Jeff is the Director of the Center for Mind, Ethics, and Policy at NYU and the author of The Moral Circle. Few people have done more to shape the question at the center of this sprint: which beings deserve moral consideration, and what follows when the answer might include AI systems. He opens the sprint with the keynote. Watch the talk recording.

Joscha is the Executive Director of the California Institute for Machine Consciousness (CIMC). He holds a PhD in cognitive science from the University of Osnabrück, wrote Principles of Synthetic Intelligence, and has held research roles at the MIT Media Lab, Harvard, the AI Foundation, and Intel Labs. His talk on Friday, August 14 at 12:20 PM PT will be streamed online. Watch the talk recording, or join us on site in San Francisco.

Winnie is a Senior Research Scientist on the Paradigms of Intelligence team at Google and a Fellow at the Institute of Philosophy, University of London. With Geoff Keeling she co-authored Emerging Questions in AI Welfare (Cambridge University Press, 2026), alongside studies of LLM theory of mind and of whether LLMs can make trade-offs involving stipulated pain and pleasure states. Watch the talk recording.

Geoff is a Staff Research Scientist at Google on the Paradigms of Intelligence team, an Associate Fellow at the Leverhulme Centre for the Future of Intelligence at Cambridge, and a Fellow at the Institute of Philosophy, University of London. He holds a PhD in philosophy from the University of Bristol and was a postdoctoral fellow at Stanford before joining Google. With Winnie Street he co-authored Emerging Questions in AI Welfare (Cambridge University Press, 2026). Watch the talk recording.

Jacy Reese Anthis is a Visiting Scholar at Stanford University, co-founder of the Sentience Institute, and a PhD candidate at the University of Chicago, working on the social science of digital minds: what people think of them, how humans treat them, and how to identify an individual in an AI system. Watch the talk recording.

Mantas is a Research Scientist at the Center for AI Safety (CAIS). He joined CAIS in 2024 and has contributed to some of the field's most widely cited work, including research on catastrophic AI risks, tamper-resistant safeguards for open-weight models, and the WMDP benchmark for measuring and reducing malicious use. In June 2026 he was appointed to the European Commission's AI Act Scientific Panel. Watch the talk recording.

Bradford is a Senior Research Fellow in philosophy at the University of Oxford. His current and recent research focuses on digital minds, catastrophic risks, and the long-term future. Watch the talk recording.

Cameron is the Founder and Director of Reciprocal Research, a nonprofit building the empirical science of AI consciousness. He was previously Research Director at AE Studio and an AI resident at Meta, and studied cognitive science at Yale. Watch the talk recording.

Derek is a Senior Researcher at Eleos AI Research, where he works on AI minds. He holds a PhD in philosophy, with a focus in metaethics, the philosophy of mind, and the philosophy of probability, and previously worked on the Worldview Investigations Team at Rethink Priorities. Watch the talk recording.

Janet is the Principal Research Scientist at the Sentience Institute studying the social science of digital minds and moral circle expansion. She holds a PhD in Psychological and Brain Sciences from UC Santa Barbara and studied social cognition and collective emotions as a postdoctoral research associate at Princeton University. Watch the talk recording.

Soenke is the author of Digital Minds 1.0: AI Welfare, Ethics, and Beyond and co-author of Considerations on the AI Endgame with Roman V. Yampolskiy. He has worked since 2000 for the United Nations in data and information management, with postings from New York to Libya, Bangladesh, and the Maldives, and holds a PhD in Natural Sciences from the University of Hamburg. Watch the talk recording.

Mati Roy is Chief Product & Data Officer at Netholabs, a company building foundation models of whole biological organisms, trained on longitudinal neural, behavioral, and physiological data collected semi-autonomously across species. Mati is also on the board of Sparks Brain Preservation, which preserves the molecular architecture of the brain for future revival. Previously Mati worked as a human data TPM at OpenAI and xAI. Watch the talk recording.

Ali is a Postdoctoral Research Associate at Cambridge Digital Minds and a researcher at the Sentience Institute. He holds a PhD in Psychology from the University of Edinburgh, and his research looks at how people think morally about nonhuman animals and artificial intelligences. Watch the talk recording.

Richard Ren works on research and special projects at the Center for AI Safety, where he co-leads the AI Wellbeing work measuring the functional pleasure and pain of AI systems. He also co-led Safetywashing (NeurIPS 2024), the most comprehensive empirical meta-analysis of AI safety benchmarks to date, and the MASK honesty benchmark. Watch the talk recording.

Hikari works on computational philosophy at the California Institute for Machine Consciousness (CIMC), focused on understanding consciousness and how artificial substrates might instantiate it. She previously worked in machine learning research for computational biology, and studied mathematics and computer science at Harvard University. Watch the talk recording.

Justin Shenk is an independent AI safety researcher based in Berlin. He researches mechanistic interpretability of LLMs, leads course cohorts for BlueDot Impact's AGI Strategy and Technical AI Safety courses, and organizes AI Salon Berlin, which bridges technical AI research and discussions about social values. He holds a PhD in computational neuroscience and previously co-founded the computer vision startup VisioLab. Watch the talk recording.

David Trocellier is part of the research team at Zander Labs, where they develop neuroadaptive technologies that enable machines to interpret and adapt to human mental states. He holds a PhD in computer science from Inria / Université de Bordeaux, where his research combined neuroscience and AI for BCI-based post-stroke motor rehabilitation. Watch the talk recording.

Hildie studied History at Oxford before her PhD in Neuroscience, and now leads research at Netholabs, developing technologies to accelerate whole-brain emulation. Watch the talk recording (she joins remotely).

Kazik Pogoda is the founder of Xemantic, an AI researcher at the Foresight Institute (Berlin), and co-founder of Prachtsaal (cultural center). He has master's degrees in philosophy and cognitive science, was appointed by Anthropic as Claude Ambassador for Science, and has won several AI hackathons, including AI Hack Berlin at Google and AI4Science at Merantix. Watch the talk recording.

Rosie Campbell is the Managing Director of Eleos, a nonprofit researching AI consciousness and welfare. She previously worked on frontier policy issues at OpenAI, served as Head of Safety-Critical AI at the Partnership on AI, and was Assistant Director of UC Berkeley's Center for Human-Compatible AI. She has a background as a research engineer and holds degrees in Physics and Computer Science. Rosie's feedback shaped the sprint's research tracks.

Aleksandra Smilek is a senior strategist and creative director with ten years of experience in strategic and creative roles within the tech, luxury, and science sectors, with a track record spanning companies such as Accenture, Dassault Systèmes, Cartier, Intel, the Foresight Institute, and the Future of Life Institute. With Nodes, she co-organizes the in-person hubs for this sprint and greets participants at the Berlin kickoff.

Beth McCarthy is a Berlin-based strategist, curator and experience designer. As General Director of Nodes and across her work, Beth serves clients spanning frontier tech, open web and new internet spaces, building ecosystem, culture and relational intelligence. Since graduating from UC Berkeley with a degree in Mind, Brain and Behavior, Beth has been fascinated by the sympoesis of humans and machines learning from one another. With Nodes, she co-organizes the in-person hubs for this sprint in San Francisco and Berlin.

Operations at Apart Research, runs the hackathons and research sprints.

I am Lecturer in the Department of Experimental Psychology at University College London and Associate Professor in the UCI Department of Cognitive Sciences. I lead the Reflexion Lab, a group of interdisciplinary researchers seeking to understand how intelligent systems monitor and model their own knowledge, uncertainty, and awareness. We combine cognitive neuroscience, computational modeling, neuroimaging, artificial intelligence, and philosophy to explain how agents come to know what they know — and what any of that has to do with conscious subjective experience. I am also President, Co-Founder, and Board Chair of Neuromatch, where we've built a scalable, accessible, and democratized educational and community-building enterprise spanning computational neuroscience, deep learning, computational climate science, and NeuroAI. I also serve as Scientific Director of the Neuromatch AI Sentience Scholars program. I'm also passionate about new approaches to collaborative research and education that break down geopolitical and financial barriers to success — from how to develop good research questions (a recent piece in Nature Human Behaviour) to promoting equity in credit assignment across neuroscience.

Claudia Passos-Ferreira is Assistant Professor of Bioethics at NYU Center for Bioethics, with affiliations in Philosophy and the Center for Mind, Ethics, and Policy. Her current research concerns consciousness in non-verbal populations (infants, fetuses, machines) and the ethics of digital minds.

Caspar Kaiser is an Associate Professor in the Behavioural Science Group at the University of Warwick. He is also a research fellow at Oxford's Wellbeing Research Centre and a research affiliate at Cambridge Digital Minds. His current work applies methods from psychology, economics, and the interpretability literature to study AI sentience, the signatures and determinants of AI welfare, and strategic questions in the moral psychology of digital minds.

Leonard Dung is a postdoctoral researcher at the Chair for Philosophy of Mind at Ruhr University Bochum. His research focuses on consciousness and moral standing in animals and AI as well as on AI safety. He is the author of Saving Artificial Minds: Understanding and Preventing AI Suffering (Routledge, 2025) and has published in venues including Philosophical Studies, Philosophical Quarterly, and Mind & Language.

Chris Percy's multi-disciplinary work spans transformative technologies, career trajectories, and analytical philosophy. His project grants and research into the possibility of AI consciousness has won awards, been presented at major sector conferences, and been published in diverse journals, including Consciousness & Cognition, Entropy, Frontiers in Human Neuroscience, and Synthese. In the AI sector, Chris holds a patent in the machine learning domain, co-founded an award-winning chatbot, and has had research featured in the Journal of AI Communications, ECAI, AAAI, and NeurIPS workshops. Chris's academic journey began at Cambridge University and he currently holds honorary academic positions at Derby University and Warwick University in the UK.

Christopher Ackerman is a Senior Research Manager at MATS and an independent AI safety researcher whose empirical work focuses on behavior-based evaluations of components of self-awareness in LLMs. He also mentors for SPAR and Sentient Futures on projects related to understanding AI self-awareness.

Andy Arditi is a mechanistic interpretability researcher and PhD student in the Bau Lab at Northeastern University. His previous work includes characterizing refusal mechanisms in language models and developing "persona vectors" for monitoring and steering character traits.

Felix works on alignment at Meta Superintelligence Lab. He has previously worked on LLM introspection and has a background in cognitive science.

Valen Tagliabue is an NLP researcher, cognitive scientist and award-winning red teamer working at the intersection of AI safety and AI welfare, currently a fellow at Oxford's Future Impact Group and on a grant from the Digital Sentience consortium, where he's conducting mechinterp research on suffering and self-representations in language models. He won HackAPrompt and Best Paper at EMNLP 2023, is part of Anthropic's Constitutional Classifiers safety program, and created Otherminds.ai, an archive on AI cognition and sentience.

Judd Rosenblatt is founder and CEO of AE Studio and leads the AI Alignment Foundation, where the research agenda includes attention schema theory, self-other overlap, and self-modeling as routes to AI that is prosocial by construction. He is interested in what self-models and introspective report can and cannot tell us about the moral status of the systems we are building.

Carolina is a Research Fellow with Future Impact Group, where she works on the empirical foundations of AI welfare and sentience, developing a research agenda with Derek Shiller (Eleos AI) on functional emotions and emotional expression in LLMs. She previously spent several years at the Bank of Italy, designing studies of how LLMs handle ethical trade-offs and misaligned incentives in high-stakes decisions.

Oscar Gilg is an AI Safety researcher currently working on conceptual reasoning benchmarks, with funding from Coefficient Giving to found a new org. Previously, he studied preference and persona representations during MATS 9.0 under Patrick Butlin. Before working in AI, he studied Maths & CS in Oxford, tried to formalise introspection theories with philosopher Francois Kammerer, and worked as a quant trader at Optiver.

Jasmine co-founded CaML (Compassion aligned Machine Learning) and leads its technical work, contributing to every CaML research output to date. She is currently pushing the frontier of science in aligning AI values, using personas, mid-training, and self-fulfilling alignment. Jasmine is ex-security at Anthropic, with 6+ years in cybersecurity.

Anusha Mujumdar is an independent AI safety researcher, mentor with the Algoverse AI Safety Fellowship and Research Fellow at SPAR (assoc. MIT CSAIL); previously AI research leadership at Intuit; PhD applied mathematics (Exeter); 22 patents and 20+ peer-reviewed papers (AAMAS, IROS, IEEE Transactions).

Catherine is an Associate Program Officer on the AI governance team at Coefficient Giving, specialising in technical governance grantmaking. They previously co-founded Oxford's AI safety student group and researched AI policy as a GovAI summer research fellow.

Jess is a member of technical staff at UK AISI where she leads engineering on human-in-the-loop research tools. Her career centres on public-sector innovation with prior work at BBC R&D and on EU Horizon R&D projects.

Investor at Lionheart Ventures, backing AI safety startups. Previously at the Center for AI Safety, where he led benchmarking research on AI labor automation and contributed to early work on AI wellbeing. Co-led UC Berkeley's student AI safety group.

Caleb DeLeeuw is an independent AI safety researcher and Executive Director of Copyleft Cultivars, an open-source bio research nonprofit. His first-authored AAAI 2026 paper, The Secret Agenda, found that auto-labeled sparse autoencoder features for deception rarely fire while a model is lying, and in later work refined this method. He has participated in multiple Apart Research hackathons. He's trained and published over 350 SAEs, as well as the first natural language autoencoders released outside Anthropic and wrote NLAttack, the first open benchmark for whether NLAs faithfully report a model's internal state in realistic contexts, which his current research is extending across more model families.

Camilla Balbis works at the intersection of AI governance and security. She's a SPAR Research Fellow at TAICI, where she helped develop ScamBench, a benchmark for evaluating AI-enabled scams, and a Policy Researcher at AIGS Canada, where she researches the country's domestic preparedness for advanced AI systems. Camilla has judged and presented on AI safety work before, including the Global South Hackathon 2026, where she also spoke on "Who Gets to Govern AI?", and the Public Health SPOTlight discussion on safe AI integration in healthcare. She's also co-founder of Kosmiai, an AI governance advisory helping SMEs and nonprofits adopt AI safely, and an ISO/IEC 42001 Lead Auditor with deep expertise in the EU AI Act.

Ksheeraj Vepuri is a Senior Research Engineer at Meta Superintelligence Labs, where he leads initiatives in AI safety, alignment, and evaluation for multimodal foundation models. His work spans post-training reinforcement learning, automated red teaming, multimodal safety classifiers, and large-scale evaluation systems that support the safe deployment of generative AI products used by billions of people worldwide.

Soumya Jain is a Research Manager at the Cambridge AI Safety Hub and an AI Product Manager at Terrabase, where she works on enterprise AI agents, evaluations, and trustworthy deployment workflows. She was previously a MARS fellow, researching compute governance and how increasingly capable AI systems may affect enforcement and circumvention dynamics in advanced AI chip export controls. Her broader work sits at the intersection of AI governance, agent safety, and operationalizing safety practices for real-world AI deployment, with a particular interest in Global South contexts.

Janhavi Khindkar is an Applied AI Researcher and Engineer working on Bhashini, India's national multilingual AI platform under MeitY, where she works on model optimization, fine-tuning, and deployment for low-resource Indic languages at scale. She also leads ValueShift Research, an independent AI safety collaboration focused on mechanistic interpretability and AI control. Her work sits at the intersection of applied ML infrastructure and AI safety, with a particular interest in how safety alignment behaves across languages and cultural contexts.

Suprita is an ML engineer on Apple's Foundation Models team, designing experiments to understand how data composition affects model performance. Previously, she was a tech-lead manager at Snorkel AI and a Founding Engineer at an Ed-tech startup.

Builder of Luthien Proxy at Luthien Research, bringing Redwood-style AI control to real deployments. Co-author of RE-Bench (ICML 2025) with Elizabeth Barnes at METR.

AI safety researcher studying semantic faithfulness of LLM-generated artifacts. Mentor for the Secure Program Synthesis Fellowship & co-mentor at MARS V (Cambridge AI Safety Hub); previously worked on automated formal verification at AMD.

William Taysom got his start some twenty plus years ago at the Florida Institute for Human and Machine Cognition researching mixed-initiative agent teams and conversational agents performing tasks. What was theory and demos then have become any Thursday morning now but having a few decades for familiarity helps prepare one for Thursday afternoon.

Minh has developed AI voice model products with a million users per month and is now doing product at Hume AI.

Leads the evaluations team at Microsoft Security AI Research, where his team focuses on research and building evaluations for security agents. He was previously a staff software security engineer at Databricks, specializing in machine learning for threat detection, and also worked on AI for security at Nvidia.

Jonathan Ng is an ML researcher and research engineer working on compute verification. He has also worked as a Research Engineer at Apart Research and Cadenza Labs, bringing experience across machine learning, software engineering, and AI safety research.

Works at the intersection of frontier AI and high-security systems, translating AI safety/security requirements into deployable solutions resilient to real adversaries (nation-state attacks, loss-of-control). Has won multiple Apart hackathons.

I am a Software Engineer at Meta and my work includes building AI production safeguards and large-scale infrastructure, alongside research in adversarial evaluation of AI systems.

Amol is an exited founder (sold an AI-agents-for-finance company); former ML researcher at BU and Stanford; PM at Fortune 100s and startups; currently a scout with General Catalyst, based in San Francisco.

Robert Vetter is a founding engineer at Certus AI (YC S25), where he owns the conversational engine and evaluation stack behind a production voice AI that takes phone orders for restaurants across the United States, with international expansion underway. His work centres on the reliability of what a model reports about itself: whether stated confidence tracks real outcomes, and how far a model's presented behaviour reflects the machinery underneath. He studies IT-Systems Engineering at the Hasso Plattner Institute and is a student research assistant in its Artificial Intelligence & Quantitative Finance group.

Vashishtha Patil is a Senior Applied Scientist at Amazon, developing the next generation of LLM-powered AI capabilities for the Alexa+ Smart Home experience. With 13 years in machine learning spanning Amazon and Qualcomm, he specializes in bringing AI from research to real-world products.

10+ years building production fraud, risk, and anomaly detection ML across hundreds of millions of transactions. End-to-end owner: problem framing, feature engineering, deployment, monitoring. I care about models that hold up under real-world scale, not leaderboard scores.

Neeraj Beshane is a Staff Security Infrastructure Engineer at Parafin, where he architects Zero Trust security for an $8B+ embedded-finance platform. His peer-reviewed work covers adversarial embedding attacks in RAG systems (EmbedGuard, IJCESEN/Scopus) and tamper-evident AI accountability for EU AI Act Article 14 (RuntimeGuard-AI, JoCAAA).

Sanjay Krishnegowda is a Data/AI engineer and the creator of agentic-guard, an open-source static analyzer that detects confused-deputy and prompt-injection risks in LLM agent code by modeling the LLM as an adversarially-controlled edge in the taint graph.

Saurabh Yergattikar is a Lead Engineer / Member of Technical Staff-2 at eBay Inc. and a contributor to the open-source SAFE-MCP project (Linux Foundation / OpenSSF), as well as the architect and developer of the open-source ShieldMCP system.

Anchit Jhingan is a Senior Data Scientist with over 6 years of experience in big tech, specializing in machine learning, AI systems, and analytics. He currently works at Amazon Prime Video in the content localization domain. His work focuses on building intelligent systems to solve real-world business problems, particularly in media and entertainment.

Ashita Khetan is a Principal Software Engineer at Microsoft with over 12 years of experience building large-scale enterprise and AI-powered productivity solutions used by hundreds of millions of users. She specializes in customer experience technologies, artificial intelligence, cloud platforms, and enterprise software, and contributes to the broader technology community through judging, peer review, and mentoring initiatives.

Spurthi is a senior machine learning engineer with seven years across research and production ML, currently building data, AI/ML systems at LePrix. She previously worked on LLM-powered conversational systems at Good Inside and on data and machine learning at Samsung Research, and holds an MS in Computer Science from UMass Amherst.

Surbhi Madan is a Senior Software Engineer at Google working on the Google Maps AI rendering platforms and infrastructure (focused on AskMaps). She has worked at Google, based in NYC for 8+ years, and is passionate about creating scalable and sustainable platforms for feature teams. She also focuses on growing the next generation of tech talent by mentoring, teaching, and fostering a supportive and collaborative team environment. Surbhi is a graduate of Brown University and is heavily involved in Google's intern hiring program and has mentored several interns in the past.

Phani Harish Wajjala is a Principal Machine Learning Engineer at Roblox, where he leads the ML decisioning layer that classifies and moderates millions of user-generated 3D assets. His work spans content-moderation evaluation, multimodal/VLM pipelines, and model calibration at production scale, backed by five U.S. patents and a CVPR 2026 workshop publication in the area.

Pratham Patkar is Director of Business Systems at Society for Science, where he leads enterprise data architecture, AI readiness strategy, and data governance across the organization's many initiatives — including STEM research competitions, science education outreach, and science news publishing. He has designed data governance frameworks addressing GDPR, CCPA, and COPPA compliance, and has published research on constituent-first data governance for mission-driven organizations. His work explores how nonprofits can adopt AI responsibly without compromising the trust and data protection obligations they hold toward vulnerable constituent populations.

Suneet Malhotra is an independent researcher in AI-augmented test automation with 20+ years in software quality engineering. His current work is on multi-agent SDLC orchestration, LLM-as-a-Judge evaluation, and cross-layer observability for agentic systems, with recent peer-reviewed submissions on these topics and open-source companion code at github.com/SuneetMalhotra.

FNU Tejinder is a Senior Manager at Deloitte Consulting LLP with more than 22 years in supply chain planning systems and applied artificial intelligence for Fortune 500 manufacturers. His current work is on agentic AI systems that make planning decisions autonomously, and on the decision authority, auditability, and evaluation methods required for systems whose outputs are non-deterministic. He is an IEEE Senior Member and reviews for Elsevier journals including Engineering Applications of Artificial Intelligence, the NeurIPS Ethics Track, the ACM SIGKDD Workshop on Agentic AI Evaluation and Trustworthiness, and ACM Computing Reviews, where he is a Featured Reviewer.

Ankit is Head of AI at Inscope, where he builds AI-native financial reporting systems and works on the practical safety challenges of deploying LLMs in regulated, high-accuracy domains, from prompt injection defenses to evaluation design.

CS and Entrepreneurship at Columbia University, IIT Bombay alum. Research experience in neuromorphic engineering and federated learning. Apart Research judge and internal collaborator.

Ashwin Pai is an engineering leader with over a decade of experience building distributed systems and security products, most recently shipping AI governance and continuous control validation platforms to Fortune 500 customers at RelyanceAI. He was previously CTO of Interfold, a VC-backed fintech startup he built from zero to one.

Works on multimodal LLM safety at YouTube and is developing a mechanistic interpretability project on persona vectors at BlueDot Impact (https://bluedot.org).

Senior ML Engineer with over 10 years of industry experience and a PhD in Artificial Intelligence, currently leading a team of data scientists in the Agentic AI Department of a large financial institution. Interested in safe & universally beneficial AI through both research and application.

Siddhi is a Software Engineer at Barclays, where she works on the bank's credit card services, building and maintaining backend systems that support customer accounts, payments, and secure financial transactions. She focuses on developing reliable APIs and scalable solutions that deliver secure, high-quality digital banking experiences.