Find Academic Supervisors

Sebastian RisiView profile

Professor

• Neuroevolution
• Evolutionary Robotics
• Self-Organizing AI
• +9 more

Sebastian Risi is a Professor at the IT University of Copenhagen , where he directs the Creative AI Lab and co-directs the Robotics, Evolution and Art Lab (REAL) . His work bridges computational evolution, deep learning, and collective intelligence for applications in robotics, art, and video game design. His research focuses on self-organizing AI systems that grow or assemble through local interactions, inspired by biological development. Key areas include neuroevolution , neural cellular automata , and generative modeling , with applications in adaptive robotics, game content creation, and damage-resilient AI. Recent publications highlight trends in self-assembling neural architectures (NDPs) and 3D functional machine generation (Minecraft experiments). Awards include ERC Consolidator Grant (2022), Best Paper at FDG’21 , and Google Faculty Award (2019). Scientific Awards : ERC Consolidator Grant (GROW-AI), Best Paper FDG’21, Runner-Up IEEE Games’20, GECCO 2017 Competition Winner, Sapere Aude Grant, Amazon/Google Faculty Awards He advises on projects like GROW-AI (EU-funded), AI-TESTER (game testing), and C2SIM (military systems). Media coverage includes Science , Wired , and Popular Science .

• Machine Learning
• Medical Image Analysis
• Deep Learning
• +5 more

Erik Bjørnager Dam is a Professor in the Machine Learning section at the Department of Computer Science, University of Copenhagen (UCPH). His research spans theoretical foundations of machine learning to practical applications in medical data analysis, sustainability, and materials science. His key research interests include: Small-scale and resource-efficient deep learning Medical image analysis and segmentation Sustainable and environmentally conscious AI development Graph neural networks for materials science Resource-constrained AI systems Professor Dam's recent publications demonstrate a strong focus on making AI more accessible and sustainable while maintaining high performance standards. His work on 'Performance Per Resource Unit' metrics addresses critical challenges in deploying AI in resource-limited environments, particularly in healthcare applications. His research bridges theoretical machine learning with practical implementations across multiple domains. His notable professional activities include: Co-founding Cerebriu A/S (since 2018) Co-founding Biomediq A/S (since 2008) Delivering lectures on AI's role in green transition (April 24, 2023) Media contributions on deep learning applications in plant research (September 13, 2018) With 74 documented research outputs, Professor Dam maintains an active research profile with significant contributions in 2023-2025 across medical imaging, sustainable AI, and materials science applications.

Ditte Hededam WelnerView profile

Researcher

• Enzyme Engineering
• Structural Biology
• Biocatalysis
• +4 more

Ditte Hededam Welner is a Senior Researcher & Group Leader at the Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark. Her research focuses on Enzyme Engineering and Structural Biology, particularly the development of enzyme biocatalysts for sustainable industrial production of natural products like aromas, dyes, and pharmaceuticals. She leads efforts to replace petroleum-based chemical synthesis with eco-friendly bio-based processes, emphasizing glycosyltransferase (GT) engineering to enhance substrate specificity, efficiency, and stability. Education: Biochemistry, University of Copenhagen (2000–2011). Research Interests: Glycosylation mechanisms, high-throughput enzyme discovery/evolution, structural biology techniques (X-ray crystallography, NMR), and biocatalysis applications in sustainable chemistry. Her work contributes to UN SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production). Recent publications highlight advancements in alginate degradation mechanisms, sucrose synthase engineering, and glycosyltransferase applications in biocatalytic routes for indigo/indican production. She supervises multiple PhD projects on enzyme optimization, machine learning for enzyme engineering, and sustainable bioprocessing. Professional Activities: Peer review for journals like Nature Catalysis and Metabolic Engineering , conference organization, and editorial contributions. Active in promoting open-access science and sustainable biotechnology. Labs/Teams: Leads the Enzyme Engineering and Structural Biology group at DTU, collaborating with industry and academic partners globally to advance biocatalytic solutions for environmental challenges.

Philip BilleView profile

Professor

• Algorithms
• Data Structures
• String Processing
• +9 more

Philip Bille is a Professor and Head of the Algorithms, Logic and Graphs section at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), College of Engineering. His research centers on the design and analysis of efficient algorithms, particularly for string processing, compressed data, and data structures. His research interests lie at the intersection of theoretical computer science and practical applications. He focuses on algorithms , data structures , string indexing , pattern matching , and compressed computation . His work enables efficient querying and processing of large-scale, repetitive data, with applications in bioinformatics, intrusion detection, and green computing. The recent publications reflect a strong trend in developing space-efficient and fast algorithms for modern computational challenges. Key themes include compressed data structures , sliding window indexing , finite automata compression , and energy-aware matrix operations . These works demonstrate expertise in balancing theoretical rigor with practical performance. Philip Bille actively supervises multiple PhD students and leads several research projects. He contributes to advancing sustainable computing aligned with UN SDGs. His work integrates algorithmic theory with real-world efficiency. Supervises PhD projects on hierarchical compression, adaptive computation, and vector processor algorithms. Involved in research on green computing, compressed formats, and efficient data models. He is affiliated with the Algorithms, Logic and Graphs group at DTU, a hub for theoretical and applied algorithmic research. The team explores fundamental problems in data representation and processing, pushing the boundaries of what is computationally feasible in terms of time and space.

Vito LatoraView profile

Professor

• Complex Systems
• Network Science
• Applied Mathematics
• +13 more

Vito Latora is a Professor of Applied Mathematics and Chair of Complex Systems at the School of Mathematical Sciences, Queen Mary University of London, and also holds the position of Professor of Theoretical Physics at the University of Catania. He leads the Complex Systems and Networks Group, driving cutting-edge research at the intersection of physics, mathematics, and interdisciplinary sciences. His research focuses on complex systems, particularly the structure and dynamics of networks, including multiplex, temporal, and higher-order networks such as simplicial complexes and hypergraphs. He explores applications in social, biological, financial, and cognitive systems, with recent work on creativity, innovation, and success through network analysis. The 15 most recent publications reveal a strong trend in advancing network theory beyond pairwise interactions, with a focus on higher-order structures, memory effects, synchronization, and epidemic spreading. His work combines rigorous mathematical modeling with real-world applications, often published in high-impact journals like Nature Communications , Physical Review Letters , and Science Advances . Dual communities in spatial and biological networks Modeling epidemics with limited detection resources Synchronization via higher-order and directed interactions AI-driven financial risk management Evolutionary games on hypergraphs Interdisciplinary success and funding dynamics Vito Latora has mentored several researchers who appear as co-authors, including Iacopini, Williams, Di Bona, and Lacasa. While specific grants are not listed, his collaborative projects with neuroscientists and anthropologists, along with frequent publications, suggest active funding. He is involved in major scientific events such as NetSci 2023, indicating leadership in the network science community. He leads the Complex Systems and Networks Group at Queen Mary, fostering a collaborative environment for studying complex systems through theoretical, computational, and data-driven approaches.

Morten BirkvedView profile

Professor

• Life Cycle Assessment
• Environmental Impact Assessment
• Circular Economy
• +3 more

Morten Birkved is a Professor at the Department of Green Technology, University of Southern Denmark, and Head of SDU Life Cycle Engineering. He leads the SDU Climate Cluster and actively contributes to research on Life Cycle Assessment (LCA) , Circular Economy , and Environmental Sustainability . His work spans cross-disciplinary collaborations in Denmark and internationally. Education: M.Sc. in Environmental Chemistry, PhD in Sustainable Development His research interests focus on integrating LCA with circular economy principles, analyzing environmental impacts of construction materials, and developing sustainable solutions for agriculture and energy systems. Recent projects include microbial protein production, green fuels in shipping, and biorefineries for organic waste valorization. Recent publications highlight 2025 advancements in: Eco-design strategies for buildings Hybrid wastewater treatment systems Carbon-storing asphalt pavements Comparative LCA of housing typologies These studies emphasize Denmark as a case study region and leverage both parametric and probabilistic modeling approaches. Scientific Awards Recipient of SCC Fast Track Prize (2025) Teaching & Supervision Supervised PhD research on circular agriculture and plastic circularity Lectured on chemical processes and environmental impacts since 2019 Labs & Projects Coordinates EU-funded initiatives like FLAVOURFERM (plant-based fermentation) and AgriLoop (circular agriculture) Develops microbial platforms for waste-to-protein conversion Advances biostimulants for sustainable agriculture

Giulio CiminiView profile

Associate Professor

• Statistical Physics
• Complex Networks
• Economic Networks
• +12 more

Giulio Cimini is Associate Professor of Theoretical Physics in the Department of Physics at the University of Rome Tor Vergata and a Research Associate at the 'Enrico Fermi' Research Center. He is a statistical physicist with a strong interdisciplinary focus on complex networks and their applications in socio-economic systems. His research interests include: Statistical Physics of Complex Networks Reconstruction and Validation of Economic Networks Social Network Interactions and Financial Markets Systemic Risk and Financial Contagion Scientific Success, Fitness, and Complexity Adaptive Social Recommendation Codon Usage Bias and Protein Interaction Networks His recent publications reveal a strong trend in applying statistical physics to real-world networks, particularly in finance and social systems. Key themes include the modeling of systemic risk in supply chains and financial networks, the dynamics of collective action on platforms like Reddit (e.g., the GameStop short squeeze), and the development of network reconstruction methods using maximum entropy and optimal transport frameworks. His work often combines empirical analysis with theoretical modeling. Scientific awards and recognitions include: Associate Editor, Frontiers in Physics – Interdisciplinary Physics Board Member, Network Science Society Member, Council of the Complex Systems Society Steering Committee, CCS/Italy He has advised or collaborated with numerous researchers, particularly in projects related to economic networks and complex systems. His work has been supported by Italian national grants such as PRIN and PNRR. He leads or co-leads research projects including RENet and C2T. His research is conducted within interdisciplinary teams involving physicists, economists, and computer scientists, often in collaboration with institutions like ISC-CNR, IMT Lucca, and the Network Science community.

Mark van LoosdrechtView profile

Professor

• Environmental Biotechnology
• Biofilm Processes
• Wastewater Treatment
• +3 more

Mark van Loosdrecht is a Full Professor of Environmental Biotechnology at Delft University of Technology (The Netherlands). He holds academic ranks including Prof.dr.ir. and is affiliated with the Faculty of Applied Sciences and the Department of Environmental Biotechnology. His research focuses on biofilm processes, nutrient conversion, and wastewater treatment innovations such as the Anammox, Nereda, and BCFS processes. He has pioneered technologies for resource recovery and sustainable water treatment. Dr. van Loosdrecht has published over 700 scientific papers, holds 15 patents, and supervised over 50 PhD students. He is Editor-in-Chief of Water Research , a member of prestigious academies (KNAW, AcTI, NAE), and has received major awards including the Stockholm Water Prize and Lee Kuan Yew Water Prize. His work integrates scientific discovery with practical process development, addressing global environmental challenges. Education: MSc/PhD from Wageningen University. Active roles include leadership in the International Water Association (IWA) and editorial boards. Key achievements include the development of full-scale processes like Nereda aerobic granular sludge technology. He has been knighted in the Order of the Dutch Lion and recognized with the Beijing Great Wall Friendship Award. Research interests emphasize microbial ecology, bioremediation, and sustainable engineering solutions. His contributions span from fundamental microbiology to industrial-scale process implementation, with a focus on circular economy principles in water management.

Federico CasanovaView profile

Associate Professor

• Sustainable food processing
• Extraction of bioactive compounds
• Green technologies in food engineering
• +3 more

Federico Casanova is an Associate Professor at the National Food Institute of the Technical University of Denmark (DTU), specializing in sustainable food processing and biotechnological valorization of food waste. His work focuses on extracting high-value molecules (proteins, chitins, fatty acids) using green technologies like ultrasound, ohmic heating, and pulsed electric fields to enhance functional properties. Education : PhD (2015–2017, Federal University of Vicosa, Brazil), MSc (Agrocampus Ouest, France, 2009–2010; Universitat Jaume I, Spain, 2006–2007), BSc (Università Cattolica, Italy, 2003–2006). Research Trends : Recent publications highlight applications of green technologies to modify protein-polyphenol interactions, characterize gelatin from jellyfish by-products, and optimize plant protein emulsifying properties. Keywords include Food Science, Food Chemistry , and Biotechnology , with subfields spanning bioactive peptides, rheological properties, and sustainable processing . Projects : Casanova contributes to active initiatives like seaweed-derived bioactives (2025–2027) and SUSTAIN-A-BITE (2025–2028), alongside supervising PhD students investigating dairy proteins and insect-based ingredients. He also serves as an editor for International Journal of Biological Macromolecules (2025–2027). External Roles : Junior Project Leader at Nestlé Purina (2017–2018), Engineer at CNRS's Soft Matter Group (2010–2014). Teaching : Delivered guest lectures on food proteins and sustainable food systems at universities globally.

Rasmus PaghView profile

Professor

• Algorithms
• Data Structures
• Big Data
• +7 more

Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications

Kristian MiltersenView profile

Professor

• Capital Structure Modeling
• Real Options Valuation
• Commodity Derivatives
• +3 more

Kristian Miltersen is a Professor at the Department of Finance and Center for Financial Frictions (FRIC) at Copenhagen Business School (CBS). He holds expertise in capital structure optimization, real options valuation, commodity derivatives, and structured financial products. His research bridges theoretical finance with practical applications in corporate finance and asset pricing. After earning his PhD in 1992 on continuous-time interest rate models, Miltersen has expanded into dynamic capital structure modeling and real options. His landmark 1997 Journal of Finance paper on LIBOR Market models critiques the Black-76 formula's limitations for fixed income derivatives. His work spans commodity derivatives, foreign exchange instruments, and R&D investment dynamics, all rooted in theoretical frameworks. Recent research focuses on dynamic debt policies, second mortgages' valuation, tax-driven corporate cash holdings, and state-contingent capital budgeting. He co-authored influential papers on callable debt renegotiations and the interaction between financing and investment decisions under varying industry structures. Teaching includes elite courses on asset pricing, energy markets, and capital structure. As program director for CBS' Advanced Economics and Finance MSc, he shapes advanced academic programs. Outside academia, he serves as an expert witness and consultant for Analysis Group, advising on financial litigation and complex economic issues. His over 40 publications since 1989 reflect deep engagement with financial modeling, spanning interest rate guarantees, commodity price dynamics, and corporate debt optimization. Current research continues exploring financial frictions' impact on corporate policy and market structures.

Shuang Ma AndersenView profile

Professor

• Electrocatalysis
• Proton Exchange Membrane Fuel Cells (PEMFCs)
• Water Splitting
• +5 more

Shuang Ma Andersen is a Full Professor at the Department of Green Technology (IGT) and SDU Chemical Engineering, specializing in electrocatalysis, fuel cell technologies, and sustainable resource recovery. Her research focuses on oxygen evolution reaction (OER) catalysts, membrane electrode assemblies, and innovative synthesis methods for iridium/platinum-based systems.

• Machine learning methods development
• Bioinformatics
• Biological sequence analysis
• +8 more

Ole Winther is a Professor at the Department of Biology, University of Copenhagen, specializing in Computational and RNA Biology. He also holds a joint appointment as Professor at DTU Compute, Technical University of Denmark. His research bridges machine learning, bioinformatics, and natural language processing with applications in biological sequence analysis, transcriptomics, and health informatics. Education: 1998: PhD in Physics, University of Copenhagen 1994: Master of Science in Physics, University of Copenhagen Winther's research focuses on developing advanced machine learning methodologies for biological applications. He has pioneered protein language models for sequence analysis (DeepLoc, SignalP, DeepTMHMM), interpretable deep learning for RNA subcellular localization, and benchmarking frameworks for DNA language models. His work spans latent variable models, variational inference, diffusion models, and novel architectures for deep generative modeling, with increasing emphasis on practical healthcare applications including rare disease diagnosis through findzebra.com and medical question answering with large language models. Scientific Recognition: ELLIS Fellow (2021) Head of ELLIS Copenhagen Unit H-index of 61 (Google Scholar, May 2023) 19,700+ citations (Google Scholar, May 2023) Winther has supervised 25+ PhD students to completion with 7 currently in progress, along with over 100 master's projects. He frequently serves as PhD opponent and committee chairman across European institutions. His research is supported by substantial funding including multiple Novo Nordisk Foundation grants totaling over 60 million DKK for the Center for Basic Machine Learning Research in Life Science and CAZAI projects, plus significant funding from the Danish Independent Research Fund. He leads an active research group developing cutting-edge machine learning approaches for bioinformatics and NLP challenges. Winther co-founded two spin-out companies: findzebra.com (2014, 2018), a search engine for rare diseases, and raffle.ai, an NLP startup for enterprise search. He initiated DTU's popular BSc in AI and Data program and teaches the highly enrolled MSc course in Deep Learning (450+ students) and PhD course in Bayesian Data Analysis.

Fabio PierellaView profile

Associate Professor

• Offshore Wind Energy
• Fluid Dynamics
• Structural Engineering
• +3 more

Fabio Pierella is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Wind and Energy Systems Flows, specializing in Wind Turbine Design Division. His research focuses on offshore wind energy systems, fluid dynamics, and structural engineering. He has contributed to projects like OC6 Phase IV and the DeRisk database, validating numerical models for floating offshore wind structures and extreme wave loads. Key research interests include computational fluid dynamics (CFD), hydrodynamic load modeling, and the design of large-scale floating wind turbines. His work spans numerical simulations, experimental validation, and database development for extreme sea states. Pierella has presented at international conferences on topics like wave-structure interaction and turbine control systems. He received the Best Poster Presentation Award (2024) and contributed to datasets such as the DeRisk Database, which provides critical wave data for offshore wind turbine design. His research emphasizes practical applications, including monopile structural integrity under extreme loads and control strategies for floating platforms. Pierella's activities include conference presentations on ultra-large floating turbines (EMULF2 project) and the impact of wave shape on 15MW turbine loads. His interdisciplinary approach integrates computational models with experimental results to address challenges in offshore renewable energy systems.

Henrik Myhre JensenView profile

Professor

• Mechanics of Materials
• Solid Mechanics
• Mechanical Engineering
• +4 more

Henrik Myhre Jensen is a Professor at the College of Engineering , Aarhus University, specializing in Mechanics of Materials , Solid Mechanics , and Mechanical Engineering . His research focuses on fracture mechanics, composite materials, and computational modeling of structural behaviors. Research Focus Fracture mechanics in composites and layered materials Computational modeling of kink band propagation Surface wear and coating technologies Ultrasound imaging applications in mechanical systems Notable Contributions Henrik has contributed to understanding crack propagation in cantilever beams, developed numerical methods for simulating delamination in composites, and explored buckling instabilities in solids. His recent work connects machine learning (holomorphic neural networks) to traditional fracture mechanics problems. Key Projects MAGFLY (2017-2021): Magnets for Flywheel Energy Storage InnoVacc (2009): Pressure Testing of Vacuum Chambers Simulation of composite structures (2011-2020): Micro-mechanical modeling