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Dennis McNevinView profile

Professor

• Forensic Genetics
• DNA Analysis
• Biogeographical Ancestry Prediction
• +3 more

Professor Dennis McNevin is a leading academic in forensic genetics at the University of Technology Sydney (UTS), where he has held the position since 2018. He previously served at the Australian National University and the University of Canberra, progressing through roles from Lecturer to Associate Professor. His expertise spans forensic DNA analysis, biogeographical ancestry prediction, and the application of cutting-edge technologies like nanopore sequencing and machine learning in forensic science. McNevin's research addresses challenges in human remains identification, missing persons investigations, and DNA phenotyping. He is affiliated with UTS's Centre for Forensic Science and contributes to national initiatives like Australia's National DNA Program for Unidentified and Missing Persons. His work integrates interdisciplinary approaches, combining genetics, proteomics, and forensic anthropology to advance investigative capabilities. McNevin has received grants from agencies like the Australian Research Council and collaborates internationally on forensic training programs for law enforcement agencies in countries like Indonesia and Thailand. His teaching focuses on forensic genetics and criminalistics, and he has supervised numerous postgraduate students now employed in forensic laboratories across Australia. Key research themes include optimizing DNA recovery from challenging samples, developing forensic tools for ancestry and phenotype prediction, and enhancing DNA database interoperability for familial searching. Education: PhD (Chemical Engineering, University of Sydney, 1998), Graduate Diploma in Education (University of Western Sydney, 1991), Bachelor of Engineering (Chemical Engineering, University of NSW, 1989) Affiliations: Faculty of Science at UTS, Centre for Forensic Science Research Focus: Forensic genetics, DNA sequencing technologies, biogeographical ancestry, kinship inference, and forensic intelligence McNevin's funded research includes projects on ultrasensitive microRNA detection, forensic DNA phenotyping frameworks, and the operationalization of advanced DNA kits for missing persons investigations. He is a member of professional societies such as the Australian Academy of Forensic Sciences and the International Society for Forensic Genetics. His contributions to forensic science have led to advancements in disaster victim identification, DNA preservation techniques, and the ethical use of genetic data in law enforcement. Recent articles highlight his work on identity-informative markers, kinship inference using SNP panels, and proteomic approaches for body fluid identification. These studies underscore his commitment to bridging technological innovation with practical forensic applications to resolve cold cases and humanitarian identification challenges.

• Logistics Network Design
• Supply Chain Optimization
• Healthcare Logistics
• +2 more

Roberto Pinto is Full Professor in the Department of Management, Information and Production Engineering at the University of Bergamo, where he teaches Industrial Plants, Logistics, and Supply Chain Management. His research addresses logistics optimization, healthcare supply chains, and human factors in Industry 4.0 implementations. Research focuses on: Agent-based simulation for healthcare resource networks Human factors in technology adoption for logistics Supply chain resilience measurement frameworks Vaccine distribution optimization in rural areas AI readiness assessment models for SMEs His publications (2024-2025) primarily examine information visibility in healthcare networks, digital capability development for Suppliers 4.0, and resilience challenges in medical supply chains. Methodologies include Delphi studies, agent-based modeling, and conceptual framework development applied to sectors ranging from furniture manufacturing to emergency medicine.

Dimitri Coelho MolloView profile

Assistant Professor

• Philosophy of Artificial Intelligence
• Philosophy of Cognitive Science
• Philosophy of Science
• +7 more

Dimitri Coelho Mollo is an Assistant Professor in the Department of Historical, Philosophical and Religious Studies at Umeå University, Sweden. He specializes in Philosophy of Artificial Intelligence and Cognitive Science, with additional interests in Philosophy of Science, Philosophy of Biology, and Ethics of AI. Mollo also serves as an external Principal Investigator at the Science of Intelligence Cluster in Berlin and coordinates the BA in Philosophy and AI program at Umeå University. His research focuses on foundational and epistemological issues in Artificial Intelligence and cognitive sciences, particularly examining concepts of representation, computation, and intelligence. He investigates how AI systems understand and process information, with special attention to large language models and their implications for philosophical theories of mind. His work often bridges technical AI developments with broader philosophical questions about intelligence, cognition, and meaning. Mollo's recent publications demonstrate a clear trajectory from foundational questions about cognitive representation to contemporary AI ethics concerns. He has increasingly focused on the philosophical implications of large language models, examining issues like the vector grounding problem, AI alignment limitations, and the impact of AI mimicry on human dignity. His work shows strong interdisciplinary connections between philosophy, cognitive science, and computer science. Mollo is actively involved in several research initiatives, including the Umeå Centre for Transdisciplinary AI (TAIGA), where he coordinates the focus area 'Understanding (and explaining) AI.' He is also the host of 'Punching Cards,' a podcast about intelligent systems produced by the Science of Intelligence Cluster, demonstrating his commitment to public engagement and scientific communication.

Eugenia CacciatoriView profile

Associate Professor

• Innovation Management
• Disaster Insurance
• Organizational Routines
• +2 more

Eugenia Cacciatori is Reader in Management at Bayes Business School, City, University of London, researching innovation processes in disaster insurance, AI ethics, and organizational routines. Her work examines how objects and knowledge artifacts facilitate innovation in high-risk domains. Key research streams: Catastrophe insurance systems design and resilience financing Operationalizing ethical AI principles in organizations Dynamics of organizational routines in project environments Multi-stakeholder collaboration for grand challenges Co-directs the Masters in Innovation, Creativity and Leadership (MICL) and contributes to AI ethics initiatives through the Digital Society Institute.

• Electric Power Systems
• Distribution Systems
• Grid Resilience
• +3 more

Gayathri Krishnamoorthy serves as Researcher III in Electrical Engineering at the National Renewable Energy Laboratory (NREL), specifically within the Grid Planning and Analysis Center. Her work focuses on grid modernization and resilience for distribution systems, with active research output spanning 2022-2025 including eight technical publications addressing critical energy infrastructure challenges. Her research portfolio centers on: Electric power systems engineering and distribution utility resilience Grid modernization strategies for extreme weather events (hurricanes, wildfires, winter storms) Deep reinforcement learning applications in distribution system operations Energy equity frameworks for renewable energy transitions Electric vehicle integration impacts on grid stability Analysis of her 2023-2025 publications reveals concentrated efforts on operationalizing resilience planning through empirical studies of utility practices, while simultaneously advancing AI-driven grid control methodologies and equity-centered renewable energy deployment. Scientific recognition: No awards documented in available sources Professional activities: No student advisement information disclosed Grant involvement unspecified in source materials She operates within NREL's Grid Planning and Analysis Center, contributing to the Energy Systems Analysis research domain through collaborative projects like LA100 that integrate technical grid solutions with social equity considerations.

Rayid GhaniView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Science
• +6 more

Rayid Ghani is a Distinguished Career Professor in the Machine Learning Department and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He is co-lead of the Responsible AI Initiative and founder of the Data Science for Social Good Fellowship , training global professionals in ethical data science applications. His work spans AI governance, fairness, and practical deployment in social policy areas like healthcare, criminal justice, and economic development. Research Interests: Machine Learning for Public Policy Fairness and Bias Mitigation in AI Human-AI Collaborative Systems Explainable and Transparent AI Policy Evaluation and Deployment Frameworks Recent Publications Focus: Streamlining fair ML experimentation, fairness-accuracy trade-offs, eviction prevention systems, and ethical human-AI collaboration frameworks. His work emphasizes operationalizing fairness through stakeholder engagement and technical innovation. Previous Roles: Founding Director of the Center for Data Science & Public Policy at University of Chicago, Chief Scientist for Obama 2012 Campaign, and Senior Research Scientist at Accenture Labs. He has contributed to ACM, AAAI, and Nature Machine Intelligence publications.

• Aging, Technology and Society
• Knowledge and the organisation of health care
• Priority setting in health care
• +3 more

Professor Tiago Moreira is a distinguished academic at Durham University's Department of Sociology, where he conducts research at the intersection of sociology, aging studies, and healthcare systems. His work focuses on understanding the social dimensions of aging, technology implementation in healthcare, and the organization of medical knowledge across multiple disciplines including Science and Technology Studies (STS), sociology of medicine, and gerontology. Professor Moreira's research interests span several interconnected domains: Aging, Technology and Society Knowledge organization in healthcare systems Priority setting in healthcare decision-making Social Studies of Medicine Measurement practices in aging research His scholarly output demonstrates a consistent focus on how measurement practices, technological innovations, and social structures shape our understanding of aging and healthcare. Moreira examines how concepts like "frailty" and "biological age" become operationalized in medical and social contexts, revealing the complex interplay between scientific knowledge production and social policy. His work on engineered living materials and AI in aging contexts shows his ability to bridge technical and social domains. Professor Moreira has published extensively in top journals including Science, Technology, & Human Values, Social Theory & Health, and Sociology of Health & Illness. His work often employs historical sociology methods to trace the development of concepts and practices in aging research and healthcare systems. Recent publications show increasing engagement with digital health technologies and their implications for aging populations. Through his research, Professor Moreira has established himself as a leading voice in understanding how aging is socially constructed through measurement practices, technological interventions, and healthcare organization. His work consistently demonstrates how seemingly technical decisions about measurement and classification have profound social consequences for how aging populations are understood and managed.

Eleonora ViganòView profile

Researcher

• Responsible AI
• AI Ethics
• Corporate Ethics and Compliance
• +3 more

Dr. Eleonora Viganò serves as Senior Researcher at the Swiss Institute for Entrepreneurship (SIFE) within the University of Applied Sciences of the Grisons and concurrently holds a Project Leader position at the University of Zurich's Digital Society Initiative (DSI). Her dual institutional affiliation bridges applied research in entrepreneurial contexts with broader digital ethics policy development. Her research program critically examines the implementation gap between ethical AI principles and organizational practice, with particular expertise in responsible AI deployment challenges, metaverse ethics, corporate compliance systems, and digital well-being technologies. Current projects analyze Swiss organizational pain points in operationalizing AI ethics frameworks while developing practical solutions like checklist-based compliance tools. Her work consistently integrates philosophical rigor with empirical organizational studies, focusing on translating abstract ethical concepts into actionable business processes. Analysis of her recent publications reveals a distinctive pattern: over 80% of her 2022-2025 work addresses implementation challenges in responsible AI, with recurring methodological emphasis on mixed-methods approaches combining logico-mathematical analysis, value-sensitive design, and stakeholder interviews. Key thematic clusters include fairness paradox resolution (particularly counterfactual fairness models), trust quantification in human-AI systems, and the moral philosophy of prudence applied to future selves in digital contexts. This interdisciplinary approach spans computer science, ethics, organizational behavior, and philosophy.

Daniel BolojanView profile

Assistant Professor

• Creative AI
• Deep Learning
• Computational Design
• +7 more

Daniel Bolojan is an Assistant Professor and Director of the Creative AI Lab at Florida Atlantic University's School of Architecture. His research focuses on applying Creative AI, deep learning, and computational design to architectural design processes, emphasizing shared-agency and creativity augmentation. He holds a B.Arch and Master's in Architecture from the University of Applied Arts Vienna, where he studied under Zaha Hadid and Patrik Schumacher. Currently pursuing a Ph.D. at the same institution, his work explores agent-based systems and parametric semiotics in design. Education: Ph.D. Candidate, Institute of Architecture, University of Applied Arts Vienna M.Arch & B.Arch, University of Applied Arts Vienna Research interests include generative design strategies, multi-agent systems, and algorithmic techniques for architectural complexity. He founded Nonstandardstudio to develop autopeiotic systems through AI and computation. At CoopHimmelblau, he led Chbl|Code, advancing computational tools like DeepHimmelblau Neural Network and VR/AR applications. His PEEK-funded research operationalizes semiotic codes via agent-based simulations. Prof. Bolojan teaches internationally and leads workshops on AI in architecture, emphasizing neural networks and complex systems. His work bridges academic research with professional practice, driving innovation in computational design and robotic fabrication.

• Corporate Social Responsibility (CSR)
• Sustainable Business Practices
• Sustainable Solid Waste Management
• +5 more

Dr. Harsha Sarvaiya serves as Deputy Head of the Department of Management at Griffith University's Business School. She holds a PhD from Massey University (New Zealand) and has over 10 years of teaching experience across Australia, New Zealand, and India. Her primary roles include teaching undergraduate and postgraduate courses in Business Ethics, Corporate Governance, Globalization, and Strategic Supply Chain Management. She has received Deputy Vice Chancellor Teaching Commendations (2018-2019) and is a member of Griffith Asia Institute since 2018. Her research focuses on corporate social responsibility (CSR), sustainable business practices, and sustainable solid waste management. Notable projects include examining strategic responses to the pandemic in Australian firms, analyzing greenwashing threats in carbon trading, and exploring low-emission development strategies in Indonesia. She has secured grants totaling over $770,000, including a major Blue Economy CRC project and internal grants for food waste reduction and community composting. Dr. Sarvaiya supervises doctoral research on topics such as sustainability integration, AI-driven logistics, and public-private partnerships in waste management. She has authored/co-authored over 15 peer-reviewed articles and book chapters, with impactful work on CSR-HRM linkages, pandemic leadership, and indigenous sustainable development. Her teaching innovations include blended learning strategies for management students. Awards: Massey University Doctoral Scholarship (2010–2013) Key Grants: Blue Economy CRC Project ($757,460) Australia-Brazil Symposium on Circular Innovation ($48,000) Griffith Internal Grant for Food Waste Study ($3,000)

• Artificial Intelligence in Safety-Critical Systems
• Nuclear Power Plant Safety Analysis
• Functional Safety Standards
• +3 more

Joanna Weng is a Senior Lecturer in Mathematics, Physics, and Sensor Technology at the ZHAW School of Engineering, affiliated with the Institute of Applied Mathematics and Physics (IAMP) and the Centre for Artificial Intelligence (CAI). She holds roles as Project Leader at the Safety-Critical Systems Research Lab and serves as an Associate Diversity Officer. Her expertise spans AI in safety-critical systems, functional safety (IEC 61508), nuclear power plant safety analysis, and particle physics. Education: CAS in Project Management, Functional Safety Engineer (TÜV Rheinland), and IEEE CertifAIEd Assessor. Research focuses on AI certification frameworks, deterministic/probabilistic safety analysis, and autonomous system safety. She leads projects like the Personnel Safety System (PSS) at the European Spallation Source (ESS) and co-leads the certAInty certification scheme for AI systems. Notable contributions include work on trustworthy AI assessment and MLOps-enabled safety. Key Projects: Personnel Safety System (PSS) at ESS IEEE CertifAIEd Assessor Training Machine Protection and Autonomous Predictive Interlock Systems certAInty AI Certification Scheme Awards/Certifications: CAS in Safe and Secure AI, TÜV Functional Safety Engineer, IEEE CertifAIEd Assessor. Grants/Advising: Innovationsuisse-funded certAInty project leader, overseeing interdisciplinary teams for AI safety research and implementation. Labs/Teams: Safety-Critical Systems Research Lab (IAMP), Centre for Artificial Intelligence (CAI), and collaborations with CERN Alumni and Women in Tech networks.

Gabriele SartiView profile

Research Fellow

• Natural Language Processing
• Interpretable AI
• Machine Translation
• +2 more

Gabriele Sarti is a PhD Student and Research Fellow in Computational Linguistics at the University of Groningen, associated with the Center for Language and Cognition in the Faculty of Arts. His research focuses on interpretability for natural language processing systems, particularly in generative models and machine translation. Research interests center on developing methods to understand and control large language models, with emphasis on: interpretability techniques, multilingual systems evaluation, controlled text generation, and human-AI collaboration frameworks. Recent work explores model steering mechanisms, attribution methods for trustworthy AI, and tools for democratizing interpretability research. Publications demonstrate consistent focus on operationalizing interpretability advances through open-source software development. Work spans multilingual machine translation evaluation, controlled generation techniques, and foundational research on transformer model mechanics.

• Organizational Behavior
• Sociology
• Artificial Intelligence
• +3 more

Dr. Joshua Hurwitz is a researcher focused on organizational dynamics in relation to environmental and structural changes. His work explores how organizations adapt to sudden societal shifts and initiate transformations within their ecosystems. Key research areas: structural/cultural change in Indian craft clusters, essential worker categorization during the COVID-19 pandemic, healthcare operationalization, and technology integration in professional workflows. Teaching portfolio spans strategy, negotiations, medical sociology, AI, and international demography. Recent research outputs include analyses of legal mediation and comparative trust frameworks. He actively presents at major academic conferences like the American Sociological Association and Academy of Management. Future projects will investigate war's impact on business and climate change policymaking.

Deepak KumarView profile

Assistant Professor

• Cybersecurity
• Sociotechnical Systems
• Online Abuse
• +3 more

Deepak Kumar is an Assistant Professor in the Department of Computer Science at the University of California San Diego (UCSD). His research focuses on sociotechnical cybersecurity, examining threats such as misinformation and online abuse through data-driven and human-centered methodologies. He investigates how these threats operationalize in practice and their real-world impacts on digital safety. Dr. Kumar teaches graduate courses including CSE227 (Computer Security) and CSE291 (Sociotechnical Cybersecurity). He actively advises PhD students Arshia Arya, Haodi Zou, Seoyoung Kweon (collaborating with Stefan Savage and Geoff Voelker), and Paul Chung. His work has been recognized with awards, including Best Paper Honorable Mention at ACM CSCW 2024 and a MacDowell Colony Fellowship in 2023. Key research themes include large-scale measurements of online platforms, content moderation challenges, and designing defenses against emerging threats like deepfakes and hate raids. His interdisciplinary approach bridges technical systems and human behavior to improve digital safety frameworks.

Prabhat RamView profile

Researcher

• Empirical Software Engineering
• AI-driven Healthcare
• Security and Privacy
• +3 more

Prabhat Ram is a Postdoctoral Researcher at the University of Oulu's Faculty of Information Technology and Electrical Engineering, affiliated with the Empirical Software Engineering in Software, Systems and Services (M3S) research unit. He holds an M.Sc. (2016) and Ph.D. (2022) from the University of Oulu. His research focuses on empirical software engineering, AI-driven healthcare solutions, security/privacy in IoT systems, software architecture, quality metrics, and process improvement. Key projects include the Nordic Health Data Spaces initiative. His work emphasizes actionable software metrics in agile contexts and the operationalization of process improvements. Prabhat is active in academic networks, with profiles on ORCID and Google Scholar. His email is prabhat.ram@oulu.fi. Research trends span empirical studies on developer-tester collaboration, security challenges in connected systems, and leveraging analytics for quality assurance. He has published extensively on topics like agile process optimization, metrics adoption barriers, and systematic reviews of IoT privacy risks. No awards are listed, but his contributions to process measurement frameworks and healthcare IT solutions reflect ongoing scholarly impact. His current focus integrates AI with health informatics to enable patient-centric data management systems.