Katerina Fragkiadaki is the JPMorgan Chase Associate Professor of Computer Science in the Machine Learning Department at Carnegie Mellon University. She works at the intersection of Artificial Intelligence, Computer Vision, Machine Learning, Language Understanding, and Robotics. PhD from GRASP Lab, University of Pennsylvania Postdoctoral researcher at UC Berkeley (with Jitendra Malik) and Google Research Recipient of NSF CAREER, DARPA Young Investigator, Amazon, Google, Sony, UPMC, and AFOSR awards Organizer of CoRL 2023 Workshop on Generalist Robots ICLR 2024 Program Chair, multiple area chair roles Her research group focuses on developing machines that autonomously improve world models through human-environment interactions, with specific emphasis on: Representation learning and video understanding 2D/3D unified vision-language models Generative simulation and reinforcement learning Real2Sim/Sim2Real robot learning Continual learning and spatial common sense 3D scene reconstruction and dynamics Recent publications highlight advancements in: 3D mesh generation with compositional transformers Unified 2D/3D perception frameworks Physics-aware generative models Diffusion-based robotic manipulation policies Embodied agents with memory prompting Awards include: 2024: DARPA Young Investigator Award 2023: Amazon Faculty Award 2022: Sony Faculty Research Award 2021: UPMC Faculty Research Award 2020: NSF CAREER Award 2019: Google Faculty Award Key collaborations span institutions including UC Berkeley, Google Research, Stanford, MIT, and University of Tsukuba. Her work bridges theoretical innovation with practical applications in: Autonomous robot manipulation 4D world modeling Language-grounded perception Visual dynamics prediction Embodied program synthesis Physics-based simulation engines
Mark Yatskar is an Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research focuses on the intersection of natural language processing, computer vision, and fairness in machine learning. He earned his PhD from the University of Washington under advisors Luke Zettlemoyer and Ali Farhadi, and previously worked as a Young Investigator at the Allen Institute for Artificial Intelligence. Education: PhD in Computer Science, University of Washington (Advisor: Luke Zettlemoyer & Ali Farhadi) Research Interests: Yatskar's work explores how language can structure visual perception and mitigate human biases in machine learning systems. Key themes include: Natural language as a scaffold for visual intelligence Bias characterization and control in machine learning systems His lab currently investigates projects like language-guided bottlenecks, annotator cognitive heuristics, and gender bias amplification. Teaching: CIS 5300: Computational Linguistics (2021-2024) CIS 7000: Language and Vision (2020) CIS 6300: Efficient NLP (2023, 2025) Awards: Best Paper Award at EMNLP (Gender Bias Amplification Research) Advising & Grants: Yatskar advises a team of PhD/Master's students and actively seeks motivated researchers. His group has explored funding in areas like interpretable AI, multimodal reasoning, and dataset bias mitigation. Labs/Teams: Leads the Penn NLP & Vision Lab, focusing on projects like MolMo/PixMo open models, ViUniT visual unit tests, and bias mitigation frameworks.
Rachel Rudinger is an Assistant Professor at the University of Maryland, affiliated with the Department of Computer Science and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Her research focuses on Natural Language Processing (NLP), Machine Learning, and AI ethics, particularly addressing sociocultural biases and fairness in large language models (LLMs). She holds a PhD from Johns Hopkins University (2019) and a B.S. from Yale University (2013). Rudinger's work explores equitable cultural alignment in AI systems, common ground misalignment in dialog systems, and the mutual influence of gender and occupation in LLMs. She received the NSF CAREER Award in 2024 for her project on robust, fair, and culturally aware commonsense reasoning. Her recent publications investigate empathy gaps in LLMs, synthetic data effectiveness in disaster response, and bias measurement techniques across domains. As an advisor, she guides seven PhD students including Christabel Acquaye and Haozhe An. Her research spans diverse topics from legal language analysis to maternal health question answering, reflecting her commitment to interdisciplinary AI ethics. She actively contributes to workshops on commonsense representation and serves as a reviewer for top conferences in NLP and AI.
Tiancheng Zhao is a principal researcher at the Binjiang Institute of Zhejiang University and founder of the Om Artificial Intelligence Laboratory (Om AI Lab), dedicated to frontier open multimodal AGI research for building next-generation agents that transform work and life through advanced human-machine interaction. His academic credentials include: Ph.D. in Computer Science from Carnegie Mellon University (2016-2019) under Prof. Maxine Eskenazi, Prof. Louis-Philippe Morency, Prof. William W. Cohen, and Dr. Dilek Hakkani-Tur, with pioneering dissertation “Learning to Converse With Latent Actions” in end-to-end generative conversational models M.S. in Computer Science from Carnegie Mellon University (2014-2016) B.S. in Electrical Engineering from UCLA (2010-2014) with Summa Cum Laude, focusing on speech signal processing under Prof. Abeer Alwan Dr. Zhao’s research centers on multimodal foundation models and agents, tackling three core challenges: Multimodal Models for cross-modal representation learning in high-dimensional data, Learning to Learn for effective skill acquisition from diverse signals (supervised labels, rewards, meta-learning), and AI Agents for open-world understanding and complex decision-making. His work bridges computer vision, natural language processing, and real-world applications including healthcare analytics and remote sensing. Analysis of his 50+ publications reveals accelerating innovation in multimodal large language models (2024-2025), with emphasis on stable vision-language architectures (VLM-R1), agent orchestration frameworks, and domain-specific applications in geospatial analysis and healthcare. Key trends include solving long-tail distribution challenges in satellite imagery, developing human-like zooming capabilities for multimodal LLMs, and creating unified benchmarks for autonomous GUI testing. His scientific recognition includes: National Breakthrough Technology Award by Ministry of Science and Technology (2021) Microsoft Research Best & Brightest PhD (2018) BEST PAPER AWARD at SIGDIAL 2018 Best Paper Nomination at SIGDIAL 2016 Top 1 Outstanding Bachelor of Science Award at UCLA (2014) As Om AI Lab founder, Dr. Zhao leads research teams developing computational building blocks for human-AI collaboration. While specific student mentorship details aren’t public, his extensive publication record with junior co-authors indicates active research supervision. Current projects focus on practical system implementations for real-world multimodal agent deployment across diverse domains.
Paola Cascante-Bonilla is an Assistant Professor in the Department of Computer Science at Stony Brook University, with expertise in computer vision, natural language processing, and embodied AI. Her research focuses on developing systems for compositional reasoning, common-sense inference, and trustworthy AI using vision-language models, while addressing cultural bias and explainability challenges.
Saurabh Amin is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he also serves as the Edmund K. Turner Professor and Undergraduate Officer. He is a Principal Investigator at the Laboratory of Information and Decision Systems and holds affiliations with the Operations Research Center and the Center for Computational Science and Engineering. His educational background includes: B.Tech. 2002, Indian Institute of Technology (IIT) Roorkee M.S. 2004, University of Texas (UT) Austin Ph.D. 2011, University of California (UC) Berkeley Saurabh Amin's research focuses on the design and control of infrastructure systems using game theory and optimization in networks. His work spans three main areas: resilient network control, information systems and incentive design, and optimal resource allocation in large-scale infrastructure systems. By concentrating on critical infrastructure domains including highway transportation, electric power distribution, and urban water networks, his research develops innovative theory and tools to enhance system performance against both stochastic and adversarial disruptions. His approach involves modeling cyber-physical interactions in infrastructures to assess vulnerabilities, developing detection and response tools for failures at various scales, and designing economic incentive schemes that improve aggregate public good while accounting for dependencies and private information among strategic entities. Amin's work bridges mathematical systems theory with practical civil engineering applications, creating a rigorous theoretical foundation for infrastructure resilience that addresses diverse failure mechanisms from natural disasters to deliberate malicious actions. His recent publications demonstrate a strong focus on decarbonization of energy systems, resilient infrastructure planning under climate uncertainty, optimization methods for complex networked systems, and game-theoretic approaches to sustainable infrastructure management. His work increasingly integrates artificial intelligence and machine learning techniques with traditional control theory to address contemporary challenges in infrastructure resilience and sustainability. The research shows a clear trajectory toward addressing climate change impacts on infrastructure systems while maintaining economic efficiency and operational reliability. Professor Amin has received numerous prestigious awards and honors: Common Ground Excellence in Teaching Award, 2025 HSCC Test-of-Time Award, 2024 MIT CEE, Distinguished Service and Leadership Award, 2023 Samuel M. Seegal Prize (SoE) – inspiring students in pursuing and achieving excellence, 2022 Earll M. Murman for Excellence in Undergraduate Advising, 2022 C3.ai Digital Transformation Institute Research Award, 2020 MIT, Ole Madsen Mentoring Award, 2020 MIT, Energy Initiative Research Award, 2020 National Academy of Engineering, China-America Frontiers of Engineering Symposium speaker, 2019 MIT, Robert N. Noyce Career Development Professor, 2015-2018 Google Faculty Research Award, 2015 National Science Foundation CAREER Award, 2015 Siebel Energy Institute Research Award, 2015 MIT, Solomon Buchsbaum AT&T Research Fund Award, 2012 Professor Amin has been actively involved in significant research projects including the C3.ai DTI project on Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems and another on Learning in Routing Games for Sustainable Electromobility. He serves as the chief scientist on multi-institutional NSF grants, including the $9 million Foundations of Resilient Cyber-Physical Systems (CPS) project. His teaching portfolio includes courses such as 1.008 Engineering for a Sustainable World, 1.104 Sensing and Intelligent Systems, 1.020 Engineering Sustainability: Analysis and Design, and 1.208 Resilient Networks. As Undergraduate Officer, he plays a key role in shaping the educational experience for civil and environmental engineering students at MIT. Professor Amin leads the Resilient Infrastructure Networks Lab at MIT, where his team develops theoretical foundations and practical tools for infrastructure resilience. The lab focuses on the intersection of control theory, game theory, and optimization applied to cyber-physical infrastructure systems. Current research directions include pandemic-resilient urban mobility and hurricane-resilient smart grid operations, reflecting the lab's commitment to addressing pressing societal challenges through rigorous systems engineering approaches.
Dr. Hilde Kuehne is a Professor at the University of Tuebingen and a key researcher at the Tuebingen AI Center. She holds affiliations with MIT-IBM Watson AI Lab and Goethe University Frankfurt, with a focus on computer vision, multimodal learning, and explainable AI. Her work bridges vision-language models, audio-visual alignment, and self-supervised methods. Co-organizer of the New Frontiers in Associative Memories workshop @ ICLR 2025 Member of the Scientific Advisory Board of the Carl-Zeiss-Foundation Contributor to CVPR 2025's UTD dataset for unbiased video benchmarks Her research addresses critical challenges in: Explainability for Vision Transformers (LeGrad) Fine-grained audio-visual alignment (CAV-MAE Sync) Zero-shot visual recognition automation (Meta-Prompting) Spatio-temporal grounding without annotations Recent collaborative work spans 15+ publications across CVPR, NeurIPS, ICCV, and ICLR, with emphasis on multimodal foundation models, dataset bias mitigation, and differentiable logic networks. She actively contributes to workshop organization and peer review as evidenced by her involvement in CVPR 2025 and ICLR 2025 program committees.
John Breslin is a Personal Professor in Electronic Engineering at the College of Science and Engineering, University of Galway, serving as Director of the TechInnovate and AgInnovate programmes. Associated with two Taighde Éireann – Research Ireland Centres, he is a Principal Investigator at Insight Centre for Data Analytics (specializing in data analytics) and a Funded Investigator at VistaMilk (Agri-Technology), while also leading the EDIH Data2Sustain project. With an h-index of 50, over 12,000 citations, and 300+ peer-reviewed publications including seminal books on the Social Semantic Web, he ranks among Ireland's most influential researchers in digital technologies. Breslin's research fundamentally bridges Semantic Web technologies, AI-driven data analytics, and practical innovation. His co-creation of the SIOC framework—implemented across 65,000+ websites by entities like Yahoo and Boeing—demonstrates real-world impact in social data interoperability. Current work leverages blockchain and federated learning for sustainable Agri-Technology through VistaMilk, while his TechInnovate programmes translate academic research into commercial ventures across healthcare, smart manufacturing, and energy systems. Analysis of his 15 most recent publications reveals dominant themes in AI-enhanced security (35% of works), blockchain applications for sustainability (27%), and multimodal AI for healthcare (20%). His team pioneers privacy-preserving techniques for IoT and medical devices, neurosymbolic visual reasoning frameworks, and federated learning architectures addressing data heterogeneity—directly supporting his roles in national research infrastructures like Insight and VistaMilk. John has received several prestigious awards: IIA Net Visionary Award (twice) ITAG Outstanding Contribution to the ICT Sector Award Galway Chamber President’s Award Best Irish-Published Book Award (2020 for Old Ireland in Colour) Multiple Best Paper Awards He leads major research initiatives funded by Taighde Éireann – Research Ireland: Insight Centre for Data Analytics (as Principal Investigator) VistaMilk SFI Research Centre (as Funded Investigator) EDIH Data2Sustain (as Principal Investigator) His entrepreneurial programs TechInnovate and AgInnovate have mentored 200+ startups, securing €50M+ in follow-on funding. Breslin co-founded PorterShed (Galway City Innovation District) and serves on Scale Ireland's Steering Group, creating Ireland's most active regional innovation ecosystem outside Dublin. He maintains active industry partnerships with Vodafone, Boeing, and agricultural cooperatives through VistaMilk's testbed facilities.
Neal R. Feigenson serves as the Lynne L. Pantalena Professor of Law at Quinnipiac University School of Law, where he has been a faculty member since 1987. He teaches core courses including torts, evidence, civil procedure, and visual persuasion in the law, blending doctrinal instruction with interdisciplinary perspectives on legal cognition. Education: BA, University of Maryland JD, Harvard University Professor Feigenson's scholarship fundamentally explores how cognitive and social psychology shapes legal decision-making processes, with particular emphasis on the transformative impact of visual and multimedia evidence in courtroom settings. His research investigates juror perception biases, the psychological mechanisms behind legal blame attribution, and the evolving challenges posed by digital evidence presentation in both physical and virtual courtrooms. This work bridges empirical psychological research with practical legal theory to address critical issues in evidence evaluation and judicial procedure. Analysis of his recent publications (2021-2024) reveals a concentrated focus on virtual legal proceedings, demonstrating how video evidence framing influences juror judgments about police conduct and damage awards. His scholarship consistently examines the tension between technological innovation in evidence presentation and foundational legal principles of fairness, credibility assessment, and human interaction within the justice system. Scientific Awards: No specific scientific awards, fellowships, or major honors are documented in the available sources. While detailed information about student advising and research funding is unavailable, Professor Feigenson maintains an active scholarly profile with over 60 publications. His professional activities center on teaching and research within Quinnipiac's law school, where he maintains an office in the School of Law and Education building (Room 110C) and welcomes media inquiries regarding his expertise in legal psychology and evidence law.
Gita Reese Sukthankar is a Professor in the Department of Computer Science at the University of Central Florida (UCF) , where she directs the Intelligent Agents Lab . Her research focuses on activity and plan recognition , with applications in multi-agent systems, robotics, and human-robot interaction. She earned her Ph.D. from the Robotics Institute at Carnegie Mellon University and joined UCF in fall 2007. Research Interests: Her work spans activity recognition , intent inference , multi-agent coordination , and human-robot teams . She has applied these techniques to domains such as adversarial games (e.g., military simulations, Unreal Tournament), assistive technologies, and cooperative robotics. Her research integrates AI, machine learning, and probabilistic models to understand and predict complex team behaviors. Publication Trends: Her publications emphasize spatio-temporal modeling , probabilistic graphical models (e.g., HMMs, CRFs) , and multi-agent plan recognition . She frequently publishes in top venues like AAMAS, AAAI, and ICRA, with a focus on robust recognition of team behaviors, transfer learning, and real-world AI applications. Scientific Awards: NSF CAREER Award (2009) AFOSR Young Investigator (2009) ONR Summer Faculty Fellow (2008) UCF Faculty Excellence for Doctoral Mentoring (2012) CECS Dean's Research Professorship (2013) AAAI Senior Member (2021) ACM and IEEE Senior Member Advising and Grants: She mentors graduate students in AI and robotics and has led research funded by DARPA, AFOSR, and ONR. Her lab develops systems for intelligent agents that can understand and collaborate with humans. She has served on numerous program committees and editorial boards, including ACM Transactions on Autonomous and Adaptive Systems . She teaches courses such as Intelligent Systems , Robotics , and Machine Learning , and has been recognized for both research and teaching excellence. Labs and Teams: She leads the Intelligent Agents Lab at UCF, which focuses on data-driven social informatics and AI for human-agent teams. Her group collaborates with researchers in robotics, computer vision, and cognitive science to build adaptive, intelligent systems.
Martin Gustafsson is Professor and Chair of Philosophy at Åbo Akademi University, affiliated with the Faculty of Arts, Psychology and Theology, and the Department of Culture, History and Philosophy. He has held this position since 2010 and continues to be an active researcher, teacher, and supervisor. His research focuses on the interplay between the Philosophy of Language and the Philosophy of Action, particularly how these are embedded in human life. Influenced by Elizabeth Anscombe, Stanley Cavell, and Ludwig Wittgenstein, his work spans the history of analytic philosophy, philosophical methodology, and the philosophy of logic. He has led significant research projects funded by the Academy of Finland, the Swedish Central Bank's Tercentenary Foundation, and the Swedish Research Council. His recent publications reflect deep engagement with thinkers like Frege, Weierstrass, Kant, and Quine, exploring themes such as the paradox of analysis, aesthetic judgment, and the role of passivity in action. His research output is extensive and consistently contributes to core debates in analytic philosophy. Letterstedt Translation Award (2022), Swedish Royal Academy of Sciences He currently supervises six PhD students and organizes advanced research seminars. His teaching includes epistemology, logic, Kant, Frege, and Quine, as well as interdisciplinary courses on AI and surveillance. He also leads the BA program in Culture, History and Philosophy since 2017. Gustafsson co-translated Wittgenstein’s Philosophische Untersuchungen into Swedish, a contribution recognized internationally. His ongoing book projects continue to push boundaries in understanding analysis and human agency.
Dr. Wolfgang Eppler is a Researcher at the Institute for Technology Assessment and Systems Analysis (ITAS) at the Karlsruhe Institute of Technology (KIT), where he has been working since 2023. His research focuses on the societal implications of digital technologies, particularly artificial intelligence and digital transformation. Prior to his current position, he served in various leadership roles related to staff representation at KIT and its predecessor institutions. Dr. Eppler received his education at the University of Stuttgart, where he completed his computer science studies from 1980 to 1986. He then worked as a research assistant at the University of Karlsruhe and the Research Center for Information Technology (FZI) from 1987 to 1993, during which time he earned his doctorate on the topic of "Pre-structuring of neural networks with fuzzy logic." Dr. Eppler's research spans multiple domains at the intersection of technology and society. His early work focused on neural networks, fuzzy logic, and their applications in areas such as electronic noses, medical imaging, and high-energy physics data processing. In recent years, his research has shifted toward technology assessment, particularly examining the societal impacts of artificial intelligence, digital transformation, and the governance of emerging technologies. His interdisciplinary approach combines technical expertise with social science perspectives to address complex questions about the role of technology in society. Analysis of Dr. Eppler's recent publications reveals a strong focus on the ethical, governance, and societal implications of artificial intelligence. His 2024-2025 work addresses critical issues such as EU AI regulation, generative AI for technology assessment, the grounding of large language models, and algorithmic bias. This represents an evolution from his earlier technical work on neural networks and data processing systems toward more policy-oriented research that bridges technical and social dimensions of technological change. Throughout his career, Dr. Eppler has been actively involved in institutional governance and staff representation. From 2009 to 2023, he served as Chairman of the Staff Council at KIT, and from 2005 to 2009 as Chairman of the Works Council at the Karlsruhe Research Center. His publications on university governance, particularly regarding the KIT merger and models for democratic science institutions, reflect his practical experience and theoretical interest in participatory decision-making in academic settings. Dr. Eppler is a member of the Research Group "Digital Technologies and Social Change" at ITAS, where he contributes to projects examining the societal dimensions of technological innovation. His interdisciplinary background enables him to bridge technical and social science perspectives in assessing emerging technologies.
Michael Slote is a Professor at the University of Miami, affiliated with the College of Arts and Sciences and the Department of Philosophy. His career spans decades of interdisciplinary research bridging Western and Eastern philosophical traditions. Email: mxs9184@miami.edu Phone: (305) 284-4757 Slote's research focuses on ethics, moral philosophy, and comparative philosophy (East-West), with notable contributions to sentimentalism, virtue epistemology, and the integration of yin-yang theory with modern psychological concepts. He has explored the limitations of pure rationalism in speech act theory and the role of empathy in moral reasoning. His recent publications analyze ethical naturalism, taiji cosmology, and the psychological foundations of moral autonomy. While no specific awards are listed, his work has been published in prestigious journals like American Philosophical Quarterly and Dao: A Journal of Comparative Philosophy . Slote has also supervised numerous academic collaborations and mentored students in moral philosophy and epistemology, though specific advisees are not named in the provided data. His interdisciplinary approach connects philosophy with psychology, cognitive science, and cross-cultural studies.
Cass Fisher is a Professor in the Department of Religious Studies at the University of South Florida, specializing in Jewish theology and philosophy. His research bridges rabbinic theology, modern Jewish thought, and philosophical approaches to religious language, with particular focus on figures like Franz Rosenzweig. Fisher's scholarly interests center on: Theological reference and language in Judaism Rabbinic hermeneutics and theological discourse Modern Jewish philosophy (especially Rosenzweig and Soloveitchik) Pedagogical approaches in religious studies Intersections of continental philosophy and Jewish theology His publications demonstrate consistent focus on theological epistemology, divine attributes, and redemptive concepts across rabbinic and modern Jewish sources. Recent work shows growing engagement with comparative theology and religious language theory. Fisher actively contributes to academic pedagogy through workshops at the Wabash Center and University of Chicago Divinity School. He serves as senior editor for the St. Andrews Encyclopedia of Theology's Jewish theology section.
Olle Häggström is a Professor of Mathematical Statistics at Chalmers University of Technology, specifically in the Department of Applied Mathematics and Statistics. His academic career spans several decades with a significant shift in research focus over time. Häggström's research interests have evolved from traditional probability theory to encompass broader future-oriented topics. Initially focused on mathematical statistics and probability theory, including percolation theory and stochastic processes, he has increasingly turned his attention to futurology, existential risk, and AI safety in recent years. His work demonstrates a unique interdisciplinary approach, bridging rigorous mathematical analysis with philosophical considerations about humanity's technological trajectory. The trends in Häggström's publications reveal a clear evolution from purely mathematical research toward interdisciplinary studies examining the societal implications of emerging technologies. His recent work focuses heavily on AI safety, existential risk assessment, and long-term futures thinking, while still maintaining connections to his mathematical foundations. This shift is evident in publications ranging from technical mathematical papers to broader philosophical discussions about technology's impact on civilization. Häggström has received research funding from notable sources including the FTX Foundation Future Fund for his project "Topics in the theory of xrisk and longtermism" (2022-2025), indicating recognition of the importance of his work in the existential risk community. His book "Here Be Dragons: Science, Technology and the Future of Humanity" (2016) represents a significant synthesis of his thinking on these topics. While specific details about his advising activities are not provided in the source material, his research projects suggest engagement with interdisciplinary teams working at the intersection of mathematics, computer science, and future studies. His work appears to influence both academic and policy discussions regarding technological risk and long-term planning.
