Alexandru G. Bardas is an Associate Professor at the University of Kansas in the Department of Electrical Engineering & Computer Science (EECS) and the Institute for Information Sciences (I2S) . He received his PhD from Kansas State University under advisors Xinming (Simon) Ou and Scott A. DeLoach. His research focuses on cybersecurity from a systems perspective , including moving target defenses, security operations center (SOC) metrics, DevOps security, power grid cybersecurity, and defensive technologies for political activists. He explores UDP-based DDoS detection, DNS traffic analysis, and the intersection of AI with cybersecurity, emphasizing foundational knowledge over tool-specific training. Key research areas: Cybersecurity, Systems Security, Moving Target Defenses, SOC Metrics, DevOps Security Recent publications in ACSAC 2024 , USENIX Security 2024/2023 , and IEEE Security & Privacy 2022 Dr. Bardas has received significant recognition including: NSF CAREER Award (2022) for SOC automation Bellows Scholar (2021) at KU NSA SoS Honorable Mention (2023) He actively advises students across disciplines, with graduates now at Sandia National Laboratories , Blue Cross Blue Shield , and Pacific Northwest National Laboratory . Dr. Bardas participates in NSF grant reviews , serves on program committees for SOUPS and MILCOM , and leads outreach initiatives like the GenCyber Summer Camp .
Josep Llach is a Senior Lecturer at the Barcelona School of Management, Universitat Pompeu Fabra, and a part-time Professor Agregat in the Department of Business Administration, Management and Product Design at the University of Girona. He is an active researcher in innovation management, organizational innovation, sustainability, and operations, with extensive involvement in European and national research projects. University: University of Girona Department: Department of Business Administration, Management and Product Design Secondary Affiliation: Barcelona School of Management, Universitat Pompeu Fabra Academic Rank: Senior Lecturer Part-Time: Yes His research focuses on the intersection of innovation, quality, and sustainability in manufacturing and service firms. He studies how lean practices, digital transformation, circular economy strategies, and green technologies impact firm performance. His work often employs advanced statistical methods such as structural equation modelling and fuzzy-set qualitative comparative analysis. The recent publications highlight a strong trend toward sustainability, digital transformation, and methodological robustness in empirical models. His work spans industries including manufacturing, hospitality, and education, with a methodological emphasis on survey-based research and configurational analysis. Scientific Awards: Emerald Literati Awards – Most Outstanding Paper in 2018 for 'Creating value through the balanced scorecard: how does it work?' Top Downloaded Paper 2018–2019: 'Socially responsible companies: Are they the best workplace for millennials?' Josep Llach has directed five doctoral theses and actively mentors PhD students. He collaborates with the Catalan University Quality Assurance Agency (AQU) as a methodological secretary in accreditation processes. His research is supported by multiple national and European grants, particularly through participation in the European Manufacturing Survey. He is a member of the Grup de Recerca Avançada sobre Dinàmica Empresarial i Impacte de les Noves Tecnologies a les Organitzacions (GRADIENT), a research group focused on organizational dynamics and the impact of new technologies.
Myropi Garri is a Senior Lecturer in Strategic Management and International Business at the University of Portsmouth's Faculty of Business & Law, within the School of Strategy, Marketing and Innovation. She serves as the Global DBA Course Director and supervises PhD students. Her research focuses on strategy and international business, with emphasis on Foreign Direct Investment (FDI), institutional influences, sustainability, and geopolitical dynamics. She has contributed to over 20 peer-reviewed publications and led projects such as the 'Dynamic Capabilities building in Ukrainian SMEs for post-war restoration' and the Portsmouth City Council-funded 'AI Leadership Skills Bootcamp.' Her work addresses UN Sustainable Development Goals (SDGs), particularly in sustainable development and global economic equity. Garri has received the Alan M. Rugman Most Promising Young Scholar Award (2016) and frequently presents at international conferences, including a 2024 invited talk at the University of Macedonia in Greece. Key research themes include configurational theorizing, institutional theory, dynamic capabilities, and resource-based strategies. Her projects often involve cross-disciplinary collaborations, such as analyzing FDI motives in South Korea and exploring SME resilience in post-war Ukraine.
Adlen Ksentini is a Professor at EURECOM, a leading graduate school and research center in Sophia Antipolis, France, specializing in digital science and communication systems. His extensive research focuses on next-generation mobile networks (5G/6G), network management, and the integration of artificial intelligence with telecommunications infrastructure. Dr. Ksentini actively contributes to major EU research initiatives including 6G-BRICKS and AC3, serving as a key researcher and project leader in the development of future network architectures. Dr. Ksentini's research interests center around network slicing, intent-based networking, edge computing, and the application of machine learning to network management problems. His work bridges theoretical advancements with practical implementations in 5G/6G systems, with particular emphasis on zero-touch network management, energy efficiency optimization, quality of service assurance, and the integration of large language models with network operations. His research has significantly contributed to the development of O-RAN (Open Radio Access Network) frameworks and the evolution of network automation. His recent publication trends reveal a strategic shift toward AI-native network architectures, with increasing focus on integrating large language models (LLMs) with network management systems. His work demonstrates a clear progression from traditional network management approaches to more autonomous, AI-powered systems capable of intent-based configuration, self-optimization, and predictive maintenance. The publications show strong emphasis on practical implementations within the 6G research ecosystem, addressing critical challenges in network slicing, resource allocation, and energy efficiency. As a research supervisor, Dr. Ksentini mentors several PhD students including Abdelkader Mekrache, Karim Boutiba, Bouziane Brik, and Houda Hafi, who frequently appear as co-authors on his publications. His research is primarily funded through major EU research projects such as 6G-BRICKS (Building Reusable Testbed Infrastructures for Cloud-to-Device Breakthrough Technologies) and AC3 (which focuses on Cloud Edge Continuum). Dr. Ksentini is actively involved with the 6G-BRICKS project consortium and the AC3 project team, where he contributes to developing next-generation network architectures that integrate communication, computing, and sensing capabilities. His work within these projects focuses on creating reusable testbed infrastructures and addressing security and trust management challenges in the cloud-edge continuum.
Sara Shafiee is a Senior Researcher at the Department of Civil and Mechanical Engineering , Technical University of Denmark (DTU) . She specializes in product configuration systems, manufacturing engineering, and AI-driven innovation. Her work bridges technical systems with organizational agility, emphasizing sustainability and customer-centric design. External Roles: Founder & CEO of DivERS (Jan 2021–) External Lecturer at Copenhagen Business School (2022–2024) Senior Business Consultant at Haldor Topsoe AS (2017–2019) Research Focus: Her work addresses challenges in product configuration systems, generative AI applications, and sustainable construction. Key themes include: Optimal product design through recommendation systems Agile methodologies in knowledge-intensive development Environmental impact monitoring via configurators Publications Trends (2023–2025): Recent work explores AI-driven manufacturing optimization, consumer-centric innovation strategies, and the integration of environmental monitoring into design systems. High-impact areas include generative AI applications (13K+ downloads) and modular construction configurators. Awards: Agnes & Betzy Award (2025) Nordic Women in Tech Leadership Award (2022) Best Digital Startup (Venture Cup Denmark, 2021) Innovation Fund Denmark Role Model (2018) Advising & Grants: Supervised PhD projects on recommendation systems and configurator design. Lead PI of the RECODE project (DFF Grant DKK 10M+, 2024–2027) focusing on deep learning for engineer-to-order systems. Labs & Teams: Core member of DTU’s Design and Manufacturing Systems group, collaborating with industry partners like Haldor Topsoe and DivERS to develop scalable configurator solutions.
Adeel AHMAD is an active Associate Professor (Maître de Conférences) conducting cutting-edge research at the intersection of artificial intelligence, industrial applications, and business process management. His academic work demonstrates strong interdisciplinary connections between computer science, industrial engineering, and business informatics. Dr. AHMAD's research interests span Explainable Artificial Intelligence (XAI), Industrial Machine Learning, Business Process Management, Ontology-Based Reasoning, and Logistics Optimization. His work focuses on developing practical AI solutions for industrial contexts, particularly in Industry 4.0 environments where human-AI collaboration is essential. He has made significant contributions to meta-learning approaches for automated algorithm selection and configuration, with particular emphasis on making these systems transparent and interpretable for domain experts. His publication record shows a clear trajectory toward integrating explainability into industrial AI systems, with recent work focusing on conversational recommendation systems for cyber-physical environments. The research demonstrates consistent evolution from foundational work in business process analysis toward sophisticated AI applications in industrial settings. Active research leadership in Explainable AI for industrial applications Significant contributions to meta-learning frameworks for automated machine learning Interdisciplinary approach bridging computer science, industrial engineering, and business processes Strong publication record in top-tier conferences and journals Dr. AHMAD demonstrates strong collaborative research patterns, frequently working with colleagues including Mourad Bouneffa, Moncef Garouani, and other researchers in the French academic community. His work shows particular relevance to manufacturing, logistics, and cyber-physical systems where AI must work alongside human domain experts.
Peter Danholt is an Associate Professor at the School of Communication and Culture, Aarhus University, affiliated with the Department of Digital Design and Information Studies, the Centre for Science-Technology-Society Studies, and the SHAPE – Shaping Digital Citizenship research initiative. His work spans multiple interdisciplinary domains, focusing on the sociotechnical dimensions of digital systems in healthcare, welfare, and organizational contexts. His research interests include IT in healthcare , pervasive computing , gender and technology , organizational change , and qualitative research methods . He employs ethnographic and fieldwork-based approaches to study how digital technologies reshape work practices, citizenship, and care relations. His work often draws on Science and Technology Studies (STS), Actor-Network Theory, and relational ontologies. The recent publications highlight a consistent focus on digital healthcare systems (e.g., Teledialogue), data-driven governance , and the ethical implications of surveillance in welfare . Themes such as vulnerability, privacy, and citizen agency recur across his research, particularly in projects involving digital interventions in social work and patient care. Principal Investigator : Shaping Digital Citizenship – SHAPE (Independent Research Fund Denmark, 2022–2023) Collaborative Projects : CDC: Cultures of Data Collaboration , Teledialog , Håndhygiejne projektet , Sundhedsbarometer projektet He has contributed extensively to academic discourse through journal articles, conference papers, and book chapters, with a strong emphasis on ethnographic depth and theoretical innovation. His public engagement includes media contributions on AI, digital ethics, and urban technology. He has participated in organizing workshops and conferences, including EASST2010 and SHAPE Workshop (2024), and has delivered lectures on technoscience, surveillance, and welfare technology. His collaborations extend across Denmark and internationally, reflecting a robust network in STS and digital society research.
Matthew Collinson is a Senior Lecturer in Computing Science at the University of Aberdeen, where he also serves as Head of Computing Science and Academic Line Manager. He holds an affiliation with the Scottish Informatics and Computer Science Alliance (SICSA) and leads the EPSRC-funded project SSPEDI (Supporting Security Policy with Effective Digital Intervention). Education: BSc Mathematics, University of Edinburgh (1997) MSc Mathematical Logic, University of Manchester (1998) PhD Computer Science, University of Manchester (2003) Research Interests: His research spans theoretical computer science and cybersecurity , focusing on non-classical logics (intuitionistic, modal, substructural), semantics of computation , concurrency theory , and type theory . He applies these foundations to information security , particularly in modelling security policies, access control, and the economics of cybersecurity decisions. His work integrates formal verification , simulation tools (e.g., Gnosis), and game-theoretic models . Publications Trends: Recent publications (2016–2022) emphasize human-centred security , exploring how persuasion and behavioural interventions can reduce cybersecurity vulnerabilities. Earlier works (2008–2015) concentrate on mathematical systems modelling , layered graph logics , and trust domains , bridging high-level policy and low-level system configurations. Projects & Grants: SSPEDI (2017–2020, EPSRC): Human dimensions of cybersecurity policy compliance. ALPUIS (EPSRC consortium): Algebra and logic for security policy and utility. Trust Domains (RCUK/TSB, 2011–2014): Framework for modelling secure information sharing. Seconomics (EU FP7, 2012–2015): Socio-economic impacts of cybersecurity regulation. PhD Supervision: He has successfully supervised PhD students including Kevin McDonald (2014), Barry Taylor (2015), and Robert (Bob) Duncan (2016), whose theses addressed logic-based security architectures, vulnerability analysis, and cloud stewardship respectively. Labs & Teams: His research is conducted within the Computing Science section of the School of Natural and Computing Sciences, leveraging collaborations with National Grid, HP Labs, and other academic partners.
Alysson Neves Bessani is an Associate Professor at the Informatics Department of Faculdade de Ciências da Universidade de Lisboa, Portugal, and a member of the LaSIGE research group. His work focuses on distributed systems, Byzantine fault tolerance, and cybersecurity, with significant contributions to blockchain consensus and intrusion-tolerant architectures. Academic Rank: Associate Professor University: Universidade de Lisboa School: Faculdade de Ciências Department: Informatics Department Research Groups: LaSIGE, Navigators Research Interests span distributed systems design, Byzantine fault tolerance, adaptive consensus protocols, and secure multi-cloud storage. His work bridges theoretical foundations with practical implementations like the BFT-SMaRt library and the Vawlt startup. Scientific Awards include multiple Test-of-Time Awards (DSN'24, DSN'21), IBM Faculty Award (2017), and Best Student Paper at Middleware'19. He has advised numerous PhD and Master’s students, contributing to advancements in fault-tolerant systems. Publications (15 most recent) reveal trends in Byzantine consensus optimization, blockchain integration, and AI-driven threat detection. His interdisciplinary work combines distributed computing with genomics and IoT security, reflecting a broad impact across computer science.
Anders Haug serves as Associate Professor at the Department of Business and Sustainability (DBS) within the University of Southern Denmark's Kolding campus. Having joined the university in 2008 as Assistant Professor in the Department of Entrepreneurship and Relationship Management before transitioning to his current role in 2010, his academic career spans over 15 years of research and teaching in operations, supply chain, and digital transformation contexts. His work bridges theoretical rigor with practical industry applications, particularly in engineer-to-order manufacturing and logistics sectors. Education: PhD in communication, representation and automation of design knowledge (2005-2007) Haug's research centers on information and knowledge management systems, with deep expertise in data quality frameworks, knowledge-based configuration, and digitalization of business processes. His fingerprint reveals distinctive contributions to product configuration systems, digital twin applications, and supply chain resilience—particularly examining how configurators transform warehouse services, manufacturing processes, and product-service ecosystems. Recent work increasingly addresses sustainability through green dynamic capabilities frameworks and life cycle assessment tools, maintaining strong empirical grounding via case studies in Danish manufacturing. Analysis of his 2024-2025 publications shows converging trends: digital technologies (configurators, digital twins) are examined through operational performance lenses while addressing sustainability imperatives. These works span operations management, information systems, and strategic management disciplines but consistently prioritize practical implementation frameworks for manufacturing SMEs. The research demonstrates methodological diversity—from conceptual modeling to empirical case studies—with strong industry relevance in logistics, engineering-to-order contexts, and manufacturing digitization. Scientific Awards: Top read paper in Business 2017/18 (Wiley) (2019) Haug has supervised 34 teaching courses between 2018-2024 covering business information systems, digitalization projects, and supply chain management. His academic service includes extensive peer reviewing for conferences like NOFOMA and DRS, plus organizational roles in Nordic business research networks. While specific grant details aren't provided, his 175+ research outputs and industry collaborations (evidenced by consultant work since 2006) indicate substantial research funding engagement. Media contributions on 3D printing and business process efficiency demonstrate effective knowledge transfer to practitioners. Though no dedicated research lab is specified, Haug's extensive co-authorship network—including collaborations on projects like digital twin implementation and configurator development—reveals embeddedness in multiple research collectives. His industry-facing approach manifests through case studies with logistics providers, manufacturer partnerships, and practical frameworks for warehouse service design and supply chain resilience.
Thomas E. DeCarlo , Ph.D., is the Ben S. Weil Endowed Chair of Industrial Distribution and Professor of Marketing and Industrial Distribution at the University of Alabama at Birmingham since 2009. He previously served at Iowa State University (1993-2006) and earned his Ph.D. in Business from the University of Georgia (1993) and BA in Accounting from North Carolina State University (1982). Research focus on strategic sales management , customer relationship management , and marketing communications Key methodologies: in-depth interviews , field experiments , and multivariable regression analysis Research Trends : His 15 most recent publications (2015-2025) examine: Salesperson ambidexterity and stress dynamics Consumer suspicion and persuasion knowledge Digital crowdfunding strategies Internal selling process optimization Service ecosystem theory in B2B contexts Scientific Awards : Recognized for outstanding teaching Multiple business impact awards Professional Activities : Served as Interim Department Chairperson (2014-2015) and ID Faculty Search Chair (2020). Actively reviews for journals like European Journal of Marketing and Industrial Marketing Management .
Qi Chen is a Professor in the Department of Geography at the University of Hawaii at Mānoa, specializing in remote sensing and geospatial technologies. His office is located in Saunders Hall, and he teaches undergraduate and graduate courses including GEO 370 (UAV and Aerial Photography), GEO 388 (Introduction to GIS), GEO 470 (Remote Sensing), GEO 489 (Applied GIS), and GEO 762 (Research Seminar: Remote Sensing. His research focuses on transforming earth observation data into actionable knowledge for environmental monitoring. Primary interests include: LiDAR applications for vegetation analysis and biomass estimation Climate change impacts on land cover and coastal systems Machine learning integration with geospatial data High-resolution mapping of agricultural and forest ecosystems Drone and satellite-based environmental assessment Chen's recent publications (2020-2025) demonstrate a strong focus on advancing remote sensing methodologies, particularly through: AI-driven approaches (GANs for vegetation indices, deep learning for marine debris) Multi-sensor fusion (LiDAR with camera systems, hyperspectral-multispectral integration) Novel applications in precision agriculture and infrastructure monitoring Hawaii-specific environmental studies incorporating indigenous knowledge systems He leads the Smart Remote Sensing Lab (smartremotesensing.org) where he mentors graduate students in developing cutting-edge geospatial solutions for ecological and societal challenges.
Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University working with 5G and Internet evolution. She completed her PhD in computer science in 2017 at the Simula Research Lab and Universitetet i Oslo under the supervision of Dr. Ozgu Alay and Prof. Michael Welzl. Her PhD dissertation focused on increasing robustness in multipath transport with MPTCP. Dr. Ferlin's educational background includes a PhD in Computer Science from the Simula Research Lab and Universitetet i Oslo (2017). Her doctoral research centered on enhancing robustness in multipath transport protocols, specifically focusing on MPTCP (Multipath TCP). She also completed undergraduate work that contributed to a book project with Prof. Friedrich Oehme on electronics and circuit technology. Dr. Ferlin's research spans multiple domains at the intersection of networking, systems, and performance engineering. Her primary interests include network and system measurements, performance analysis, security, and congestion control. She investigates how networks like the Internet evolve, examining technology development, adoption patterns, and their impacts on various entities. Additionally, she explores ways to harmonize security and privacy while making them more usable and assessable. Her work particularly focuses on transport layer and multipath transport protocols, examining their performance and security aspects. She also investigates application and transport layer performance, automation, and monitoring. Her research extends to network programming in both Linux kernel and user space, mobile broadband networks from 2G to 5G, and their intersection with the Internet. She is deeply engaged in observability, distributed and system performance monitoring, and automation. Analysis of Dr. Ferlin's recent publications reveals a strong focus on next-generation networking technologies. Her work spans multiple domains including 5G/6G networks, transport protocols (particularly QUIC and MPTCP), network virtualization, container orchestration, and the application of machine learning to networking problems. She has increasingly incorporated large language models into network configuration and automation research. Her publications demonstrate a consistent emphasis on performance measurement, optimization, and security across diverse networking environments from the edge to the cloud. Dr. Ferlin has received notable recognition for her research contributions: Best paper award at IEEE ICIN'21 for 'Learning-based Incast Performance Inference in Software-Defined Data Centers' Applied Networking Research Prize (ANRP)'25 winner for 'NetConfEval: Can LLMs Facilitate Network Configuration?' Dr. Ferlin is actively involved in mentoring the next generation of networking researchers. She has co-supervised numerous Master's and PhD students across multiple institutions including Karlstad University, KTH, TU Berlin, University of Oslo, and universities in Brazil. Her students have worked on diverse topics including NAT64 performance comparison, system tracing visualization, network observability, ML applications to multipath transport, FEC integration with QUIC, high-performance networking for 5G, congestion control, shared bottleneck detection, multipath IoT applications, and container runtime performance. She is also involved in several significant research projects including Vinnova's SEMLA (Securing Enterprises via Machine-Learning-based Automation), Horizon Europe's CODECO (Cognitive Decentralised Edge Cloud Orchestration), and the Knowledge Foundation of Sweden's DRIVE (Data-driven Latency-Sensitive Mobile Services for a Digitized Society). Dr. Ferlin serves as Workshop Chair for ACM SIGCOMM '25, is a member of the ACM/IRTF Applied Networking Research Workshop (ANRW) steering committee, and co-chairs the Internet Congestion Control Research Group (ICCRG) at the IRTF. She previously served as Associate Technical Editor for IEEE Communications Magazine and has been active on numerous program committees for major networking conferences including SIGCOMM, CoNEXT, IMC, and PAM.
Dr David Johnson is an Associate Professor of Entrepreneurship at Durham University Business School, where he serves as Associate Chair for the £9 million Smart & Scale initiative supporting SME innovation in North-East England. He is also a Fellow of the Wolfson Research Institute for Health and Wellbeing and maintains active Visiting Fellow positions at international institutions. Johnson's educational background includes: PhD in Management (Entrepreneurship), University of Edinburgh Business School MSc by Research (Entrepreneurship), University of Edinburgh Business School MBA, Adam Smith Business School, University of Glasgow Master's degree in Science, University of Edinburgh Bachelor's degree in Science, University of Leeds PG Cert in Learning, Teaching, and Assessment Practice His research centers on academic entrepreneurship , life science commercialisation , and university-industry engagement , with particular focus on linguistic approaches and machine learning applications. Johnson examines how institutional practices shape entrepreneurial activities across contexts ranging from regenerative medicine to Freemasonry, emphasizing the built environment's role in ecosystem development. Johnson's publication trajectory reveals evolving methodological sophistication, shifting from early studies on regenerative medicine venturing (2014-2017) toward computational linguistics and machine learning applications (2024-2025). His work consistently bridges theoretical frameworks with practical innovation challenges, spanning entrepreneurial ecosystems, technology transfer, and narrative analysis in resource mobilization. His scientific recognition includes: NASA Innovation and Technology Transfer: Space2Pitch Final Visiting Research Fellow at Interface, Edinburgh Fellow of Wolfson Research Institute for Health and Wellbeing Visiting Research Fellow at Skolkovo Institute Visiting Research Scholar at Wisconsin School of Business Fellow of Higher Education Academy Johnson supervises postgraduate students including Clare Talbot-Jones and Olivia King, supported by over £500,000 in research funding: Science commercialisation activities at university-industry boundary (£390,824) Cardiology-focused point-of-care device development (£38,934) Primary Research Support Fund for Zambian field research (2025) Global Engagement Grant for Dartmouth College knowledge exchange (2024) He actively leads research infrastructure as Co-Director of Durham Enterprise Centre and through his Smart & Scale initiative role, while contributing to interdisciplinary health research via the Wolfson Institute fellowship.
Sebastian Gottschalk is a researcher at Paderborn University, Germany, specializing in business model development within software ecosystems, virtual reality applications, and model-driven software engineering. His research focuses on creating situation-specific approaches to business model development, with particular emphasis on tool support, method composition, and knowledge provision. His research interests span business model innovation, virtual reality applications for education and collaboration, model-driven development, and end-user programming. He has made significant contributions to understanding how business models can be developed in context-aware ways within software ecosystems, with practical applications in tool development and method engineering. His publication record shows a clear progression from foundational work on business model development to innovative applications in virtual reality and gamification. Recent work demonstrates increasing focus on practical implementations, particularly in educational contexts using VR technology to teach UML and software modeling concepts. Gottschalk has collaborated extensively with Gregor Engels (27 publications together), Enes Yigitbas (20 publications), and Alexander Nowosad (7 publications), indicating strong research partnerships that have driven much of his recent work in business model development and virtual reality applications.
