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Brita WårvikView profile

Professor

• Discourse Analysis
• Pragmatics
• Historical Linguistics
• +7 more

Brita Wårvik is a Professor in the Department of Languages at Åbo Akademi University, affiliated with the Faculty of Humanities, Psychology and Theology. She holds a Doctor of Philosophy (Phil. Dr.) from the same institution, awarded in 2013, and has been actively contributing to linguistic research for decades. Doctor of Philosophy (Phil. Dr.), Åbo Akademi University, 2013 Her research centers on discourse analysis, pragmatics, and historical English linguistics, with a particular focus on Early Modern and Medieval English texts. She investigates discourse interaction, textual structures, and pragmatic conservatism in religious prose, often employing corpus-based and textual analysis methods. Her work bridges micro and macro perspectives in discourse, exploring how semantic units contribute to broader text worlds. Analysis of her recent publications reveals a consistent trajectory in historical discourse studies, with increasing emphasis on corpus linguistics, manuscript variation, and the evolution of discourse markers. Her editorial work, such as the 2024 volume Structures in Discourse , highlights her leadership in synthesizing interdisciplinary perspectives on language use. Scientific Awards: Teacher of the Year (2001) ÅAU Student Union's Rose (2007) Brita Wårvik actively supervises and mentors academic visitors and collaborators, as seen in her hosting of scholars like Carmen Lee and Lieselotte Anderwald. She is the coordinator of the ongoing Project ICLE (International Corpus of Learner English) , securing research continuity and international collaboration. Her involvement in organizing workshops, such as the ICLE+30 FI-subcorpus Workshop in 2024, underscores her role in fostering academic exchange. In terms of research infrastructure, she is deeply embedded in the ICLE network, contributing to the development of learner language corpora. Her activities reflect strong international collaborations, particularly in the fields of historical linguistics and discourse studies, with a visible presence in both research and academic community-building.

Hedvig KjellströmView profile

Professor

• Computer Vision
• Artificial Intelligence
• Human-Computer Interaction
• +6 more

Hedvig Kjellström is a Professor at the Division of Robotics, Perception and Learning within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. She holds significant affiliations with the Swedish e-Science Research Centre and the Max Planck Institute for Intelligent Systems in Germany. Her work spans multiple interdisciplinary domains and she serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025. Her research centers on Computer Vision as a sub-field of AI, with three interconnected themes: Computational Aesthetics (exploring aesthetic aspects of human communicative behavior), Communicative Behavior (developing models of how humans and animals perceive and produce non-verbal communication), and Embodied Artificial Intelligence (creating methodologies for robots and autonomous agents to perceive the world through sensors, primarily vision). Her work has significant applications in medical diagnostics, animal welfare, human-robot interaction, and creative arts. Analysis of her recent publications reveals a strong trend toward multimodal AI systems that integrate vision, language, and action understanding. Her research increasingly focuses on animal-centered applications, particularly equine pain detection and behavior analysis, while maintaining strong foundations in human communication modeling, gesture recognition, and 3D reconstruction techniques. The interdisciplinary nature of her work bridges computer science with veterinary medicine, neuroscience, and performing arts. Hedvig Kjellström actively supervises numerous PhD and Master's students across various projects and maintains extensive collaborations with institutions including Karolinska Institutet, Swedish University of Agricultural Sciences, and international partners. Her research is supported by major funding bodies including WASP, VR, and SeRC. She leads or participates in several notable projects including OrchestrAI (communication between conductor and orchestra), ANITA (Animal Translator), MARTHA (3D horse motion analysis), and STING (synthesis and analysis with transducers and invertible neural generators). Her work with ACAI (Animal Centered Artificial Intelligence), which she co-founded and directs, demonstrates her commitment to applying AI for animal welfare.

Kostas DaniilidisView profile

Professor

• Computer Vision
• Robotics
• Machine Learning
• +5 more

Kostas Daniilidis is the Ruth Yalom Stone Professor at the University of Pennsylvania in the School of Engineering and Applied Science , specifically the Department of Computer and Information Science . He is also affiliated with the GRASP Laboratory and Archimedes, Athena Research Center, Greece . Education : PhD in Computer Science (1992) from the University of Karlsruhe with Hans-Hellmut Nagel Diploma in Electrical Engineering (1986) from the National Technical University of Athens Research Interests : Kostas Daniilidis is a leading researcher in Computer Vision and Robotics , with significant contributions to event-based vision , equivariant learning , 3D human pose estimation , and hand-eye calibration . His work spans neural rendering , dynamic scene modeling , and low-latency sensing systems . Article Trends : Daniilidis’s recent publications focus on event cameras for low-light and high-speed applications, Gaussian splatting for real-time 3D reconstruction, and equivariant neural architectures for robust motion estimation. His work bridges deep learning with geometric vision , emphasizing human mesh recovery and multi-agent coordination . Scientific Awards : Best Conference Paper Award at ICRA 2017 IEEE Fellow (2012) Teaching : He has taught courses such as CIS580: Machine Perception and CIS121: Data Structures , alongside advanced topics in robotics and computer vision. Lab & Collaborations : As director of the GRASP Laboratory (2008–2013), he fostered interdisciplinary research in robotics, and currently collaborates with institutions like the Athena Research Center in Greece.

Richard GarnerView profile

Lecturer

• Category Theory
• Algebraic Structures
• Homotopy Type Theory
• +3 more

Richard Garner is a lecturer at Macquarie University's School of Mathematical and Physical Sciences, Faculty of Science and Engineering. He specializes in teaching mathematics to engineering and computing students in units like MATH2055 and MATH1007, focusing on problem-solving and real-world applications. His teaching philosophy emphasizes authentic mathematical experiences, blending abstract concepts with practical examples, such as connecting multivariable calculus to AI technologies. School: School of Mathematical and Physical Sciences University: Macquarie University Teaching Areas: Mathematics for engineering and computing, convolution, multivariable calculus Richard won a Student Nominated Award in the 2023 Vice Chancellor’s Learning and Teaching Awards, reflecting his commitment to student-centered education. He prioritizes clarity in course design, using visual tools and accessible materials to enhance learning, and fosters a supportive environment where students feel comfortable asking questions. Key Teaching Strategies Organized iLearn layouts following Macquarie University's standards Multiple formats for lecture materials (diagrams, color-coded slides) Weekly task clarity and real-world problem framing Live worked examples and transparent success criteria His research spans category theory, computational effects, and homotopy theory, with publications on topics like comodels, monoidal bicategories, and enriched categories. Richard's work bridges abstract mathematics with applications in computer science and logic. Scientific Awards 2023 Vice Chancellor’s Learning and Teaching Award (Student Nominated) Students praise his ability to make complex concepts intuitive, his enthusiasm for mathematics, and his dedication to explaining the 'why' behind the subject. His teaching design, including time-sensitive banners and structured weekly content, has been highlighted as exemplary.

Anand BhattadView profile

Assistant Professor

• Computer Vision
• Computer Graphics
• Generative Modeling
• +2 more

Anand Bhattad is an Assistant Professor in the Department of Computer Science at Johns Hopkins University, starting Fall 2025. Previously, he held positions as a Research Assistant Professor at the Toyota Technological Institute at Chicago (TTIC) and a visiting scholar at UC Berkeley. His research focuses on the intersection of computer vision, generative modeling, and physical reasoning, aiming to develop perception-driven and physics-aware visual models. His academic journey includes a PhD in Computer Science from the University of Illinois Urbana-Champaign under David Forsyth, with mentorship from Derek Hoiem, Svetlana Lazebnik, Greg Shakhnarovich, and Shenlong Wang. Prior to his PhD, he earned dual master’s degrees in Computer Science and Civil and Environmental Engineering at UIUC and a bachelor’s in Civil Engineering from NITK Surathkal, India. Research interests center on how generative models encode physical and perceptual knowledge, with key contributions in intrinsic image emergence, projective geometry limitations, and physics-aware relighting techniques. His work bridges classical computer vision concepts with modern deep learning, producing state-of-the-art methods for 3D scene synthesis and image editing. Articles span topics like 3P Vision , diffusion models, and 360° video datasets, reflecting interdisciplinary approaches in computer graphics and computational photography. Scientific awards include Outstanding Reviewer at ICCV 2023, CVPR 2022 Best Paper Finalist, and multiple conference service roles as workshop organizer and area chair. He designed the TTIC course Past Meets Present: A Tale of Two Visions , teaching connections between historical and modern computer vision research.

Cristina BicchieriView profile

Professor

• Game Theory
• Social Norms
• Decision Science
• +11 more

Cristina Bicchieri is the S. J. Patterson Harvie Professor of Social Thought and Comparative Ethics at the University of Pennsylvania , where she also holds appointments as Professor of Philosophy and Psychology and Professor of Legal Studies at the Wharton School. She founded and directs the Penn Center for Social Norms and Behavioral Dynamics , the Philosophy, Politics & Economics Program , and the Master of Behavioral and Decision Sciences . Education : PhD in Philosophy from Cambridge University and a Laurea (Summa cum Laude) from the University of Milano . Her research lies at the intersection of philosophy , game theory , and cognitive psychology , focusing on: Judgment and Decision-Making : Fairness, trust, cooperation, and how expectations influence behavior. Social Norms : Their nature, evolution, measurement, and application in policy (e.g., sanitation, corruption). Epistemic Foundations of Game Theory : Rational choices under bounded knowledge and computational models for game solutions. Her recent articles explore topics like norm stability , language framing effects , and sanitation interventions in India . These works emphasize behavioral dynamics , cognitive psychology , and public policy applications . Scientific Awards : Member, American Academy of Arts and Sciences (2021) Member, German Academy of Sciences (2021) Honorary Fellow, Wolfson College, Cambridge (2016) Pufendorf Medal (2015) Cavaliere Ordine al Merito della Repubblica Italiana (2007) She leads the Behavioral Ethics Lab and collaborates with organizations like UNICEF , the World Bank , and the Gates Foundation to implement norm-based interventions globally.

• Formal Methods
• Software Engineering
• Software Verification and Validation
• +7 more

Carlo Alberto Furia is an Associate Professor and Vice Dean at the Faculty of Informatics, Università della Svizzera italiana (USI). He is affiliated with the Software Institute, where he leads the ATOM research group. His academic journey includes prior roles as an Associate Professor at Chalmers University of Technology and a Senior Researcher at ETH Zurich’s Chair of Software Engineering. PhD in Computer Science, Politecnico di Milano Master of Science in Computer Science, University of Illinois at Chicago Laurea in Computer Science and Engineering, Politecnico di Milano His research centers on formal methods for software engineering, aiming to enhance software correctness, reliability, and quality through rigorous techniques. Key areas include automated program verification, contract-based development, loop invariant inference, and empirical evaluation using Bayesian data analysis. He emphasizes practical applicability and automation in formal methods. His recent publications reflect a strong focus on program analysis at the bytecode level, multilingual software analysis, automated repair of Android security issues, and empirical methodologies. These works span topics such as JVM substitutability, exception behavior in Java bytecode, and information flow security, demonstrating a consistent thread in improving software robustness through formal and automated techniques. He is actively involved in the software engineering research community as an Associate Editor of the Empirical Software Engineering (EMSE) journal and as a Program Committee member for major conferences including FASE, FM, ASE, ICSE, and CauSE. Carlo Furia has advised multiple research projects and supervised student theses. He has led and contributed to funded research initiatives, particularly in program analysis and verification. His group has developed tools such as AutoProof and other software artifacts available through the ATOM software page. He regularly teaches courses such as Software Analysis, Programming Fundamentals, and Software Design & Modeling. He leads the ATOM research group, which focuses on advancing automated techniques for software testing, analysis, and verification. The group develops practical tools and conducts empirical studies to validate research outcomes.

• Programming Languages
• Formal Methods
• Software Engineering
• +4 more

Alexander Summers is an Associate Professor at the Department of Computer Science , University of British Columbia . He joined UBC in March 2020 after serving as a Senior Researcher (Oberassistent) at ETH Zurich from 2014-2020. His research bridges Programming Languages , Formal Methods , and Software Engineering , with a focus on automated verification tools for heap-based and concurrent programs. MSc Joint Mathematics and Computer Science, Imperial College London (2004) PhD Computer Science, Imperial College London (2009) Postdoc, ETH Zurich (2009-2014) Summers leads the Prusti Project , developing deductive verification tools for Rust, and contributes to the Viper Project for intermediate verification languages. His work addresses challenges in: Memory safety and concurrency verification Ownership models and aliasing control Automated reasoning with SMT solvers Resource-oriented programming specifications Debugging verification condition quantifiers Formal validation of verification infrastructure His research has been recognized with a Amazon Research Award and ACM SIGPLAN Distinguished Paper Awards . He teaches courses like Advanced Software Engineering and Program Verifiers and Program Verification , and supervises graduate students in formal verification and Rust-related research.

Matilde MarcolliView profile

Professor

• Noncommutative Geometry
• Mathematical Physics
• Number Theory
• +5 more

Matilde Marcolli is the Robert F. Christy Professor of Mathematics and Computing and Mathematical Sciences at the California Institute of Technology (Caltech). She holds joint appointments in the Division of Physics, Mathematics, and Astronomy (PMA) and the Division of Engineering and Applied Sciences (EAS). Her research spans noncommutative geometry, mathematical physics, number theory, and mathematical linguistics. She has been recognized with prestigious awards such as the Sofja Kovalevskaya Award (2001) and the Heinz Maier Leibnitz Prize (2001). Marcolli has advised numerous PhD students and contributed to over 300 publications. Her work bridges abstract mathematics with applications in cosmology, quantum field theory, and computational linguistics. Education : PhD in Mathematics, University of Chicago, 1997 M.Sc., University of Chicago, 1994 Laurea in Mathematics, University of Pavia, 1993 Research Interests : Marcolli’s research explores the intersection of geometry, number theory, and physics. Key areas include noncommutative geometry models of particle physics and cosmology, motives in quantum field theory, and algebraic models of generative linguistics. She applies advanced techniques such as Feynman integrals, spectral action principles, and Hopf algebras to interdisciplinary problems. Grants & Awards : NSF grants DMS-2104330, DMS-1707882, and others NSERC Discovery Grant RGPIN-2018-04937 FQXi grant FQXi-RFP-1804 Collaborations & Labs : Marcolli collaborates with institutions like the Perimeter Institute and Florida State University. She leads research groups on topics such as quantum statistical mechanics, holography, and neural information networks. Her work on syntax-semantics interfaces and quantum gravity models has been pivotal in interdisciplinary studies.

Hasan DavulcuView profile

Professor

• Sociocultural Modeling
• Artificial Intelligence
• Machine Learning
• +5 more

Hasan Davulcu is a Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He holds a B.S. in Mathematics from Middle East Technical University (Turkey) and M.S./Ph.D. in Computer Science from Stony Brook University (NY). His research focuses on sociocultural modeling, AI, machine learning, and behavioral analytics for fraud detection. He leads the CIPS-AI Lab, developing data mining tools for semantic information extraction from social media and web data. Affiliations: Senior Global Futures Scientist (Global Futures Scientists and Scholars Program), Co-founder & CIO of ARTIS MAGI (AI-driven behavioral analysis startup). Education: Ph.D. Computer Science (Stony Brook, 2002), M.S. Computer Science (Stony Brook, 1995), B.S. Mathematics (METU, 1993). Research interests include: Sociocultural modeling and persuasive AI. Web/social media mining, information extraction, and database systems. Behavioral analytics for fraud detection and countering extremist influence. Key achievements: 2011 HSCB Focus Exceptional Scientific Achievement Award for work on sociocultural modeling in the DOD Minerva project. Principal Investigator on NSF and DoD grants, including behavioral analytics for financial fraud and social influence analysis of extremist groups. Grants & Projects: NSF PFI:BIC Grant (2014-2019): Behavioral analytics for fraud detection via visual analytics infrastructure. DoD Minerva (2015-2019): Measuring social influence of extremist groups. ONR Projects (2018-2021): Modeling polarization, adversarial framing, and disinformation tracking. Labs/Teams: Cognitive Information Processing Systems (CIPS-AI) Lab, which pioneers data mining techniques for unstructured social media data and semantic representation systems.

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +7 more

Barbara Plank is a full professor and chair for AI and Computational Linguistics at Ludwig Maximilian University of Munich (LMU), where she heads the Munich AI and NLP (MaiNLP) lab and co-directs the Center for Information and Language Processing (CIS). She additionally serves as a visiting full professor at the IT University of Copenhagen, maintaining active dual institutional affiliations in computational linguistics and NLP research. Her research focuses on human-centric natural language processing challenges, particularly learning under sample selection bias (domain adaptation, transfer learning) and annotation bias, learning with limited data through continual/semi-supervised/weakly-supervised methods, multimodal learning at language-vision-speech interfaces, and fortuitous supervision for variety-space aware language understanding. She pioneers methodologies addressing human label variation as a critical factor in model robustness rather than mere noise. Recent publications (2024-2025) reveal dominant trends in modeling human label variation across NLP tasks, especially natural language inference and entity recognition, alongside dialectal language processing and LLM evaluation frameworks. Her work systematically investigates how human disagreement in annotations can be leveraged to build more robust, adaptable systems rather than treated as errors. Scientific recognition includes: ERC Consolidator Grant for the DIALECT project advancing natural language understanding for non-standard languages and dialects ACL 2024 Area Chair Award for the paper 'VariErr NLI: Separating Annotation Error from Human Label Variation' Leading the MaiNLP lab at CIS (LMU), she directs research integrated with MCML (Munich Center for Machine Learning), Munich Intelligent Robotics, ELLIS Unit Munich, UniDive, and COST action. Current projects include ERC-funded DIALECT and KLIMA-MEMES, focusing on human-facing NLP solutions for real-world language diversity challenges. She actively shapes the field through ACL leadership as VP-Elect and numerous keynotes emphasizing human-centric approaches. The MaiNLP lab at Akademiestr. 7, 80799 Munich, drives innovation in computational linguistics through interdisciplinary collaboration, maintaining strong ties with European research networks while developing practical applications for language variation and robust NLP systems. The lab's work directly informs her teaching in LMU's Computational Linguistics programs, bridging research and education in cutting-edge NLP methodologies.

Jason J. CorsoView profile

Professor

• Computer Vision
• Robotics
• Artificial Intelligence
• +6 more

Dr. Jason J. Corso is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan . His research focuses on high-level computer vision , video understanding , and the intersection with human language and robotics . His work emphasizes Bayesian approaches to segmentation and recognition, with applications spanning biomedicine and recreational video analysis . He is particularly known for contributions to video object segmentation , activity recognition , and vision-language frameworks . Scientific awards include: NSF CAREER award (2009) ARO Young Investigator award (2010) Google Faculty Research Award (2015) DARPA CSSG grant He also leads major projects like YouCook2 dataset , Video2Text.net , and LIBSVX framework.

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

Freda ShiView profile

Assistant Professor

• Computational Linguistics
• Natural Language Processing
• Multilingualism
• +4 more

Freda Shi is an Assistant Professor at the David R. Cheriton School of Computer Science, University of Waterloo, and a Faculty Member at the Vector Institute. She holds a Canada CIFAR AI Chair. Her research focuses on computational linguistics, natural language processing (NLP), and grounded language learning, with emphasis on multilingualism and spatial reasoning in vision-language systems. She earned her Ph.D. in Computer Science from the Toyota Technological Institute at Chicago (2024), advised by Karen Livescu and Kevin Gimpel, supported by a Google Ph.D. Fellowship. Her undergraduate degree is from Peking University (2018), with a minor in Sociology. Her academic career includes affiliations with the CompLING Lab at Waterloo and contributions to major conferences like ACL and NAACL. She has organized tutorials on NLP grounding and is actively involved in research on model robustness and cognitive insights. Awards include the Google Ph.D. Fellowship and Best Paper Nominations at ACL 2024 and EMNLP 2021, alongside her Thesis of Distinction. She teaches courses such as CS 784 (Computational Linguistics) and CS 486/686 (Artificial Intelligence), emphasizing both theoretical and applied aspects of NLP. Research trends in her articles highlight advancements in vision-language spatial reasoning, multilingualism, and model interpretability. Her work bridges cognitive science and computational methods, exploring how human language mechanisms inform the design of more trustworthy AI systems. Scientific Awards: Google Ph.D. Fellowship Best Paper Nominee (ACL 2024) Best Paper Nominee (EMNLP 2021) Thesis of Distinction (2024) Advising and Grants: As an advisor, she encourages prospective students to review her guidelines. Her grants include support from the Canada CIFAR AI Chair program and the Vector Institute. She collaborates in labs such as CompLING at Waterloo and co-organizes events at NAACL and ICLR. Labs/Teams: She leads the CompLING Lab at the University of Waterloo, affiliated with the Vector Institute. Her work integrates interdisciplinary teams focusing on grounded learning and multilingual NLP challenges.

Adrienne WoodView profile

Assistant Professor

• Social Psychology
• Emotion
• Social Networks
• +3 more

Adrienne Wood is an Assistant Professor in the Department of Psychology at the University of Virginia. Her research lab, Emotion and Behavior Lab, investigates social connections through multimodal approaches including mobile sensing, social network analysis, and behavioral economics. She holds a Ph.D. from the University of Wisconsin-Madison and a B.A. from Colorado College. Wood's research examines how people form and maintain social ties across cultural divides, addressing loneliness through analysis of nonverbal behavior, emotion contagion, and network dynamics. Her work emphasizes: Behavioral mechanisms of connection (laughter, synchrony) Social network formation in diverse communities Cross-cultural relationship building She employs innovative methodologies like acoustic analysis and agent-based modeling. Her recent publications (2023-2025) demonstrate strong focus on: Emotional communication in evolving relationships Cultural influences on social competence Crisis impacts on behavior Nonverbal synchronization mechanisms Longitudinal analysis of social interactions No scientific awards are mentioned in the source material. Wood leads the Emotion and Behavior Lab, studying verbal/nonverbal behaviors underlying social bonds. Her team explores: Real-world interaction patterns Diverse community integration Computational social science approaches