Karolina Drobotowicz is a Doctoral Researcher in the Department of Computer Science at Aalto University, affiliated with the School of Science. Her work focuses on the design and ethical implications of AI services in the public sector, emphasizing inclusivity, civic empowerment, and trustworthy technology implementation. She holds a Master's in Engineering and Technology from Aalto University (2020) and dual Bachelor's degrees in Engineering and Technology, and Control Engineering and Robotics from Gdańsk University of Technology (2016). Her research explores practitioners' and citizens' perspectives on AI adoption in public services, addressing challenges in algorithmic fairness, public trust, and equitable access. Key contributions include studies on Finnish public sector AI governance and co-design methodologies for citizen-centric AI solutions. Active in interdisciplinary projects like CAAI (Citizen Agency in AI), she investigates democratizing algorithmic services in urban environments. Her work aligns with UN Sustainable Development Goals related to quality education and innovation. Recent activities include organizing public workshops on AI in the public sector and presenting at international conferences on topics such as LLM-powered decision systems and civic empowerment through technology.
Dr. Zoë Walters is an Associate Professor in Translational Epigenomics at the University of Southampton, affiliated with the Faculty of Medicine and Cancer Sciences department. She leads the MSc Genomics program's Genomics Guided Treatment and Dissertation modules and contributes to BMedSci teaching. Her research focuses on epigenetic mechanisms in cancer and developmental disorders, particularly targeting therapies for pediatric cancers like neuroblastoma and rhabdomyosarcoma. She collaborates on projects addressing therapy resistance, tumor microenvironment dynamics, and precision medicine approaches. Current research includes investigating EZH2 inhibitors in combination therapies, leveraging omic data for sarcoma treatment, and understanding mechanisms of therapeutic resistance. She has received awards such as the Norman Williams Prize (2024) and Young Investigator Award (2023). Her lab also explores AI applications in clinical decision-making for oesophageal cancer. Zoë has supervised numerous PhD students and contributed to over 10 peer-reviewed publications. She serves on editorial boards (e.g., Frontiers in Cell and Developmental Biology) and reviews for journals like Nature Communications and Clinical Epigenetics. Her work spans interdisciplinary collaborations, including with engineering and computer science teams for AI-driven oncology solutions.
Prof. Theo Araujo is a Full Professor of Media, Organisations and Society at the University of Amsterdam's Department of Communication Science, and Scientific Director of the Amsterdam School of Communication Research (ASCoR). He leads the Digital Data Donation Infrastructure (D3I) consortium, co-directs the Trust in the Digital Society research priority area, and is a senior researcher in the Public Values in the Algorithmic Society (AlgoSoc) program. His research focuses on AI's societal impacts, computational social science methodologies, and data donation frameworks. Key roles include coordinating multi-university initiatives and advising on digital ethics. Research interests emphasize automated decision-making, conversational agents, and digital inequality. He has pioneered tools like the Conversational Agent Research Toolkit and OSD2F framework. His work bridges communication science with computational methods, addressing challenges in data collection, algorithmic transparency, and human-AI interaction. Recent studies explore chatbot persuasion mechanisms, public trust in AI systems, and cross-cultural consumer behavior. He has published extensively on brand engagement, media analytics, and the ethical implications of automated systems. Current projects include smart speaker data donation studies and hybrid methods for health communication research. Grants and collaborations involve EU-funded initiatives and partnerships with Dutch universities. His lab work focuses on developing ethical AI applications and improving digital trace data methodologies. Future directions include advancing participatory data donation practices and mitigating algorithmic biases in automated decision-making systems.
Johannes Peter Wallner is an Associate Professor at Graz University of Technology (TU Graz), working in the Institute of Software Engineering and Artificial Intelligence within the Faculty of Computer Science and Biomedical Engineering. He leads the Knowledge Representation and Reasoning (KRR) research group and has previously been a researcher at TU Wien's DBAI group and the Constraint Reasoning and Optimization group at the University of Helsinki. Dr. Wallner's research focuses on knowledge representation and reasoning, artificial intelligence, argumentation, abduction, belief change, inconsistency handling and measurement, computational social choice, computational complexity, Boolean satisfiability, and answer set programming. His work bridges theoretical foundations with practical applications, particularly in developing computational models for argumentation systems. He has made significant contributions to structured argumentation frameworks, including assumption-based argumentation and ASPIC+. His recent publications demonstrate a strong trend toward advancing algorithmic approaches to probabilistic argumentation, abstraction techniques in argumentation systems, and applications of argumentation in domains like healthcare. He has been particularly active in exploring the computational complexity of various argumentation semantics and developing efficient algorithms for reasoning tasks. Dr. Wallner has received multiple prestigious awards including being selected for the IJCAI 2024 Early Career Track (only 12 researchers globally selected), being named a Top Scholar by ScholarGPS in 2024 (top 0.5% worldwide in AI), and receiving the AI 2000 Most Influential Scholar Honorable Mention in Knowledge Engineering in 2021 and 2022. As Principal Investigator, Dr. Wallner has secured significant research funding from the Austrian Science Fund (FWF), including two major projects: "A Novel Computational Workflow for Argumentation in AI" (grant P 35632, 358,848 €) and "Extending Belief Change to Advance Dynamics in Argumentation" (grant P30168-N31, 353,438 €). He is highly active in the academic community, serving on program committees for major AI conferences including AAAI, IJCAI, KR, and ECAI, and was a member of the Program Committee Board of IJCAI (2022-2024). He leads the Knowledge Representation and Reasoning (KRR) research group at TU Graz, which develops both theoretical foundations and practical implementations for computational argumentation systems. The group has contributed to several software systems including CEGARTIX (a SAT-based argumentation system), Vispartix (visualization of argumentation frameworks), ADFsys (an ASP-based argumentation system for abstract dialectical frameworks), and others that implement various argumentation frameworks.
Sebastian Heese is a Professor of Supply Chain Management at NC State University's Poole College of Management , where he serves as Interim Department Head of Business Management . Previously, he held the SGL Carbon Endowed Chair at EBS Business School, Germany and was a faculty member at Indiana University's Kelley School. Ph.D. from University of North Carolina at Chapel Hill His research examines supply chain efficiency , decentralized operations , and healthcare workflow integration . He developed an operational framework for clinical adoption of diagnostic tests, published in Production and Operations Management (2021), and investigates how social media backlash affects corporate financials (2021 studies). Current work includes analyzing automotive clusters in India (2025) and supplier bankruptcy risks (2023). While his 15 most recent articles show diverse applications in pharmaceuticals , medical diagnostics , pricing strategy , and conflict minerals , the consistent theme is supply chain resilience across industries. His 2025 work on automotive clusters and 2023 studies on surge pricing demonstrate cross-sector adaptability. Scientific Recognition Owens Distinguished Professorship of Supply Chain Management Heese actively bridges academic research and practical implementation , addressing challenges in stock market reactions to supply chain issues (2021 studies) and environmental regulation impacts on business (2024). His work emphasizes system-level analysis and long-term recovery strategies post-disruption.
Emily Jefferson is a Professor of Health Data Science at the University of Dundee, currently serving as CTO of Health Data Research (HDR) UK and Interim Director of DARE UK. She holds an honorary professorship in Population Health and Genomics. With a PhD in Bioinformatics and industry experience in Big Data and project management, her career spans academia, finance, and solo global travel. Her research focuses on Trusted Research Environments (TREs), data governance, and machine learning applications in healthcare. She led the Health Informatics Centre (2013–2022), managing a 60-person team supporting over 100 projects. Key achievements include ISO27001 certification and Scottish Government-accredited Safe Haven infrastructure. Since 2014, she has secured over £120M in grants as PI/Co-I, delivering £28M. Notable projects include HT-ADVANCE (hypertension biomarkers), Alleviate (chronic pain data hub), and GRAIMATTER (TRE disclosure control guidelines). She chairs boards at Swansea University and European Bioinformatics Institute. Awards include the 2016 Farr Institute Future Leader. Her work addresses SDG 3 (Good Health) and 9 (Industry/Innovation). Recent publications emphasize TRE innovation, hypertension subtyping, and pandemic data infrastructure (e.g., CO-CONNECT for COVID-19).
Kyle J. Hunt is an Assistant Professor in Management Science and Systems at the School of Management, University at Buffalo. He is affiliated with the Institute for Artificial Intelligence and Data Science and focuses on interdisciplinary research bridging academia and industry. Education: PhD in Industrial Engineering (Operations Research), University at Buffalo BS in Industrial Engineering, University at Buffalo His research integrates operations research, machine learning, and empirical methods to address challenges in security and defense, healthcare analytics, information management, and technology management. Key areas include attacker-defender games, pandemic decision-making, and misinformation detection during crises. Recent publications analyze adversarial belief formation, counterterrorism technology signaling, and open-set recognition algorithms. Research trends highlight interdisciplinary approaches combining game theory, machine learning, and policy analysis in security and public health contexts. Grants: STTR Phase 2: Machine Learning Detection and Response for Space Force Ground Systems ($540,000, Air Force Research Lab, 2024–2025) AMiRA: Assessing and Mitigating Risks in the Arctic ($460,000, Department of Homeland Security, 2024–2025) NSF DDRIG: Multi-target Technology Deployment in Attacker-Defender Settings ($15,325, 2022–2023) Professional affiliations include INFORMS, Association for Information Systems, INFORMS Information Systems Society, and INFORMS Decision Analysis Society.
Dr. Tayo Obafemi Ajayi is an Associate Professor in the Department of Electrical and Computer Engineering at Missouri State University, where she holds the Mace/Turblex Professor of Engineering title. She also serves as an Adjunct Professor at Missouri University of Science and Technology and directs the Computational Learning Systems (CLS) Lab. As site coordinator for the Missouri Louis Stokes Alliance for Minority Participation (MoLSAMP), she champions diversity in STEM while leading committees in IEEE organizations like the Bioinformatics and Bioengineering Technical Committee and the Engineering in Medicine and Biology Society. Primary Affiliation: Missouri State University Secondary Affiliation: Missouri University of Science and Technology Labs: Computational Learning Systems Lab Leadership: IEEE Technical Committees, MoLSAMP Her research focuses on Explainable Artificial Intelligence (XAI) for biomedical applications, integrating Data Mining , Machine Learning , and Bioinformatics to address complex health problems. Key projects include: Anemia prediction models for spinal surgery outcomes Alzheimer’s disease severity analysis Autism genotype-phenotype mapping Traumatic brain injury subgroup identification Recent publications span IEEE Access , Frontiers in Human Neuroscience , and the Pacific Symposium on Biocomputing . Her work emphasizes model transparency, statistical rigor, and practical validation through biomedical case studies. Scientific Awards Bear Bridge Outstanding Mentoring Award (2023) IEEE CIBCB Best Student Paper Award (2021) College of Natural and Applied Sciences Faculty Research Award (2019) Dr. Ajayi's research combines Computational Learning with Clinical Applications , securing grants through collaborative projects with institutions like Missouri S&T and participation in national conferences. Her work has been cited over 560 times with an h-index of 14, reflecting sustained impact in AI-driven healthcare solutions.
Dr. Dimitrios Diochnos is an Assistant Professor in the School of Computer Science at the University of Oklahoma (OU) . His research focuses on theoretical and practical aspects of machine learning, including adversarial learning, semi-supervised learning, and imbalanced data classification. Prior to OU, he was a Hobby Postdoctoral Research Fellow at the University of Virginia and a Research Associate at the University of Edinburgh. He holds a PhD in Mathematics from the University of Illinois at Chicago, an MS in Mathematics from the University of Athens, and a BS in Informatics and Telecommunications from the University of Athens. Research Interests: Dr. Diochnos works on foundational aspects of machine learning, particularly under adversarial conditions. His current projects include developing semi-supervised learning techniques, analyzing online/streaming learning algorithms, and exploring theoretical guarantees for imbalanced classification. He is also involved in the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), focusing on trustworthy AI applications in environmental science. Awards and Recognition: He has received NeurIPS Top Reviewer awards (2023, 2019), NSF reviewer status, and the Teaching Award (2009). His postdoctoral fellowship at UVA was supported by the Hobby Endowment. He has held fellowships from the Zossima Brothers Foundation and the University of Illinois at Chicago. Service and Editorial Work: Dr. Diochnos serves as Managing Associate Editor of the Annals of Mathematics and Artificial Intelligence and has been a program committee member for major conferences like NeurIPS, AAAI, and IJCAI. He has organized events such as the Symposium on AI & ML at OU and served on the Scientific Committee for the International Olympiad in Informatics. Grants and Collaborations: His work is supported by NSF grants, including leadership in AI2ES. He collaborates with researchers in meteorology, oceanography, and climate science to address challenges in trustworthy AI for environmental systems. Labs and Affiliations: Dr. Diochnos is affiliated with the OU School of Computer Science and contributes to interdisciplinary initiatives like AI2ES. His research lab focuses on advancing machine learning theory with practical applications in adversarial robustness and environmental forecasting.
Dr. Abolfazl Zaraki is a Senior Lecturer in AI and Robotics at the University of Hertfordshire's Department of Computer Science, part of the School of Physics, Engineering & Computer Science. He leads the Robotics Research Group and previously held roles at Cardiff University's School of Engineering and the IROHMS Research Centre. His academic journey includes a Master's in Mechatronics from University Technology Malaysia (2010) and a PhD in Automatic Robotic and Bioengineering from the University of Pisa (2014). He has held Research Fellow positions in Italy and the UK until 2019. Dr. Zaraki's research focuses on AI-driven autonomous systems, social robotics, and assistive technologies. Key projects include the EASEL, BabyRobot, and JAMES EU initiatives, alongside the Innovate UK-funded InSight project. His work emphasizes Human-Robot Interaction (HRI), trusted autonomy, and applications in healthcare and industrial contexts. Notable contributions include the development of the Kaspar humanoid robot for autism therapy and advancements in reinforcement learning for robotic control. His recent publications (2021–2025) explore agentic AI, memory-driven systems, and personalized LLMs for HRI, alongside technical advancements in robotic control, communication systems, and bio-inspired robotics. His research bridges theoretical AI innovation with practical applications in healthcare, education, and industrial automation. Zaraki has collaborated internationally across institutions and industry partners, contributing to 35+ research outputs. His work aligns with global trends in ethical AI, explainable systems, and human-centric robotics design.
Dr. Bartosz Marcinkowski serves as Professor and Head of the Department of Business Informatics at the University of Gdańsk's Faculty of Management, concurrently holding the positions of Deputy Dean for Research and Head of the Doctoral School. His academic leadership spans departmental administration, faculty research strategy, and doctoral program oversight within Poland's prominent management education institution. Marcinkowski's research centers on the intersection of information systems and practical business applications, with dominant focus areas including agile software development methodologies, digital transformation frameworks, and facility management technology adoption. His work consistently addresses contemporary challenges such as post-pandemic recovery in IT projects, generative AI integration, and sustainable business practices through empirical industry-academia collaborations. Recent publications demonstrate particular expertise in scaling agile frameworks for distributed teams and implementing blockchain solutions in enterprise environments. Analysis of his 2022-2025 publications reveals a strategic research trajectory emphasizing practical solutions for complex business-technology challenges. His work shows increasing integration of sustainability considerations across domains, from facility management to corporate governance, while maintaining strong methodological focus on agile approaches and systems integration. The recurring industry-academia collaboration theme highlights his commitment to bridging theoretical research with real-world business applications.
Jatinder Singh is a Professor at the RC Trust and Principal Research Associate (equivalent to Research Professor) at the Department of Computer Science & Technology, University of Cambridge. He is primarily affiliated with the University of Duisburg-Essen, Germany, where he leads the Compliant and Accountable Systems research group within the Law department. His work operates at the critical intersection of computer science, legal frameworks, and societal impact, focusing on practical implementations that align technology with regulatory requirements while addressing user and community concerns. Research interests center on accountability mechanisms for AI systems, responsible development practices, data governance, and privacy/security in emerging technologies. He examines governance, agency, trustworthiness, and transparency gaps in algorithmic systems through interdisciplinary socio-technical lenses. Current work addresses bias in LLMs, stakeholder participation frameworks, and human rights implications in domains like healthcare, maritime enforcement, and consumer IoT, emphasizing contextual awareness and real-world applicability. His 15 most recent publications (2025-2024) reveal dominant trends in AI transparency, fairness proxy development, and legal-compliance engineering. Key focus areas include stakeholder involvement in AI governance, bias mitigation in language models, data justice applications for vulnerable populations, and operationalizing human-centered AI in clinical settings. The work consistently bridges technical implementation with regulatory frameworks like the EU Cyber Resilience Act and GDPR. Scientific Awards: No awards or fellowships were mentioned in the provided text. Advising and Grants: The text does not specify PhD/Master's students or grant details. As leader of an active research group publishing high-impact work on EU regulations and human rights, he likely directs funded projects and mentors early-career researchers, though concrete evidence is absent in the source material. His position suggests involvement in interdisciplinary grant consortia addressing socio-technical challenges. Labs and Teams: Singh leads the Compliant and Accountable Systems research group at University of Duisburg-Essen, which collaborates across university-wide clusters including Artificial Intelligence and Society, Human-AI Interaction, Trustworthy Human Language Technologies, and Verification of Machine Learning. The group develops frameworks for legal compliance in AI, focusing on demonstrable accountability through tools for transparency, bias auditing, and stakeholder engagement in real-world deployments.
Anastasia Kozyreva is a Senior Research Scientist at the Max Planck Institute for Human Development, leading the research group Cognition in Online Environments within the Adaptive Rationality Research Area. With a background in philosophy, her work bridges disciplines by integrating conceptual and empirical approaches to analyze the cognitive and ethical impacts of digital technologies on society. Education: PhD (Dr.Phil.) in Philosophy, Heidelberg University (2016) M.Phil in Europhilosophie, Université catholique de Louvain-la-Neuve, Université de Toulouse II, Bergische Universität Wuppertal (2012) Her research focuses on desinformation policy , public attitudes toward content moderation, and cognitive interventions to combat misinformation. Key projects include developing tools for digital resilience and analyzing algorithmic personalization ethics. Recent publications examine misinformation mitigation , digital citizenship , and public trust in technology . These works span psychology, political science, and digital ethics, addressing challenges like online manipulation and democratic integrity. Kozyreva collaborates with interdisciplinary teams and contributes to policy reports, including the 2020 EU publication Technology and Democracy . She co-authored the influential 2020 Psychological Science in the Public Interest paper on cognitive tools for confronting digital challenges.
Jaime S. Cardoso is a prominent researcher at the University of Porto and Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) in Portugal. His extensive publication record spanning two decades demonstrates his leadership in computer vision, medical image analysis, and pattern recognition. His research primarily focuses on applying artificial intelligence to healthcare challenges, particularly in medical imaging and diagnostics. Cardoso's research interests center on explainable AI for medical applications, biometrics, and computer vision. His work bridges the gap between theoretical machine learning and practical medical solutions, with significant contributions to breast cancer diagnosis, medical image segmentation, and biometric security systems. He has developed innovative approaches to medical image analysis, including virtual staining techniques and privacy-preserving explanation methods for medical AI systems. His recent publications (2023-2025) reveal a strong emphasis on explainable AI in medical contexts, with multiple papers addressing how to make deep learning models more transparent and trustworthy for healthcare applications. He has also made significant contributions to face recognition technology, video anomaly detection, and specialized medical imaging techniques for breast cancer and neonatal EEG analysis. Among his scientific contributions are numerous collaborations with researchers across Portugal and internationally. His work has appeared in top-tier journals including IEEE Access, Medical Image Analysis, and Neurocomputing, reflecting the high impact of his research. Cardoso has supervised numerous students who have become established researchers in their own right, including Ricardo P. M. Cruz, Kelwin Fernandes, and Ana Filipa Sequeira. His research group appears to focus on the intersection of deep learning, medical imaging, and biometrics, with strong connections to clinical applications.
Emanuel Vahid Towfigh is a Professor of Public Law, Empirical Legal Research and Law & Economics at EBS University of Business and Law in Germany. He holds the Chair in Public Law at EBS Law School and is Professor of Law & Economics at EBS Business School. Since October 2024, he serves as a Max Planck Fellow at the Max Planck Institute for Comparative Public Law and International Law in Heidelberg, where he heads the Center for Diversity in Law funded by Stiftung Mercator. He is also Director of the BRYTER Center for Digitalization & Law and supports the EBS Diversity & Refugee Law Clinic. Additionally, he is a Distinguished Scholar in Residence at Peking University's School of Transnational Law and a Research Affiliate at the Max Planck Institute for Research on Collective Goods. Having earned his doctorate from the University of Münster in 2005 with a thesis on religious communities (focusing on the Bahá'í faith), Towfigh completed his habilitation at the same university in 2014 with his work 'The Party Paradox.' His academic journey includes research positions at the Max Planck Institute for Research on Collective Goods (2007-2016), a Global Fellowship at NYU School of Law (2011/12), and a Visiting Professorship at the University of Virginia School of Law (2012/13). He served as Dean of EBS Law School from 2018 to 2020 and has been Vice Dean for Research since 2023. Towfigh's research spans interdisciplinary governance, combining interests in public and constitutional law, democracy theory, religious constitutional law, party law, municipal law, European law, and corporate law. His work employs doctrinal, comparative, economic, and empirical methodologies. His recent publications reflect a strong focus on diversity in law, algorithmic decision-making systems, digitalization's impact on legal frameworks, and the intersection of constitutional principles with contemporary social challenges. The trend in his scholarship shows increasing attention to how legal systems can accommodate diversity while maintaining constitutional principles, with growing emphasis on digital governance and algorithmic fairness. 2005 Dissertation Prize by the University of Münster 2015 Prize for the Promotion of Young Academics by the University Society of Münster Member of Young Academy at Brandenburg Academy of Sciences and Leopoldina (2011-2016) As Co-Editor in Chief of the German Law Journal since 2016 (previously Editor since 2011), Towfigh has significantly shaped scholarly discourse in comparative constitutional law. His leadership extends to directing the BRYTER Center for Digitalization & Law, which focuses on legal education in the digital age and the intersection of law and technology. He also heads the Center for Diversity in Law, examining how legal systems can better address diversity perspectives. Towfigh serves on the supervisory board of Freudenberg SE and as a member of the National Spiritual Assembly of the Bahá'í Community in Germany. His professional memberships include the Vereinigung der Deutschen Staatsrechtslehrer, International Society of Public Law (ICON•S), and Society for Empirical Legal Studies. Through the BRYTER Center, Towfigh has pioneered innovative teaching approaches including 'Legal Engineering' courses and workshops on legal tech automation. His 'Smartbook Fundamental Rights' integrates 67 learning videos with traditional legal education. The Center for Diversity in Law under his direction examines diversity perspectives in legal research, law as an instrument for managing human diversity, and legal pluralism.
