Nicholas Evans is Distinguished Professor of Linguistics and Director of the ARC Centre of Excellence for the Dynamics of Language (CoEDL) at the Australian National University’s School of Culture, History & Language. His work bridges fieldwork-based language documentation with theoretical questions in typology, cultural evolution, and social cognition. Focus on endangered Australian and Papuan languages Director of ARC Laureate Project on 'The Wellsprings of Linguistic Diversity' Co-leader of SCOPIC (Social Cognition Parallax Corpus) study Collaborator in global linguistic diversity initiatives His research explores how micro-level community multilingualism shapes macro-level linguistic diversity, with fieldwork spanning seven years in remote Indigenous communities. Recent projects include PARABANK (paradigm syncretism analysis) and Southern New Guinea language studies, particularly Nen and Yam family languages. Scientific recognition includes the Ken Hale Award (Linguistic Society of America), Anneliese Maier Forschungspreis, and fellowships in the Australian Academy of Humanities, Australian Social Sciences Academy, and the British Academy.
Jiaxuan You is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign, leading the U Lab focused on achieving Artificial General Intelligence (AGI) in digital environments. His research spans graph neural networks (GNNs), relational data, foundation models, and machine learning systems. PhD and MS in Computer Science from Stanford University (2021) Developed GraphGym and PyTorch Geometric (PyG) for graph learning Core member at Kumo AI (2021-2023) His research explores: Graph-enhanced LLMs: Integrating relational structures into foundation models AGI Development: Self-optimizing AI agents and tool utilization ML Systems: Scalable architectures and redundancy-free computation Interdisciplinary Applications: Financial networks, crop yield prediction, and metro systems Recent publications focus on temporal reasoning, multi-agent dynamics, and hybrid architectures for LLMs. He actively develops open-source tools like DBGYM and GraphRouter. Scientific recognition includes: JPMC PhD Fellowship Baidu Scholarship Best Student Paper at AAAI 2017 World Bank Big Data Innovation Challenge winner He mentors PhD and intern students, emphasizing machine learning systems expertise. His lab collaborates on AGI workshops (e.g., ICLR 2024) and industry projects.
Adam Runions is a researcher in the Department of Computer Science at the University of Calgary, leading the MPG Partner Group in computational analysis of leaf development through collaborative work with Miltos Tsiantis. His group is embedded in the Graphics Cluster, focusing on interdisciplinary problems at the intersection of computer science and developmental biology. University of Calgary - Department of Computer Science MPG Partner Group (2022) Graphics Cluster affiliation His research explores computational modeling and analysis of plant form and development across multiple scales, integrating geometric modeling, physically-based simulation, and computer-aided design. Key themes include plant morphogenesis, self-organization of natural forms, and cross-disciplinary applications in computer graphics and animation. Recent publications emphasize plant development (leaf shape, bark patterning), mathematical modeling (auxin-driven patterning), and geometric techniques (subdivision surfaces, PUPs). Collaborations span institutions like the Max Planck Institute for Plant Breeding Research. Scientific Awards Marie Sklodowska-Curie Fellowship Best Paper Award (International Conference on Cyberworlds 2015) Best Student Paper Award (Computer Graphics International 2011) The group actively recruits BSc, MSc, and PhD students with backgrounds in computer science and mathematics for projects on plant form simulation and digital content creation. Research integrates evolutionary biology, biomechanical modeling, and computational techniques.
Kazuhiro Saitou is a Professor of Mechanical Engineering at the University of Michigan, affiliated with the College of Engineering. His research focuses on computational design synthesis, topology optimization, and manufacturing process integration. He leads the Algorithmic Synthesis Laboratory (ASL), advancing algorithms for automated design and optimization of mechanical systems. Education: Ph.D. (1996), MIT; M.S. (1992), MIT; B.Eng. (1990), University of Tokyo. He has held tenured positions since 1997, including roles as Founding CEO of Comnext, Inc. (2007–2012) and visiting professorships at École Centrale Paris and Donghua University. Research interests include multi-material topology optimization (M^3 TO), AI-driven design, and sustainable manufacturing. Key projects address additive manufacturing, composite structures, and energy-efficient production systems. He has pioneered methods for manufacturability-driven design and assembly optimization. Notable awards include IEEE Fellow (2018), ASME Kos-Ishii Award (2015), and NSF CAREER Award (1999). He serves as Editor-in-Chief for IEEE Transactions on Automation Science and Engineering and holds leadership roles in ASME and IEEE societies. Teaching includes courses on design optimization, CAD, and global product development. His lab has advised over 30 students, with alumni in academia and industry. Current research explores biomechanical modeling, traffic flow optimization, and medical image registration algorithms.
Dawn Y. Sumner is a Professor in the Department of Earth and Planetary Sciences at the University of California, Davis. Her research focuses on geobiology, paleobiology, and planetary science, particularly reconstructing ancient environments on Earth and Mars. She is a key member of NASA’s Mars Science Laboratory team, contributing to the Curiosity rover’s exploration of Gale Crater on Mars. Sumner’s work integrates field studies, lab analyses, and interdisciplinary approaches to understand microbial life’s role in shaping Earth’s history and potential habitability on other planets. Education: Ph.D., Massachusetts Institute of Technology (1995). Research interests include microbialite formation, Antarctic lake ecosystems, and the evolution of oxygenic photosynthesis. She investigates modern microbial communities in ice-covered lakes (e.g., Lake Vanda) to understand ancient environments and their biosignatures. Her scientific awards include the California Academy of Sciences Academy Fellow (2020) and Geological Society of America Fellow (2014). Sumner emphasizes inclusive education and supports student success in STEM through feminist research practices. Labs/Teams: W.M. Keck Center for Active Visualization in the Earth Sciences (KeckCAVES), Antarctic Lake Research Group.
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Joel Mokyr is the Robert H. Strotz Professor of Arts and Sciences and Professor of Economics and History at Northwestern University , with additional affiliation as the Sackler Professor at the Eitan Berglas School of Economics, Tel Aviv University. His work bridges Economic History , Technological Change , and Population Economics , emphasizing evolutionary models and institutional frameworks. Research Focus : His scholarship explores how knowledge systems and technological innovation drove Industrial Revolutions , European economic divergence , and institutional evolution . Teaching : Courses include Economic History of the US Since 1865 , Advanced Topics in European Economic History , and History of Modern Europe , with syllabi and resources provided. Article Trends : His recent publications examine the role of institutions , intellectual property , and cultural contexts in technological progress, spanning from the Industrial Revolution to modern economic growth . Papers address evolutionary economics , counterfactual analysis , and knowledge diffusion . Scientific Awards : 2011 Upton Scholar Advising and Grants : While specific students and grants are not listed, his work has influenced economic historians and technology scholars through publications and conference presentations. Collaborations include co-authored studies on Irish famine mortality and industrial policy .
Sharon Street is a Professor of Philosophy and Department Chair at New York University, affiliated with the Department of Philosophy in the College of Arts & Science. She holds a B.A. from Amherst College (1995) and a Ph.D. from Harvard University (2003). Her research focuses on metaethics, particularly reconciling normativity with scientific worldviews, emphasizing evolutionary biology's role in understanding practical and epistemic reasons. Her work challenges traditional realist theories of value and explores constructivist frameworks to address ethical and epistemic challenges. Her recent publications (2015–2022) investigate themes like normative relativism, the implications of theism on moral skepticism, and the contingency of value. Articles such as A Darwinian Dilemma for Realist Theories of Value (2006) and Evolution and the Nature of Reasons (2003) underscore her long-standing engagement with evolutionary perspectives in ethics. She critiques quasi-realism and defends constructivist accounts of practical reason, often addressing tensions between biological contingency and normative commitments. No scientific awards were explicitly listed. Her advising and grant activities are not detailed in the provided text. She is affiliated with NYU's Philosophy Department at 5 Washington Place, NYC.
Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.
Rina Dechter is a Professor of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences (ICS). She specializes in automated reasoning, probabilistic and constraint-based graphical models, and causal inference. Dechter has held leadership roles, including Co-Editor-in-Chief of Artificial Intelligence since 2011 and editorial board memberships in journals such as the Constraint Journal and Journal of Machine Learning Research . Education : Ph.D., Computer Science, University of California, Los Angeles (UCLA) M.S., Applied Mathematics, Weizmann Institute B.S., Mathematics and Statistics, Hebrew University of Jerusalem Research Interests : Dechter’s work focuses on computational aspects of automated reasoning, constraint processing, probabilistic reasoning, and causal inference. She develops efficient algorithms for graphical models, emphasizing tractable reasoning tasks and anytime search strategies. Her recent projects include causal decision-making frameworks funded by a $5M NSF grant. Awards : Presidential Young Investigator Award (1991) AAAI Fellow (1994) ACP Research Excellence Award (2007) ACM Fellow (2013) Elected to the American Academy of Arts & Sciences (2025) Grants & Collaborations : She leads a multi-institutional NSF-funded project on causal foundations of AI decision-making. Her work emphasizes trustworthiness in AI through causal models, with applications in robotics and public health.
Qiaowei Pan is a Researcher at the University of Lausanne , focusing on Evolution and Ecology . They have held a Guest Researcher role at the Institute of Molecular Biology gGmbH (IMB) in Mainz, Germany since 2023, and a Postdoctoral Researcher position at the University of Lausanne since 2018. Education: PhD in Molecular and Evolutionary Biology (2014-2018), INRAe, University of Rennes II, France Erasmus Mundus Master in Evolutionary Biology (MEME) (2012-2014), University of Groningen (Netherlands) & University of Montpellier II (France) BSc in Biology (2008-2012), University of North Carolina-Chapel Hill, USA Research Interests: Qiaowei Pan's work centers on the intersection of molecular genetics , evolutionary biology , and developmental biology , particularly in sex determination mechanisms across diverse animal models. Their studies span non-coding RNA regulation , sex chromosome evolution , and signal transduction pathways like TGF-β in reproductive systems. Publication Trends: Recent articles highlight expertise in sex determination systems (5/12 publications), genomic approaches (6/12), and fish developmental evolution . Collaborative work includes computational methods ( RADSex workflow ) and comparative studies across ant , goldfish , catfish , and cavefish models. Labs & Teams: Currently affiliated with the Keller-Valsecchi group at IMB and the Department of Evolution and Ecology at the University of Lausanne.
Howie Choset is a Professor of Robotics at the Robotics Institute, Carnegie Mellon University. He directs the Undergraduate Robotics Minor and leads the Biorobotics Laboratory, where his research focuses on snake robots, motion planning, and medical robotics. He is also affiliated with the Manufacturing Futures Institute. Ph.D., Mechanical Engineering, California Institute of Technology (1996) M.S., Mechanical Engineering, California Institute of Technology (1995) B.S.E., Computer Science and Engineering, University of Pennsylvania (1990) B.S., Economics, The Wharton School of Business (1990) Choset's research centers on robotics for confined and complex environments, particularly through the development of snake robots. His work integrates mechanism design, path and motion planning, and estimation to enable applications in surgery, manufacturing, infrastructure inspection, and search and rescue. He is a pioneer in medical robotics and has co-founded Medrobotics to commercialize minimally invasive surgical robots. His recent publications highlight a strong focus on ergodic exploration, multi-agent systems, motion planning under uncertainty, and medical robotics. Themes include optimizing robot trajectories for information gathering, solving complex path planning problems with dynamic obstacles, and advancing autonomous systems for disaster response and space exploration (e.g., the EELS robot for Enceladus). MIT Technology Review Top 100 Innovators under 35 (2002) Best Paper Award, RIA (1999) Best Paper Award, ICRA (2003) Best Paper, IEEE Bio Rob (2006) Best Video, ICRA (2011) Nominations for best papers at ICRA, IROS, and CLAWAR Choset has advised numerous students, many of whom have won top awards. His lab has received significant funding for robotics research, including projects in surgical robotics, additive manufacturing, and autonomous exploration. He is the lead author of the textbook Principles of Robot Motion and is actively involved in educational innovation through custom robotics labs. He leads the Biorobotics Laboratory at CMU, which develops advanced robotic systems like snake robots and the EELS (Exobiology Extant Life Surveyor) robot for NASA missions. The lab collaborates with industry and government agencies on applications ranging from surgery to space exploration.
Benjamin Machta is an Assistant Professor of Physics at Yale University, affiliated with the Department of Physics and the QBio Institute. He holds a BS from Brown University and a PhD from Cornell University, followed by a postdoctoral fellowship at Princeton University. His research focuses on applying theoretical physics to understand biological systems, particularly leveraging statistical physics and information theory to study biological membranes near critical points and the energetic constraints of biological signaling. Education: BS in Physics (Brown University), PhD in Physics (Cornell University), Postdoc at Princeton University (Lewis-Sigler Theory Fellow). Research Interests include: membrane criticality, phase transitions in biological systems, information-theoretic limits in organism function, and energy dissipation in biological processes. His work often bridges theoretical models with experimental data, such as collaborations with Sarah Veatch’s lab on membrane phase behavior. Publications highlight themes like membrane criticality, protein phase separation, and energy constraints in signaling. His group’s current projects explore cochlear mechanics, thermodynamic control in biological systems, and the role of criticality in sensory systems. Awards: 2019 Simons Investigator Award. Lab Affiliations: QBio Institute and Department of Physics at Yale, located in YSB-C164. Group members include postdocs Isabella Graf and Michael Abbott, and graduate students Asheesh Momi, Mason Rouches, and others.
Dylan Hadfield-Menell is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, holding the Bonnie and Marty (1964) Tenenbaum Career Development Professorship. His research focuses on AI alignment and human-AI interaction within MIT's School of Engineering. His research interests center on agent alignment problems in AI systems, particularly examining uncertainty in objective optimization for human-robot teams and societal oversight of machine learning systems. Key areas include the principal-agent alignment problem , assistance games frameworks , and robust preference learning that accounts for hidden contextual factors in reinforcement learning from human feedback. His recent publications reveal strong trends toward multi-agent cooperation , formal contract mechanisms for resolving social dilemmas, and advanced evaluation methodologies for AI safety. The research spans theoretical frameworks like open-universe assistance games while addressing practical challenges in language model alignment and cultural bias assessment. Scientific awards include: AI2050 Early Career Fellowship from Schmidt Futures Berkeley Fellowship NSF Graduate Research Fellowship C.V. Ramamoorthy Distinguished Research Award His work bridges theoretical computer science with real-world AI governance challenges, as demonstrated through MIT's participation in AI policy white papers. Current research directions include developing frameworks for transparent AI systems and addressing fundamental limitations in aligning recommender systems with human values through interdisciplinary synthesis.
Martin Haspelmath is a Senior Research Scientist at the Department of Linguistic and Cultural Evolution at the Max Planck Institute for Evolutionary Anthropology (MPI-EVA), Leipzig, and an honorary (adjunct) professor at Leipzig University. His research focuses on comparative linguistics, language universals, and typology, particularly in syntactic and morphological systems. He co-edited the World Atlas of Language Structures (2005/2013) and co-founded Language Science Press . Education: PhD in Linguistics, Freie Universität Berlin (1990–1993) MA in Linguistics, University of Cologne and University at Buffalo (1985–1989) Undergraduate studies in Linguistics, University of Vienna (1983–1985) Research Interests: Haspelmath investigates global grammatical diversity, form-function correspondences, and universals in syntax, morphology, and lexical systems. His work emphasizes comparative concepts for cross-linguistic analysis and critiques traditional grammatical categories. Grants & Projects: ERC project leader at Leipzig University (2015–2020) Co-creator of Grambank , an open-access database of grammatical structures Leading initiatives for open-access publication and linguistic data sharing Labs/Teams: Active in the MPI's Department of Linguistic and Cultural Evolution, collaborating on projects like APICS (Atlas of Pidgin and Creole Language Structures) and ValPal (Valency Patterns Leipzig).
