جست‌وجوی استاد و پژوهشگر

Pedram Raminمشاهده پروفایل

پژوهشگر

• Process Systems Engineering
• Wastewater Treatment
• Bioprocess Modeling
• +۱۲ مورد دیگر

Pedram Ramin is a Senior Researcher in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), affiliated with the PROSYS - Process and Systems Engineering Centre. His work contributes to UN Sustainable Development Goals related to clean water and sustainable cities. His research focuses on process systems engineering, particularly in wastewater treatment, bioprocess modeling, and digital twin development. Key areas include fault detection using machine learning, anaerobic digestion, industrial fermentation, and sewer system modeling. He applies data-driven techniques like Random Forest and Long Short-Term Memory networks to address challenges in imbalanced big data from wastewater systems. His recent publications highlight trends in integrating artificial intelligence with process engineering for environmental applications, especially in monitoring and optimizing wastewater and biomanufacturing systems. These works span fault diagnosis, life cycle assessment, and hybrid modeling for industrial-scale processes. Senior Researcher, DTU Chemical and Biochemical Engineering Supervisor, Mathematical modelling for digital twins of fermentation processes (2023–2026) PhD Graduate, DTU (2013–2017) He has contributed to multiple research projects and has presented at international conferences on topics such as wastewater-based epidemiology and biogas reactor optimization. While no formal scientific awards are listed, his work is widely published and cited in the field of process engineering and environmental technology. He supervises PhD students, including M. Lemperle, and collaborates extensively within DTU and with external partners. His lab environment is centered around the PROSYS research group, focusing on advanced modeling and simulation for sustainable industrial processes. Future work appears directed toward enhancing digital twins and improving wastewater monitoring through AI-driven analytics.

Nicolas von Solmsمشاهده پروفایل

استاد

• Thermodynamics
• Phase Equilibrium
• Gas Hydrates
• +۱۳ مورد دیگر

Nicolas von Solms is a Professor in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), where he leads research in thermodynamics, gas hydrates, and CO 2 capture and transport. He is affiliated with the KT Consortium and the Center for Energy Resources Engineering (CERE), contributing significantly to sustainable energy technologies. Department: Chemical and Biochemical Engineering Research Centers: CERE, KT Consortium Email: nvs@kt.dtu.dk ORCID: 0000-0002-5007-8987 His research focuses on thermodynamic modeling, phase equilibrium, and experimental validation in complex systems such as gas hydrates and CO 2 capture processes. Key areas include statistical mechanics, flow assurance, polymer interactions in hydrate inhibition, and subsurface CO 2 sequestration. His work supports UN Sustainable Development Goals related to affordable and clean energy and climate action. Recent publications highlight advancements in CO 2 capture efficiency, hydrate-based energy storage, and molecular-level insights into hydrate formation. His studies combine theoretical modeling with pilot-scale demonstrations and microfluidic experiments, demonstrating a strong trend toward applied thermodynamics for energy transition technologies. He has supervised numerous PhD and master's students, with active projects in carbon capture process optimization, glycol process digitalization, and methane recovery from hydrates. His group offers opportunities for bachelor’s, master’s, and doctoral research. Prof. von Solms leads multiple funded research projects and collaborates extensively across Denmark and internationally. His lab integrates computational modeling, experimental thermodynamics, and process engineering to tackle challenges in energy and environmental systems.

Jens Abildskovمشاهده پروفایل

دانشیار

• Thermodynamic Modeling
• Chemical Process Simulation
• Biocatalysis
• +۳ مورد دیگر

Jens Abildskov is an Associate Professor at the Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU). He is affiliated with the KT Consortium PROSYS - Process and Systems Engineering Centre. His research focuses on thermodynamic properties of fluids, chemical process modeling, and simulation, with applications in biocatalysis, mixed solvents, and separation process optimization. Key areas include CO2 capture, biofuel processing, and energy-efficient separation systems. He collaborates extensively on integrating process modeling with control systems. His work aligns with UN Sustainable Development Goals addressing clean energy and responsible consumption. Recent projects include biogas upgrading technologies and open-source simulation tools like CADET-Julia. He supervises multiple PhD students in areas such as carbon capture, process digitalization, and safety engineering. Abildskov leads the PROSYS Centre, emphasizing process systems engineering. His lab develops models for fluid behavior in non-ideal systems, leveraging statistical mechanical methods and molecular correlation functions. He also explores applications in organic rankine cycles and heat integration for energy savings. Publications emphasize practical solutions for industrial challenges, such as solvent systems for CO2 capture and dynamic feeding strategies in separations. His research bridges theoretical and applied aspects of chemical engineering, with a focus on sustainability and innovation.

• Construction Engineering
• Structural Health Monitoring
• Concrete Structures
• +۵ مورد دیگر

Muhammad Usman Hanif is an Assistant Professor at the Department of Technology and Innovation within the Faculty of Engineering at the University of Southern Denmark (SDU). His research focuses on structural health monitoring , concrete durability , and damage assessment in civil engineering systems. Research Highlights Advanced signal processing for bridge damage detection Acoustic Emission techniques in CFRP-concrete debonding Machine learning applications in concrete durability prediction Augmented Reality integration with bridge monitoring systems Recent Publications (2023-2025) 2025: Machine learning in concrete durability 2024: Novel ΔT mapping for debonding detection 2023: FBG sensors in CFRP retrofitted beams 2022: MEMS accelerometers for damage assessment Teaching Activities Finite Element Method (2025) Non-linear Finite Element Method (2025) Advanced Finite Element Analysis (2024)

Fan Zhouمشاهده پروفایل

پژوهشگر

• Fuel Cell Technology
• Hydrogen and Electro-fuels
• Thermal Engineering
• +۳ مورد دیگر

Fan Zhou is a Researcher at Aalborg University's Department of Thermal Engineering within the Faculty of Engineering and Science, specializing in hydrogen and electro-fuels. His work focuses on high-temperature proton exchange membrane (HT-PEM) fuel cells and solid oxide electrolysis systems, with applications in power-to-X and micro combined heat and power (micro-CHP) solutions. He holds a PhD awarded in February 2016 and maintains an active research profile with 27 documented publications. His research interests center on Fuel Cell Technology , Hydrogen and Electro-fuels , and Thermal Engineering , with specific expertise in performance degradation mechanisms, fault diagnosis using electrochemical impedance spectroscopy (EIS) and machine learning, thermal management, and dynamic operation of energy conversion systems. Current investigations address real-time monitoring challenges in residential microgrids and power-to-X applications, examining how operational parameters like temperature, pressure, and gas composition affect system efficiency and durability. Analysis of his 15 most recent publications (2021-2025) reveals a strong emphasis on data-driven approaches for fault detection in fuel cells, dynamic operation effects on electrolysis cells, and integration of clean energy systems. Key trends include the application of convolutional neural networks for online diagnostics, investigation of AC/DC frequency effects in solid oxide electrolysis, and development of control systems for micro-CHP applications using HT-PEM fuel cells. Dr. Zhou currently participates in two major research projects: Robust And Dynamic Electrolysis for Power-to-X (2024-2027), focusing on advanced electrolysis technologies for power-to-X applications, and FC-COGEN (2023-2025), developing micro combined heat and power systems. Both projects are funded by the Energy Technology Development and Demonstration Program (EUDP) and involve collaboration with industry partners and researchers including Søren H. Jensen and Simon L. Sahlin from AAU's Power Electronics and Drives group.

Sonia Corianiمشاهده پروفایل

استاد

• Quantum Chemistry
• Computational Spectroscopy
• Molecular Properties
• +۷ مورد دیگر

Sonia Coriani is a Professor in Physical Chemistry at DTU Chemistry, Technical University of Denmark, since 2017. She leads a research group focused on theoretical chemistry and computational spectroscopy. Her academic journey includes a PhD from Aarhus University (2000), a permanent research scientist position at the University of Trieste (1999-2014), and associate professorship there since 2014. She held an adjunct associate professor position at the Centre for Theoretical and Computational Chemistry in Oslo (2007-2011) and was a Marie Curie IEF fellow (2010-2012) and AIAS-COFUND senior fellow (2015-2016). Education: Chemistry, University of Modena (1993) PhD in Theoretical Chemistry, Aarhus University (2000) Her research centers on developing quantum-chemical methodologies for static and dynamic molecular properties, particularly for systems with high dimensionality, complex environments, or novel spectroscopic phenomena. Key areas include non-linear optical experiments, magnetic circular dichroism, X-ray spectroscopies, and quantum computing applications in chemistry. Her recent publications highlight advancements in quantum linear response theory, polarizable embedding environments, X-ray absorption in water, and quantum algorithms for molecular properties. Collaborative work spans interdisciplinary projects with experimentalists, covering gas-phase molecules to biomolecular systems. Scientific Awards: Marie Curie IEF fellowship AIAS-COFUND senior fellowship Her work addresses challenges in ultrafast dynamics, photoionization, and the intersection of chemistry with physics and computational science, emphasizing accuracy and novel experimental guidance.

Haoshui Yuمشاهده پروفایل

دانشیار

• Energy Engineering
• Chemical Process Systems Engineering
• Decarbonization
• +۷ مورد دیگر

Haoshui Yu is an Associate Professor in the Department of Chemistry and Bioscience at Aalborg University’s Faculty of Engineering and Science in Esbjerg, Denmark. His research focuses on sustainable energy systems, decarbonization, and process systems engineering with a strong emphasis on energy storage, waste heat recovery, and renewable integration. He holds a visiting researcher experience at KU Leuven (June–August 2019) and has led significant projects like the 2022 initiatives on zero-emission energy systems and methane production using offshore infrastructure. His work bridges chemical engineering with environmental sustainability, addressing challenges in energy efficiency, carbon capture, and system optimization. Key research interests include Organic Rankine Cycles, compressed air energy storage (CAES), LNG cold energy utilization, and AI-driven process modeling. Over 68 publications since 2014 highlight contributions to energy systems, with recent work emphasizing machine learning applications in reactor design and system integration. Yu received the 2019 Excellent Researcher Award and has been actively involved in interdisciplinary collaborations, including visits to SLB (Schlumberger) in 2025. His lab’s projects often involve multi-objective optimizations and sustainability assessments, aiming to transition energy systems toward net-zero emissions.

Hans Martin Kjerمشاهده پروفایل

دانشیار

• Ultrasound Imaging
• Super-Resolution Imaging
• Biomedical Image Analysis
• +۷ مورد دیگر

Hans Martin Kjer is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), where he is affiliated with the UltraSound and Biomechanics group within the Visual Computing Center and the Center for Fast Ultrasound Imaging. His research bridges engineering and medical imaging, with a strong emphasis on developing and validating advanced ultrasound techniques for biomedical applications. Research Interests: His work focuses on super-resolution ultrasound imaging, microvascular analysis, 3D reconstruction of biological structures, and image registration. He applies computational methods to improve the resolution and accuracy of ultrasound, particularly in renal and lymph node vasculature imaging. His research contributes to the UN Sustainable Development Goals in health and well-being through innovative diagnostic tools. Publication Trends: Over the past several years, Kjer has consistently published in high-impact journals and conferences in biomedical engineering and imaging. His recent work emphasizes the validation of super-resolution ultrasound against micro-CT, realistic 3D blood flow simulation, and the application of AI in enhancing imaging resolution. These studies reflect a strong trend toward quantitative, reproducible, and clinically relevant imaging solutions. Scientific Contributions: While no specific awards are listed, his leadership in major research projects and frequent collaborations with leading experts in ultrasound (e.g., Jørgen Arendt Jensen) underscore his significant role in the field. Advising and Funding: Kjer serves as a supervisor and principal investigator in several funded research initiatives, including AI for Extreme Super-Resolution CT , 3DIM: 3D Imaging Center , and QIM: Center for Quantification of Imaging Data from Max IV . He mentors PhD students and collaborates across disciplines, contributing to both biomedical and materials science imaging projects. Laboratories and Teams: He is an integral member of the Center for Fast Ultrasound Imaging and the Visual Computing Center at DTU. These teams focus on cutting-edge ultrasound technologies, image processing algorithms, and multimodal imaging integration, positioning Kjer at the forefront of computational biomedical imaging in Denmark.

Patrick Billerمشاهده پروفایل

دانشیار

• Hydrothermal Liquefaction
• Waste Valorization
• Chemical Recycling of Plastics
• +۱۲ مورد دیگر

Patrick Biller is an Associate Professor in the Department of Biological and Chemical Engineering at Aarhus University, under the AU Engineering faculty. His research is centered on advanced thermochemical processes for sustainable resource recovery from waste streams, particularly through hydrothermal liquefaction (HTL). His research interests include: Hydrothermal liquefaction of biomass and waste Chemical and energy recovery from sewage sludge, plastics, and textiles Pollutant degradation, especially PFAS Process modeling and simulation using Aspen Plus Integration of HTL with anaerobic digestion and wet air oxidation Development of catalytic systems for enhanced conversion His recent publications demonstrate a strong focus on the technical and environmental challenges of converting complex waste feedstocks into valuable products while minimizing hazardous byproducts. The work spans experimental studies, process modeling, and reviews, published in leading journals such as Water Research , Chemical Engineering Journal , and Renewable and Sustainable Energy Reviews . Scientific contributions and projects: Principal investigator or key contributor to major projects including REBOOT, ACTPAC, PAVITR, BioBase, and Thermochemical Processing using Willow systems Focus on circular economy solutions for plastic and organic waste Active in developing sustainable technologies for water and wastewater treatment He advises and collaborates with researchers and students in the fields of chemical engineering and environmental technology. His work is supported by national and international grants, reflecting strong engagement in both fundamental and applied research. He is based in Aarhus N, Denmark, and can be contacted at pbiller@bce.au.dk .

Hamidreza M. Nickمشاهده پروفایل

پژوهشگر

• CO2 Storage
• Subsurface Engineering
• Geothermal Energy
• +۱۲ مورد دیگر

Hamidreza M. Nick is a Senior Researcher in GeoEnergy Engineering at the Technical University of Denmark (DTU), affiliated with the Danish Offshore Technology Centre and the Laboratory for Off-Shore Production Sciences. He is actively engaged in cutting-edge research on subsurface energy systems, including CO₂ storage, geothermal energy, hydrogen storage, and coupled thermo-hydro-mechanical-chemical (THMC) processes in porous and fractured geological formations. His research interests span a broad range of topics in subsurface engineering, including fluid flow in porous and fractured media, reactive transport, geomechanics of chalk reservoirs, numerical modeling using finite element methods, microbial processes in underground reservoirs, and the application of machine learning to reservoir simulation. His work contributes significantly to global efforts in climate change mitigation and sustainable energy solutions, aligning with several UN Sustainable Development Goals. The trends in his recent publications (2021–2025) reflect a strong focus on CO₂ sequestration in depleted reservoirs, particularly chalk fields, with emphasis on mechanical integrity, chemical interactions, and coupled simulations. He also explores emerging areas such as in situ hydrogen generation, microbial impacts on storage integrity, and deep learning applications for sparse data environments in reservoir modeling. Hamidreza M. Nick actively supervises multiple PhD students and leads research on key projects related to subsurface fluid dynamics, clogging phenomena, and reservoir simulation. His collaborative network includes researchers across Europe and beyond, and he regularly presents at major international conferences such as EAGE. Scientific Contributions and Supervision: Supervises PhD projects on bio-chemical clogging, subsurface fluid leaks, coupled flow, and formation damage. Active contributor to 297 publications and 23 research projects. Develops advanced numerical models for CO₂ and hydrogen storage, integrating physical, chemical, and biological processes. Engaged in field-scale modeling and validation using real-world data from North Sea reservoirs. Laboratories and Research Groups: He is a key member of the Laboratory for Off-Shore Production Sciences and the Danish Offshore Technology Centre at DTU, where he conducts experimental and computational research on offshore and subsurface energy systems.

Konstantinos Anastasakisمشاهده پروفایل

دانشیار

• Bioenergy
• Biomass Conversion
• Renewable Energy
• +۵ مورد دیگر

Konstantinos Anastasakis serves as Associate Professor in the Department of Biological and Chemical Engineering at Aarhus University, Denmark. His research focuses on sustainable conversion of biomass and waste streams into energy and value-added products through advanced thermochemical processes. His primary research domains include: Bioenergy Systems : Specializing in hydrothermal liquefaction and pyrolysis for bio-oil/biogas production Wastewater Valorization : Developing integrated systems for sewage sludge conversion in treatment plants Process Optimization : Utilizing Aspen Plus and systems engineering for biorefinery design Sustainable Technology Assessment : Conducting techno-economic analyses of emerging bioenergy pathways Recent publications (2024-2025) reveal a strategic shift toward integrated process design, particularly combining hydrothermal liquefaction with wet oxidation for autothermal biorefineries. His work demonstrates strong emphasis on practical implementation, scalability, and economic viability across chemical engineering, environmental science, and renewable energy disciplines. Dr. Anastasakis has supervised one PhD student and secured significant research funding through: ELHYOs Project (2020-2022): Electrochemical Hydrogenation of biO-crude as Participant Hydrate Promoters Project (2023-2025): CO 2 capture technology development as Co-PI His collaborative approach is evident through conference leadership (e.g., Session 9 on System Integration at May 2024 events) and supervision of three specialized courses in reactor modeling, biogas upgrading, and power-to-X systems.

• Machine Learning
• Quantum Computing
• Computational Biology
• +۲ مورد دیگر

Lasse Bjørn Kristensen is a Research Fellow at the Department of Computer Science, University of Copenhagen, specializing in Machine Learning with a focus on quantum computing applications. Research Interests His work bridges quantum computing, machine learning, and computational biology, with contributions to: Quantum neural networks and spiking neurons Quantum error correction and circuit robustness Quantum chemistry simulations Information flow in parametrized quantum systems Notable Research Trends Kristensen's publications reveal a strong emphasis on quantum-classical hybrid models, entanglement-enhanced devices, and computational methods for chemistry and physics. His recent work explores error-driven learning paradigms and quantum eigensolvers. Contact Email: lakr@di.ku.dk Address: Universitetsparken 1, 2100 Copenhagen Ø

Tejs Veggeمشاهده پروفایل

استاد

• Autonomous materials discovery
• Energy conversion and storage
• Battery materials
• +۴ مورد دیگر

Tejs Vegge is a Professor and Head of the Section for Autonomous Materials Discovery (AMD) at the Department of Energy Conversion and Storage, Technical University of Denmark (DTU). His research focuses on accelerating the discovery of clean energy materials through integrated computational and experimental approaches. Key areas include battery materials, hydrogen/ammonia storage, and electrocatalysts for sustainable fuels. Vegge leads major initiatives like the Pioneer Center CAPeX and the Villum Center V-Sustain, and has received awards such as the August-Wilhelm Scheer Visiting Professorship and the Ellen and Hans Hermers Award. His projects include the CAPeX Center (2023–2036) for P2X materials, the DELIGHT project (2021–2024) on green catalysis, and collaborations like Battery2030+. He supervises multiple PhD students in topics like battery electrolytes, autonomous workflows, and machine learning for materials design. Research Themes: Autonomous materials discovery, AI-driven experiments, sustainable energy systems Key Tools: Density Functional Theory (DFT), high-throughput screening, self-driving labs Recent Trends: Focus on strain engineering for ion conductivity, CO₂ reduction catalysts, and quantum computing applications Publications span over 300 articles, emphasizing interdisciplinary methods like reinforcement learning and Bayesian optimization. Vegge advocates for open-access research infrastructure and has pioneered lab automation frameworks like Finales.

Carina Loureiro da Costa Lira Gargaloمشاهده پروفایل

پژوهشگر

• Chemical Engineering
• Biorefineries
• Engineering Education
• +۴ مورد دیگر

Carina Loureiro da Costa Lira Gargalo is a PhD Researcher (Tenure Track) at the Department of Chemical and Biochemical Engineering at the Technical University of Denmark, affiliated with the PROSYS - Process and Systems Engineering Centre. She maintains an active research profile with 58 publications and involvement in multiple significant projects, including supervision of PhD students in cutting-edge research areas at the intersection of chemical engineering and artificial intelligence. Her research expertise spans several interconnected domains: Application of Artificial Intelligence and Large Language Models in Chemical Engineering Education Development of virtual educational bioprocess plants and simulators Biorefinery systems design and sustainable energy production Process systems engineering approaches to environmental impact assessment Digitalization of pilot plant operations Dr. Gargalo's recent publications (2024-2025) demonstrate a clear research trajectory toward integrating AI technologies into chemical engineering education. Her work focuses on developing educational tools that automate repetitive tasks, create virtual laboratories for bioprocess training, and use AI to enhance the learning of complex fermentation processes. This represents a significant contribution to the digital transformation of engineering education and aligns with UN Sustainable Development Goals related to quality education and sustainable industry. Her key research projects include: Mathematical modelling of fermentation processes (2023-2026) - as Supervisor Digitalisation of Pilot Plant Operations (2021-2025) - as Supervisor Development of a Virtual Educational Bioprocess Plant (2018-2022) - as Supervisor Sustainable design of biorefinery systems for biorenewables (2013-2017) - as PhD Student She actively supervises PhD students including M. Albino, F. Caccavale, and S. Caño de Las Heras, focusing on the integration of AI technologies with chemical engineering principles. Her research contributes significantly to multiple UN Sustainable Development Goals, particularly Quality Education (SDG 4), Industry Innovation (SDG 9), and Climate Action (SDG 13).

Andrea Vandinمشاهده پروفایل

دانشیار

• Formal methods
• Qualitative and quantitative system modeling and analysis
• Domain Specific Languages
• +۷ مورد دیگر

Andrea Vandin serves as an Associate Professor in the Formal Methods for Safe and Secure Systems section at DTU Compute, Department of Applied Mathematics and Computer Science, Technical University of Denmark. Her research integrates theoretical computer science with practical system analysis, focusing on formal verification methodologies for complex systems. Her primary research interests include: Formal methods for system verification Qualitative and quantitative modeling techniques Domain-specific language development Large-scale performance analysis Model reduction algorithms Chemical reaction network analysis Statistical model checking Recent publications demonstrate expertise in constrained lumping of chemical systems, network embedding through equitable partitions, and stochastic conformance checking. Her work bridges computer science, mathematics, and systems biology with applications in sustainable system design. She actively contributes to UN Sustainable Development Goals through formal verification approaches for safe and secure systems. Her research shows strong trends toward applying model reduction techniques to chemical reaction networks and agent-based systems, with increasing focus on statistical verification methods and probabilistic modeling. The integration of MultiVeStA with Mesa for Python agent-based models represents a significant contribution to verification capabilities in simulation environments.