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April NowellView profile

Professor

• Paleolithic Archaeology
• Cognitive Archaeology
• Neanderthal Studies
• +7 more

Dr. April Nowell is a Professor of Anthropology in the Department of Anthropology at the University of Victoria's Faculty of Social Sciences, specializing in Paleolithic archaeology, cognitive archaeology, and the archaeology of children. Currently on leave, she leads internationally recognized research projects across Europe, the Levant, Australia, and Africa while actively accepting graduate students. She earned her PhD from the University of Pennsylvania and has developed expertise in Neanderthal lifeways, Paleolithic art, and hominin life histories. Her academic journey reflects deep engagement with both theoretical frameworks and fieldwork across diverse geographical contexts. Nowell's research examines how prehistoric societies structured knowledge transmission, childhood development, and symbolic expression. Her groundbreaking work on finger flutings in Australian caves reveals children's roles in Paleolithic storytelling traditions, while her analysis of Levantine wetland ecosystems demonstrates how Pleistocene humans adapted to environmental shifts. She challenges conventional narratives about Neanderthal cognition and has pioneered methodologies for reconstructing prehistoric childhood experiences through skeletal and material evidence. Her recent publications show consistent innovation in archaeological methodology, particularly in digital documentation of rock art and interdisciplinary approaches to human development. Key trends include integrating bioarchaeological data with cognitive models, examining material culture as evidence of social learning, and analyzing environmental archives to understand human dispersal patterns. Her scientific recognition includes: 2023 EAA Book Prize for Growing Up in the Ice Age: Fossil and Archaeological Evidence of the Lived Lives of Plio-Pleistocene Children Nowell secures major research funding including Social Sciences and Humanities Research Council grants supporting her Azraq Basin project in Jordan and Koonalda Cave research in Australia. She mentors graduate students in Paleolithic theory while collaborating with Indigenous communities and international scholars on field projects spanning five continents. Her work bridges academic research and public engagement through TEDx talks and media appearances examining science communication. She directs field programs at Jordan's Azraq Basin wetlands and Australia's Koonalda Cave, working with multidisciplinary teams including geochronologists, bioarchaeologists, and Traditional Owners to investigate Pleistocene human adaptation and cultural transmission.

David R. ClarkeView profile

Professor

• Materials Science
• Ceramics
• Metals
• +6 more

Professor David R. Clarke is the inaugural Extended Tarr Family Professor of Materials at Harvard School of Engineering and Applied Sciences. He is a Senior Fellow of the Hong Kong Institute for Advanced Study (HKIAS) and member of the US National Academy of Engineering. PhD in Physics (University of Cambridge) B.Sc. in Applied Sciences (Sussex University) ScD (University of Cambridge) His research spans fundamentals and applications of ceramics, metals, semiconductors, and polymers, focusing on mechanical properties, thermal barrier coatings, dielectric elastomers, oxidation fundamentals, and microelectronics reliability. Recent work explores electro-adhesive forces and nanopore evolution in yttria-stabilized zirconia. With over 500 publications in journals like Nature and Advanced Materials, Clarke's work has been cited >50,000 times (h-index 107). He holds 13 patents and has advised students across MIT, UC Berkeley, and Harvard. 2008 Japanese NIMS Award 1993 Humboldt Senior Scientist Award Distinguished Life Member, American Ceramic Society Teaching includes undergraduate courses on heat transfer and materials design, plus graduate courses on dislocations and composites. His lab recently worked on quantum dot displays and fatigue crack sensing technologies.

• Quantum Chromodynamics (QCD)
• Heavy Quark Physics
• Lattice Gauge Theory
• +4 more

Antonio Vairo is a full Professor at the Department of Physics, TUM School of Natural Sciences, Technical University of Munich, where he holds the Chair of Theoretical Physics - Applied Quantum Field Theory (T39) at the James-Franck-Str. 1/I campus in Garching bei München. His research focuses on the theoretical foundations of quantum chromodynamics with emphasis on heavy quark systems and non-perturbative phenomena. Professor Vairo's primary research interests include Quantum Chromodynamics (QCD), Heavy Quark Physics, Lattice Gauge Theory, Effective Field Theories, and Exotic Hadron Spectroscopy. His work bridges computational approaches with analytical frameworks to investigate quarkonium dynamics in extreme environments like the quark-gluon plasma, while developing novel applications of Born-Oppenheimer effective theory to multi-quark systems. Recent investigations extend into dark matter bound state formation in the early universe, demonstrating interdisciplinary reach across particle physics and cosmology. Analysis of his 2024-2025 publications reveals three dominant research thrusts: (1) quarkonium suppression mechanisms in heavy-ion collisions using open quantum systems approaches, (2) high-precision lattice QCD computations of static forces and chromoelectric correlators, and (3) systematic development of effective field theories for exotic hadrons and dark matter pairs. His work on pNRQCD (potential non-relativistic QCD) provides critical connections between lattice results and experimental observables in heavy-ion physics. Professor Vairo maintains active research leadership through collaborations with international groups including the Belle II experiment, as evidenced by his contributions to 'The Belle II Physics Book'. His methodological innovations in applying quantum trajectory methods to quarkonium evolution and developing FeynOnium computational tools for effective field theories demonstrate significant technical contributions to the field. Current research directions emphasize next-to-leading order corrections in heavy quark dynamics and Debye mass effects in dark matter bound state formation.

• Computer Graphics
• 3D Reconstruction
• Deep Learning
• +5 more

Maks Ovsjanikov is a Professor in the Computer Science Department at École Polytechnique, France , and a Visiting Research Scientist at Google DeepMind. His research focuses on mathematically principled approaches for geometric data analysis and synthesis, including learning on surface meshes, 3D point clouds, and graphs. Key Collaborations: Google DeepMind, Sanofi, Dassault Systèmes Research Themes: Non-rigid shape matching, 3D reconstruction, transfer learning, learning on geometric data, functional maps, deep learning for scientific discovery Recent Article Trends emphasize geometric deep learning, with publications at top venues like SIGGRAPH Asia, ICCV, and CVPR. Topics include surface reconstruction, functional maps, 3D keypoint detection, and diffusion models for shape matching. Scientific Honors include: ERC Consolidator Grant (VEGA Project, 2023) ERC Starting Grant (2017) ACM SIGGRAPH 2023 Test-of-Time Award Best Paper Awards at 3DV 2021 and 3DV 2022 Student Advisees have received prestigious awards, such as the IP Paris Best PhD Thesis Award (Souhaib Attaiki, 2023) and GdR IG-RV Runner-Up (Nicolas Donati, 2024). The GeomeriX Team at École Polytechnique drives his group's research, supported by the VEGA and AIGRETTE projects.

Mitchell L.R. Walker IIView profile

Professor

• Electric Propulsion
• Plasma Physics
• Hypersonic Aerodynamics/Plasma Interaction
• +6 more

Mitchell L.R. Walker II is a tenured Professor and the W.R.T. Oakes Chair at the Daniel Guggenheim School of Aerospace Engineering , Georgia Institute of Technology . He serves as the Associate Chair for Graduate Studies and Director of the Joint Advanced Propulsion Institute . His research focuses on electric propulsion , plasma physics , and hypersonic aerodynamics/plasma interaction , with expertise in Hall thrusters, ion engines, and plasma diagnostics. Education : Ph.D. (2004), M.S.E. (2000), B.S.E. (1999) in Aerospace Engineering from the University of Michigan. Labs : Leads the High-Power Electric Propulsion Laboratory (HPEPL) , one of the largest academic vacuum test facilities for propulsion research. Dr. Walker has authored over 130 technical publications and holds patents in ion focusing and cold cathode technology . His 15 most recent articles focus on Hall thruster performance under varying propellants, advanced diagnostics (THz spectroscopy, Thomson scattering), and plasma-material interactions. His research trends highlight plasma stability , vacuum facility effects , and non-invasive diagnostics . Awards : AIAA Fellow (2023), Georgia Power Professor of Excellence (2017), AFOSR Young Investigator (2006), Lawrence Sperry Award (2010), NASA Faculty Fellow (2005). Service : Chair of AIAA Electric Propulsion Technical Committee, member of NASA Advisory Council, and contributor to national standards for electric propulsion testing .

Mark CrowleyView profile

Associate Professor

• Reinforcement Learning
• Deep Learning
• Ensemble Methods
• +6 more

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.

Andrew ThompsonView profile

Professor

• Physical Oceanography
• Southern Ocean Dynamics
• Climate Science
• +3 more

Andrew Thompson is the John S. and Sherry Chen Professor of Environmental Science and Engineering at the California Institute of Technology. He serves as Director of the Ronald and Maxine Linde Center for Global Environmental Science and Executive Officer for Environmental Science at Caltech. With a Ph.D. from Scripps Institute of Oceanography (2006), his career at Caltech spans from Assistant Professor (2011-17) to his current Professor role since 2017. Education: B.S. in Physics from Dartmouth College (2000), C.A.S. (2001) and M.Phil. (2002) at University of Cambridge Leadership: Director of Linde Center (2023-), Academic Officer (2019-22) His research focuses on ocean circulation dynamics and physical processes governing climate systems . Key areas include: Ocean Turbulence and Submesoscale Dynamics Antarctic Circumpolar Current and Drake Passage Dynamics Climate Change Impacts on Ice Shelf Melt Rates Current projects involve ChinStrAP (Changes in Stratification at the Antarctic Peninsula), using autonomous ocean gliders to study eddy formation and air-sea exchange. His group employs idealized numerical models , remote sensing , and climate simulations to explore topics like: Warm water pathways onto Antarctic continental shelves Role of mesoscale/submesoscale eddies in ocean mixing Global overturning circulation responses to climate change Scientific achievements include the Packard Fellowship for Science and Engineering . He mentors graduate students Xiaozhou Ruan , Giuliana Viglione , and Andrew Delman , fostering interdisciplinary collaboration with institutions like Scripps Institution of Oceanography and CSIR . His group emphasizes inclusive training for early-career scientists in climate-relevant STEM careers .

Alex ShermanView profile

Lecturer

• Representation Theory
• Supergeometry
• Lie Superalgebras
• +7 more

Dr Alex Sherman is a Lecturer at UNSW Sydney in the School of Mathematics & Statistics . He previously held postdoctoral positions at the University of Sydney with Kevin Coulembier and at Ben-Gurion University of the Negev with Inna Entova-Aizenbud. His research focuses on representation theory and supergeometry , with applications to Lie superalgebras , modular representation theory , and tensor categories . He has published extensively on topics such as ghost distributions, Duflo-Serganova functors, and the geometry of spherical supervarieties. Email: alex.sherman@unsw.edu.au Location: Room 4111, The Red Centre, UNSW Sydney, NSW 2052 In 2025 , he will lecture the Linear Algebra stream of MATH1241. He organizes the UNSW Pure Maths Seminar and Algebra Seminar , and has co-organized courses on Kazhdan-Lusztig equivalences and tensor categories.

Bo ChenView profile

Research Fellow

• Networking
• Machine Learning Systems
• Virtual Reality
• +5 more

Bo Chen is a postdoctoral researcher at the Siebel School of Computing and Data Science and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. His work focuses on AI-system co-design for immersive computing, particularly in extended reality (XR) and multi-modal content delivery over wireless networks. Ph.D. in Computer Science (2022), advised by Klara Nahrstedt B.S. in Computer Science from Shanghai Jiao Tong University (2016) His research integrates AI techniques with system-level optimizations to address challenges in XR infrastructure , including multi-view video streaming , NeRF-based content delivery , and uncertainty management in video transmission . He has pioneered methods like Loose Frame Referencing for learned codecs and Context-Aware NeRF Serving for mobile XR applications. Bo Chen's recent publications span top venues like ACM MobiSys, ACM SenSys, and USENIX NSDI. Key themes include AI-driven compression , dynamic 3D rendering , and reliable streaming over mobile networks . He has received recognition including the Rising Star Best Presentation Award (ACM MobiSys 2025) and Best Student Paper Award (ACM MMSys 2022). Bayesian optimization for XR systems Multi-view video aggregation at edge networks 3D Gaussian Splatting for immersive media

Samuel Jean BassettoView profile

Associate Professor

• Industrial Engineering
• Artificial Intelligence
• Cognitive Science
• +4 more

Samuel Jean Bassetto is an Associate Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. He serves as Director of the Continuous Improvement Laboratory (LABAC) and holds membership in multiple prestigious research groups including the Research Group on Globalisation and Management of Technology (GMT), Poly-Industries 4.0 Laboratory, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), and Institute for Data Valorization (IVADO). Dr. Bassetto's research spans multiple disciplines, focusing on continuous improvement through the integration of engineering, artificial intelligence, cognitive science, psychology, and design. His primary sphere of excellence is in New Frontiers in Information and Communication Technologies, with secondary expertise in Modeling and Artificial Intelligence and Human Health. He develops tools that place humans at the center of technology to enhance organizational performance while respecting human rhythms and cognitive limitations. His recent publication portfolio reveals a strong interdisciplinary approach, with research bridging industrial engineering, cognitive neuroscience, and AI ethics. His work addresses practical challenges in lean manufacturing assessment, racial bias in medical AI systems, cognitive data collection in natural environments, and condition monitoring for industrial machinery. The research consistently demonstrates a commitment to developing practical solutions that integrate human factors with technological innovation. NSERC Synergy Prize for Innovation recipient Principal investigator on multiple research grants from NSERC, FRQ, and MITACS Collaborations with over a dozen institutions across multiple countries Supervision of over 150 highly qualified personnel throughout his career Dr. Bassetto teaches specialized courses including CAP7011 (Creativity in Research), IND8444 (Continuous Improvement), IND8203 (Industrial Launch), and previously taught IND8178 (Production). His teaching philosophy emphasizes practical application, with courses featuring hands-on exercises, real-world scenarios, and gamification techniques to enhance learning. His supervision portfolio includes numerous Ph.D. and Master's students working on topics ranging from human-technology collaboration to reinforcement learning for production management. Through LABAC, Dr. Bassetto leads research initiatives focused on developing human-centered tools for continuous improvement in organizational settings. The laboratory conducts projects related to industrial IoT applications, cognitive aspects of process improvement, and the development of practical frameworks for organizations to enhance performance while maintaining respect for human rhythms and cognitive capabilities.

Thorsten ChmuraView profile

Professor

• Behavioral Economics
• Experimental Economics
• Game Theory
• +4 more

Thorsten Chmura is a Professor in the Department of Economics at Nottingham Business School, Nottingham Trent University. His work focuses on experimental and behavioral economics, utilizing laboratory and field experiments to address real-world challenges. He maintains collaborations within NTU’s Applied Economics and Policy Research Group, Public Service Management Research Group, and international partnerships across Europe, China, and the US. Chair of Industrial Economics at University of Nottingham (previous) Director, Centre for Research in the Behavioural Sciences (previous) PhD in Economics and Physics from University of Bonn Research interests span behavioral economics, experimental economics, game theory, and traffic modeling. His work examines decision-making under risk, wage discrimination, and behavioral responses in complex systems. Recent publications explore AVOD streaming economics (2024), social trading herding (2022), and toll road choice dynamics (2014). Key article trends include: Behavioral responses in financial markets Risk attitudes across 30 countries Cultural value impacts on loyalty programs Traffic flow simulations Game theory applications in coordination problems Experimental validation of economic theories

Scott L. DiamondView profile

Professor

• Mechanobiology
• Thrombolysis
• Coagulation
• +10 more

Scott L. Diamond is the Arthur E. Humphrey Professor of Chemical and Biomolecular Engineering and Bioengineering at the University of Pennsylvania's School of Engineering and Applied Sciences. He serves as Director of the Penn Center for Molecular Discovery, Director of the Penn Biotechnology Masters Program (one of the largest in the country with over 130 students), and Associate Director of the Institute for Medicine and Engineering (IME). His laboratory is located in the Roy and Diana Vagelos Laboratories at 3340 Smith Walk, 1020 Vagelos Research Laboratories, Philadelphia, PA. Diamond's research spans multiple interconnected fields in blood biology and biotechnology. His work focuses on mechanobiology, thrombolysis, coagulation, bioadhesion, gene therapy, drug/device development, proteomics, drug discovery, systems biology, and microfluidics. His laboratory has developed numerous specialized microfluidic devices for studying blood clotting under various flow conditions, including 8-channel devices for high-throughput clotting assays, side-view devices for clot structure analysis, stenosis devices for high shear clotting assays, and impingement-post devices for studying von Willebrand factor fibers. Diamond's research group has pioneered approaches to model and predict blood function using systems biology principles. His team has developed computational models that integrate reaction-transport phenomena with platelet signaling networks to predict thrombus formation under flow. These models have enabled the development of 'virtual blood' computer simulations that can predict the effectiveness of anticoagulation drugs for individual patients, contributing significantly to personalized medicine approaches in hemostasis and thrombosis. His extensive publication record demonstrates a consistent focus on understanding the fundamental mechanisms of blood clot formation and dissolution. Recent work has emphasized microfluidic approaches for point-of-care diagnostics, patient-specific modeling of platelet function, and the development of novel therapeutic strategies for thrombotic disorders. His research bridges engineering principles with clinical hematology to address significant challenges in cardiovascular medicine. NSF National Young Investigator Award NIH FIRST Award American Heart Association Established Investigator Award AIChE Allan P. Colburn Award George Heilmeier Excellence in Research Award Elected Fellow of the Biomedical Engineering Society (BMES) Diamond has secured significant research funding, including a $2.8 million NIH grant for 'Blood Systems Biology' and a $9.5 million NIH grant for the Penn Center for Molecular Discovery. His laboratory has developed numerous microfluidic devices for blood analysis and has collaborated extensively with clinicians and industry partners. Diamond has served on advisory committees for NSF, NIH, AHA, and NASA, and has consulted extensively for industry and government. With over 180 publications and patents, his work has significantly advanced the understanding of blood clotting mechanisms and the development of diagnostic and therapeutic approaches for thrombotic disorders.

David L. Vander MeulenView profile

Professor

• Eighteenth-century English literature
• Bibliography
• Textual criticism
• +6 more

David L. Vander Meulen is a Professor of English at the University of Virginia, specializing in eighteenth-century English literature, bibliography, and textual criticism. He has served as editor of Studies in Bibliography since 1991 and previously collaborated with Fredson Bowers on editorial projects. His teaching includes courses on scholarly editing principles and practices, and he has contributed to major editorial works such as Pope's Dunciad and Samuel Johnson's translation of Sallust. University of Virginia: Professor of English Editor, Studies in Bibliography (1991-present) Specializes in 18th-century literature and textual scholarship His research focuses on bibliography, textual criticism, and scholarly editing, with an emphasis on eighteenth-century print culture and unauthorized editions. He has collaborated on critical editions of works by Pope, Johnson, and Faulkner, and contributed extensively to book history methodologies. Recent publications highlight his engagement with bibliographic pedagogy, the evolution of textual analysis tools, and the material study of printed texts. While no formal scientific awards are documented, his editorial leadership and scholarly editions have significantly shaped the field of textual criticism.

• Branching processes
• Random trees
• Reinforcement processes
• +9 more

Cécile Mailler is a Reader in Probability at the University of Bath, where she is a member of the probability group Prob-L@B. She has held significant research positions including an EPSRC postdoctoral fellowship (2018-2021) titled "Random trees: analysis and applications" and previously worked as a postdoc at Prob-L@B (2013-2016) as part of Peter Mörters' EPSRC project "Emergence of Condensation in Stochastic Networks". She earned her PhD under the supervision of Brigitte Chauvin and Danièle Gardy at the Laboratoire de Mathématiques de Versailles. Her research focuses on probability theory with emphasis on branching processes, random trees, reinforcement mechanisms, Pólya urns, stochastic approximation, random networks, and statistical physics. She has made significant contributions to understanding preferential attachment models, zero-range processes, and random Boolean trees. Her work bridges theoretical probability with applications in statistical physics and combinatorics. Analysis of her recent publications shows a strong focus on random tree structures, branching processes, and reinforcement learning algorithms, with applications spanning from network theory to statistical mechanics. Her research demonstrates sophisticated mathematical techniques applied to complex stochastic systems, particularly those with reinforcement mechanisms and memory effects. Associate Editor of the Applied Probability Trust (since October 2020) Associate Editor of Stochastic Processes and Their Applications (since March 2022) Author of a general introduction to Pólya urns for the LMS Newsletter (November 2020) Co-organizer of the "Random Walks: Applications and Interactions" conference at CIRM (January 2026) She actively supervises PhD students working on topics including the multi-city ants process, Pólya urns with growing initial composition, large deviations for the Monkey walk, and competing growth processes. She has secured research funding through EPSRC fellowships and has been involved in multiple collaborative projects with prominent researchers in probability theory. Mailler regularly teaches mini-courses on advanced probability topics at international summer schools and workshops, demonstrating her commitment to knowledge dissemination in the field.

Cesare FranchiniView profile

Professor

• Quantum Materials
• Computational Physics
• First Principles Methods
• +7 more

Cesare Franchini is a full Professor at the University of Vienna's Faculty of Physics, leading the Computational Materials Physics research group. His work focuses on theoretical understanding and computational modeling of quantum materials using first principles methods, particularly VASP. He maintains an active research program with numerous postdocs, PhD students, and collaborations across multiple institutions including the University of Bologna. Professor Franchini's research centers on quantum materials with many interacting degrees of freedom (lattice, spin, and electron orbital) that enable novel electronic and magnetic phases. His specific interests include metal-insulator transitions, polaron physics (electron-phonon interactions), non-collinear spin orderings, topological Dirac/Weyl phases, multiferroism, and superconductivity. He has increasingly incorporated machine learning data-driven tools and diagrammatic Monte Carlo techniques into his computational approaches. Analysis of his recent publications (2024-2025) reveals a strong focus on polaron physics across multiple material systems, with significant work on hematite, titanium dioxide, and quantum paraelectrics like KTaO3. His research increasingly integrates machine learning with traditional first-principles methods, particularly for studying hydrogen diffusion, surface science phenomena, and electronic structure calculations. There's also substantial work on single-atom catalysis and the application of advanced computational techniques to understand fundamental charge transport mechanisms in energy materials. Professor Franchini actively supervises numerous PhD students and postdocs, including Andrea Angeletti, Viktor Birschitzky, Lorenzo Celiberti, and several others working on diverse aspects of computational materials physics. He leads or participates in major research projects including TACO (Taming Complexity in Materials Modeling), DCAFM (Doctoral College Advanced Functional Materials), and the recently launched Spin-orbit entangled anharmonic polarons project. His group maintains strong collaborations with experimentalists at Charles University, Technical University of Vienna, and other international institutions.