at Urbana-Champaign with dual appointments in the Department of Mechanical Science and Engineering and the Prairie Research Institute. His research focuses on sustainable energy technologies, including carbon capture, molecular simulation of sorbent materials, cost analysis of emission reduction strategies, and thermodynamic modeling of fluid behavior. He maintains active collaborations in materials science and environmental engineering domains. His research interests center on developing scalable solutions for climate challenges, with expertise in: Carbon capture optimization and sequestration economics Molecular-level design of functional materials Thermodynamic system modeling Integration of renewable energy with emission reduction technologies Analysis of his 15 most recent publications reveals three dominant themes: (1) Economic feasibility studies of carbon capture systems across energy/industrial sectors; (2) Advanced material engineering for gas separation and conversion; and (3) Fundamental studies of fluid behavior and surface interactions. His work consistently bridges theoretical modeling with experimental validation.

• Energy Research
• Environmental Science
• Geology
• +۳ مورد دیگر

Ankit Chakraborty is a Postdoctoral Fellow at the Bureau of Economic Geology, University of Texas at Austin. His research focuses on energy-environment intersections, including carbon capture and storage, unconventional resource recovery, and hydrological systems. Fields of Interest: Energy Research, Environmental Science, Geology, Hydrology Research Trends: Recent publications highlight CO₂ storage optimization, induced seismicity from energy operations, Arctic permafrost dynamics, and Permian Basin environmental impacts. His work combines field studies, geospatial analysis, and computational modeling. Contact: ankit.chakraborty@beg.utexas.edu

Lei Gaoمشاهده پروفایل

پژوهشگر

• Complex Systems Modelling
• Sustainability Assessment
• Adaptive Management
• +۶ مورد دیگر

Dr. Lei Gao is a Principal Research Scientist at CSIRO Land and Water with over 20 years of expertise in complex environmental systems research. A nationally and internationally recognized thought leader, he pioneers methods in sustainability modelling and AI-driven environmental predictions while collaborating with institutions like Oxford University, IIASA, and the Chinese Academy of Sciences to address land and water management challenges. His research centers on complex systems modelling, sustainability assessment, adaptive management under uncertainty, and machine learning applications for environmental systems. He specializes in translating these methodologies into practical solutions for water resources, land systems, and socio-economic analysis, with a focus on robust decision-making under climate extremes and global change. Recent publications reveal a dominant trend integrating artificial intelligence with environmental modelling, particularly in water flow prediction, soil carbon sequestration, and climate impact assessment. His work increasingly addresses systemic sustainability challenges through scenario analysis, trade-off assessments, and SDG-focused frameworks, demonstrating strong interdisciplinary convergence. Dr. Gao's scientific accolades include: Cell Press China Paper of the Year Award (Sustainability Category) CSIRO Chairman’s Medal for Science Excellence Julius Career Award for exceptional early to mid-career scientists MVIPIT Best Paper Award Impactful Publication Award Publons Peer Review Award — Top reviewers for CSIRO Multiple Best Paper Awards and Research Excellence recognitions As Project Leader for the CAS-CSIRO Joint Project on agricultural climate adaptation, CSIRO Strategic Project on AI-based water banking, and Australia-China Science Fund on soil carbon sequestration, he demonstrates exceptional grant leadership in securing competitive funding for high-impact environmental research. Based at CSIRO Land and Water, Dr. Gao operates within a dynamic international research ecosystem, leveraging cross-program collaborations and partnerships with global institutions to develop innovative sustainability solutions for complex environmental challenges.

Francesca Aureliمشاهده پروفایل

دانشیار

• Hydraulic Engineering
• Hydrology
• River Hydraulics
• +۷ مورد دیگر

Francesca Aureli is an Associate Professor in the Department of Engineering and Architecture at the University of Parma, specializing in Hydraulic and Maritime Constructions and Hydrology. She has been actively involved in teaching and research since the early 2000s and currently teaches courses such as Hydraulic Plants, River Basin Management, and Laboratory of Hydrology and Hydraulic Constructions for both Civil Engineering and Environmental and Land Management Engineering programs. Her research focuses on hydrology, river hydraulics, flood modeling, and sustainable water infrastructure. She has participated in around thirty research agreements with public and private entities, contributing to studies on flood hazard modeling, detention reservoirs, and hydroelectric applications. She is also a reviewer for over fifteen international journals. The recent publications reflect a strong trend in advanced 2D hydrodynamic modeling of flood events, historical flood reconstruction, and sustainable revitalization of water systems. Her work bridges theoretical analysis with practical engineering solutions, particularly in the context of Italian river basins and urban waterways. She has served on the PhD Committee in Civil Engineering from 2007 to 2013 and in Civil Engineering and Architecture from 2013 to 2021, indicating her long-standing commitment to academic mentoring. While specific grants are not listed, her leadership in numerous research projects suggests significant grant involvement. Francesca Aureli leads and contributes to research teams focused on flood risk assessment, hydraulic modeling, and sustainable infrastructure. Her lab work likely involves high-resolution parallel computing for flood simulation and integrated approaches to water resource management.

• Clean Energy Technologies
• Enhanced Oil Recovery
• Surfactant Chemistry
• +۷ مورد دیگر

Gina Javanbakht is a Research Fellow in Clean Energy Technologies within the Department of Engineering at the School of Computing and Engineering, University of Huddersfield, United Kingdom. Her research focuses on interfacial phenomena in energy and environmental systems, particularly in enhanced oil recovery and subsurface contaminant remediation. She actively contributes to scientific discourse through peer-reviewed publications and editorial work. Research Interests: Her work centers on surfactant and microemulsion applications in porous media, with emphasis on asphaltene behavior, NAPL mobilization, and nanoscale interfacial interactions. These areas align with sustainable energy development and environmental protection goals. The published articles reflect a consistent focus on molecular and micro-scale mechanisms in energy and environmental fluid dynamics, particularly in complex geological media. Her research integrates experimental and computational approaches to understand phase behavior and displacement efficiency. Scientific Contributions: Active editorial role in the journal Energies (2024–present) Research contributing to UN Sustainable Development Goals in clean energy and environmental sustainability Work referenced in patents and widely read on platforms like Mendeley Advising and Grants: While no formal students or grant funding are mentioned in the provided text, her collaborative research with institutions in North America suggests active scientific networking. Her publications involve multi-institutional teams, indicating potential involvement in funded research projects. Labs and Research Teams: Though not explicitly named, her research on micro-scale displacement and interfacial phenomena likely involves advanced laboratory facilities for porous media experiments, microfluidics, and interfacial characterization at the University of Huddersfield.