Alessandro Lucantonio is an Associate Professor at the Department of Mechanical and Production Engineering in Aarhus University , specializing in computational mechanics and machine learning applications in soft matter systems. His work focuses on predictive modeling of active materials, transient morphing structures, and biomedical device optimization. Research Areas: Soft robotics, machine learning for mechanics, poroelastic materials, and bioinspired design. Contact: a.lucantonio@mpe.au.dk , +45 93 51 77 76 His recent publications highlight interdisciplinary approaches combining symbolic regression, computational modeling, and experimental validation in soft robotics and responsive materials. Key trends include adaptive shape morphing, fluid-structure interactions, and predictive simulations for biomedical applications.
Dirk Helbing is a Full Professor of Computational Social Science at the Department of Humanities, Social and Political Sciences at ETH Zurich, with an affiliation at the Department of Computer Science. He is also a member of the External Faculty at the Complexity Science Hub Vienna. His research integrates computational modeling, data science, and social theory to study complex socio-technical systems, with a focus on digital societies, smart cities, and democratic innovation. ETH Zurich – Department of Humanities, Social and Political Sciences Affiliate, Department of Computer Science, ETH Zurich External Faculty, Complexity Science Hub Vienna Former Affiliate Professor, TU Delft (Technology, Policy and Management) Helbing’s research spans computational social science, complexity science, urban sustainability, and digital democracy. He pioneered work in pedestrian and traffic modeling and expanded into socio-economic systems, agent-based simulation, and systemic risk. His team investigates topics such as digital governance, participatory budgeting, resilience, and ethical smart city design. He emphasizes interdisciplinary integration and real-world policy impact. The recent publications reflect a strong trend toward using AI, agent-based modeling, and data analytics to address urban challenges—particularly in traffic management, air quality monitoring, and participatory governance. His work increasingly focuses on ethical and democratic dimensions of technology, advocating for decentralized, inclusive, and resilient digital societies. Idee Suisse Award Honorary PhD, Delft University of Technology (2014) Helbing has advised numerous PhD and postdoctoral researchers and led major initiatives such as the FuturICT project and the doctoral program on Engineering Social Technologies at TU Delft. His research is supported by significant grants, including an ERC Advanced Investigator Grant. He has co-founded several interdisciplinary centers, including the Risk Center, the Decision Science Laboratory (DeSciL), and the Competence Center for Coping with Crises. He leads the Computational Social Science (COSS) group at ETH Zurich, which combines fundamental research with applied policy innovation. The team uses evolutionary game theory, simulations, and experiments to study collective behavior, cooperation, and societal transformation.
Karam Eliker is an Assistant Professor in the Department of Engineering Technology and Didactics at the Technical University of Denmark. His research focuses on advanced control systems for unmanned aerial vehicles, particularly quadcopters, with emphasis on robust control algorithms that address system uncertainties and input constraints. Primary research areas include: Robust attitude control for quadcopters Energy-efficient UAV design Finite-time adaptive control systems Flight trajectory optimization Recent publications demonstrate expertise in developing advanced control methodologies that address practical challenges in UAV operations, including payload transportation, energy efficiency improvements, and robust performance under uncertainties. Research consistently bridges theoretical control concepts with aerospace engineering applications.
David Bue Pedersen is a Professor at the Technical University of Denmark (DTU) in the Department of Civil and Mechanical Engineering. His research focuses on Additive Manufacturing (AM), Materials Science, and advanced manufacturing processes. He leads projects involving open-source laser-based metal AM systems, polymer extrusion tooling, and hydrophobic surface design. Key contributions include nondestructive material evaluation techniques and 3D-printed medical training models. He has supervised multiple PhD students, including Artemeva, Pellizzon, and Lalwani. Notably, his team won the Symposium Best Papers award at the 2021 Solid Freeform Fabrication Symposium. Research interests span AM technologies like powder bed fusion, vat photopolymerization, and material extrusion. His work addresses challenges in surface topography, interlayer bonding, and material characterization. Collaborations include developing cost-effective surgical training models and optimizing polymer and metal AM processes for industrial applications. Over 200 publications and 30 active/completed projects highlight his interdisciplinary impact across academia and industry. Key Projects: Additive Manufacturing Farm, Big Area AM of Composites, Numerical Modeling of Volumetric AM Awards: Symposium Best Papers (2021) Advising: Supervises 5+ PhD students in AM and materials research Labs/Teams: Active in DTU's Construct and Mek departments, contributing to AM innovation and cross-disciplinary collaborations.
Bjarne Kjær Ersbøll is a Professor in Statistics and Data Analysis at the Department of Applied Mathematics and Computer Science, DTU Compute, Technical University of Denmark (DTU). He has held academic positions since 1983, progressing from Research Assistant (1983-1986) to Full Professor (2010-present). His research focuses on applied statistics, data analysis, and their applications in industrial and medical projects, emphasizing collaborative solutions with industry and institutions. He holds M.Sc. (1983) and Ph.D. (1990) degrees from DTU. Key research interests include image analysis, multivariate statistics, and big data methodologies. He has supervised numerous master’s and Ph.D. theses and organized conferences on image analysis and statistics. Notable projects include studies on environmental contaminants in food, cardiovascular mortality linked to drinking water magnesium, and interventions in childhood dietary habits. His work contributes to UN Sustainable Development Goals related to health, sustainable cities, and responsible consumption. Recent publications highlight trends in public health (e.g., dietary interventions), environmental science (e.g., PFAS in eggs), and machine learning applications (e.g., deep learning for quality assessment). He actively participates in academic activities, including lecturing on applied statistics and supervising interdisciplinary projects.
Irini Angelidaki is a Professor at the Technical University of Denmark (DTU), leading the BioConversions (BioCon) Section within the Department of Chemical and Biochemical Engineering. She specializes in bioconversion of biomass to bioproducts, biofuels, and bioenergy, with a focus on optimizing anaerobic processes and sustainable waste treatment. Her research group, BioCon, actively explores biogas, microbial electrochemistry, algae-based biorefineries, and waste-to-value strategies. Key research areas include anaerobic digestion, bioelectrochemical systems, and sustainable resource recovery. Her work contributes to UN Sustainable Development Goals related to clean energy and responsible consumption. Angelidaki has over 700 scientific publications and holds patents in bioprocess technologies. She serves on editorial boards and national/international committees, including the DTU Microbes Initiative and the AD Specialist Group of IWA. Her projects emphasize synergies between microbial systems and environmental engineering, with applications in waste valorization, bioenergy systems, and circular economy frameworks. Current research includes ammonia recovery, CO₂ capture in biofuel sectors, and microbial community dynamics under stress conditions. Angelidaki supervises PhD students in anaerobic microbiology, biogas enhancement, and microbial interactions. She coordinates large-scale projects funded by EU and national grants, focusing on biorefinery integration, bioaugmentation strategies, and anaerobic process modeling. Her lab develops innovative technologies for sustainable waste management, including electrochemical systems for biogas upgrading and microbial protein production from waste streams. Future directions target enhanced process efficiency, microbial consortia engineering, and scalable biorefinery solutions.
Gürkan Sin is a Professor in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU). He leads research in process systems engineering, focusing on interdisciplinary challenges in chemical, biotechnology, and pharmaceutical industries. His work integrates process modeling, simulation, optimization under uncertainty, and environmental impact analysis. Key affiliations include the KT Consortium and PROSYS (Process and Systems Engineering Centre). Education: PhD from Ghent University (2004), MSc and BSc from Middle East Technical University (METU, Turkey). Prior to DTU, he was an Assistant Professor there from 2008–2010. Research interests span process design for wastewater treatment, biorefineries, and biopharmaceuticals, with emphasis on sustainability and AI-driven solutions. Notable contributions include global sensitivity analysis, Monte Carlo methods, and virtual sensor technologies for large-scale processes. Advises PhD students in areas like machine learning for molecular design, risk assessment in chemical processes, and sustainable energy systems. Projects often involve collaborations with industry partners for practical implementation. His work contributes to UN Sustainable Development Goals, particularly in clean energy and responsible consumption. Labs/Teams: PROSYS Centre and KT Consortium, where interdisciplinary teams tackle complex industrial challenges through advanced modeling and data analytics.
Abhishek Sivaram is a Postdoctoral Researcher in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), affiliated with the KT Consortium PROSYS - Process and Systems Engineering Centre. His research integrates chemical engineering with artificial intelligence to solve complex process challenges. His primary research spans Chemical Engineering, Machine Learning, and Process Control, with specific expertise in photobioreactor systems, microalgae cultivation, and hybrid modeling approaches. He develops frameworks combining first-principles engineering models with data-driven algorithms for applications ranging from bioreactor optimization to protein precipitation processes. Recent publications reveal a strong emphasis on machine learning integration across chemical engineering domains, particularly using hybrid models to enhance prediction accuracy in multiphase systems and bioprocesses. Key application areas include gas-liquid reactors, single-cell cultivation dynamics, and metabolic flux analysis in cell cultures. Sivaram serves as supervisor for the active PhD project 'Biomolecule Production Mapping via Biosynthesis using Quantum Generative Artificial Intelligence' (2024-2027), collaborating with Prof. S. S. Mansouri and other researchers. This project has attracted significant academic interest with 20 Mendeley readers. He operates within DTU's PROSYS research environment, which specializes in advanced process systems engineering and control strategies for sustainable chemical production.
Xavier Flores Alsina is a Senior Researcher in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU). His work focuses on process engineering for sustainable water treatment systems. Education includes a PhD in Chemical and Environmental Engineering from the University of Girona (2008) with research stays at Oxford and DTU. Postdoctoral experience spans Laval University, Lund University, University of Queensland, and University of Cape Town. Research interests include multiobjective decision-making in environmental systems, wastewater treatment modelling, and resource recovery optimization. His work integrates bench-scale experimentation with full-scale process validation. Publications emphasize greenhouse gas mitigation, membrane bioreactor design, and industrial symbiosis. Recent work explores dynamic prediction models for emissions control and power-to-X integration in water facilities. Collaborative projects include international initiatives in South Africa and Australia focusing on resource recovery innovations. He coordinates research on anaerobic digestion optimization and sustainable nutrient management.
Jonatan Bohr Brask is an Associate Professor in the Department of Physics at the Technical University of Denmark (DTU), specializing in Quantum Physics and Information Technology. His research focuses on quantum foundations, quantum thermodynamics, and quantum information science, with particular emphasis on nonlocality, entanglement generation, and randomness certification. He supervises multiple PhD projects exploring quantum computing architectures, error correction, and device-independent protocols. His work includes theoretical studies on autonomous quantum thermal machines, quantum contextuality, and the application of quantum mechanics to practical technologies like quantum key distribution and random number generation. Brask has contributed to advancing methodologies for quantum state discrimination and certification under experimental constraints. Notable collaborations involve developing novel frameworks for quantum repeaters and exploring the interplay between quantum coherence and thermal environments. His research has been published in high-impact journals such as Physical Review Letters and Quantum .
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.
Rasmus John Normand Frandsen is an Associate Professor at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU). He leads research in synthetic biology and microbial metabolism, focusing on fungal genetics and metabolic engineering. His work contributes to the UN Sustainable Development Goals related to sustainable agriculture and innovation. Frandsen is affiliated with the Section for Synthetic Biology and DTU Microbes Initiative. He holds a PhD in Biotechnology and has expertise in microbial engineering, automated laboratory systems, and AI-driven biological analysis. His research integrates robotics, deep learning, and genetic engineering to advance biotechnological applications. Key research areas include fungal secondary metabolite biosynthesis, microbial interaction networks, and high-throughput screening methods. He has developed novel robotic platforms for Streptomyces conjugation and AI-based systems for fungal identification and lab quality control. Recent projects involve metabolic pathway engineering in fungi for biofuel production and automated analysis of plant-microbe interactions. Frandsen supervises multiple PhD projects focusing on microbial systems biology, deep learning in genomics, and actinomycete engineering. His work emphasizes translational research with applications in biotechnology, agriculture, and environmental science.
Teddy Groves is a Tenure Track Researcher at the Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark (DTU), focusing on quantitative modeling of cell metabolism and computational methods. His work bridges systems biology, machine learning, and biotechnology. Research Themes : Quantitative cell metabolism, neurovascular coupling, CRISPR-based apoptosis resistance, and data-driven bioreactor optimization. Supervision : Actively supervises PhD students in projects related to human glycolysis, multiscale modeling, and cyanobacteria enzyme allocation. Key Contributions : Developments in Bayesian regression, high-dimensional pathway visualization, and CRISPR knockouts in CHO cells.
Giovanni Bacci is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. His primary affiliation is within The Technical Faculty of IT and Design, specifically the Distributed, Embedded and Intelligent Systems group, focusing on Artificial Intelligence and Machine Learning. He holds an ORCID identifier (0000-0001-8529-0681) and his contact information includes giovbacci@cs.aau.dk and a personal website. His research interests center on probabilistic systems, formal methods, and stochastic models, with a focus on Markov chains, Markov decision processes, and bisimilarity distances. He has contributed to the development of tools like the BisimDist library and Jajapy, a learning library for stochastic models. Bacci has received notable awards, including the Best Paper Award at QEST 2018 and Teacher of the Year 2022/2023 for the Faculty of IT and Design. His work spans theoretical foundations and practical applications, such as optimizing membrane desalination processes via reinforcement learning (2023-2024 project). Key publications include studies on dissimilarity in linear dynamical systems, parameter estimation in continuous-time Markov chains, and active learning of MDPs using Baum-Welch algorithms. His research often bridges theoretical computer science and real-world engineering challenges.
Lene Tolstrup Sørensen is an Associate Professor at the Department of Electronic Systems, Aalborg University, affiliated with The Technical Faculty of IT and Design. Her research focuses on usable privacy, cybersecurity, and gamified learning platforms, with a strong emphasis on human-computer interaction and GDPR compliance. She leads projects like FGPE++ (Gamified Programming Learning) and contributes to initiatives such as the Danish-Japanese Network on Cybersecurity and the Nordic PROPHET ICT program. Education: Master and Ph.D. in Engineering from the Technical University of Denmark. Research areas include hybrid cloud computing, process mining, and digital transformation across healthcare and education sectors. She has supervised 2 Ph.D. students and actively participates in conferences/workshops on cybersecurity, privacy, and educational technology. Notable collaborations include the I3LUNG project (AI-driven cancer care) and the PISH initiative (STEM education innovation). Her work bridges technical systems with user-centric design, aiming to enhance privacy control and educational engagement through innovative interfaces and gamification strategies. Awards: Although no specific prizes are listed, her extensive publication record (94+ outputs) and international project leadership highlight significant academic contributions. She is actively involved in media discussions on cybersecurity and IT governance, reflecting her role as a thought leader in digital transformation.
