Julia Netter is an Assistant Professor of the Practice of Computer Science and Philosophy at Brown University. She serves as Research Interests Coordinator for the university's Socially Responsible Computing Program within the Computer Science Department. Her work bridges political philosophy, ethics in technology, and moral pluralism. She can be reached at jnetter@cs.brown.edu . Her research focuses on challenges posed by moral disagreement to liberal political theory, including topics like reasonable coercion and the ethics of technology. Office hours are held by appointment in Arnold Lab 309. Netter's publications explore intersections of political liberalism and computational ethics, as seen in her 2017 article on moral pluralism and 2013 work analyzing unreasonable views in liberal frameworks. She has no listed awards but actively contributes to interdisciplinary academic programs at Brown.
Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.
Simon Reginald Barker is a Lecturer in Philosophy at the University of Tartu's Institute of Philosophy and Semiotics within the Faculty of Arts and Humanities. He has held visiting and adjunct roles at institutions including the University of Sheffield, Tallinn University, and the University of Iceland. His academic background includes a PhD in Philosophy from the University of Sheffield (2020), supervised by Miranda Fricker and others, focusing on disagreement and self-trust, and a PhD in Classics from Royal Holloway, University of London (2008), examining Stoic and Epicurean ethics. His research interests span epistemology, ethics, metaphysics, and the intersection of mental health with philosophical inquiry. Notable work includes exploring epistemic self-trust in contexts of bipolar disorder and analyzing epistemic norms in deep disagreement scenarios. He has contributed to journals like Synthese and Episteme , and his interdisciplinary work includes studies on cultural practices like breakdancing. Barker's academic trajectory reflects a commitment to bridging theoretical philosophy with applied ethical and social questions. His recent publications highlight the epistemic dimensions of mental health crises in academia and the philosophical implications of conspiracy theories.
Bo Han is an Associate Professor in the Department of Computer Science at Hong Kong Baptist University's Faculty of Science, where he leads the Trustworthy Machine Learning and Reasoning (TMLR) Group. He also holds a visiting scientist position at the RIKEN Center for Advanced Intelligence Project (RIKEN AIP) in Japan. His research focuses on developing trustworthy and efficient machine learning systems, particularly under imperfect data conditions such as noisy labels, out-of-distribution data, and weak supervision. Bo Han's research interests span Machine Learning , Deep Learning , Foundation Models , Causal Representation Learning , Weakly and Self-supervised Learning , Robustness and Security in Machine Learning , Federated Learning , and AI for Science . His work aims to build intelligent systems that can reliably learn and reason from complex, imperfect real-world data. His recent publications reveal a strong trend toward trustworthy foundation models , robust reasoning with large language models , out-of-distribution detection , privacy-preserving learning , and causal robustness . His research integrates theoretical foundations with practical applications, often published in top-tier venues like NeurIPS, ICML, ICLR, and TPAMI. Notable Awards and Honors: Outstanding Paper Award, NeurIPS Most Influential Paper, NeurIPS IEEE AI's 10 to Watch Award IJCAI Early Career Spotlight INNS Aharon Katzir Young Investigator Award Dean's Award for Outstanding Achievement RGC Early CAREER Scheme Bo Han has been actively involved in the academic community, serving as a Senior Area Chair and Area Chair for NeurIPS, ICML, and ICLR, and as an Associate Editor for IEEE TPAMI, MLJ, and JAIR. He has advised numerous PhD and research students and leads a globally distributed research group. His work is supported by major grants from RGC, NSFC, GDST, RIKEN, and industry partners including Microsoft, Alibaba, Tencent, and Baidu. He also leads research initiatives in Trustworthy Machine Learning , including projects on federated learning, model unlearning, privacy-preserving AI, and robust foundation models, often in collaboration with industry and international institutions.
Sophie Horowitz is an Associate Professor of Philosophy at the University of Massachusetts Amherst, where she has been a core faculty member since 2016. She currently chairs the Climate Committee and maintains active teaching responsibilities, including regular instruction in Medical Ethics. Prior to UMass, she served as an Assistant Professor at Rice University from 2014 to 2016, following her PhD completion at MIT. Her educational background includes: BA in Philosophy and Studio Art from Swarthmore College (2008) PhD from MIT (2014), with a dissertation examining the relationship between epistemic rationality and truth Horowitz's research centers on epistemology, specifically dissecting the interplay between rationality and truth through formal frameworks. She investigates higher-order evidence, permissivism (the Uniqueness Thesis), accuracy norms, and partial belief structures, while also exploring ethical dimensions of belief formation and practical rationality. Her work bridges traditional epistemological questions with mathematical precision, often utilizing epistemic utility theory to analyze truth-conducive belief practices. She has contributed influential perspectives on when evidence demands belief changes and how rational agents should handle conflicting epistemic inputs. Her publication trends reveal deep engagement with epistemic normativity across three distinct phases: early work on epistemic akrasia and rationality (2013-2015), mid-career focus on evidence aggregation and transformative experience (2015-2019), and recent contributions to permissivism debates and credal dynamics (2021-2025). Articles consistently target top philosophy journals while addressing foundational questions about truth, evidence, and rational constraints. Scientific recognition includes: 2015 Marc Sanders Prize in Epistemology for "Accuracy and Educated Guesses" Horowitz demonstrates significant teaching activity across institutions, with Medical Ethics being a recurring course at UMass. She actively shares pedagogical tools like annotated student papers and grading rubrics, indicating commitment to educational innovation. The texts confirm no formal advisees or grant projects are documented, though she co-teaches seminars and has developed specialized courses on higher-order evidence. Her academic service extends to editorial contributions, notably for the Stanford Encyclopedia of Philosophy entry on higher-order evidence. Outside academia, she maintains a documented practice as an oil painter focused on food subjects, reflecting her dual background in philosophy and studio art.
Cecilia R. Aragon is a Professor in the Department of Human Centered Design & Engineering at the University of Washington, where she also serves as an Adjunct Professor in Computer Science & Engineering, Electrical and Computer Engineering, and the Information School. She is additionally a Senior Data Science Fellow at the eScience Institute. Aragon directs the Human-Centered Data Science Lab and has made significant contributions at the intersection of human-computer interaction and data science. Her research interests focus on human-centered data science, human-centered artificial intelligence, human-centered machine learning, human-computer interaction (HCI), computer-supported cooperative work (CSCW), visual analytics, aviation and astronautics sociotechnical systems, and emotion in informal text communication. Aragon's work bridges technical and social aspects of data science, particularly examining how humans interact with and gain insight from large datasets through both quantitative and qualitative methods. Aragon's recent publications demonstrate a strong focus on understanding online communities, sentiment analysis, distributed mentoring systems, and the ethical implications of AI. Her work spans multiple disciplines including social computing, data visualization, and astrophysics data analysis, showing her interdisciplinary approach to human-centered data science. Presidential Early Career Award for Scientists and Engineers (PECASE) 2008 Fulbright Fellowship 2017-18 HCDE Faculty Innovator in Research Award, University of Washington, 2015 Distinguished Alumni Award, Computer Science, University of California, Berkeley, 2013 Top 25 Women of the Year, Hispanic Business Magazine, 2009 Aragon has secured over $28 million in research funding from organizations including the National Science Foundation, National Institute of Standards and Technology, Department of Energy, Gordon and Betty Moore Foundation, Alfred P. Sloan Foundation, Washington Research Foundation, and industry partners like Microsoft and Intel. Her educational background includes a Ph.D. in Computer Science from UC Berkeley (2004), an M.S. in Computer Science from UC Berkeley, and a B.S. with Honors in Mathematics from Caltech. She leads the Human-Centered Data Science Lab and is affiliated with the eScience Institute, the Nearby Supernova Factory, and various research groups focused on data-intensive scientific collaborations. Her work on collaborative visual analytics systems like Sunfall has had significant impact in both academic and applied settings.
Christian Pascal Hirsch is an Associate Professor for Data Science and Statistics at the Department of Mathematics, Aarhus University. His research focuses on random networks inspired by biology and health sciences, utilizing techniques from topological data analysis and stochastic geometry. He is affiliated with the Stochastics group, AU DIGIT Centre, and AU Quantum Campus. Research Interests: Topological data analysis, large deviations theory, spatial random networks, and stochastic geometry. His work includes studies on percolation theory, Gibbs measures, and applications to neural networks and geometric functionals. Publications span journals such as the Journal of Applied and Computational Topology, Journal of Statistical Physics, and Stochastic Processes and Their Applications, covering topics from network topology to Poisson approximation.
Andreas Holzinger is a Professor at Graz University of Technology, with additional affiliations at Medical University Graz and University of Natural Resources and Life Sciences Vienna in Austria. He is recognized as an IFIP Fellow (2021) for his significant contributions to information processing and computer science. His work spans multiple institutions across Europe, with notable collaborations extending to the University of Alberta in Canada. Professor Holzinger's research focuses on Human-Centered AI, Explainable AI (XAI), and their practical applications across diverse domains. His work bridges theoretical AI advancements with real-world implementations in healthcare, forestry, and human-robot interaction. He has pioneered approaches in counterfactual explanations, graph neural networks, and human-in-the-loop systems that emphasize transparency and trustworthiness in AI decision-making processes. His recent publications demonstrate a strong trend toward integrating large language models with traditional AI systems while maintaining explainability. Holzinger's work consistently emphasizes the human element in AI systems, ensuring that technological advancements serve human needs rather than obscuring decision processes. His research in medical AI, smart forestry, and agricultural applications shows a commitment to solving practical problems with human-centered technological solutions. Scientific Awards: IFIP Fellow (2021) Professor Holzinger has been instrumental in establishing design guidelines for explainable AI systems, particularly through his work on post-hoc versus ante-hoc explanations. His research on Kandinsky Patterns has provided valuable experimental frameworks for pattern analysis and machine intelligence. He has secured significant research funding for projects bridging AI with practical applications in healthcare and environmental monitoring. His leadership extends to the organization of major conferences and workshops, including the CD-MAKE conference series, where he has fostered interdisciplinary collaboration between AI researchers and domain experts. His work on the CLARUS platform demonstrates practical implementations of interactive explainable AI for medical applications.
Christian Hirsch is an Associate Professor for Data Science and Statistics at Aarhus University, where he studies random networks motivated from biology and health sciences through techniques from topological data analysis and stochastic geometry. He is a member of the Stochastics group at the Department of Mathematics and holds additional affiliations as an Associate Fellow of the Aarhus Institute for Advanced Studies, and with the AU DIGIT Centre and the AU Quantum Campus. Current Position: Associate Professor for Data Science and Statistics, Aarhus University Previous Positions: Assistant Professor at University of Groningen and University of Mannheim Postdoctoral Experience: Aalborg University, LMU Munich, WIAS Berlin Education: PhD from Ulm University Christian Hirsch's research focuses on the statistical foundations of topological data analysis, large deviations theory in stochastic geometry, and percolation theory of spatial random networks. His work bridges theoretical mathematics with practical applications in data science, particularly in analyzing complex structures through topological methods. He investigates how topological features form and disappear in growing data structures, developing statistical tests to determine whether observed patterns are significant or merely random occurrences. His recent publications reveal a strong trend toward applying topological data analysis to increasingly complex structures, with significant focus on statistical validation of topological features. Hirsch has made substantial contributions to understanding the probabilistic behavior of persistent homology, developing functional central limit theorems and large deviation principles for topological functionals. His work spans theoretical foundations in stochastic geometry while finding applications in materials science, neural networks, and wireless communication systems. As an educator, Hirsch teaches graduate courses including Topological Data Analysis, Stochastic Geometry, Monte Carlo Simulation, Markov Decision Processes, Probability Theory, and Stochastic Processes. He has supervised numerous PhD, MSc, and BSc students, with several of his former students securing academic positions at institutions like University of Leiden, Tokyo Institute of Technology, and Budapest University of Technology. Hirsch leads a research group within the Stochastics group at Aarhus University, collaborating extensively with researchers across Europe and North America. His work demonstrates how topological methods can provide rigorous statistical insights into complex data structures, making significant contributions to both theoretical mathematics and practical data analysis techniques.
Cécile Laborde is the Nuffield Professor of Political Theory at the University of Oxford and a Fellow of the British Academy. She holds a position in the Department of Politics and International Relations (DPIR) and is affiliated with Nuffield College. Previously, she was a Professor of Political Theory at University College London, and has held permanent posts at the University of Exeter and King's College London. She also served as Associate Professor at the École des Hautes Études en Sciences Sociales in Paris and was a Fellow at the Institute for Advanced Study in Princeton during the 2010-11 academic year. Professor Laborde received her DPhil from Oxford University in 1996, where she was a Rhodes Scholar, after studying political science in France. Her academic journey reflects a deep commitment to political theory across multiple prestigious institutions in the UK, France, and the United States. Her research focuses on the intersection of political philosophy, secularism, and equality. Laborde's work explores how republican theories of freedom relate to issues of discrimination, particularly concerning race and gender. She has made significant contributions to understanding secularism beyond Western contexts, notably through her analysis of Indian secularism. Her approach often challenges conventional wisdom about the relationship between liberalism and religion, arguing for a more nuanced understanding of religious freedom within liberal democracies. Professor Laborde has been recognized with numerous prestigious awards, including the Spitz Prize in 2019 for her book "Liberalism's Religion." She is a Fellow of the British Academy and was elected to the Royal Academy of Belgium in December 2022. Her work has been supported by significant grants, including a European Research Council (ERC) personal grant that funded UCL's Religion and Political Theory Centre, which she directed. As an academic mentor, Laborde supervises several doctoral students including María-José Gómez Ruiz, Cecile Degiovanni, Simeon Goldstraw, and Samuel Burry. She convenes the Nuffield Political Theory Workshop, fostering scholarly exchange in her field. Her research continues to influence debates on secularism, republicanism, and equality across multiple national contexts.
Ludvig Beckman is a Professor at the Department of Political Science, Stockholm University, specializing in democratic theory, political legitimacy, and the boundaries of inclusion in political systems. His work critically examines foundational concepts like popular sovereignty, voting rights, and the impact of emerging technologies on democratic governance. Research Focus: Beckman's scholarship centers on three interconnected themes: (1) The conceptual and practical challenges of defining the 'demos' in democratic systems, particularly regarding marginalized groups, Indigenous peoples, and non-human entities like AI; (2) The legitimacy of state authority in transnational contexts (e.g., extraterritorial border controls); and (3) The role of public institutions in sustaining democratic discourse amidst digital disruption and populist threats. Active Research Projects: Reconstructing democracy in times of crisis (REDEM): Voter behavior analysis for democratic resilience. Den digitala offentlighetens begränsningar: Regulatory impacts of social media on democratic discourse. Det demokratiska självförsvarets dilemman: Public service media responses to populism/extremism in Europe. Globalisering och nya politiska rättigheter: Challenges to nation-states from self-determination claims. Vilka är folket i folkstyret?: Comparative analysis of national/Indigenous constitutional orders.
Rev. Dr. Michael Hakmin Lee is Associate Professor of Ministry & Leadership and Program Director of three M.A. programs (M.A. Evangelism & Leadership, M.A. Ministry Leadership, M.A. Missional Church Movements) at Wheaton College. He holds a Ph.D. in Intercultural Studies from Trinity Evangelical Divinity School, a Th.M. in Systematic Theology from Dallas Theological Seminary, and a B.A. in Biochemistry from the University of Texas at Austin. Ph.D., Intercultural Studies – Trinity Evangelical Divinity School Th.M., Systematic Theology – Dallas Theological Seminary B.A., Biochemistry – University of Texas at Austin Dr. Lee's research centers on missiology, intercultural studies, religious deconversion, race and ethnicity, theology of religions, and the social impact of technology. He explores how contemporary challenges—such as AI, social media, and religious pluralism—affect Christian discipleship and gospel witness. His work bridges theological reflection with practical ministry engagement. His recent and forthcoming publications reveal a strong trend in analyzing digital culture, deconversion, and interfaith dynamics. He investigates how artificial intelligence and social media reshape disciple-making, while also addressing deep existential questions behind why evangelicals leave the faith. His scholarship integrates interdisciplinary perspectives from theology, sociology, and communication studies. Dr. Lee is an active scholar in the Evangelical Missiological Society, where he currently serves as VP of Finance. He has contributed to numerous peer-reviewed journals and edited monograph series, reflecting sustained academic engagement. He advises on graduate theological education and has led initiatives in distance learning pedagogy. Though no formal advisees are listed, his leadership in M.A. programs suggests significant mentorship. He is also involved in community service as a church elder, certified judo instructor, and youth baseball coach, reflecting a holistic integration of faith and vocation. Dr. Lee is affiliated with Wheaton College’s College of Ministry and Leadership and contributes to the mission of advancing evangelical scholarship and practice in a changing world.
Fosca Giannotti is a Full Professor at Scuola Normale Superiore in Pisa, Italy, and leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR. Founded in 1994, the Pisa KDD Lab is one of the earliest research labs focused on data mining. Giannotti is a pioneering scientist in mobility data mining, social network analysis, and privacy-preserving data mining. Her educational background includes a Master Degree in Computer Science from the University of Pisa (1982) with 110/100 cum laude. She has held numerous visiting positions including at MCC in Austin, CWI Amsterdam, UCLA, and the Barabasi Lab at Northeastern University. Giannotti's research focuses on social mining from big data, encompassing smart cities, human dynamics, social and economic networks, ethics and trust, and diffusion of innovations. She has authored more than 300 papers and coordinated tens of European projects and industrial collaborations. Her current work increasingly centers on Explainable AI (XAI), as evidenced by her prestigious ERC Advanced Grant for the XAI project focused on "Science and technology for the explanation of AI decision making." Her recent publications reveal a strong emphasis on trustworthy AI, with research spanning privacy-preserving techniques, fairness in machine learning, human-AI collaboration frameworks, and medical applications of explainable AI. The breadth of her work demonstrates how data mining principles are being applied across diverse domains from social sciences to healthcare. ERC Advanced Grant for XAI project Premio Internazionale Tecnovisionarie 2021 Intelligenza Artificiale Giannotti has coordinated numerous significant projects including SoBigData (the European research infrastructure on Big Data Analytics and Social Mining), XAI, TAILOR (Foundations of Trustworthy AI), HumanE-AI-Net, and AI4EU. As former coordinator of SoBigData, she led an ecosystem of ten cutting-edge European research centers providing an open platform for interdisciplinary data science. She leads the Pisa KDD Lab, which serves as a hub for research on knowledge discovery and data mining. The lab has been instrumental in developing techniques for mobility data analysis, social network mining, and privacy-preserving data analytics, with applications ranging from smart cities to pandemic response.
Julia Christiane Gabriela Netter is an Assistant Professor at Brown University, jointly affiliated with the Department of Computer Science and the Department of Philosophy. Her work bridges technical and ethical dimensions of digital technologies, focusing on responsible computer science, data politics, and moral pluralism. DPhil (2018) and MPhil (2013) in Philosophy from the University of Oxford BA (2011) from Otto Friedrich University and Universität Bamberg Her research explores intersections of ethics, political philosophy, and technology governance. Key themes include: Ethical frameworks for digital technology and data practices Moral pluralism in algorithmic decision-making Legitimacy of coercion in liberal democratic systems Philosophical foundations of responsible AI Recent publications analyze challenges to liberal political theory from unreasonable perspectives and the role of reasonableness in digital governance. She teaches courses on ethics of digital technology, politics of data, and moral pluralism, emphasizing practical applications in computer science education.
Robert B. Talisse is W. Alton Jones Professor of Philosophy and Professor of Political Science at Vanderbilt University, where he also serves as Chair of the Philosophy Department. He is a leading figure in contemporary political philosophy, with a focus on democracy, pluralism, and moral disagreement. Institution: Vanderbilt University School: College of Arts and Science Department: Philosophy Rank: Professor His research centers on democratic theory, particularly from a pragmatist epistemological perspective. He explores how democratic institutions can function amid deep moral disagreement, drawing on the work of Charles S. Peirce to defend democracy not on moral but epistemic grounds. His work bridges American pragmatism, social epistemology, and argumentation theory, emphasizing the role of inquiry and reason in sustaining democratic life. His recent publications reveal a consistent focus on the challenges of over-politicization, the need for civic distance, and the epistemic foundations of democratic legitimacy. Books like Overdoing Democracy and Civic Solitude analyze the psychological and social costs of political saturation, while earlier works like Democracy and Moral Conflict and A Pragmatist Philosophy of Democracy lay the theoretical groundwork for his epistemic defense of democracy. He is actively engaged in public philosophy through multiple platforms: Host of the podcast Why We Argue Co-host of New Books in Philosophy Monthly columnist for 3 Quarks Daily These initiatives reflect his commitment to making philosophical ideas accessible and relevant to broader public discourse. While no formal list of students or awards is provided, his leadership role and extensive publication record suggest a significant influence on students and the academic community.
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