Bhaskar Reddy Sudireddy is an Associate Professor in the Department of Energy Conversion and Storage at the Technical University of Denmark (DTU). His research focuses on advanced materials for energy technologies, including solid oxide fuel cells, electrocatalysts, and ceramic processing. He contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG 7) and industry innovation (SDG 9). His work emphasizes the development of high-performance electrodes, metal-supported solid oxide cells, and gas sensors. He leads projects on eco-friendly fabrication methods for energy storage systems and collaborates on piezoelectric materials sintered in humid air. His research group, Applied Ceramics and Processing, explores novel ceramic materials for applications in renewable energy and environmental monitoring. Advises five PhD students working on projects like high-temperature electrolysis cells and antiferroelectric materials. Supervises interdisciplinary research spanning electrochemistry, materials synthesis, and device fabrication. Located at DTU’s campus in Kgs. Lyngby, Denmark, with extensive international collaborations.
Jan Madsen is a Professor at DTU Compute, Technical University of Denmark, and Head of the Embedded Systems Engineering section. His research focuses on system-level modeling and design of embedded computing systems, particularly cyber-physical systems, microfluidic biochips, and synthetic biology applications. Develops design automation tools and methodologies for embedded systems Supervises numerous PhD students and leads major research projects Research Interests Key areas include: Embedded systems-on-a-chip Cyber-Physical Systems (Internet-of-Things) Microfluidic Lab-on-Chip devices Synthetic biology with molecular computing Design, modeling, and optimization of complex systems Scientific Awards DATE Fellow (2019) IEEE CEDA Outstanding Recognition (2019) DTU Scientific Advise Award (2013) Best Paper Awards at MECO (2013) and CASES (2009) Jorck’s Foundation Research Award (1995) Publications His 14+ journal papers and 115+ conference papers demonstrate expertise in: SystemC-based modeling frameworks Energy-aware sensor networks Self-healing eDNA architectures Microfluidic biochip synthesis RTOS modeling and MPSoC exploration
Olga Saukh is an Associate Professor at the Institute of Technical Informatics, Graz University of Technology (TU Graz), and a Faculty member at the Complexity Science Hub Vienna (CSH). She leads the Embedded Learning and Sensing Systems research group, which operates across both institutions, focusing on the design and deployment of efficient AI-based systems on edge and mobile platforms. Her work bridges deep learning and embedded systems, with applications in environmental monitoring, precision agriculture, and digital health. Ph.D. in Computer Science, University of Bonn (2009) Habilitation in Embedded Systems, TU Graz (2020) Postdoctoral Training, ETH Zurich (2010–2016) B.Sc. in Applied Mathematics, Taras Shevchenko National University of Kyiv (2002) M.Sc. in Applied Computer Science, University of Freiburg (2004) Her research centers on efficient machine learning, particularly model optimization, neural network pruning, and contrastive learning for resource-constrained devices. She is deeply engaged in solving real-world challenges in IoT, sensor networks, and cyber-physical systems. Her work emphasizes data privacy, sustainability, and practical deployment of AI at the edge. The 15 most recent publications highlight a strong trend in efficient deep learning, including model compression, pruning, and transfer learning, applied to diverse domains such as environmental sensing (air quality, pollution tracking), digital agriculture (cattle farming), and embedded AI (sensor calibration, on-demand sensing). Her work frequently appears in top-tier venues like NeurIPS, ICLR, and IEEE/ACM IPSN, reflecting her leadership at the intersection of machine learning and embedded systems. Scientific awards include: CONET Ph.D. Academic Award (2010) Multiple Best Paper Awards at IEEE PerCom, ACM/IEEE IPSN, IEEE ICPADS, IEEE SECON, and UrbCom Spotlight and Oral presentations at ICML and CoLLAs workshops Ph.D. scholarship from IPVS, University of Stuttgart (2004–2005) Prizes in Ukrainian national mathematics competitions (1996–1998) Olga Saukh actively serves on program committees of leading international conferences in machine learning and embedded systems. She has advised multiple students and leads a collaborative research group spanning TU Graz and CSH Vienna. Her group develops practical AI systems for real-world deployment, with a focus on sustainability and privacy. She co-organizes the public EfficientML reading group and has secured recognition through numerous grants and awards. Her future work continues to explore the theoretical and practical challenges of deploying efficient, trustworthy AI in mobile and embedded environments. Her research group, Embedded Learning and Sensing Systems, operates jointly between TU Graz and CSH Vienna, fostering interdisciplinary collaboration across institutions. The team develops AI solutions for edge computing, sensor networks, and cyber-physical systems, with a strong emphasis on environmental sustainability and data privacy. Members work on joint challenges using advanced collaboration tools, reflecting the distributed nature of modern academic research.
Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)
Anja Boisen is a Professor and Head of the Drug Delivery and Sensing Section at the Department of Health Technology, Technical University of Denmark (DTU). Her research focuses on advanced drug delivery systems, sensing technologies, and nanotechnology applications in biomedical engineering. She leads a multidisciplinary team developing innovative devices such as microcontainers, microneedles, and lab-on-a-disc platforms for targeted drug delivery and diagnostics. Her work contributes to UN Sustainable Development Goals, particularly in improving health and reducing inequalities. Key research areas include surface-enhanced Raman spectroscopy (SERS), microfabrication for medical devices, and biomaterials for tissue engineering. She has supervised multiple PhD students, including projects on oral drug delivery systems, gastrointestinal retention devices, and energy-harvesting materials for biomedical applications. Boisen’s team has pioneered technologies like self-unfolding foils for oral delivery and smart drug delivery microparticles. Their innovations aim to enhance therapeutic efficacy while minimizing side effects. She has been recognized with the Sensor Division Outstanding Achievement Award (2022) for her contributions to sensor technology. Her lab actively collaborates internationally, advancing applications in cancer therapy, antibiotic monitoring, and gut microbiota research. Current projects explore high-throughput 3D tumor modeling, SERS-based diagnostics, and biodegradable materials for bone fixation.
Jesper Rindom Jensen is an Associate Professor in the Department of Electronic Systems at Aalborg University, Denmark, under the Technical Faculty of IT and Design. He is the Head of the Audio Analysis Lab, a leading research group in audio signal processing, since 2023. His work bridges theoretical signal processing and practical applications in artificial intelligence and audio systems. Full Name: Jesper Rindom Jensen Institution: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Audio Analysis Lab Email: jrj@es.aau.dk Office: Fredrik Bajers Vej 7B, B5-206, 9220 Aalborg Øst, Denmark Education: M.Sc. in Electronic Systems, Aalborg University (cum laude, 2009) Ph.D. in Signal Processing, Aalborg University (2012) Research Interests: Jesper Rindom Jensen's research centers on audio signal processing, with a strong emphasis on artificial intelligence, speech enhancement, noise reduction, beamforming, and multichannel systems. His work applies to diverse domains including robot and drone audition, spatial audio, and active noise control. He develops novel filtering techniques, including variable span linear filters and harmonic beamformers, to improve speech quality and intelligibility in noisy and reverberant environments. Publication Trends: His recent publications (2023–2025) show a strong trend toward integrating deep learning with classical signal processing, particularly in direction-of-arrival estimation, underwater acoustics, and robust multichannel systems. There is a clear focus on real-world applications, including sound zone control, active noise control, and limited-data scenarios using knowledge distillation. His work consistently emphasizes robustness, efficiency, and practical deployment. Scientific Awards and Recognition: AAU Talent for emerging research leaders Recipient of a competitive postdoc grant from the Danish Independent Research Council Advising and Grants: Jesper has supervised multiple PhD and master’s students, including Nørholm, Karimian-Azari, Zhang, and Wang. He has led significant research projects such as 'Sound Processing for Robots and Drones' (2018–2020) and participated in others related to joint audio-visual tracking and speech enhancement. His research has been supported by national funding bodies, reflecting its innovation and impact. Labs and Teams: He is a founding and core member of the Audio Analysis Lab at Aalborg University, which focuses on cutting-edge audio signal processing and AI-driven solutions. The lab fosters interdisciplinary collaboration and has produced numerous publications, datasets, and real-world applications. Jensen’s leadership since 2023 underscores his pivotal role in shaping the lab’s research direction.
Christian Igel is a Professor at the Department of Computer Science, University of Copenhagen, and serves as director of the SCIENCE AI Centre . He is also a co-lead of the Pioneer Centre for Artificial Intelligence in Denmark. His academic journey includes a Doctoral degree from Bielefeld University (2002) and a Habilitation degree from Ruhr-University Bochum (2010). Igel is a Juniorprofessor (2002–2010) and has held editorial roles at journals like KI - Künstliche Intelligenz and Artificial Intelligence Journal . Doctoral degree: Faculty of Technology, Bielefeld University, Germany (2002) Habilitation degree: Department of Electrical Engineering and Information Sciences, Ruhr-University Bochum, Germany (2010) His research spans Machine Learning , focusing on Support Vector Machines , Evolution Strategies , Reinforcement Learning , Deep Neural Networks , and PAC-Bayesian Analysis . He applies these methods to Environmental Monitoring , Medical Diagnostics , and Climate Research . Recent publications highlight work on adversarial machine learning , environmentally sustainable AI , and tree resource mapping using deep learning. His scientific awards include being a ELLIS Fellow . Igel’s software tools like Shark , woody , and Multi-Planar UNet are widely used in research and industry. Notable grants and collaborations involve projects with European Lab for Learning and Intelligent Systems (ELLIS) , SCIENCE AI Centre , and international teams in Denmark , Germany , and France . His lab leadership emphasizes open-source frameworks and reproducible research. Editorial Roles: German Journal on Artificial Intelligence , Evolutionary Computation Journal , Artificial Intelligence Journal Software Projects: Shark , woody , Multi-Planar UNet , U-Time Collaborations: SCIENCE AI Centre , Pioneer Centre for Artificial Intelligence , European Lab for Learning and Intelligent Systems
Qiongxiu Li is a Tenure-Track Assistant Professor in the Cyber Security group at Aalborg University's Copenhagen campus, part of the Technical Faculty of IT and Design. Her research focuses on cybersecurity, distributed optimization, privacy/security, and federated learning. She has authored/co-authored 38 papers in top-tier venues including IEEE Transactions on Information Forensics and Security, ICLR, and EUSIPCO. Education: PhD in Privacy and Security from Aalborg University (2018-2021). Notable achievements include winning the EUSIPCO 2020 3MT Contest and co-delivering a tutorial on privacy-preserving distributed optimization at EUSIPCO 2024. She actively reviews for conferences like NeurIPS, ICLR, and journals such as TPAMI and TIFS. Research Themes: Privacy-preserving distributed algorithms, federated learning security, differential privacy, and adversarial machine learning. Recent Trends: Focus on securing AI systems (e.g., LLM vulnerabilities, federated clustering privacy), quantization for privacy, and theoretical bounds in decentralized learning. Awards: 2020 EUSIPCO 3MT Winner (outstanding finalist in EURASIP's annual doctoral research competition). Grants/Projects: Co-PI of the AI:SECURITY project (2025-2029) addressing AI security threats like phishing and malicious actors. Labs/Teams: Leads the Cyber Security group at Aalborg's Copenhagen campus, focusing on theoretical and applied research in secure distributed systems.
Ankit Kariryaa is a Tenure Track Assistant Professor at the Department of Computer Science and Department of Geosciences and Natural Resource Management , University of Copenhagen. His work bridges Machine Learning and Environmental Informatics , focusing on remote sensing, geospatial analysis, and ecological modeling. University of Copenhagen, Denmark Machine Learning Section, Department of Computer Science Geography, Land, Environment and Society, Department of Geosciences Kariryaa specializes in applying deep learning and computer vision to environmental challenges. His research includes: Automated tree detection and biomass estimation via satellite imagery Multi-modal geospatial representation learning Monitoring farmland tree decline and carbon sequestration potential Agroforestry system mapping using AI Developing AI tools for climate policy and sustainability Recent work trends show a focus on quantum-inspired machine learning , environmental monitoring , and cross-cultural AI applications . His 15 most recent publications span topics in remote sensing , ecological modeling , and AI ethics , with methods ranging from neural networks to tensor-based learning. He collaborates across disciplines, notably with researchers in ecology , climate science , and quantum computing . His outreach includes seminars on AI in agroforestry and ecosystem management , while his team contributes to global tree resource databases like TreeSense.
Teresa Hirzle is a Tenure Track Assistant Professor at the Department of Computer Science , University of Copenhagen , specializing in Human-Centred Computing . Her research focuses on Human-Computer Interaction (HCI) , Virtual Reality (VR) , Extended Reality (XR) , and Gaze-Based Interaction . Research Interests: Designing interaction techniques for immersive environments Eye movement analysis for educational applications Addressing digital eye strain in interactive systems Evaluating user experience in VR/AR Recent Research Trends: Her recent publications examine AI representation in VR co-creation, VR sickness in locomotion, eye strain in gaze-driven systems, and hybrid applications of comics/AR. She also explores pedagogical implications of eye tracking in remote learning. Contact: Email: tehi@di.ku.dk Office: Sigurdsgade 41, 2200 København N.
Bo Markussen is a Professor at the University of Copenhagen within the Department of Mathematical Sciences . He is also a member of the Data Science Laboratory , where he contributes to statistical methodology and interdisciplinary collaborations. His academic journey began with a Cand.Scient (MSc) and PhD in Statistics from the University of Copenhagen, awarded in 1998 and 2002 respectively. 2012–present: Professor, Department of Mathematical Sciences, University of Copenhagen 2009–2012: Associate Professor, Department of Basic Sciences and Environment, University of Copenhagen 2006–2009: Assistant Professor, Department of Basic Sciences and Environment, University of Copenhagen Bo Markussen's research focuses on applied statistics , particularly in functional data analysis and multiple testing corrections in genetics . His work spans diverse domains including environmental science, agriculture, and public health. Recent research output highlights applications in Arctic climate data analysis, fire risk modeling, plant stress phenotyping, and nutritional biomarker prediction. His recent publications demonstrate a strong trend toward machine learning integration with statistical modeling , addressing challenges in high-dimensional data analysis and environmental risk assessment. Collaborations span institutions in Denmark and internationally, reflecting his engagement in pan-Arctic climate studies and tropical agricultural research. 2018–present: Associate Editor, Scandinavian Journal of Statistics 2017–2019: Chair, Danish Society for Theoretical Statistics 2015–2017: Board Member, Danish Society for Theoretical Statistics As a central figure in the Data Science Laboratory , Markussen leads statistical consultancy initiatives and contributes to methodological advancements. His expertise bridges theoretical statistics with real-world applications, particularly in handling complex datasets across biological and environmental domains.
Jesper Liniger is an Associate Professor at AAU Energy within the Faculty of Engineering and Science at Aalborg University. He works in the Esbjerg Energy Section focusing on Offshore Renewable Energy Systems and is affiliated with AAU BLUE – Marine & Maritime Research. His office is located at Niels Bohr Street 8, 6700 Esbjerg, Denmark. Research Interests Marine Growth Engineering and automated cleaning solutions for offshore structures Underwater robotics including Remotely Operated Vehicles (ROVs) and autonomous inspection systems Wind turbine engineering with emphasis on hydraulic pitch systems and fault detection Fluid power engineering applications in marine environments Development of robotic solutions for offshore renewable energy infrastructure Research Trends Dr. Liniger's recent publications demonstrate a strong focus on developing robotic solutions for offshore renewable energy infrastructure. His work bridges theoretical control systems with practical marine applications, particularly addressing marine growth (biofouling) challenges on offshore structures. The research shows increasing interdisciplinary collaboration, combining robotics, fluid mechanics, and wind energy systems to create integrated solutions that improve operational efficiency and reduce maintenance costs in offshore environments. Scientific Awards Innovation Project of the Year (2024) - For underwater robotics development Esbjerg Universitetspris (2018) - University award recognizing research excellence Advising and Research Leadership Dr. Liniger actively supervises PhD students and serves as principal investigator or supervisor on multiple major projects including "NextGen Robotics" for offshore wind farms and "Towards Enhancing Perception and Navigation for Autonomous Underwater Inspection Drone." His research portfolio includes collaborations with industry partners like Vattenfall and Business Center Funen, demonstrating strong industry-academia connections focused on practical applications with economic impact. Research Teams and Facilities Liniger is part of AAU BLUE – Marine & Maritime Research, which provides specialized facilities for marine robotics testing and development. His work involves close collaboration with researchers in control systems, fluid mechanics, and renewable energy. The research group has developed experimental frameworks for testing underwater and surface vehicle operations, with recent media coverage highlighting their innovative approaches to solving marine growth challenges on offshore structures.
Nicola Dragoni is a Professor in Cybersecurity Engineering at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). As Deputy Director and Head of Section, he leads research initiatives focused on securing emerging technologies. Key Research Areas : Internet of Things (IoT) security, machine learning for intrusion detection, cyber-deception techniques, fog computing, malware analysis, blockchain applications, and wireless sensor network security. Supervision : Actively supervising multiple PhD students in projects related to cyber-deception, moving target defense, and bio-inspired security mechanisms. Recent Publications : Contributions to IoT honeypots, drone identification via RF signals, passkey adoption challenges, and cyber range taxonomies.
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
Charles Marcus is a Professor at the University of Copenhagen's Niels Bohr Institute, holding the Villum Kann Rasmussen Chair in Quantum Sciences. He directs the Center for Quantum Devices and Microsoft Station Q – Copenhagen, while affiliating with the Niels Bohr International Academy. Education : Stanford University (B.S. 1984), Harvard University (Ph.D. 1990), IBM Postdoctoral Fellow (1990-92) Employment : Faculty at Stanford (1992-2000), Harvard (2000-2011), and UCPH (2012-present) His research focuses on experimental condensed matter physics, particularly quantum coherent electronics in semiconductors/superconductors. Key areas include spin qubits for quantum computing, Majorana modes in nanowires, quantum Hall systems, and superconductor-semiconductor hybrids. Recent work explores topological quantum information schemes and novel magnetic resonance imaging approaches. Scientific publications span quantum devices, Josephson junctions, and topological materials. Awards include the H.C. Ørsted Gold Medal, AAAS Newcomb-Cleveland Prize, and fellowships from AAAS and APS. He serves on advisory boards for quantum technology centers globally. Significant Awards : H.C. Ørsted Gold Medal (2020) Industry Prize, Danish Academy of Natural Sciences (2019) Member, National Academy of Sciences (2018) Award for Research Excellence in Nanotechnology (2014) Professional Roles : Director, Center for Quantum Devices (2012-2019) Lab Director, Microsoft Quantum (2016-2021) Scientific Director, Harvard Center for Nanoscale Systems (2004-2009)
