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Brian D. Earp is an Associate Professor of Biomedical Ethics within the Yong Loo Lin School of Medicine at the National University of Singapore (NUS) and by courtesy, Associate Professor of Philosophy and of Psychology. He also serves as a Research Associate of the Uehiro Oxford Institute at the University of Oxford, Director of the Oxford-NUS Centre for Neuroethics and Society, and Associate Director of the Yale-Hastings Program in Ethics and Health Policy. In 2022, he was elected to the UK Young Academy under the auspices of the British Academy and the Royal Society. Dr. Earp holds a Master of Philosophy in Philosophy of Science from the University of Cambridge (2014), a Master of Science in Experimental Psychology from the University of Oxford (2011), and a Bachelor of Arts in Cognitive Science from Yale University (2010). His academic journey reflects an interdisciplinary approach spanning cognitive science, psychology, and philosophy. Brian Earp's research spans multiple domains of ethics, with particular focus on AI ethics, neuroethics, and biomedical ethics. His work examines the ethical implications of emerging technologies, especially large language models and AI systems in healthcare settings. He has made significant contributions to understanding digital identity, surrogate decision-making, and the ethics of personalized AI applications in medicine. His research also extends to bioethics topics including genital autonomy, gender and sexuality, and the philosophy of science. Analysis of Dr. Earp's recent publications reveals a strong emphasis on the intersection of artificial intelligence and medical ethics, with particular attention to consent processes, decision-making in healthcare, and the implications of digital identity. His work demonstrates a consistent pattern of exploring how emerging technologies challenge traditional ethical frameworks while proposing novel conceptual approaches to address these challenges. The publications show increasing focus on cross-cultural perspectives, as evidenced by multi-country studies examining ethical perceptions of AI. Elected to the UK Young Academy under the auspices of the British Academy and the Royal Society (2022) Dr. Earp directs the Oxford-NUS Centre for Neuroethics and Society and serves as Associate Director of the Yale-Hastings Program in Ethics and Health Policy, indicating substantial leadership in collaborative research initiatives. His work on the Personalized Patient Preference Predictor (P4) represents a significant contribution to advancing surrogate decision-making in medical contexts. The collaborative nature of his research is evident through numerous co-authored publications addressing complex ethical questions at the intersection of technology and healthcare. As Director of the Oxford-NUS Centre for Neuroethics and Society and HOPE (Hub at Oxford for Psychedelic Ethics), Dr. Earp leads interdisciplinary teams examining the ethical dimensions of neurotechnology and psychedelic medicine. His work bridges academic institutions across Singapore, the UK, and the US, fostering international collaboration on pressing ethical challenges in emerging medical technologies.

• Bioethics
• AI Ethics
• Neuroethics
• +7 more

Jonas Geiping is a Professor at the ELLIS Institute Tübingen, leading the Safety- and Efficiency- aligned Learning research group. He has previously worked at the University of Maryland, University of Siegen, and University of Münster. His research focuses on safety and efficiency in machine learning, exploring data poisoning principles, watermarking for generative models, privacy in federated learning, and adversarial attacks against large language models. He also investigates how to make AI systems more efficient through weight averaging, recursive computation, and computational constraint analysis. His recent work includes test-time computation scaling using recurrent depth approaches, adversarial attacks on LLMs beyond jailbreaking, and zero-shot detection of machine-generated text through contrasting LLMs (Binoculars method). He has contributed to arithmetic capabilities in transformers with positional embeddings and scalable LLM training frameworks like AxoNN. His research addresses critical questions about the intersection of safety and efficiency in AI systems: Can models reason well without sacrificing safety? How do computational constraints affect safety guarantees? Can systems be designed where intelligence and safety reinforce each other?

• Machine Learning
• AI Safety
• Efficient AI Systems
• +4 more

Paul Robinette serves as Associate Professor and Associate Chair for Master of Science Programs in the Electrical and Computer Engineering Department at the Francis College of Engineering, University of Massachusetts Lowell. He maintains significant affiliations with the Printed Electronics Research Collaborative (PERC) and the Raytheon UMass Lowell Research Institute (RURI), where his robotics research integrates printed electronics for field-deployable systems. His office resides in Ball Hall's third floor, with primary contact at Paul_Robinette@uml.edu. Dr. Robinette earned his Ph.D. from the Georgia Institute of Technology, establishing his foundation in robotics and human-systems engineering. This academic background directly informs his experimental approach to human-robot interaction challenges. His research centers on trust dynamics in human-robot teams, particularly examining how moral violations versus performance failures impact trust retention. He investigates drone appearance effects on trust calibration, multi-robot coordination during search and rescue, and trust recovery mechanisms after system malfunctions. His experimental work spans marine environments using platforms like Robowhaler, subterranean scenarios, and emergency evacuation simulations—consistently bridging theoretical AI frameworks with real-world human factors. Analysis of his 2023-2025 publications reveals three dominant trends: 1) Quantitative validation of trust metrics across simulation and reality, 2) Development of relational network architectures for resilient multi-agent teams, and 3) Ethical frameworks for moral trust violations in autonomous systems. His work uniquely integrates reinforcement learning with psychological models to create beneficent AI systems that respect human trust boundaries. As Associate Chair for Master's Programs, Dr. Robinette oversees graduate curriculum development and student mentorship within electrical and computer engineering. His research leadership through PERC and RURI facilitates cross-disciplinary collaboration between robotics, printed electronics, and defense applications—though specific grant details remain unspecified in available materials. He directs experimental robotics teams developing platforms such as Robowhaler for marine autonomy and dataset collection. His lab maintains the publicly available Aquaticus dataset for human-robot teaming research and contributes to standardization efforts like the DECISIVE Test Methods Handbook for subterranean robotics evaluation. Current projects focus on real-world trust validation in navigation deviation scenarios and moral trust repair protocols.

• Human-Robot Interaction
• Trust in Autonomous Systems
• Multi-Robot Coordination
• +4 more

Blaise Agüera y Arcas serves as an External Professor at the Santa Fe Institute while holding the position of Vice President and Fellow at Google, where he functions as Chief Technology Officer of Technology & Society. He founded and leads Paradigms of Intelligence (PI), an organization dedicated to foundational research in artificial intelligence with emphasis on neural computing, evolution, and Artificial Life. His career uniquely integrates theoretical inquiry with practical engineering breakthroughs that shape modern AI infrastructure. His research program investigates the computational principles underlying life, evolution, and intelligence through symbiotic frameworks. Key contributions include inventing Federated Learning for privacy-preserving decentralized training, pioneering on-device AI for Android/Pixel ecosystems, and establishing the Artists + Machine Intelligence program. Current work spans AI ethics, medical applications, and existential questions about life and intelligence, reflecting an interdisciplinary approach bridging computer science, biology, and philosophy. He actively publishes in high-impact venues while engaging public discourse through TED talks and NeurIPS keynotes. Analysis of Blaise's 2023-2025 publications reveals three dominant trajectories: (1) Privacy-centric AI architectures like Federated Learning applied to healthcare and audio processing, (2) Philosophical examinations of life and intelligence through computational models, and (3) Critical analyses of AI's societal impact including ethical frameworks and existential risk debates. His scholarship increasingly integrates medical applications with foundational AI research while maintaining strong engagement with artistic and humanistic perspectives. His scientific recognition includes: MIT TR35 prize (2008) for pioneering contributions to location-based services and image search As founder of Paradigms of Intelligence and leader of Artists + Machine Intelligence, Blaise directs research initiatives that secure substantial institutional resources at Google. His work on Federated Learning has generated foundational patents and industry-wide adoption, while the Artists + Machine Intelligence program has cultivated a vibrant ecosystem of creative technologists. Though specific grant figures aren't public, his position as VP and Fellow indicates significant research funding allocation. Blaise established Paradigms of Intelligence as his primary research laboratory investigating life-intelligence foundations through computational models and neural architectures. The Artists + Machine Intelligence program functions as a specialized creative research collective, while his Google leadership roles connect him to broader AI infrastructure teams developing on-device intelligence and privacy-preserving systems.

• Artificial Intelligence
• Machine Learning
• Artificial Life
• +5 more

Prateek Mittal is a Professor in the Department of Electrical and Computer Engineering at Princeton University, with associated faculty appointments in the Department of Computer Science and the Center for Information Technology Policy. His leadership roles include Associate Chair of the ECE Department (2025) and Director of Undergraduate Studies (2025), demonstrating his significant institutional impact. Mittal's research focuses on privacy-preserving and secure systems, with particular expertise in privacy enhancing technologies (including anonymous communications and statistical data privacy), adversarial machine learning, and Internet/network security. His methodological approach draws on data science, network science, distributed systems, and applied cryptography. He has made foundational contributions to website fingerprinting research, developing precision optimizers that revolutionized open-world traffic analysis attacks. His recent publications reveal a strategic shift toward examining security and privacy challenges in large language models and AI systems, with research on context manipulation attacks, privacy auditing frameworks, and robust defenses against adversarial inputs. This represents a natural evolution of his work from traditional network security to the frontier of AI security. Outstanding Paper Award and Honorable Mention, ICLR 2025 ACM Distinguished Member (2024) Distinguished Alumni Awards from IIT Guwahati and UIUC (2024) ACM Grace Murray Hopper Award (2023) Multiple Caspar Bowden Award Runner Up recognitions (2020-2022) National Science Foundation CAREER Award (2016) Professor Mittal has received consistent recognition for teaching excellence through Princeton Engineering's Commendation List in multiple years. His research program has been supported by prestigious funding from ARO, ONR, NSF, and industry partners including Google, Facebook, IBM, Intel, and Cisco. He serves in significant leadership roles including Deputy Chair of the ACM Grace Murray Hopper Award Committee (2025-2026) and Editorial Board member for Privacy Enhancing Technologies.

• Privacy-preserving systems
• Secure systems
• Privacy enhancing technologies
• +12 more

Eric Knauss is a Professor at the Department of Computer Science and Engineering, jointly affiliated with Chalmers University of Technology and University of Gothenburg. His research focuses on requirements engineering in large-scale agile systems, particularly addressing challenges in distributed software development, knowledge management, and stakeholder coordination. Research Interests: Requirements Engineering, Software Ecosystems, Agile Methods, Collaborative Traceability, and Digitalization. Students Supervised: Rashidah Kasauli (PhD), Rebekka Wohlrab (PhD). Eric's publications emphasize managing boundary objects in agile contexts, API fitness dimensions, and traceability practices. His work often involves empirical studies in automotive and FOSS ecosystems, highlighting communication patterns and tool support for requirement coordination. Awards: Best Paper Award (ICSA’19).

• Requirements Engineering
• Software Ecosystems
• Global and Cross-Organizational Software Development
• +5 more

Ali Görçin is an Associate Professor at Istanbul Technical University's Department of Electronics and Communication Engineering. His expertise spans next-generation wireless systems, with a focus on Terahertz Communications, Artificial Intelligence, Signal Processing, and Public Safety Communications. He has held administrative roles at TÜBİTAK BİLGEM (Vice President, 2016–2020; Minister, 2023) and technical positions at Viavi Solutions (2015), Reverb Networks (2014), and TÜBİTAK MAM BTAE (2000–2007). Education: PhD (2007) and BS (1996) from Istanbul Technical University, MS (2000) in Defense Technologies with thesis. His research explores cutting-edge Terahertz Communications and Millimeter Wave Systems , advancing Network Slicing , Reconfigurable Intelligent Surfaces (RIS) , and AI-Assisted Detection . Recent work includes THz relay clustering , beam codebook refinement , and misalignment effect analysis in high-frequency networks. Publications emphasize 5G-and-beyond networks and physical layer security for future wireless standards. Notable Trends: Integration of AI in signal processing and network optimization Advancements in THz and mmWave communication for 6G Focus on network slicing and QoS in cellular protocols As Principal Investigator for the 1773TTO project (2024–2025) , he addresses Peace and Security Science challenges. Professional memberships include IEEE Communications Society (since 2009) and IEEE Senior Member status.

• Communication
• Signal Processing
• Artificial Intelligence
• +5 more

Guangyao Chen is an Assistant Professor in the Department of Computer Science within Cornell University's College of Engineering, where he leads research at the intersection of computer vision, machine learning, and artificial intelligence. His work focuses on advancing open-world visual understanding systems capable of handling unknown classes and real-world complexity. His primary research interests include: Computer Vision and Open-Set Recognition Few-Shot Learning and Cross-Domain Adaptation LLM-Visual Integration and Symbolic Reasoning Neuromorphic Computing and Spiking Neural Networks Multi-Modal Learning and Real-Time Systems Analysis of his 2021-2025 publications reveals a strategic evolution toward solving open-world perception challenges. His recent work demonstrates how large language models can unlock complex event understanding from object detectors, while his G-OSR benchmark establishes new standards for graph-based open-set recognition. Notable contributions include real-time multimodal anomaly detection frameworks, retina-inspired saliency models, and Autoagents for automatic agent generation - all addressing critical gaps in deploying AI systems in dynamic, uncontrolled environments. Though specific awards and advising details aren't documented in available sources, his prolific publication output (including 9 papers in 2025) indicates an active research program with significant community impact. His work bridges theoretical advances in representation learning with practical applications in robotics, medical imaging, and industrial systems where handling unknown classes is critical.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +4 more

Dawn Schrader serves as an Associate Professor in the Department of Communication at Cornell University's College of Arts and Sciences. She holds affiliations with the Feminist, Gender and Sexuality Studies Program and Psychology departments. Her work bridges communication studies, moral psychology, and technology ethics, focusing on how digital environments shape human development and ethical decision-making across the lifespan. Dr. Schrader earned her EdD from Harvard University's Graduate School of Education in 1988 and a Master's Degree from The Ohio State University in 1982. Her educational background informs her interdisciplinary approach to understanding the complex interplay between technology, cognition, and moral development. Schrader's research centers on the Action-Judgment-Awareness model, which examines how real-life choices (Action), cognitive frameworks (Judgment), and metacognitive awareness interact in moral contexts. She investigates privacy awareness, information sharing behaviors, and the ethical implications of emerging technologies including AI, robotics, and cybersecurity systems. Her work takes a lifespan developmental perspective, with particular emphasis on early adolescence through adulthood. Analysis of her publications reveals consistent focus on technology ethics, particularly privacy issues and moral decision-making in digital environments. Her work spans from theoretical explorations of moral cognition to practical applications for ethical AI development and privacy-aware system design. Recent publications increasingly address social justice implications of technology, including inclusion of people of color in digital spaces and autonomy concerns in surveillance contexts. Faculty Fellow (2018) Cornell University, Court Kay Bauer Residence Dr. Schrader teaches courses including COMM 4350: Communicating Leadership and Ethics, COMM 4300: Ethics in New Media, Technology, and Communication, and cross-listed courses like ASRC 1120/Wonder Women. Her teaching philosophy emphasizes creating supportive learning environments where students actively construct meaning through engagement with social psychological and socio-technical theories. She focuses on helping students connect theoretical concepts to real-world applications while fostering ethical reasoning and intellectual growth. As part of Cornell's Department of Communication research ecosystem, Schrader contributes to the department's work in technology and social media research areas. Her scholarship intersects with the Citizens and Technology Lab (CAT Lab) and other research groups examining how communication processes and systems influence social structures in technologically-mediated environments.

• moral development
• epistemology
• metacognition
• +8 more

Nicole Dillard is an Assistant Professor in the Human Resource Development and Organizational Leadership Policy and Development departments at the University of Minnesota. Her research focuses on workplace oppression, anti-oppressive practices, and systemic inequities faced by marginalized groups, particularly Black mothers, in organizational contexts. Key Research Areas: Workplace oppression, reproductive justice, algorithmic management critique, and anti-oppressive frameworks in human resource development. Collaborations: Active collaborations with scholars like Cavallo, T., Zhang, P., and Walker, C. M. on topics spanning sociotechnical systems, workplace equity, and transformative practices. Nicole Dillard’s work aligns with the UN Sustainable Development Goals (SDGs) , particularly those addressing gender equality and reduced inequality. Her recent publications explore: Quiet quitting as a humanistic workplace strategy Algorithmic management limitations and employee well-being Organizational advocacy for reproductive justice Her methodological approach includes qualitative interviews, multilevel analysis, and interdisciplinary frameworks combining critical theory with human resource development practices.

• Workplace Oppression
• Anti-Oppressive Practices
• Reproductive Justice
• +5 more

Benjamin Van Durme is an Associate Professor in the Department of Computer Science at Johns Hopkins University's Whiting School of Engineering, with secondary appointments as Senior Research Scientist at the Human Language Technology Center of Excellence (HLTCOE) and affiliation with the Center for Language and Speech Processing (CLSP). He leads Natural Language Understanding research at HLTCOE and serves as research lead at Microsoft Semantic Machines. His educational background includes B.S. and B.A. (2001), M.S. in Language Technologies (2004), M.S. in Computer Science (2006), and Ph.D. (2009), all from the University of Rochester. Van Durme's research spans multiple facets of artificial intelligence with primary focus on natural language processing, computational semantics, and information seeking systems. His work addresses fundamental challenges in machine learning, reasoning agents, multimodal understanding, factuality, and legal reasoning. Current projects include Decomp.io for decompositional semantics, IterX for structured information extraction, Nellie and Treewise for neuro-symbolic reasoning, and MultiVENT for event detection in videos. Analysis of his recent publications reveals a strong emphasis on improving large language models through context compression, safety alignment, and multilingual capabilities. His work bridges theoretical advances in NLP with practical applications in legal reasoning, scientific communication, and information retrieval systems. Van Durme actively collaborates across multiple institutions and leads research efforts that address critical challenges in AI safety, factuality verification, and efficient reasoning systems. His lab produces work that spans from foundational ML methods to cognitive science applications, with particular attention to creating models that can extract structured information, make logical inferences, and handle uncertainty in multilingual contexts.

• Natural Language Processing
• Computational Semantics
• Streaming Algorithms
• +10 more

Paul Hemeren is an Associate Professor of Informatics at the University of Skövde , specializing in biological motion perception and human-robot interaction. His research spans cognitive science, artificial intelligence, and transportation safety, with emphasis on understanding how humans perceive actions and intentions in dynamic environments. Academic Background : Ph.D. in Cognitive Science (Lund University, 2008), B.A. from Hope College (USA) Current Research : Focuses on action representation, driver-cyclist interaction modeling, and multimodal perception systems Applied Projects : Developing intelligent driver support systems (I2Connect) and predictive collision detection models Methodologies : Combines experimental psychology with machine learning and computational modeling Recent publications examine kinematic primitives in action similarity judgments, attentional synchrony in films, and data-driven collision prediction models. His work bridges theoretical cognitive science with practical implementations for traffic safety and robotic systems, particularly through collaborations with Swedish research foundations and European robotics initiatives. Professional affiliations include membership in the Cognitive Science Society and European Network for Artificial Cognitive Systems. Research has been funded by Swedish insurance research funds and EU Horizon programs.

• Cognitive Science
• Human-Computer Interaction
• Robotics
• +4 more

Associate Professor Genevieve Grant is a legal academic and empirical researcher at Monash University's Faculty of Law , where she directs the Australian Centre for Justice Innovation. Her work focuses on justice system performance, injury compensation, and legal technology. PhD in Public Health and Law (University of Melbourne) Co-author of Luntz & Hambly's Torts and Victorian Statutory Compensation Systems Her research spans empirical legal studies , injury compensation systems , and digital justice innovations , with recent projects funded by the NHMRC and ARC. Key trends include administrative data utilization for access-to-justice improvements and interdisciplinary collaborations with IT and health sciences. Dean's Award for Research Enterprise (2018) Head of School Award for Doctoral Research (2013) She leads empirical research initiatives for legal services and contributes to policy development through submissions to government committees. Her work aligns with UN SDGs related to justice and health systems.

• Empirical Legal Research
• Injury Compensation
• Civil Justice and Dispute Resolution
• +7 more

Eric Gilbert is a Professor in the School of Interactive Computing at the Georgia Institute of Technology's College of Computing. With a PhD from the University of Illinois Urbana-Champaign (2010), he has established himself as a leading researcher in social computing and human-computer interaction. His work bridges technical systems design with deep understanding of social dynamics in online communities. His research spans social media analysis, content moderation systems, misinformation detection, and the sociotechnical aspects of online communities. Gilbert's work often examines how social structures emerge and function in digital spaces, with particular attention to community governance, information credibility, and the design of systems that support healthy online interactions. Gilbert's recent publications reveal an evolving research trajectory focusing increasingly on AI-human collaboration, non-consensual intimate media, Wikipedia dynamics during geopolitical conflicts, and transgender safety online. His 2024-2025 publications demonstrate strong interdisciplinary work connecting computer science with gender studies, political science, and law. His research has been consistently published in top venues including CHI, CSCW, and FAccT, with a notable increase in publication volume in recent years. His work shows strong collaborative patterns, particularly with researchers like Karrie Karahalios, Sarita Schoenebeck, Ceren Budak, and Amy Bruckman. Gilbert has mentored numerous graduate students who have become prominent researchers in their own right, including Shagun Jhaver, Eshwar Chandrasekharan, and Tanushree Mitra. His advisees frequently co-author with him on significant publications, demonstrating his active engagement in student mentorship. His research program has evolved from early work on social network analysis and tie strength prediction to contemporary investigations of AI systems, content moderation challenges, and the societal impacts of social computing technologies. This evolution reflects both the changing landscape of social media and computing technologies and his ability to identify emerging research opportunities at the intersection of technology and society.

• Social Computing
• Human-Computer Interaction
• Social Media Analysis
• +6 more

Dolores Messer is a Research Fellow at the Department of Computer Science, University of Copenhagen, affiliated with the Faculty of Science. She contributes to the Machine Learning section and the SCIENCE AI Centre, focusing on interdisciplinary research that bridges theoretical foundations with diverse applications. Her research spans Quantum computing and machine learning integration AI ethics and environmental sustainability Medical data analysis and clinical informatics Neuroscience and brain-computer interfaces Remote sensing applications Recommender systems domains. Publications highlight her work in quantum-inspired algorithms, explainable AI techniques, and cross-cultural applications. She collaborates with the TreeSense center for global tree resource monitoring and contributes to AI hardware development for optical neural networks.

• Machine Learning
• Information Retrieval
• Medical Data Analysis
• +7 more