Find Academic Supervisors

Markus TatzgernView profile

Professor

• Augmented Reality
• Virtual Reality
• Mixed Reality
• +3 more

Dr. Markus Tatzgern serves as Professor for Mixed Reality and Game Development and Head of Research at the Department for Creative Technologies, Salzburg University of Applied Sciences. He leads the Digital Realities Lab, a multi-disciplinary research group focused on human-centered solutions at the intersection of software, design, and creative engineering for technology interaction. His academic foundation includes a Master of Science and Doctorate with highest distinction from Graz University of Technology. He furthered his expertise through post-doctoral research at the Christian Doppler Laboratory for Handheld Augmented Reality, recognized as a world-leading facility in mobile AR. Tatzgern's research spans Augmented Reality, Virtual Reality, Mixed Reality, and Human-Computer Interaction with emphasis on practical applications. His work addresses critical challenges in view management, haptic feedback systems, industrial procedure visualization, medical imaging interfaces, and game development. Key contributions include novel techniques for eye-perspective rendering, breathing-based VR interaction, and latency compensation in medical robotics. His publication trajectory reveals evolving focus from foundational AR visualization (2010-2016) toward applied XR solutions in healthcare, industrial training, and user experience optimization (2017-2024). Recent work demonstrates increasing integration of physiological inputs, real-world safety applications, and enterprise-grade XR prototyping. Scientific recognition includes: Honorable Mention for Best Paper at CHI 2022 for 'AirRes Mask' breathing interface Honorable Mention for Best Paper at IEEE 3DUI 2017 for adaptive rendering techniques As Head of Research, Tatzgern actively shapes the field through program committee roles and peer review for top venues including ACM CHI and IEEE VR. His four patents in AR visualization demonstrate translational impact from academic research to practical applications. The Digital Realities Lab operates as an innovation hub where software engineers, designers, and creative technologists collaborate on next-generation interaction paradigms. Current projects emphasize medical XR applications, industrial training systems, and accessibility-focused AR solutions for vulnerable populations.

Mirsad TrobradovićView profile

Associate Professor

• Automotive Engineering
• Electric Vehicles
• Additive Manufacturing
• +7 more

Mirsad Trobradović is an Associate Professor at the Faculty of Mechanical Engineering , University of Sarajevo , Bosnia and Herzegovina, where he conducts research and teaches in the broad domain of mechanical and automotive engineering. His office is located in room 523, and he welcomes consultations every working day by appointment. Education & Academic Standing: While the page does not detail his prior degrees, his current academic rank of docent (equivalent to Associate Professor) and the title doc. dr. indicate completion of a doctoral degree and fulfilment of all requirements for tenure-track advancement at the University of Sarajevo. Research Interests: Trobradović’s work centres on automotive engineering , electric mobility , additive manufacturing , polymer materials , 3D scanning technologies , and finite element analysis . He explores how electrification of transport affects national energy demands, investigates durability and failure mechanisms of 3D-printed polymer gears, and integrates advanced scanning techniques into furniture manufacturing processes. Additional interests include the biomechanical performance of medical fixation devices, emission reduction in diesel engines, and the mathematical modelling of dynamic systems. Publication Trends: Across more than 15 peer-reviewed articles and book chapters since 2005, Trobradović demonstrates a clear trajectory from foundational vehicle dynamics and alternative fuels toward cutting-edge topics such as electric-vehicle energy regeneration, 3D-printed component reliability, and digital transformation of manufacturing. His most recent 2025 contributions focus on quantifying the electrical-energy impact of vehicle electrification in Bosnia and Herzegovina and on assessing service life of additively manufactured polymer gears. Scientific Awards: No specific awards or distinctions are listed on the University of Sarajevo page. Advising & Projects: Although individual student names are not disclosed, Trobradović collaborates extensively with colleagues such as Adis Muminović, Nedim Pervan, and Vahidin Hadžiabdić, indicating active supervision of graduate researchers and participation in multi-institutional projects. Detailed project listings are absent, yet the breadth of co-authored works suggests ongoing grant activity. Laboratory & Teams: He carries out his investigations within the research environment of the Faculty of Mechanical Engineering, leveraging laboratories for automotive testing, additive manufacturing, and computer-aided engineering simulation.

• Vehicle Dynamics
• Noise, Vibration and Harshness (NVH)
• Automotive Engineering
• +5 more

Professor Danijela Miloradović is a distinguished faculty member at the University of Kragujevac, Faculty of Engineering Sciences, Department of Motor Vehicles and Engines. She currently holds the position of Full Professor, having been promoted to this rank in 2022 after serving as Associate Professor (2017-2022) and Assistant Professor (2012-2017). Her extensive academic career spans over 25 years at the same institution, with progressive appointments from Research Associate in 1994 to her current position. Prof. Miloradović's research focuses primarily on vehicle dynamics, noise, vibration and harshness (NVH), steering and suspension systems, brake systems, and vehicle safety. Her work has significant practical applications in automotive engineering, particularly in improving vehicle performance, safety, and environmental impact. She has made notable contributions to understanding the interaction between steering and suspension systems, brake noise problems, and vehicle vibration comfort. Her publication record is impressive, with over 50 scientific and professional papers, including numerous articles in prominent international journals. Her research has evolved from fundamental vehicle dynamics studies to more specialized areas like brake wear particle emissions and their environmental impact. Recent work shows a strong focus on sustainable automotive technologies and environmental considerations in vehicle design. Among her notable recognitions are the KSME award for the second best paper in JMST magazine (2017) and the "Editor's Choice Article" award from the journal "Machines" (2022). She has also received early career recognition as the best student at the Faculty of Mechanical Engineering in 1990 and for excellent academic achievement in 1994. Prof. Miloradović has been actively involved in mentoring doctoral students, serving as mentor for Aleksandar Poznić's doctoral dissertation and participating in numerous doctoral defense committees. She has also contributed significantly to educational development through textbook writing, curriculum design, and supervision of numerous academic courses in vehicle dynamics and related fields. Her leadership extends to administrative roles including serving as Vice-Dean for Teaching (2012-2015), Head of the Department of Motor Vehicles and Engines, and currently as President of the Faculty Council of the Faculty of Engineering Sciences. She has also played key roles in organizing international conferences and serving on accreditation committees for academic programs.

Márton LőrincView profile

Professor

• Control Theory of Dynamic Networks
• Nonlinear Systems Control
• Population Dynamics Modeling
• +3 more

Lőrinc Márton is a Professor of Control Systems at the Sapientia Hungarian University of Transylvania, where he serves as deputy head of the Department of Electrical Engineering and leads the Networked and Autonomous Control Systems research group. He also acts as a PhD supervisor at the Doctoral School of Information Science and Technology, University of Pannonia. Research Interests: Control-oriented modeling of dynamic systems Fault diagnosis in interconnected networks Delay compensation in communication systems Population dynamics and migration modeling Robot swarm coordination Key Contributions: Developed control strategies for chemical reaction networks Created delay-robust algorithms for computer networks Formulated migration cost-based population stabilization methods Contact: martonl@ms.sapientia.ro | Office: 1C Calea Sighisoarei, Corunca, Mures 94305, RO

• Network Performance Evaluation
• Software-Defined Networking (SDN)
• Network Function Virtualization (NFV)
• +4 more

Thomas Erich Zinner is Professor at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU), a position held since August 2019. Previously, he served as visiting professor and head of the FG INET research group at TU Berlin, and led the 'Next Generation Networks' research group at the University of Würzburg's Communication Networks chair. His educational background includes a diploma (2006) and Ph.D. (2012), both from the University of Würzburg. His research spans network architecture performance evaluation with emphasis on SDN/NFV and QoE-centric management approaches for emerging networks. Zinner's recent publications reveal strong trends toward intelligent 6G architectures integrating AI in the user plane, QoE-aware 5G resource allocation, and autonomic management of softwarized networks. His work combines theoretical modeling, simulation frameworks like OMNeT++, and practical implementations focused on real-world applicability in beyond-5G systems. He leads the Networking Research Group at NTNU working on the TeraFlow project, developing secure cloud-native SDN controllers for autonomic traffic management at massive scale. This initiative addresses critical challenges in next-generation network infrastructure through innovative controller architectures and flow management techniques.

Katharina KohlsView profile

Professor

• System Security
• Mobile Network Security
• Privacy and Anonymity
• +3 more

Prof. Dr. Katharina Kohls serves as a Professor at Ruhr University Bochum specializing in system security, with research spanning mobile network vulnerabilities (4G/5G), privacy/anonymity systems, and internet censorship detection. Her work addresses critical security flaws in cellular infrastructure and anonymity networks through empirical attack simulations and defensive techniques. Her primary research domains include: Mobile Network Security : Investigating protocol vulnerabilities in 4G/5G including fake base stations, bidding-down attacks, and voice call eavesdropping (ReVoLTE/IMP4GT) Privacy & Anonymity : Analyzing traffic on Tor, location leaks in messaging apps, and information leakage in mobile VPNs Internet Measurement : Leading censorship monitoring initiatives like Censored Planet for longitudinal internet freedom analysis Analysis of her 2019-2024 publications reveals escalating focus on 5G security challenges and machine learning applications for intrusion detection, with consistent contributions to identifying practical attack vectors against real-world communication systems. Her methodology combines large-scale simulations with field measurements to expose systemic vulnerabilities. No scientific awards or student advising information was documented in the provided materials. Her contact details (room MC 4.137, tel +49 (0)234 32-27814) confirm active faculty status without indication of specialized labs or research teams in the source data.

Min-Wook KangView profile

Professor

• Advanced traffic operations and safety
• Artificial intelligence in traffic management and transportation infrastructure design
• Accident analysis and modeling
• +3 more

Dr. Min-Wook Kang is a Professor of Civil Engineering specializing in Transportation Engineering at the University of South Alabama's Department of Civil, Coastal, and Environmental Engineering. He is a licensed Professional Engineer (P.E.) with a robust academic background and extensive research contributions in traffic operations, safety, and AI applications in transportation. Education: Ph.D. in Civil and Environmental Engineering, University of Maryland M.S. in Civil and Environmental Engineering, University of Maryland M.S. in Transportation System Engineering, Hanyang University B.S. in Transportation System Engineering, Hanyang University Research Interests: Dr. Kang's research spans advanced traffic operations and safety , artificial intelligence in transportation systems , and accident analysis and modeling . He leverages quantitative methods, AI-based optimization techniques, and simulation-based approaches to enhance highway and intersection safety and efficiency. His work integrates genetic algorithms , machine learning , and mathematical modeling to solve complex transportation challenges, including red-light running prevention, dilemma zone protection, and sustainable infrastructure design. Publications and Contributions: Dr. Kang has authored or co-authored numerous peer-reviewed journal articles and a 2020 scholarly book titled Artificial Intelligence in Highway Location and Alignment Optimization . His research has been published in top-tier journals such as Transportation Research Record , Transportation Research Part C , and Journal of Safety Research . Teaching and Mentorship: He teaches a wide range of courses including transportation engineering, highway geometric design, traffic safety, and machine learning applications in transportation. He actively supervises M.S. and Ph.D. students, as indicated by co-authorships with advisees marked by asterisks in his publications. Contact: Email: mwkang@southalabama.edu Phone: (251) 460-6174

• Data Science
• Data Mining
• Big Data Analytics
• +8 more

Nikolaos Pelekis is a Professor at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus, where he teaches courses in Data Science, Data Management, Information Systems, and Computer Programming. He has been actively involved in both undergraduate and postgraduate education, offering specialized courses such as "Statistical Data Mining Methods" in the Applied Statistics Master's program and "Big Data Management" in the Cybersecurity and Data Science postgraduate program. Born in 1975, Professor Pelekis earned his Bachelor's degree in Computer Science from the University of Crete (1998), followed by an MSc in Information Systems Engineering (1999) and a PhD in Moving Object Databases (2002) from UMIST University in the United Kingdom. His educational background laid the foundation for his distinguished career in data science and database management. Professor Pelekis' research spans multiple domains within data science and database management, with particular emphasis on mobility data analytics. His work focuses on data mining, big data management and analytics, with special attention to location and motion data including trajectories of moving objects. He has made significant contributions to spatial and spatiotemporal database management, moving object database systems, privacy-preserving data mining, and OLAP analysis. His research bridges theoretical foundations with practical applications, particularly in maritime and transportation domains. An analysis of Professor Pelekis' recent publications reveals a strong trend toward maritime data analytics and vessel traffic prediction. His work increasingly focuses on applying machine learning techniques to maritime trajectory data, developing systems for collision risk assessment, vessel location forecasting, and maritime route prediction. The research demonstrates a progression from foundational database management techniques to sophisticated analytics for time-critical mobility forecasting, with applications in aviation and maritime domains. Five best research paper awards 1st & 3rd place in the SemEval-2017 competition 3rd place in the ACM SIGSPATIAL Cup 2016 competition Best paper award at ACM SIGSPATIAL'14 (Path-based Queries on Trajectory Data) Best paper award at ER'13 (Baquara: A Holistic Ontological Framework for Movement Analysis with Linked Data) Best application paper award at ICDM'09 (Clustering Trajectories of Moving Objects in an Uncertain World) Ralf H. Güting best research paper award at SSTD'21 (A Novel Indexing Method for Spatial-Keyword Range Queries) Best Demo Paper award at SSTD'21 (MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories) Professor Pelekis has been actively involved in advising and research funding acquisition. He has participated in over 10 European and National Research and Development projects as principal investigator or key researcher. His leadership extends to directing research laboratories and coordinating large-scale collaborative projects. As co-founder of the Data Science Lab - DataStories at the University of Piraeus, he has mentored numerous researchers and students. His research has been supported by prestigious funding programs including Horizon Europe, Horizon 2020, and national research initiatives. Professor Pelekis co-founded and leads the Data Science Lab - DataStories at the University of Piraeus, which comprises 9 faculty members from 4 different Departments along with experienced and young researchers. He previously served as Head of Research for the Information Management Lab (InfoLab) at the Department of Informatics, University of Piraeus (2005-2014). His current research team is actively engaged in multiple European projects including "DAT.AI – Energy-efficient AI-ready Data Spaces" and "EMERALDS – Extreme-scale Urban Mobility Data Analytics as a Service," focusing on cutting-edge applications of data science in maritime and urban mobility contexts.

• Artificial Intelligence
• Internet of Things (IoT)
• Blockchain Technology
• +7 more

MSc. Sinem Alturjman is a Lecturer in the Department of Artificial Intelligence Engineering at Near East University's College of Engineering. Her academic work focuses on the intersection of artificial intelligence, blockchain technology, and internet of things (IoT) systems. Research areas include: Development of AI-powered learning facilitators and educational tools Integration of blockchain for secure IoT architectures Optimization of mobile cloud computing services Application of machine learning in cybersecurity frameworks 6G communication systems with intelligent routing protocols Recent publications demonstrate expertise in: AI-enhanced scheduling mechanisms Decentralized cloud-IoT architectures Reinforcement learning applications Smart healthcare systems with blockchain Energy-aware routing protocols for sensor networks

• Software Development
• Internet of Things (IoT)
• Blockchain
• +7 more

Joanna F. Defranco is an Associate Professor of Engineering at the Engineering Division (Great Valley) of Pennsylvania State University. Her research focuses on software development, internet of things (IoT), blockchain, and artificial intelligence, with a particular emphasis on quality assurance, security, and practical implementations in engineering and healthcare. Research Interests Defranco's work addresses critical challenges in IoT security, digital twins for manufacturing, and AI-driven software quality analysis. She explores secure data sharing frameworks, blockchain applications in healthcare, and the evolution of low-code/no-code platforms. Her recent publications highlight interdisciplinary approaches to telemedicine, smart agriculture, and urban infrastructure. Publication Trends Her 2023-2025 publications show increasing focus on IoT integration with AI, secure healthcare data systems, and the societal implications of emerging technologies. Key themes include digital twin adoption in SMEs, generative AI's impact on software development, and cybersecurity resilience. Collaborations She collaborates with institutions like IEEE and researchers such as Paul Laplante, Joseph Voas, and Thrasyvoulos Speicher. Her work bridges engineering education with real-world applications in manufacturing, agriculture, and healthcare.

Robert SzalaiView profile

Associate Professor

• Applied Mathematics
• Dynamical Systems
• Nonlinear Dynamics
• +3 more

Dr. Robert Szalai is an Associate Professor of Applied Mathematics at the School of Engineering, University of Bristol. He is affiliated with the Engineering Mathematics Research Group and the Intelligent Systems Laboratory, focusing on nonlinear dynamics, piecewise smooth systems, and invariant manifold theory. Research Interests: Nonlinear dynamics, dynamical systems, mathematical modeling of mechanical and biological systems, bifurcation analysis, and reduced order modeling. Key Collaborations: Active collaborations include researchers like Paul Glendinning, Stephen J. Hogan, and Alan R. Champneys. His recent work explores piecewise smooth systems, contact mechanics, and data-driven model reduction using invariant foliations and machine learning. Research spans applications from mechanical vibrations to bio-mathematical systems. Dr. Szalai’s publications cover diverse topics including Filippov-type singularities, nonlinear cochlear models, and traffic jam dynamics. His methodological focus includes invariant manifolds and bifurcation analysis. Contact: R.Szalai@bristol.ac.uk | ORCID 0000-0002-3602-2397

Weibing GongView profile

Assistant Professor

• Climate change-related hazards
• Seismic hazards
• Infrastructure resilience against natural hazards
• +3 more

Weibing Gong is an Assistant Professor of Geological Engineering in the Department of Geosciences and Geological and Petroleum Engineering at Missouri University of Science and Technology (Missouri S&T), affiliated with the Center for Intelligent Infrastructure in Rolla, Missouri. His educational background includes: Ph.D. in Geosystems Engineering, University of California, Berkeley (2023) M.S. in Geotechnical Engineering, Tongji University (2018) B.S. in Civil Engineering, Central South University (2015) Dr. Gong's research centers on natural hazard mitigation , with emphasis on climate change impacts , seismic resilience , and AI-driven infrastructure monitoring . His work integrates remote sensing and machine learning to enhance geological engineering solutions, particularly for landslide prediction and pavement systems, while exploring emerging applications in carbon capture technologies. Analysis of his 2023-2025 publications reveals a pronounced shift toward physics-informed AI for geotechnical challenges, featuring recurrent themes in regional landslide modeling (especially in Puerto Rico and Greece), dynamic pavement response under traffic loads, and unsaturated soil mechanics . This interdisciplinary approach bridges computational science, civil engineering, and environmental systems through advanced numerical frameworks. Dr. Gong actively contributes to Missouri S&T's Center for Intelligent Infrastructure, focusing on developing next-generation methodologies for infrastructure resilience against natural hazards through computational innovation and field-based validation.

Francesc Alías PujolView profile

Professor

• Speech Processing
• Acoustic Signal Processing
• Text-to-Speech Synthesis
• +7 more

Francesc Alías Pujol is a Professor at the Department of Engineering, Ramon Llull University (La Salle Campus Barcelona), where he also serves as Director of Teaching and Research Staff Policies since September 2019 and coordinates the PhD Program in Information Technologies since February 2022. He is a researcher in the Human-Environment Research (HER) group, focusing on speech and acoustic signal processing for natural human-machine interaction. His educational background includes: BSc in Telecommunications Engineering (1997) MSc in Electronics Engineering (1999) PhD in ICT and their application in Management (2006) MBA in Business Administration (2013) University Expert Program in Digital Transformation (2023) Dr. Alías's research primarily focuses on signal processing, with special emphasis on speech and acoustic signal processing to achieve natural interaction between humans, machines, and their environment. His work spans from Text-to-Speech (TTS) synthesis to vocal biomarkers for digital health applications, numerical voice simulation, and environmental acoustics. He has developed expertise in expressive speech analysis and synthesis, sound source identification, and smart city applications through wireless acoustic sensor networks. His publication record shows a consistent trajectory in speech and acoustic processing, with recent work focusing on the impact of global events like the COVID-19 pandemic on urban soundscapes, advanced techniques for glottal source analysis, and the development of algorithms for anomalous noise event detection in smart city applications. His research bridges theoretical signal processing with practical applications in environmental monitoring and human-computer interaction. Dr. Alías has received numerous scientific awards including: 3rd six-year research merit (2018-2023) from AQU Catalunya Most cited paper in Noise Mapping (2021) for his work on COVID-19's impact on urban noise 2nd six-year research merit (2012-2017) from AQU Catalunya Best academic record award for his MBA (2013) Multiple best paper awards from the Spanish Thematic Network on Speech Technology He has led and participated in numerous research projects including DISTRESIA (stress biomarker identification), FEMVoQ (3D voice simulation), SUARAMAP (acoustic monitoring for dementia detection), GENIOVOX (expressive voice generation), and DYNAMAP (dynamic noise mapping). His work has been supported by various funding bodies including the European Commission, Spanish Ministry of Science, and Catalan Government. As coordinator of the PhD Program in Information Technologies and former Director of the Department of Engineering (2014-2021), Dr. Alías plays a significant role in academic leadership at La Salle-URL. His research group focuses on the intersection of speech processing, environmental acoustics, and smart city applications, contributing to both theoretical advancements and practical implementations in these fields.

• Control Systems
• Energy Management
• Distributed Optimization
• +4 more

Yutaka Iino serves as an Associate Professor at Waseda University's Advanced Collaborative Research Organization for Smart Society (ACROSS) and Research Institute for Advanced Network Technology (RIANT). With over 35 years of professional experience, he transitioned from a long career at Toshiba Corporation (1984-2018) where he worked on energy management and energy-saving technologies, to his current academic position focusing on smart society element technologies including power, transportation, and information systems. Doctor of Engineering from Tokyo Institute of Technology (2015) Master's in Electrical Engineering from Waseda University (1984) Bachelor's in Electrical Engineering from Waseda University (1982) Professor Iino's research focuses on control and system engineering with particular emphasis on energy management systems and distributed optimization. His work bridges theoretical control systems with practical applications in smart grids, electric transportation, and distributed energy resources. He has pioneered approaches in decentralized optimization, modeling techniques for energy systems, and demand science applications in power networks. His research interests include Di-centralized and distributed optimization, Distributed Energy Resource management, System Control Theory, and Demand Science. Analysis of his recent publications reveals a strong focus on practical applications of distributed energy resources, particularly in the context of electric buses, photovoltaic integration, and grid congestion management. His work demonstrates a consistent trajectory toward developing market-oriented solutions for energy systems, with increasing emphasis on machine learning techniques for parameter optimization and federated learning for smart inverter control. The research spans multiple domains including electrical engineering, transportation systems, and control theory, with a clear practical orientation toward solving real-world energy challenges. SICE Paper Award, No.1995 for 'Cyber-physical Optimal Traffic Signal Control Based on a Macroscopic Traffic Model and Its Verification Using Microscopic Traffic Simulator' Best Paper Award of IEEJ Transactions on Electrical and Electronic Engineering 2021 for 'Evaluation of Mutual Effect between Power and Traffic Aiming Electrified Urban Transportation System Using Integrated Light Rail Transit and Distribution System Model' Professor Iino has secured research funding through Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research, including current projects on cooperative next-generation distribution system operation methods for mass introduction of photovoltaic power generation (2023-2027) and hybrid model analysis methods with data and physical models for automatic energy analysis (2020-2023). His committee memberships include roles in IEEE, Japan Society of Energy and Resources, The Institute of Electrical Engineers of Japan, and The Society of Instrument and Control Engineers (where he holds Fellow status). At Waseda University, Professor Iino contributes to the research ecosystem through the Advanced Collaborative Research Organization for Smart Society, where he leads efforts in developing practical energy management solutions that bridge theoretical control systems with real-world applications in smart grids and transportation electrification. His work exemplifies the integration of academic research with industry applications, leveraging his extensive industrial experience at Toshiba to inform his current academic pursuits.

Lars BoletView profile

Researcher

• Traffic Engineering
• Road Safety
• Accident Prediction Modeling
• +5 more

Lars Bolet is affiliated with the Department of the Built Environment at the Faculty of Engineering and Science, Aalborg University (AAU), Denmark. His work focuses on traffic engineering, road safety, and municipal infrastructure management. He has contributed extensively to research and public discourse on transportation systems. His research interests include: Traffic safety and accident prediction modeling Integration of hospital data in traffic risk assessment Energy-efficient transportation technologies Winter road maintenance and de-icing policies Economic impacts of traffic accidents on municipalities Sustainable urban mobility and infrastructure planning The analysis of his 15 most recent publications reveals a consistent focus on practical applications in civil and traffic engineering, emphasizing data-driven decision-making, public safety, and cost-efficiency in municipal road management. His work often bridges technical engineering solutions with socioeconomic implications, particularly in how local governments manage traffic risks and infrastructure investments. Scientific contributions and media engagement: Active contributor to traffic safety research since the 1990s Frequent media commentator on road conditions, traffic policies, and accident prevention Presenter at public and private sector events on municipal transport costs and safety investments Co-author of influential reports using real-world injury data to improve accident hotspot identification Lars Bolet has also engaged in advisory and outreach activities, including contributions to national infrastructure reporting and expert commentary in policy debates. While formal PhD supervision appears limited, he has played a significant role in applied research and knowledge dissemination. His work is closely tied to public institutions such as the Danish Road Directorate and various Danish municipalities, reflecting a career deeply integrated with practical civil engineering challenges.