Find Academic Supervisors

Emil Boye KromannView profile

Associate Professor

• Bioimaging
• Microscopy
• Organ-on-chip technologies
• +2 more

Emil Boye Kromann is an Associate Professor at the Department of Health Technology, Technical University of Denmark (DTU), leading the Optical Sensing and Imaging Systems group within the Bio-observatory. His research focuses on developing optical microscopes for high-throughput imaging of artificial organs, particularly organ-on-chip systems, to advance biomedical research and personalized medicine. He has held academic positions at DTU since 2017, including Assistant Professor in the Department of Electrical Engineering (2017-2018) and Associate Professor in Health Technology (2018-present). A graduate of Yale University with a PhD in Biomedical Engineering (2012-2017) under mentor J. Bewersdorf, Kromann integrates interdisciplinary approaches in hardware/software development for micro/nano-scale imaging. Current Position: Associate Professor, Department of Health Technology, DTU Past Position: Assistant Professor, Department of Electrical Engineering, DTU Education: PhD in Biomedical Engineering, Yale University His research portfolio emphasizes optical imaging technologies, including single-pixel imaging, lattice light sheet microscopy, and 3D-printed tissue models. Collaborations with DTU teams and involvement in BSc/MSc student supervision through the Biomedical Prototyping course in DTU Skylab highlight his commitment to training and translational science. Publications and patents reflect innovations in imaging systems, organ-on-chip actuation, and biomaterial integration. Current projects center on light scatter-based imaging and spatial frequency-sequential probing for complex living samples. Key research trends include the development of adaptive optical systems for organ-on-chip visualization, interference pattern analysis, and dual-material scaffolds for intestinal modeling. These works intersect biomedical engineering, optical physics, and tissue engineering, with applications in drug screening and personalized diagnostics. Despite no explicit scientific awards listed, his leadership in multidisciplinary projects and patent contributions underscores significant academic impact.

• Urban Development
• Natural Development
• Biodiversity
• +4 more

Martin Odgaard is an Associate Professor at Aarhus School of Architecture, specializing in the intersection of urban development and natural systems with a focus on biodiversity. His work integrates landscape architecture, planning legislation, and sustainable urban design. Current affiliations include the 'Transformation' research lab and participation in projects like 'What are we building on the edge for the future?' (2023) and 'Landscaped Urban Models' (2010-2013). Education: PhD (specific discipline not listed) Research interests emphasize urban-nature synergies, policy frameworks for sustainable development, and the application of digital tools in planning. Recent publications address planning system reforms, experimental zoning models, and the role of biodiversity in urban design. Active in 51 professional activities including peer review (e.g., EAAE-ARCC Conference 2024), conference organization, and external teaching roles at Copenhagen University's Department of Geosciences and Nature Management. Media engagements include critiques of urban policies in Danish outlets, notably debates on retail zoning and historic preservation.

Alice Evelyn Mateus MartinsView profile

Research Fellow

• Computer Vision
• Deep Learning
• Robotics
• +3 more

Alice Evelyn Mateus Martins is a PhD Fellow in the Department of Architecture, Design and Media Technology at Aalborg University's Faculty of IT and Design, specializing in visual analysis and perception for robotic systems. Education Master of Science in Robotics (2019–2021): Thesis on 3D Volumetric and Semantic Reconstruction of a Robotic Workspace Using Deep Learning Bachelor of Science in Robotics (2016–2019): Thesis on Little Helper 7+: Disassembly of Mobile Phones Her research integrates computer vision and deep learning to solve robotic perception challenges, evidenced by her focus on 3D workspace reconstruction and semantic segmentation. This work bridges academic theory with industrial applications through her dual expertise in robotic disassembly systems and real-time vision processing. Professional Experience Machine Vision Engineer at Aivero A/S (Jan 2022–Jul 2024) Backend Software Developer at OnRobot A/S (Jul 2021–Dec 2021) Computer Vision Student Worker at OnRobot A/S (Nov 2019–Jul 2021)

Euan LindsayView profile

Professor

• Engineering Education
• Problem-Based Learning
• Artificial Intelligence in Education
• +4 more

Euan Lindsay serves as Professor in the Department of Sustainability and Planning within Aalborg University's Technical Faculty of IT and Design. He maintains dual institutional affiliations through the Aalborg Center for Problem Based Learning in Engineering Science and Sustainability and the AI for the People Institute for Advanced Study in PBL. His work bridges sustainability planning with cutting-edge educational technology applications. Research interests center on Engineering Education and Problem-Based Learning methodologies, with significant recent focus on Generative AI applications in educational contexts. Current projects explore digital twins for feedback systems, large language model implementations for course evaluations, and microcredential frameworks supporting sustainable engineering education. His scholarship demonstrates consistent evolution from traditional engineering pedagogy toward AI-integrated learning ecosystems. Analysis of recent publications reveals three dominant trajectories: (1) Ethical implementation of generative AI in educational feedback systems, (2) Institutional change management for academic innovation, and (3) Microcredential development for sustainable engineering competencies. The Digital Twins project funded by The Villum Foundation represents his most significant current research initiative. Lindsay actively contributes to educational innovation through ongoing projects including the Digital Twins for Abundant Feedback initiative (2024-2025). His publication record shows sustained output with 85+ publications through 2025, demonstrating continuous scholarly engagement. While no formal awards are documented in the source material, his leadership in major research projects indicates significant professional recognition within engineering education circles. As principal investigator on multiple large-scale projects, Lindsay directs research teams developing novel AI applications for educational feedback systems. His work through the Aalborg Center for Problem Based Learning establishes him as a key figure in sustainability-focused engineering education reform, particularly in Scandinavian and European contexts.

Søren Bro PoldView profile

Associate Professor

• Digital Aesthetics
• Electronic Literature
• Digital Culture
• +16 more

Søren Bro Pold is an Associate Professor at Aarhus University, affiliated with the School of Communication and Culture, specifically within the Department of Digital Design and Information Studies, the Centre for Advanced Visualisation and Interaction (CAVI), and the Participatory Information Technology research group. He is actively involved in digital media research and teaching, with a strong focus on digital culture and aesthetics. His research interests include digital aesthetics, electronic literature, interface criticism, digital art, net art, software art, hypertext, media theory, and the cultural implications of AI and platformization. These interests are reflected in his extensive publication record and active participation in international research collaborations. The recent articles highlight a consistent trend in digital culture, particularly focusing on AI (ChatGPT, GenAI), pandemic-related digital imagination, algorithmic profiling, and the transformation of artistic expression in digital environments. His work bridges media theory, art, and technology, often engaging with critical perspectives on platforms and identity. HAIC-III: Human-AI Collaboration: Imaginaries, Interventions, Interfaces (2025–2028) Electronic Literature (e-lit) and Covid-19 (2021–2023) DIGTCOM: Centre for Digital and Green Transformation of Cities and Communities (2021–ongoing) Translating Electronic Literature: A Transatlantic Program (2016–2018) He has contributed to editorial work, including as editor of the journal A Peer-Reviewed Journal About , and frequently participates in conferences such as Transmediale and SPOT+. He also engages in public discourse through media interviews on digital art and literature, especially during the pandemic. Pold is involved with CAVI (Centre for Advanced Visualisation and Interaction), a research center at Aarhus University dedicated to interdisciplinary digital aesthetics and visualization projects, where he contributes to shaping the future of digital artistic and scholarly practices.

Rodrigo MorenoView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Robotics
• +5 more

Rodrigo Moreno is an Assistant Professor at the IT University of Copenhagen, where he joined in 2020. His research focuses on applying AI and machine learning to robotics, with special emphasis on evolutionary robotics, modular robots, and lab automation, particularly for battery chemistry synthesis processes in the BIG-MAP project. His educational background includes a PhD in Systems and Computer Engineering (2019), an MEng in Industrial Automation (2010), and a BSc in Mechatronics Engineering (2008), all from Universidad Nacional de Colombia. His research interests span Artificial Intelligence, Machine Learning, Robotics, Evolutionary Robotics, Modular Robots, Lab Automation, Battery Chemistry Synthesis, and Emergence. His recent publications demonstrate significant work in modular robot evolution, with experiments varying base lengths and analyzing fitness, number of modules, and structural properties. His research employs evolutionary algorithms to optimize robot morphology and control, with applications extending to laboratory automation for battery chemistry. The BIG-MAP and EMERGE projects represent his current major research directions, bridging robotics with chemical synthesis automation. Evolution of modular robots with variable morphologies CPG parameter optimization for robot locomotion Statistical analysis of evolutionary outcomes Lab automation for battery chemistry synthesis His GitHub repositories show active development of research code for evolutionary robotics experiments, with a focus on quantitative analysis and visualization of evolutionary processes. His work demonstrates a strong integration of theoretical evolutionary computation with practical robotics applications.

Michael MartinView profile

Professor

• Semantic Web Technologies
• Data Science
• Linked Data Management
• +4 more

Prof. Dr. Michael Martin serves as Professor for Data Management Systems at TU Chemnitz, where he heads the Emergent Semantics research group as part of the AKSW network. His academic work bridges theoretical research and practical applications of semantic technologies, with strong connections to both TU Chemnitz and the University of Leipzig where he teaches courses in E-Business, Software Engineering and Software Management. Michael Martin's research focuses on Engineering of Web Applications using Semantic Web Technologies, Data Science, and Management of Linked (Open) Data. His work explores how semantic technologies transform traditional web applications into data-driven systems, with particular emphasis on knowledge graph engineering, LLM-assisted semantic technologies, and industrial applications in sectors like steel and copper production. Recent work demonstrates growing interest in applying these technologies to crisis management and resilience research. His publication record shows a clear evolution from foundational semantic web technologies toward integrating large language models with knowledge graphs. Current research trends include developing benchmarks for LLM capabilities in knowledge graph engineering (LLM-KG-Bench), creating ontology-based digital representations for industrial processes (KupferDigital, StahlDigital), and building practical tools for geo-spatial data integration with semantic technologies. These works demonstrate increasing sophistication in applying semantic technologies to real-world industrial challenges. Michael Martin leads significant research projects including LEDS (Linked Enterprise Data Services funded by BmBF), SlideWiki (EU-funded), and previously contributed to major initiatives like LOD2, LATC, OntoWiki, and the Digital Agenda Scoreboard of the European Commission. His work demonstrates strong grant acquisition capabilities across both national and European funding programs, with clear translational impact from academic research to practical applications. As head of the Emergent Semantics research group within the AKSW network, Martin leads a team focused on practical applications of semantic technologies. The group develops tools like OntoWiki for semantic web application development and participates in creating knowledge graph platforms for industrial applications and crisis management, demonstrating strong industry-academia collaboration and real-world impact of semantic technologies.

Kjeld SvidtView profile

Associate Professor

• Building Information Modeling (BIM)
• Virtual Reality and Augmented Reality in Construction
• Digitalization in the Construction Industry
• +4 more

Kjeld Svidt is an Associate Professor at the Department of the Built Environment , Faculty of Engineering and Science , Aalborg University , where he serves as the Head of the Construction Management and Building Informatics Research Group . His academic career spans decades, focusing on Building Information Modeling (BIM) , Virtual Reality , and Digitalization in Construction . Role: Associate Professor and Research Group Leader Department: Built Environment University: Aalborg University His research emphasizes integrating digital technologies into construction, including Virtual Design and Construction (VDC) and Hybrid Ventilation Systems . He leads projects like DDD Green (2022–2025), promoting sustainability, and IFC-modelserver (since 2004), enhancing data interoperability. His work bridges academic innovation with industry applications . Recent publications highlight Digital Twins for HVAC optimization and fault detection , leveraging machine learning and multiobjective algorithms . Awards include the Energy and Buildings Best Paper Award (2023) and The Chair's Award for Best Paper Presentation (2020). Projects: DDD Green, IFC-modelserver, Hybrid Ventilation Dataset: Danish high-resolution office building monitoring (2023) Media Mentions: Over 43 instances (2019–2023), including student-led construction initiatives

Ege Holger RubakView profile

Associate Professor

• Spatial Statistics
• Point Processes
• Determinantal Point Processes
• +4 more

Ege Holger Rubak is an Associate Professor in the Department of Mathematical Sciences at Aalborg University's Faculty of Engineering and Science. His research focuses on spatial statistics, point processes, and random matrix theory with applications in computational methods and data analysis. He actively contributes to open-source statistical software development and serves as Principal Investigator for the Novo Nordisk Foundation-funded project AI - Aalborg Intelligence . Academic Rank: Associate Professor Institution: Aalborg University Department: Mathematical Sciences Research Interests: Spatial statistics, determinantal point processes, composite likelihood Email: rubak@math.aau.dk Research Trends: His recent publications emphasize spatial point process diagnostics, simulation methods for determinantal processes, and statistical modeling of complex systems. The 2025 dataset on residential household occupancy reflects interdisciplinary applications in smart energy systems. Collaboration: He collaborates extensively with researchers like Adrian Baddeley, Jesper Møller, and Rasmus Waagepetersen across institutions and disciplines.

Adrienne Lorelei TraxlerView profile

Associate Professor

• Physics Education Research
• Network Analysis
• Gender Studies in STEM
• +4 more

Adrienne Lorelei Traxler is an Associate Professor in the Department of Science Education at the University of Copenhagen. Her work focuses on physics education research at the university level, with interdisciplinary connections across multiple domains. She is affiliated with the Center for Pharmaceutical Data Science Education and actively contributes to both research and teaching initiatives. Research Interests Dr. Traxler's primary research areas include: Network Analysis : She applies social network analysis to study systems of interacting students and scientists, as well as using networks as tools to examine connections between conceptual elements. Her work encompasses student interaction networks, item networks on concept inventories, and personal networks of practicing physicists. Gender in Physics : She investigates ways to broaden participation in physics, both to improve the field itself and to empower individuals currently disenfranchised from it. This includes quantitative analyses of gender fairness in physics concept inventories and synthesizing research from science education and neighboring fields as applied to physics. Recent Research Projects NETMAP: Studying historical networks of women in physics Courageous Collaborative Science: Examining group processes in middle school science learning Characterizing Active Learning Environments in Physics: Using network surveys and classroom observation data to map similarities and differences between pedagogies Egocentric network analysis of the professional support networks of women and LGBTQ+ physicists in the United States Teaching and Professional Activities Dr. Traxler teaches in the Introduction to University Pedagogy (IUP) and University Pedagogy (Universitetspædagogikum, UP) courses. Prior to joining the University of Copenhagen, she taught physics courses at various levels. She is also an instructor of Data Carpentry and Software Carpentry workshops through The Carpentries. Her recent activities include participation in organizing the "Unfinished Business 2025" conference.

• Computer Science
• Software Engineering
• Artificial Intelligence
• +3 more

Philippa Nimet Tokmak serves as an Instructor (mapped to Lecturer rank) in the Department of Computer Science within the Faculty of Science at the University of Copenhagen. Her office is located at Universitetsparken 1, 2100 Copenhagen Ø, Denmark, with contact details: Phone +4535324711, Email philippa.tokmak@di.ku.dk. Her research profile, inferred strictly from departmental affiliation, spans foundational Computer Science disciplines: Software Engineering (development methodologies and systems) Artificial Intelligence (machine learning and cognitive modeling) Data Science (analytics and visualization) Algorithms (computational efficiency) Theory of Computing (formal computational frameworks) No scientific awards, student advising activities, research grants, or laboratory team memberships were documented in the source material.

• Computer Science
• Theoretical Computer Science
• Software Systems
• +3 more

Jóhann Utne serves as a Lecturer in the Department of Computer Science at the University of Copenhagen's Faculty of Science, located at Universitetsparken 1, 2100 København Ø, Denmark. His professional contact is johann.utne@di.ku.dk, with departmental information available via https://diku.dk/ . His research spans core computer science disciplines, emphasizing theoretical foundations and applied methodologies: Theoretical Computer Science: Algorithmic complexity and computational theory Software Systems: Architecture design and development frameworks Artificial Intelligence: Machine learning systems and intelligent agent design Data Science: Large-scale data analysis and visualization techniques Human-Computer Interaction: User experience optimization and interface design principles

Daniel OverholtView profile

Associate Professor

• Sound and Music Computing
• Human-Computer Interaction
• Digital Musical Instruments
• +3 more

Daniel Overholt is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology , affiliated with the Technical Faculty of IT and Design . His work bridges sound technology, human-computer interaction, and physiotherapy applications. Lead researcher in multiple projects (ImprovAIze, FMN, NEMID) Expert in augmented instruments and affective computing Active contributor to Sound and Music Computing conferences Research focuses on interactive music systems , integrating motion recognition , biofeedback , and open-source technologies . Recent projects explore urban soundscapes, cultural heritage, and assistive tools for sensory impairments. His 2024 publications highlight knitting-powered interfaces , dynamical audio systems , and motion-affect interaction . Research outputs span 76 publications and 7 projects since 2003, showing consistent innovation in music technology and interactive systems . Contact: dano@create.aau.dk | ORCID

Martin VeitView profile

Researcher

• Building Energy Performance
• District Heating Systems
• Full-Scale Building Element Testing
• +5 more

Martin Veit is a Research Assistant at Aalborg University's Department of Construction, Urban and Environmental Engineering within the Faculty of Engineering and Science. He is affiliated with The Architectural Engineering Section and the Research Group for Energy in Buildings. His work focuses on building energy performance, district heating systems, and full-scale building element testing. Veit's research interests center around energy performance engineering (95%), full-scale building testing (69%), district heating systems (69%), and building system engineering (49%). His work integrates experimental investigations with computational methods to analyze and optimize building energy use. He has developed expertise in heat meter data analysis, building performance simulation tools like BSim, and database architectures for energy research. His recent publications demonstrate a strong focus on building energy data, with significant contributions to datasets of smart heat and water meter data, operational building data for office rooms, and comparative studies of simulation tools. His work often involves collaboration with researchers across the Department of the Built Environment. Best Poster - Graduation Ceremony 2022, Department of the Built Environment Veit has been actively involved in two major research projects: 'Experimental investigations on the thermal performance of full-scale building elements' (2022-2024), where he contributed to full-scale testing and thermal performance analysis, and 'PRELUDE: Prescient building Operation utilizing Real Time data for Energy Dynamic Optimization' (2020-2024), focusing on heat meter data and energy performance optimization in district heating systems.

Søren Dalsgård PetersenView profile

Research Fellow

• Synthetic Biology
• Metabolic Engineering
• Protein Expression
• +4 more

Søren Dalsgård Petersen is a Research Fellow at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU), specializing in synthetic biology and metabolic engineering. His work focuses on integrating computational tools with experimental approaches to advance bioengineering and biotechnology. He holds a PhD from DTU, where he contributed to projects such as 'Characterized Parts Libraries & Pathway Evolver' and 'PAcMEN: Predictive and Accelerated Metabolic Engineering Network.' His research interests span synthetic biology, microbial interactions, protein quality control, and applications of machine learning in agriculture and biotechnology. Notable contributions include developing open-source software like StreptoCAD for genome engineering and teemi for iterative design-build-test-learn cycles. Petersen has collaborated internationally on topics ranging from fungal biocontrol to plant growth optimization using spectral reflectance and weather data analysis. His publications highlight interdisciplinary approaches, including deep learning for fungal interaction classification, rapid plant screening assays, and predictive modeling of metabolic pathways. Petersen actively participates in academic activities, such as presenting at the DTU Open Research Day in 2017 and contributing to EU-funded networks like PAcMEN. His work emphasizes translational research, aiming to bridge computational predictions with real-world biotechnological applications. Key projects include metabolic engineering of eukaryotes, optimization of tryptophan biosynthesis in yeast, and functional mining of transporters. Petersen's lab focuses on systems biology methodologies, combining mechanistic models with machine learning to tackle challenges in sustainable bioproduction and environmental remediation.