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Dong XuView profile

Professor

• Decision Analysis under Uncertainties
• Decision Theory
• Utility Theory
• +7 more

Prof. Dong Xu is a Professor of Decision Sciences & Systems at the University of Manchester's Management Sciences School. Her research focuses on decision analysis under uncertainties, utility theory, and optimization, with applications in performance assessment for supplier selection, environmental impact, and sustainability. She leads the Decision and Cognitive Sciences Research Centre and the Data Science Institute. Teaching includes MBA/PhD supervision and courses like Risk Analysis, Decision Modeling, and Quantitative Methods. Her work contributes to UN Sustainable Development Goals through Digital Futures and the Christabel Pankhurst Institute. Research interests span evidential reasoning, decision-making frameworks, and their applications in healthcare, finance, and engineering. She has supervised 25 students and co-authored 170+ publications. Collaborations include studies on AI-human collaboration in FinTech and data-driven decision models for healthcare outcomes. Labs/Teams: Decision and Cognitive Sciences Research Centre, Data Science Institute.

Luca BenedettoView profile

Research Fellow

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +3 more

Dr Luca Benedetto is a Research Fellow in the Department of Computer Science and Technology at the University of Cambridge. His work focuses on applying Natural Language Processing (NLP), Machine Learning, and Artificial Intelligence to educational technology, particularly in areas such as question difficulty estimation, large language model (LLM) applications in language teaching, and automated assessment systems. His research themes include: Natural Language Processing for language assessment Machine Learning-driven curriculum design AI-enhanced educational tools for personalized learning Key contributions include developing frameworks for estimating question difficulty using knowledge graphs and transformers, simulating student exam responses via LLMs, and creating the Cambridge Multiple-Choice Questions Reading Dataset. His work bridges computational methods with practical educational needs, aiming to improve automated evaluation and adaptive learning systems. Dr Benedetto is affiliated with the William Gates Building at the University of Cambridge and can be reached at lb990@cam.ac.uk .

Zhiwei Steven WuView profile

Assistant Professor

• Machine Learning
• Algorithms
• Differential Privacy
• +6 more

Steven Wu is an Assistant Professor in the School of Computer Science at Carnegie Mellon University, with a primary appointment in the Software and Societal Systems Department and affiliations in the Machine Learning Department, Human-Computer Interaction Institute (HCII), CyLab, and the Theory Group. His research focuses on algorithms and machine learning, particularly in responsible AI, privacy, bias, and uncertainty. He has received funding from NSF CAREER, Okawa Foundation, Amazon, Google, and others. Research Interests: Foundations of responsible AI (privacy, bias, uncertainty) Interactive learning (imitation, reinforcement learning) Causal inference, game theory, econometrics, and language modeling Grants and Awards: NSF CAREER Award Okawa Foundation Award Amazon Research Award Google Faculty Research Award J.P. Morgan Faculty Awards Advising: Supervises PhD, master's, and undergraduate students across multiple programs, with notable alumni now at Amazon, Stanford, Tsinghua, and others. Leads the Tartan Federer team, which won all four tracks of The Vector Institute's MIDST challenge in 2025. Labs and Collaborations: Active in CyLab (CMU's cybersecurity institute) and the Theory Group, focusing on privacy-preserving machine learning and algorithmic fairness.

Roni RosenfeldView profile

Professor

• Epidemic Forecasting
• Computational Biology
• Machine Learning
• +4 more

Roni Rosenfeld is a Professor in the School of Computer Science at Carnegie Mellon University, holding joint appointments in Machine Learning, Language Technologies, Computer Science, and Computational Biology. He has served as Head of the Machine Learning Department from 2018 to 2024. His education includes a BSc in Mathematics and Physics from Tel Aviv University (1985) and a PhD in Computer Science from Carnegie Mellon University (1994). His research focuses on epidemic forecasting via the Delphi Group, named a National Center for Epidemic Forecasting by the U.S. CDC. Past work includes speech recognition, SLT4D (Spoken Language Technologies for Development), and ML4SG (Machine Learning for Social Good). He has advised over a dozen PhD students and mentored postdocs in epidemiology, computational biology, and speech technologies. Rosenfeld has published 150+ peer-reviewed articles and received the Spira Teaching Excellence Award (2017) and Allen Newell Medal for Research Excellence (1992, 2022). His current projects emphasize real-time epidemic tracking, public health data quality, and collaborative forecasting frameworks. Key collaborations include the CDC-funded Delphi Group’s work on influenza, dengue, and pandemic surveillance systems. He also pioneered viral spread analysis in low-literacy regions through speech-based technologies, addressing global development challenges.

Chris BarkerView profile

Professor

• Linguistics
• Formal Semantics
• Syntax-Semantics Interface
• +3 more

Chris Barker is a Professor of Linguistics at New York University, specializing in formal semantics, syntax-semantics interfaces, and quantifier scope phenomena. His work integrates type-logical grammar with empirical linguistic analysis. Research focuses on scope islands, anaphora resolution, and syntactic discontinuity, with notable contributions to quantifier raising and polarity sensitivity theories. Key research interests include the formal analysis of possessive constructions, evaluation order effects in syntax, and the logical structure of linguistic meaning. He has extensively explored issues like crossover constraints, reconstruction, and the role of continuations in natural language semantics. His publications span over three decades, addressing topics from dynamic semantics to syntactic constraints on scope ambiguity. Barker’s work bridges theoretical linguistics with computational models, emphasizing the interplay between syntax, semantics, and pragmatics.

Colin KleinView profile

Professor

• Philosophy of Mind
• Cognitive Science
• Artificial Intelligence
• +5 more

Colin Klein is a Professor in the School of Philosophy at The Australian National University. His research spans philosophy of mind, cognitive science, artificial intelligence, and social epistemology. He leads major interdisciplinary projects such as the International Climate Psychology Collaboration, investigating behavioral interventions across 63 countries, and studies the ethical implications of AI and cognitive automation. Key projects include the ANU Futures Scheme exploring artificial intelligence comparisons, and Trust and Distrust in Social Epistemic Networks analyzing digital trust dynamics. Klein’s work bridges philosophy with empirical science, addressing topics like pain perception, climate change behavior, and algorithmic bias in generative AI systems. His recent research emphasizes computational models of cognition, moral language processing via tools like Mformer, and the philosophical implications of machine learning in neuroscience. Klein actively collaborates internationally, contributing to global initiatives on behavioral science and policy design.

Daoyi DongView profile

Professor

• Quantum control
• Machine learning
• System identification
• +3 more

Prof. Daoyi Dong is a Professor and ARC Future Fellow at the School of Engineering, The Australian National University (ANU), and an IEEE Fellow. He holds a B.E. (2001) and Ph.D. (2006) from the University of Science and Technology of China. His research focuses on quantum control, machine learning, system identification, and renewable energy systems. He has received prestigious awards including the Humboldt Research Fellowship and the ACA Temasek Young Educator Award. Education: B.E., University of Science and Technology of China (2001) Ph.D., University of Science and Technology of China (2006) Research Interests: Quantum control and stabilization Machine learning applications in quantum systems System identification and optimization Renewable energy systems and microgrids Key Contributions: Developed quantum tomography methods using neural networks Advanced reinforcement learning for quantum gate design Optimized energy management strategies for community microgrids Awards: ARC Future Fellowship (Australia) Humboldt Research Fellowship (Germany) ACA Temasek Young Educator Award (Asia) Grants & Editorial Roles: Recipient of Australian Research Council grants (Discovery, International) Associate Editor: IEEE Transactions on Neural Networks, Cybernetics, and Mechatronics Labs & Collaborations: Active in quantum control and energy systems research, collaborating with global institutions including the Alexander von Humboldt Foundation and the Asian Control Association.

John BagbyView profile

Assistant Professor

• Phenomenology
• History of Philosophy
• Process Philosophy
• +4 more

John (Jack) Bagby is an Assistant Professor at the School of Consciousness and Transformation, California Institute of Integral Studies. He holds a PhD in philosophy from Boston College and a B.A. in philosophy and ancient Greek language from Pennsylvania State University. His research spans phenomenology, process philosophy, philosophy of music, and the evolution of consciousness, with particular focus on Aristotle, Bergson, and Spinoza. Bagby explores how philosophical frameworks intersect with ecological awareness and transdisciplinary methodologies. His publications demonstrate a consistent focus on reconstructing historical philosophical arguments—especially concerning temporality, psychical activity, and ethics—while developing integrative approaches to contemporary philosophical questions.

Elisabetta SacchiView profile

Associate Professor

• Philosophy of Language
• Philosophy of Mind
• Intentionality
• +5 more

Elisabetta Sacchi is an Associate Professor in Philosophy of Language at the Faculty of Philosophy, Vita-Salute San Raffaele University, Milan. She holds a permanent Research Fellow position since 2008 and teaches Theories of Communication in the undergraduate program. Her academic journey includes teaching roles at the University of Bologna, University of Padua (Philosophy of Language and Philosophy of Mind), and the University of Modena and Reggio Emilia. PhD in Philosophy of Language (University of Padua) Degree in Philosophy, cum laude (University of Bologna) Visiting student at Oxford University Her research focuses on Philosophy of Language and Philosophy of Mind , with specific interests in intentionality, singular reference, content individuation, ontology of thought, and cognitive externalism. She has published extensively on these topics, including two books and numerous papers in international journals. Her recent work explores the intersection of ontology and the metaphysics of mind. Key trends in her publications include logical foundations of singular reference, ontology of propositions, and the graspability of Fregean concepts. She has contributed to edited volumes and conference proceedings, often collaborating with scholars like Massimiliano Carrara and Annalisa Coliva. Board Member, Italian Society for Analytic Philosophy (SIFA) (2004-2008) Her career spans interdisciplinary collaborations, including work on the ontological commitment of natural and formal languages, and translations of seminal works by Sellars and Putnam into Italian.

Lukas MuttenthalerView profile

Researcher

• Computer Vision
• Cognitive Science
• Computational Neuroscience
• +3 more

Lukas Muttenthaler is a Senior ML Research Scientist at Aignostics and a part-time Senior Researcher at TU Munich's Computer Vision Explainable Machine Learning Group . His research focuses on representation learning in computer vision, human-machine alignment, and cognitively-inspired ML. He holds a PhD from TU Berlin (summa cum laude), MSc in IT & Cognition from University of Copenhagen, and BSc in Cognitive Psychology from University of Vienna. Affiliations: TU Munich (part-time), Aignostics (full-time), previously at Google DeepMind, Max Planck Institute for Human Cognitive and Brain Sciences Key Collaborations: Simon Kornblith (Anthropic), Martin Hebart (MPI), Klaus-Robert Müller (TU Berlin) Research interests include representational alignment between humans and neural networks, computational neuroscience, and interpretable vision models. Notable contributions include the VICE framework for interpretable concept embeddings and the THINGSvision toolbox. Recipient of Google Research Collabs grant (2022), Best Demonstration Award (EDOC 2019), and multiple top-tier conference acceptances (NeurIPS, ICLR, ICML).

• Artificial Intelligence
• Cognitive Modeling
• Buddhist Philosophy
• +5 more

Justin Brody is an Assistant Professor of Computer Science at Franklin & Marshall College, with interdisciplinary interests spanning artificial intelligence, Buddhist philosophy, and cognitive modeling. His research explores self-awareness in AI systems, blending insights from mathematics, robotics, and Eastern philosophy. Prof. Brody holds a Ph.D. and M.S. from the University of Maryland, where he studied under Prof. Don Perlis. Before joining F&M, he served as an Associate Professor at Goucher College and a Visiting Assistant Professor at Franklin & Marshall. His research focuses on enabling AI agents to develop robust self-models through embodied cognition principles. Key projects include grounding self-awareness in robotic systems, exploring Buddhist concepts like agency, and developing logical frameworks for commonsense reasoning. He collaborates with institutions like the University of Maryland Institute for Advanced Computer Studies and anticipates interdisciplinary work with Philosophy, Psychology, and Religious Studies departments. Brody’s work bridges AI technical challenges with philosophical inquiry, addressing topics like agency detection, perspective-taking biases, and consciousness measurement. His teaching philosophy emphasizes student-driven exploration across conceptual, computational, and analytical dimensions of computer science.

• Medical Image Segmentation
• Deep Learning
• Computer-Aided Diagnosis
• +3 more

Zhe Liu is a researcher at Jiangsu University , School of Computer Science and Telecommunication Engineering, China. He has extensive collaborations across institutions including University of Edinburgh , IBM Almaden Research Center , and Nanyang Technological University . His research focuses on medical image segmentation , deep learning , and multimodal learning . Key areas include liver vessel segmentation , pancreas segmentation , lesion detection , and healthcare AI . He has developed frameworks like MMMViT and HI-Net to address challenges in missing modality handling and feature fusion . Recent publications highlight trends in 3D convolutional networks (RC-3DUNet with SOM), semi-supervised learning for segmentation, and anomaly detection in time-series medical data. His work often combines computer vision with clinical applications , emphasizing robustness and data efficiency . He has co-authored over 60 publications (2012-2025), frequently collaborating with Kai Han , Yuqing Song , and Victor S. Sheng on topics like medical imaging , deep learning , and biomedical signal processing .

Giorgio MarianiView profile

Researcher

• Generative Models
• Audio Generation
• Computer Graphics
• +3 more

Giorgio Mariani is a PostDoctoral Researcher at the University of Milano-Bicocca, having completed his Ph.D. in Computer Science at Sapienza, University of Rome under the supervision of Prof. Emanuele Rodolà. His work bridges theoretical machine learning with practical applications in audio processing and computer graphics. His primary research focuses on: Generative models, particularly autoregressive and diffusion-based approaches Audio and music synthesis technologies Computer graphics applications for animation and gaming Adversarial vulnerabilities in geometric data Mariani's publication trajectory shows significant progression from geometric deep learning toward advanced audio generation techniques. His recent work on music generation using diffusion models has been accepted at ICASSP 2024-2025, with 'Latent Autoregressive Source Separation' earning an oral presentation at ICLR 2024. His foundational work on 'Generating Adversarial Surfaces via Band-Limited Perturbations' (Computer Graphics Forum, 2020) established his expertise in 3D shape analysis security. Notable achievements include: Oral presentation at ICLR 2024 (top 5% acceptance rate) Multiple paper acceptances at ICASSP 2024 and upcoming 2025 conference Research bridging audio processing, computer graphics, and security domains As a postdoctoral researcher, Mariani continues to push boundaries in generative AI for audio applications while maintaining connections to his foundational work in 3D geometric data analysis, demonstrating exceptional interdisciplinary research capabilities.

Elizabeth BehrmanView profile

Professor

• Quantum Information Theory
• Quantum Computing
• Quantum Machine Learning
• +3 more

Elizabeth Behrman is a Professor at Wichita State University (WSU), affiliated with the Department of Mathematics, Statistics, and Physics within the Fairmount College of Liberal Arts and Sciences. She holds a Ph.D. from the University of Illinois at Urbana-Champaign (1985). Her research spans quantum computing, quantum machine learning, and quantum neural networks, with interdisciplinary collaborations in Mathematics, Electrical Engineering, Aerospace Engineering, and Chemistry. Her work includes pioneering studies on quantum control, entanglement estimation, and applications of quantum algorithms in fields like medical imaging and language processing. Key research interests include quantum information theory, quantum algorithms, and the integration of machine learning with quantum systems. Behrman’s contributions to quantum repeaters, quantum generative adversarial networks, and qutrit-based learning networks highlight her focus on advancing quantum technologies for practical applications. She has published extensively on topics ranging from quantum circuit design to noise-resilient algorithms. Collaborative projects involve optimizing quantum hardware through machine learning and exploring hybrid quantum-classical methods. Her work has been featured in venues like IEEE Transactions and YouTube, emphasizing both theoretical and experimental advancements. Behrman’s research also extends to historical contributions in materials science, including studies on ceramic superconductors and inorganic buckyballs. While no specific scientific awards are listed, her prolific publication record and interdisciplinary impact reflect significant contributions to quantum science. Her advising and grant activities are not detailed here, but her collaborations suggest active participation in research networks and funding initiatives.

James MickleyView profile

Lecturer

• Botany
• Plant Ecology
• Conservation Biology
• +3 more

James Mickley is an Instructor in the Department of Botany and Plant Pathology at Oregon State University (OSU), where he also serves as Curator of the OSU Herbarium. He holds a Ph.D. (2017, University of Connecticut), M.A. (2010, Stony Brook University), and B.A. (2008, Kalamazoo College). His research focuses on plant collections management, herbarium outreach, and ecological studies of plant-pathogen interactions, forest fragmentation impacts, and floral evolution. He teaches courses including BOT313 (Plant Structure), BOT325 (Plants and Humanity), and BOT425/525 (Flora of the Pacific Northwest). He leads the Oregon Flora Project collaboration to digitize 600,000 herbarium specimens and develop public access tools. His mentoring emphasizes skills training, fostering confidence in underrepresented students, and group-based learning. Notable awards include the 2023 OSU Ask Extension Answer of the Year Award and a 2015 Department Service Award. His professional activities include iNaturalist community engagement, GitHub repository development (e.g., environmental sensor systems), and contributions to open-access biodiversity databases. Current projects emphasize leveraging technology for ecological monitoring and public botanical education.