Find Academic Supervisors

Guido ToselloView profile

Associate Professor

• Injection Moulding
• Additive Manufacturing
• Manufacturing Engineering
• +7 more

Guido Tosello is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark. His research focuses on advanced manufacturing technologies, including injection molding, additive manufacturing, and process optimization. He leads projects addressing sustainability-by-design, digital manufacturing systems, and precision engineering. Tosello has supervised multiple PhD students and contributed to over 395 publications, with recent work emphasizing data-driven modeling, oxide classification in silicon crystal growth, and root cause analysis using AI techniques. His research interests span injection molding, additive manufacturing integration, process chain optimization, and quality control. Key projects include Digital Moulding 4.0 (zero-defect injection molding) and improving silicon crystal growth efficiency through digital tools. Tosello actively collaborates on industry 4.0 frameworks and has pioneered methods for smart polymer acoustofluidic chip manufacturing. Notable contributions include over 40 projects and 395+ publications, with recent articles focusing on sustainability in manufacturing processes, AI-driven defect analysis, and additive manufacturing applications in extrusion tools. His work aligns with UN Sustainable Development Goals, emphasizing environmental and industrial progress. Tosello advises PhD students in areas like digital manufacturing, polymer tooling, and silicon crystal growth. His lab integrates advanced simulation tools and experimental validation to bridge design, production, and sustainability challenges.

Tianbo YuView profile

Researcher

• Microstructure of Metallic Materials
• Materials Characterization
• Metal Alloys
• +3 more

Tianbo Yu is a Senior Researcher in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), specializing in metallic microstructure analysis and industrial material applications. His work integrates advanced characterization techniques with manufacturing process optimization. Education: Bachelor degree from Tsinghua University PhD degree from Risø DTU Research Focus: Dr. Yu's expertise spans experimental microstructure characterization using electron microscopy and synchrotron X-ray techniques, microstructure evolution during deformation/annealing/additive manufacturing, and microstructure-property relationships in industrial alloys. His fingerprint analysis reveals dominant work in aluminum processing (65%), stainless steel (34%), mechanical strength (60%), and transmission electron microscopy (31%). Publication Trends: Recent 2025 publications demonstrate concentrated investigation into additively manufactured stainless steel microstructures, particle-stimulated nucleation in aluminum alloys, and deformation mechanisms in multilayered systems. These works consistently bridge fundamental microstructural phenomena with industrial manufacturing challenges, particularly in electric vehicle components and 3D printing. Supervision & Projects: Actively supervises five PhD candidates across DTU projects including sustainable aluminum busbars for EVs, LPBF stainless steel microstructure, and particle-stimulated nucleation. His collaborative network spans metallurgy, additive manufacturing, and semiconductor printing with international partners.

Søren FæsterView profile

Researcher

• Wind Energy Systems
• Materials Science
• Additive Manufacturing
• +3 more

Søren Fæster is a Senior Researcher at the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His research focuses on materials science, additive manufacturing, and structural analysis with applications in wind energy systems and metallurgy. He has led and participated in major projects such as the 3D imaging center (3DIM) and initiatives addressing offshore wind turbine blade erosion. His work frequently involves advanced techniques like tomography and scanning electron microscopy. Research Interests: Material characterization of wind turbine components Metallurgical processes in cast iron and aluminum alloys Non-destructive testing methodologies Additive manufacturing material optimization Awards: Recipient of the FEMS Lecture Price (2005). Key Projects: MicroLab at DTU Wind Energy (2021–present) 3DIM: 3D Imaging Center (2016–2029) EPE: Estimation and Prevention of Erosion on Off-Shore Wind Turbine Blades (2020–2023) Labs/Teams: Active in the Wind Energy Materials and Components Division, collaborating with interdisciplinary teams on advanced materials research.

Adnan Adil Ebrahim HajomerView profile

Researcher

• Quantum Key Distribution
• Continuous Variable Quantum Systems
• Quantum Cryptography
• +3 more

Adnan Adil Ebrahim Hajomer is an active Researcher in the Department of Physics at the Technical University of Denmark (DTU), specializing in quantum information technology. His work focuses on cutting-edge quantum communication systems with institutional affiliation at Fysikvej 307, 2800 Kgs. Lyngby, Denmark. His research interests center on quantum key distribution , particularly continuous-variable systems and squeezed light applications . Key areas include quantum cryptography implementation over optical fibers, high-speed quantum networking, and measurement-device-independent protocols. His fingerprint analysis reveals dominant contributions to Continuous Variable (100%), Quantum Key Distribution (71%), and Squeezed Light (35%) research domains. Analysis of his 17 publications shows consistent focus on practical quantum communication deployment, with recent work emphasizing integrated photonic receivers, finite-size security, and passive optical network architectures. His 2024-2025 publications demonstrate strong collaboration with Ulrik L. Andersen and Tobias Gehring at DTU. No scientific awards or student advisement information is currently documented in available sources. His research appears centered in quantum optics laboratories with emphasis on experimental quantum communication systems development.

Line Hagner NielsenView profile

Associate Professor

• Drug Delivery
• Pharmaceutical Technology
• Biomedical Engineering
• +3 more

Line Hagner Nielsen is an Associate Professor and Groupleader at the Department of Health Technology , Technical University of Denmark (DTU) , specializing in Drug Delivery and Sensing within Pharmaceutical Technology . Her work spans Oral Drug Delivery , Transdermal Systems , and Mental Health Promotion , aligning with UN Sustainable Development Goals . Research Interests : Development of microcontainers for localized drug release Advancements in pectin-based delivery systems Innovations in 3D-printed medical devices Studying mental health within academic and public health contexts Supervision : Led PhD projects on in situ hydrogels , buccal patches , and microscale biofilm treatment Methodologies : Microfluidic fabrication X-ray imaging for device tracking Biodegradable polymer systems

Lars Keld NielsenView profile

Professor

• Metabolic Modeling
• Systems Biology
• Bioreactor Engineering
• +4 more

Lars Keld Nielsen serves as Scientific Director at the Novo Nordisk Foundation Center for Biosustainability within the College of Engineering at the Technical University of Denmark (DTU). His research integrates quantitative modeling with experimental biology to advance sustainable biomanufacturing solutions. His primary research interests span Metabolic Modeling , Systems Biology , and Bioreactor Engineering , with significant contributions to mammalian cell engineering and microbial biotechnology. Current work focuses on genome editing for metabolic optimization, computational modeling of bioreactor dynamics, and high-throughput metabolomics workflows. Analysis of his recent publications reveals strong emphasis on industrial biotechnology applications, particularly in: Metabolic engineering of mammalian cells for therapeutic protein production One-carbon feedstock utilization in bacterial systems AI-driven bioreactor process optimization Nielsen actively supervises multiple PhD candidates including Muyo Abad, Chen T., and Volkova D. across projects focused on fermentation automation, human glycolysis modeling, and viral vector production. His research directly contributes to UN Sustainable Development Goals through sustainable biomanufacturing innovations. Current projects include: PhD scholarship in Automation and Integration of Quantitative Fermentation Data (2025-2027) Computational kinetic modelling of human glycolysis (2024-2027) Mammalian cell engineering for rAAV production (2024-2026)

Giulia RavenniView profile

Researcher

• Biochar Applications
• Gasification Technology
• Pyrolysis
• +4 more

Giulia Ravenni is a Tenure Track Researcher at the Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU), affiliated with the CHEC Research Centre. Her work focuses on biochar applications, gasification, pyrolysis, and adsorption processes, with contributions to UN Sustainable Development Goals related to clean energy and sustainable agriculture. She leads projects investigating biochar's role in reducing Campylobacter in poultry farming and environmental pollutant mitigation. Her research combines engineering approaches with environmental sustainability, including carbon sequestration and anaerobic digestion optimization. Key projects include supervising PhD students in studies on biochar-pollutant interactions and managing projects like Sorption, Leaching and Persistence of Organic Pollutants Released from Biochar . She contributed to the SafeChicken initiative aiming to enhance poultry meat safety through Campylobacter reduction strategies. Her work has been highlighted in media for its practical implications in food safety and environmental science. Ravenni actively participates in academic activities, including organizing conferences such as ProBioRefine 2021 and presenting at international workshops on biochar characterization and gasification byproducts. Her research bridges chemical engineering, environmental science, and agricultural practices, addressing both technical and societal challenges in sustainability.

Irfan KuvvetliView profile

Professor

• Astrophysics
• Space Science
• Radiation Detection Technology
• +3 more

Professor Irfan Kuvvetli is affiliated with the Department of Space Research and Technology at DTU Space, Technical University of Denmark. His research focuses on radiation detection technology, astrophysical phenomena, and space mission instrumentation. Key projects include leadership roles in initiatives such as the THESEUS satellite mission, eXTP (enhanced X-ray Timing and Polarimetry), and the Athena Wide Field Imager (WFI). His work contributes to UN Sustainable Development Goals related to advancing space science and technology. Research interests span theoretical and applied aspects of gamma-ray and X-ray detectors, with emphasis on CdZnTe and perovskite-based technologies. He has pioneered advancements in detector design for space missions, including Compton cameras and polarimetry systems. Collaborations span international teams in Europe and beyond, addressing transient astrophysical events and early universe studies. Projects: i-RASE (radiation sensor systems), Athena WFI, eXTP, LOFT (X-ray timing missions) Grants/Activities: Principal Investigator for multiple long-term projects; organizer of conferences like ADAM2019 and AHEAD2020 Labs/Teams: Leading detector development at DTU Space; member of expert groups on gamma-ray astronomy

Fuad MehraliyevView profile

Associate Professor

• Tourism
• Big Data
• Sentiment Analysis
• +5 more

Fuad Mehraliyev is an Associate Professor at Roskilde University's Department of Social Sciences and Business, focusing on smart tourism, sentiment analysis, and experience management. He holds affiliations with the Centre for Tourism Research and has served as a Visiting Scholar at Hong Kong Metropolitan University (2019–2021) and the University of Florida (2018). His research integrates big data, deep learning, and interdisciplinary methods to address challenges in hospitality, tourism strategy, and digital marketing. Key areas of expertise include sentiment analysis in tourism reviews, smart tourism frameworks, and the application of text-mining techniques to consumer behavior. He actively contributes to academic discourse through conferences like 'Smart Tourism and Sustainability' (2023) and 'Sustainable Tourist Practice' (2022), emphasizing sustainable transitions and innovation. His 24+ publications span topics such as emotional analytics in hospitality, sustainability reporting, and sharing economy dynamics. Recent work explores hybrid models for emotion recognition and typologies of smart tourism frameworks, reflecting a blend of theoretical and applied research. He has organized events focusing on sustainability and technological integration in tourism, underscoring his commitment to bridging academic insights with practical industry challenges.

Chris SchwiegelshohnView profile

Associate Professor

• Machine Learning
• Algorithm Design
• Data Mining
• +3 more

Chris Schwiegelshohn is an Associate Professor at the Department of Computer Science, Aarhus University, specializing in theoretical computer science and algorithm design. His research focuses on clustering algorithms, coresets, approximation algorithms, and fairness in machine learning. He has contributed significantly to the development of efficient algorithms for large-scale data analysis and privacy-preserving techniques. Key research interests include optimization in k-means clustering, distributed privacy protocols, and fair recommendation systems. His work bridges theoretical foundations with practical applications in data mining and machine learning. Publications span topics such as PAC learning for k-means, dynamic facility location, and fair projections for balanced recommendations. He has explored tradeoffs between computational efficiency and accuracy in big data clustering, as well as low-distortion clustering techniques for ordinal data. No scientific awards or grants are explicitly listed in the provided texts. His advising record remains unspecified.

Ehsan Yousefzadeh-Asl-MiandoabView profile

Research Fellow

• Deep Learning
• Computer Systems
• Computer Architecture
• +6 more

Ehsan Yousefzadeh-Asl-Miandoab is a Postdoctoral Researcher at the IT University of Copenhagen (ITU), Denmark, specializing in computer systems and deep learning hardware optimization. His research targets GPU efficiency challenges in large-scale AI training workloads. He earned his PhD from ITU investigating GPU underutilization in deep learning training through analytical models and system designs. His Master's research focused on microarchitectural GPU energy efficiency, proposing novel on-chip memory architectures to reduce power consumption without performance loss. Yousefzadeh-Asl-Miandoab's core research spans deep learning systems, computer architecture, and sustainable AI. He develops resource-aware approaches for GPU resource management, collocation strategies, and monitoring frameworks to enhance hardware sustainability in AI infrastructure. His 2023-2025 publications reveal a clear trajectory toward optimizing deep learning training efficiency through GPU memory management, collocation analysis, and benchmarking methodologies. These works collectively advance sustainable AI by addressing critical hardware utilization bottlenecks in modern data centers. As Co-Investigator on the RAD (Resource-Aware Data Science) project funded by the Independent Research Fund Denmark (2021-2025), he develops resource-efficient data science frameworks. His collaborative work includes a 2023 visiting researcher position at the University of Basel.

Oliver KrancherView profile

Associate Professor

• Digital Sourcing
• Automation
• Project Management
• +6 more

Oliver Krancher is an Associate Professor in the Digital Business Innovation Section at the IT University of Copenhagen. His research focuses on digital sourcing, automation, and project management, with a strong emphasis on multisourcing governance, agile methodologies, and AI ethics. He holds a PhD from the University of Bern, Switzerland, and has served as an Assistant Professor there. He has held visiting scholar positions at Georgia Institute of Technology, University of Auckland, and Technical University of Dresden. Education: PhD in Information Systems, University of Bern, Switzerland Consulting experience at Accenture, Germany Roles: Associate Editor, Journal of the Association for Information Systems Department Editor, Business & Information Systems Engineering Track Chair, European Conference on Information Systems Research Interests: Krancher’s work explores digital sourcing dynamics, including agential shifts and governance mechanisms in multisourcing projects. He investigates how psychological safety impacts software quality in agile teams and evaluates AI systems in public sectors. His research bridges theoretical frameworks with practical applications in project management and IT governance. Grants & Projects: PI of projects like ‘When AI goes live: Managing AI risks during maintenance’ (Danish Business Authority) ‘Augmenting Manufacturing Control with AI’ (Innovation Fund Denmark) Focus areas include AI risks, enterprise system adoption, and ML project success Awards: AIS SIG Sourcing Early & Mid Career Award (2022) AIS Innovation in Teaching Award (2015) Best Paper Awards at ICIS 2024 and others Labs & Activities: Krancher collaborates internationally, contributing to research networks and advising on AI governance frameworks. His work emphasizes practical outcomes, such as designing tools for enterprise system adoption and evaluating AI risks in maintenance phases.

• Natural Language Processing
• Machine Translation
• Large Language Models
• +3 more

Ratish Surendran Puduppully is an Assistant Professor in the Department of Data Science at the IT University of Copenhagen. His research focuses on natural language processing (NLP), machine translation, and large language models with particular emphasis on multilingual systems and low-resource languages. He has published extensively since 2014, with over 20 peer-reviewed works in top conferences like ACL and NeurIPS. Key research themes include adapter efficiency analysis, Hindi instruction-tuned LLMs (Airavata), zero-shot MT evaluation for Indian languages, and bidirectional state space models (Hydra). His work bridges theoretical advancements in neural architectures with practical applications in multilingual contexts. Collaborations span international teams addressing challenges in computational linguistics and cross-lingual AI systems. Publications emphasize open access and have been cited over 6 times with significant reader engagement (12+).

• Software Engineering
• Software Quality and Metrics
• Technical Debt
• +3 more

Helge Pfeiffer is an Associate Professor in the Department of Software Engineering at the IT University of Copenhagen. His research focuses on software quality, technical debt, DevOps, dependency management, and reverse engineering. He is affiliated with the Danish Institute for IT Program Management and the Research Centre for Government IT. Key research contributions include developing the DaSEA dataset for software ecosystem analysis and investigating energy consumption in Python environments. His work bridges academic and industrial practices, particularly in software education and tool development. Projects: Co-Investigator in FCOIT (2018-2021), Villum Foundation Professorship (2022-2027) Datasets: Creator of DaSEA and other reproducibility packages

• Algorithms
• Complexity
• Sorting
• +7 more

Riko Jacob is an Associate Professor and Head of Section in Theoretical Computer Science at the IT University of Copenhagen. His research focuses on algorithms, complexity, sorting, differential privacy, and combinatorial optimization. He leads projects such as DIREC (Digital Research Centre Denmark) and DISTRUST (Distributed business process execution under partial trust), emphasizing interdisciplinary collaboration. Research Interests: Jacob's work spans algorithm design, competitive analysis, randomized algorithms, and matrix operations. His recent studies address bichromatic sorting, saddlepoint detection, and parallel sorting with comparison errors, contributing to foundational advancements in theoretical computer science. Projects: Jacob is the Principal Investigator (PI) in key initiatives including DIREC (2020–2025), focusing on digital research innovation, and DISTRUST (2020–2025), addressing secure distributed systems. He also contributed to SSS (Scalable Similarity Search) under EU funding. Awards: No scientific awards explicitly listed, though his extensive publication record reflects scholarly impact. Advising & Grants: Supervised 1 student (name unspecified). Secured funding through Innovation Fund Denmark and EU grants, totaling millions in research support. Labs/Teams: Affiliated with the Center for Information Security and Trust and collaborates on global networks in algorithmic research.