Christopher J. Earls is a Professor in the Department of Civil and Environmental Engineering at Cornell University's College of Engineering. His work bridges applied mathematics, artificial intelligence, and scientific computing to address challenges in understanding natural and engineered systems, particularly focusing on uncertainty quantification, sparse sensing, and complexity. B.S. (Civil Engineering), Virginia Tech 1990 M.S. (Civil Engineering), Virginia Tech 1992 Ph.D. (Civil Engineering), University of Minnesota 1995 Earls' research explores Scientific Artificial Intelligence (SciAI) and Inverse Problems, with applications to computer-aided diagnosis and complex systems. His recent publications highlight intersections with Large Language Models (LLMs), geometric analysis, and neural scaling laws in dynamical systems. Outstanding Young Alumni Award (Virginia Tech) 2004 Outstanding Professor of the Year Award (ASCE) 2001 James and Mary Tien Teaching Award (Cornell) 2016 Ralph E. Powe Junior Faculty Enhancement Award (ORAU) 2000 Peter S. Michie Outstanding Teacher Award (West Point) 1998
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Steve Oneyمشاهده پروفایل
دانشیار
Steve Oney is an Associate Professor at the University of Michigan School of Information and Computer Science and Engineering (by courtesy). His research focuses on enabling and encouraging more people to write and customize computer programs by creating new programming tools and exploring usability issues in programming environments. With a strong background in Human-Computer Interaction, he bridges the gap between theoretical research and practical applications in programming education, accessibility, and developer tool design. Dr. Oney completed his Ph.D in Human-Computer Interaction at Carnegie Mellon University's Human-Computer Interaction Institute under Professor Brad Myers and Dr. Joel Brandt. He also earned an M.Eng in Computer Science and SB degrees in Computer Science and Mathematics from MIT. His research spans multiple interconnected areas with a unifying theme of making programming more accessible and understandable. Key focus areas include programming education tools that help instructors understand student code at scale, web automation systems that simplify repetitive tasks, accessibility research addressing challenges faced by visually impaired programmers, and innovative VR programming environments. His work consistently emphasizes the human aspects of programming, exploring how tools can better support diverse programming needs and contexts. Dr. Oney's research output shows a strong trajectory toward increasingly sophisticated tools that integrate AI capabilities while maintaining a focus on human-centered design principles. Recent publications demonstrate growing emphasis on inclusive design, educational applications, and the integration of generative AI in programming environments. L@S 2024 Best Paper Award for CFlow CHI 2023 Honorable Mention for VizProg UIST 2024 Best Short Paper (EdCode) VL/HCC 2019 Best Short Paper Recognition for Contribution to Diversity and Inclusion (CSCW 2021) UMSI Excellence in Instruction Award (2021) University of Michigan President's Postdoctoral Fellowship (2015) As a mentor, Oney advises multiple Ph.D. students and postdoctoral researchers, with several successful graduates including Dr. Lei Zhang (June 2024). His research has secured over $1 million in funding from the National Science Foundation, Google, and Adobe, supporting projects that address critical challenges in programming education, accessibility, and developer tool design. He leads the Programming Tools Lab at the University of Michigan, where his team develops innovative tools that help programmers work more effectively. Current projects focus on AI-enhanced programming education, web automation, accessibility for diverse user groups, and next-generation programming environments for virtual and augmented reality.
Dr. Fariba Mostajeran is a Researcher at the Human-Computer Interaction research group within the Department of Informatics at the University of Hamburg. Her interdisciplinary work bridges computer science, psychology, and environmental science to investigate the psycho- and physiological effects of immersive media on users across different age groups, with particular focus on therapeutic applications of virtual and augmented realities. Her educational background includes: B.Sc. in Computer Engineering-Software from the University of Isfahan (Iran) M.Sc. in Digital Media from the Universität Bremen Ph.D. in Human-Computer Interaction at the Universität Hamburg Dr. Mostajeran's research centers on Medical Mixed Reality , Digital Health , and Human-Computer Interaction , with emphasis on how virtual environments can enhance cognitive performance, psychological well-being, and therapeutic outcomes. She systematically investigates the impact of virtual nature exposure on memory, attention, and mood, developing applications for mental health treatment, rehabilitation, and workplace design. Her methodological approach combines controlled experiments with user-centered design to create effective immersive interventions. Analysis of her recent publications reveals three major research thrusts: (1) the therapeutic applications of virtual nature for mental health and cognitive enhancement, (2) the development and evaluation of intelligent virtual agents for healthcare applications, and (3) understanding the cognitive and physiological mechanisms underlying user responses to immersive environments. Her work increasingly focuses on multimodal interaction with virtual agents and their implementation in clinical settings. Her scholarly contributions have been recognized through: Ideas and Venture Fund (IVF), Universität Hamburg, 2024-2025 EXIST-Gründerstipendium (EXIST Founder Scholarship), 2014-2015 Deutschlandstipendium (German Scholarship), 2012-2013 Dr. Mostajeran has supervised over 30 master's and bachelor's theses focusing on virtual reality applications across diverse domains including mental health interventions, cognitive training, and therapeutic environments. Her research has received support from university innovation funds and national scholarship programs. She serves on multiple academic committees including professorship selection committees and examination boards, contributing significantly to institutional governance. Her active participation in major conferences as program committee member and reviewer demonstrates her standing in the HCI and VR research communities. She works within the Human-Computer Interaction research group at the University of Hamburg led by Prof. Dr. Steinicke, which maintains strong connections with clinical partners and industry collaborators to translate research findings into practical healthcare applications. The group's facilities include state-of-the-art VR laboratories equipped for comprehensive user studies measuring both behavioral and physiological responses.
David J. Yuمشاهده پروفایل
دانشیار
David J. Yu is an Associate Professor at Purdue University with primary appointments in the Lyles School of Civil Engineering (75%) and Department of Political Science (25%) . He contributes to interdisciplinary research through Purdue’s Building Sustainable Communities cluster, focusing on sustainability and community resilience. His research examines resilience of coupled systems to change and uncertainty, combining natural, physical, and institutional factors across scales from local to global. Methodological approaches include mathematical modeling , case study analysis , and behavioral experiments to understand human-infrastructure-water interactions. Recent publications demonstrate expertise in socio-hydrology of reservoir operations groundwater governance frameworks agent-based modeling of water systems cognitive biases in water management His work was recognized with an NSF CAREER Award (2022) for innovative research on resilience engineering. He actively seeks graduate students for projects in Civil Engineering, Ecological Sciences, Environmental Engineering, and Political Science programs at Purdue. Current research includes logical interdependencies in water infrastructure and AI-enhanced resilience frameworks for reservoir management.
Xiaoyang Wangمشاهده پروفایل
مدرس ارشد
Xiaoyang Wang is a Senior Lecturer in the School of Computer Science and Engineering (CSE) at the University of New South Wales (UNSW). He holds a Bachelor's and Master's degree in Computer Science from Northeastern University, China, and earned his PhD from CSE UNSW. Dr. Wang's research focuses on database systems with a special emphasis on query processing and data mining on large-scale graph, spatial, and streaming data. His expertise extends to data-driven machine learning, smart contract analysis on blockchain, and FinTech with financial network analysis. His work spans Graph Processing, Graph Neural Networks, Spatial Data Processing, AI for Databases (AI4DB), Database for AI (DB4AI), and FinTech applications. His publication record shows significant contributions to the field with 7 book chapters, 56 journal articles, 61 conference papers, 7 edited conference proceedings, and 4 conference abstracts. Recent publications (2022-2025) demonstrate his strong research trajectory in advanced graph processing techniques, neural network applications, and innovative database approaches. Key themes include hierarchical contrastive learning, robust attack frameworks, temporal graph processing, influence maximization, knowledge graph-enhanced reasoning, and rumor mitigation. Dr. Wang actively recruits PhD students interested in pursuing research in related fields and encourages current undergraduate and master's students at UNSW to contact him about research opportunities. He maintains an active research agenda with practical implications for industries dealing with large-scale network data, financial technology applications, and data-intensive systems. He can be reached at xiaoyang.wang1@unsw.edu.au and is located in Engineering building K17-501D at UNSW.
Luis Miguel Bergasa is a Full Professor at the Department of Electronics, University of Alcalá (UAH), with a career spanning over 25 years. He leads the RobeSafe Lab (since 2010) and serves as Director of Digital Transformation at UAH (since 2022). His academic roles include heading the Department of Electronics (2004–2010) and coordinating multiple educational programs. He teaches Perception Systems (Master in Industrial Engineering) Intelligent Control Systems (Computer Science) Computer Vision (Computer Science) His research focuses on Perception Systems for Intelligent Vehicles , emphasizing driver behavior analysis, scene understanding, and sensor fusion via deep learning. He has authored over 300 papers and holds 9 patents. Notable recognitions include being ranked #81 in Computer Science (Spain) by Research.com (2025) and receiving 30+ awards in Robotics/Automotive fields. Recent publications highlight advancements in Transformer-based driver action recognition (2025) Infrastructure-vehicle cooperative frameworks (2025) 3D semantic segmentation for autonomous perception (2024) Simulation-to-reality gap bridging (2024) Scientific Leadership Senior Editor, IEEE Transactions on ITS (2025) International Program Committee roles in 15+ conferences (2024–2025) Co-founder of Vision Safety Technologies Ltd (2009–2016) He supervises 9 active PhD students and has advised 14 former PhD candidates. His group collaborates with institutions in Germany, USA, China, and Spain, including KIT, UC Berkeley, and Northwestern Polytechnic University.
Silvia Cascianelli is an AI and Computer Vision Researcher at the University of Modena and Reggio Emilia (UNIMORE). She actively contributes to the computer vision and document analysis communities through research, conference organization, and academic mentorship. She serves as Area Chair for major computer vision conferences including CVPR2025, BMVC2025, and ECCV2024, demonstrating her standing in the field. Her research focuses on several key areas within computer vision and document analysis: Image Generation : Developing efficient and lightweight methods for image generation with desired characteristics, particularly using diffusion models Handwriting Imitation : Creating algorithms for generating images of text with specific content and handwriting styles, along with evaluation methods Document Understanding : Extracting information from 2D and 3D document images, ranging from modern documents to historical artifacts like carbonized Roman papyri Dr. Cascianelli's work shows a clear progression toward more sophisticated generative models and evaluation frameworks, with recent publications focusing on diffusion models for handwritten text generation, efficient token reduction for multimodal tasks, and innovative approaches to historical document analysis. Her research bridges theoretical advancements with practical applications across diverse document types. Her scientific contributions have been recognized through invitations to serve as Area Chair for top-tier computer vision conferences (CVPR, ECCV, BMVC) and opportunities to organize specialized workshops including VisionDocs at ICCV, AI4DH at ECCV, and ADAPDA at ICDAR. Area Chair at CVPR2025 Area Chair at BMVC2025 Area Chair at ECCV2024 Organizer of VisionDocs Workshop at ICCV2025 Organizer of AI for Digital Humanities Workshop at ECCV2024 Organizer of ADAPDA Workshop at ICDAR2024 Dr. Cascianelli actively mentors the next generation of researchers: Vittorio Pippi - PhD Student at UniMoRe (National PhD program in AI) Fabio Quattrini - PhD Student at UniMoRe (ICT program) Carmine Zaccagnino - Research Intern at UniMoRe (formerly MSc student) Kostantina Nikolaidou - PhD Student at Luleå University of Technology Pau Torras Coloma - PhD Student at Computer Vision Center, Universitat Autònoma de Barcelona Bram Vanherle - CV Engineer at Colruyt Group Smart Innovation (formerly PhD student) She is actively involved in several research initiatives including the AI Governance Lab where she serves as a lecturer, and collaborates with institutions worldwide. Her current projects focus on advancing diffusion models for image generation, improving handwritten text recognition systems, and developing novel methods for document understanding across historical and contemporary contexts.
Grzegorz Chrupała is an Associate Professor at the Department of Cognitive Science and Artificial Intelligence , Tilburg University, where he leads research in computational approaches to multimodal communication. Previously, he was a postdoctoral researcher at Saarland University's Spoken Language Systems group and earned his PhD from Dublin City University's School of Computing. His research bridges biological and artificial computation , focusing on enabling machines to learn language from multimodal data (speech, gestures, visual-auditory stimuli) as children do naturally. This involves developing and interpreting deep learning architectures, analyzing emergent representations, and advancing speech technology for under-resourced languages. Key themes include Visually grounded speech modeling Feature attribution and model interpretability Human-inspired learning paradigms BlackboxNLP workshop leadership His recent publications examine speech model reliability , lexical tone encoding , and contextual dependencies in NLP systems. He mentors a team of PhD candidates and alumni working on topics like user-centric interpretability, bioacoustics, and disentangled speech representations. He also serves on the board of the Dutch Open Speech Technology Foundation, chairs Interspeech 2025 tutorials, and contributes as an Action Editor for TACL.
David Serfass is a Lecturer at the National Institute of Oriental Languages and Civilizations (INALCO) specializing in Chinese studies. He serves as Co-manager of international mobility, Tutoring Manager, and Referent to the Cross-functional Commission at the institution. His teaching portfolio includes courses on the History of East Asia (19th-20th centuries), Communication and Media in East Asia, Introduction to Ancient Chinese History, Sinological Culture and Practice, Republican China through Texts and Media, and History of Taiwan. Dr. Serfass's research focuses on the History of the Japanese Occupation of China (1931-1945), the History of the Modern Chinese State, Sino-Japanese Relations, and the History of the Sino-Japanese War. His work examines state-building processes during wartime, particularly through the lens of the Wang Jingwei regime and collaboration governments in occupied China. He approaches these topics through spatial history, bureaucratic documentation, and memory studies, revealing how territorial control, administrative practices, and historical narratives shaped wartime China. His scholarly contributions demonstrate a consistent focus on the complexities of political authority during periods of fragmentation and occupation. Rather than viewing the Wang Jingwei regime as merely a Japanese puppet government, Serfass's research reveals the regime's internal dynamics, state-building efforts, and complex negotiations of sovereignty. His work challenges teleological narratives of central state formation in Republican China, highlighting instead the fragmented and contested nature of political authority during this period. Member of editorial board, Études chinoises (2014-2024) Member of editorial board, Terrains de Taiwan Member, ERC project Elites, Networks and Power in Modern China Member, French Taiwan Studies Project Member, Occupation Studies Research Network Dr. Serfass is an active contributor to academic discourse through conference presentations, editorial work, and collaborative research projects. His approach combines traditional historical research with spatial analysis and attention to bureaucratic practices, drawing on Chinese, Japanese, and Western archival sources to provide multi-perspective understanding of wartime China. His work has established him as a significant voice in the field of modern Chinese history, particularly regarding the complex dynamics of occupation, collaboration, and state formation during the Sino-Japanese War period.
Kathryn Seigfried-Spellarمشاهده پروفایل
استاد مدعو
Kathryn Seigfried-Spellar serves as an Adjunct Professor in the cyberforensics program within the School of Applied and Creative Computing at Purdue University's Polytechnic Institute. She holds a prominent international reputation as an expert in the psychosocial and technological factors associated with cybercriminal behavior, with particular expertise in the criminological characteristics and grooming strategies of online child sex offenders. Her professional appointments include membership in the Tippecanoe High Tech Crime Unit and Special Deputy status for the Tippecanoe County Prosecutor's Office. Dr. Seigfried-Spellar completed her academic training at Purdue University, earning a PhD in Technology with concentration in Cyberforensics and Psychology (2011), an MA in Forensic Psychology from City University of New York, John Jay College of Criminal Justice (2007), and a BA in Psychology and Law and Society from Purdue University (2005). Her research interests focus on the psychological aspects of cybercrime, particularly the personality and motivation of cyberdeviants, child sexual exploitation, and behavioral analysis of digital evidence. Her work bridges the gap between psychological theory and digital forensics practice, with significant contributions to understanding online child sex offenders' behaviors and characteristics. She has conducted international research including a 2022-2023 Fulbright Scholar position at the University of Valencia, Spain, studying criminological differences in online child sex offenders, and has been awarded the International Fellows Award for Summer 2024 at the University of Adelaide, Australia. Dr. Seigfried-Spellar's scholarly contributions have been recognized with numerous awards including the 2023 Jefferson Award, 2022 University Faculty Scholar designation at Purdue, the 2022 Outstanding Early Career Achievement in Forensic Science Award from the American Academy of Forensic Sciences, and multiple Outstanding Research Awards from the Digital and Multimedia Sciences Section of the American Academy of Forensic Sciences (2015-2018). She serves as the Chair of the Digital and Multimedia Sciences section of the American Academy of Forensic Sciences and is a Fellow of this organization. Her professional affiliations also include membership in the American Psychological Association, American Psychology-Law Society, and International Association of Law Enforcement Intelligence Analysts. In December 2023, she co-founded and co-organized the Child Sexual Abuse Reduction Research Network workshop at the University of Adelaide, bringing together academics, nonprofit institutions, and law enforcement professionals focused on combating online child sexual abuse.
Dr. Xing Fang is a Lecturer in Marketing at the School of Business and Management, Royal Holloway, University of London. Prior to joining RHUL, he held a Visiting Assistant Professor role at Tulane University. His research focuses on data-driven approaches in recommendation systems, customer journey analysis, online retailing, and influencer marketing, with a particular emphasis on leveraging quantitative methods to understand consumer behavior in digital environments. Key research areas include: Recommendation Systems Customer Journey Online Retailing Influencer Marketing Marketing Analytics Consumer Behavior Recent publications explore speech act strategies in influencer marketing, information cues in recommender systems, and data-driven approaches to targeted referral programs. His work spans both theoretical and applied studies, addressing critical aspects of digital marketing and consumer analytics. Collaborators include researchers such as Shangkun Shin, Xingyu Huang, Soo Kim, and Puneet Chintagunta. Dr. Fang teaches courses on Marketing Management, Strategic Marketing, and Marketing Analytics, integrating his research into practical applications.
Åsa Maria Wikforss is a Professor in Theoretical Philosophy at Stockholm University, specializing in intersections of philosophy of language, mind, and epistemology. Her research focuses on semantic externalism, content externalism, and normativity of meaning, with significant grants from the Swedish Research Council and Bank of Sweden Tercentenary Foundation. Ph.D., Columbia University (1996) Docent, Stockholm University (2002) Research interests include challenges to semantic normativity, self-knowledge, and knowledge resistance. She critiques Kripke-Putnam theories of natural kind terms and develops 'reason-providing functionalism' for belief characterization. Key publications address transparency of content, semantic externalism, and belief justification Organized international workshops on internalism/externalism and Wittgenstein/Davidson Scientific awards include: Swedish Research Council grants (2007-2010, 2013) Bank of Sweden Tercentenary Foundation grant (2004-2006) Project leadership in CCCOM and Eurounderstanding initiatives She supervises doctoral students and has co-led Nordic graduate seminars on epistemology and philosophy of mind. Her popular science work addresses knowledge resistance, pseudoscience, and self-knowledge in media debates.
Arianna Bisazza is an Associate Professor in the Computational Linguistics Group at the University of Groningen, where she leads the InClow research group focused on Interpretable, Cognitively inspired, Low-resource language models. Her work bridges computational linguistics, cognitive science, and language acquisition to develop more robust and interpretable language processing algorithms that can adapt to diverse linguistic phenomena worldwide. Dr. Bisazza's research interests span statistical modeling of human languages in multilingual contexts, with particular focus on improving language model performance for "challenging" or low-resource languages. Her work explores how insights from human language acquisition can inform better language modeling techniques, and she investigates methods to make state-of-the-art NLP systems more interpretable and transparent. As a cross-disciplinary researcher, she actively seeks to enhance our understanding of human language processing and evolution through computational modeling tools. Her recent publications reveal a strong emphasis on multilingual evaluation frameworks (like TurBLiMP and MultiBLiMP), interpretability of language models, and connections between human language acquisition and neural network learning. Her work consistently addresses the challenge of making language technology more robust across diverse linguistic structures and typological features. Outstanding Paper Award at the BabyLM Challenge (CoNLL'24 Shared Task) for "BabyLM Challenge: Exploring the Effect of Variation Sets on Language Model Training Efficiency" Dr. Bisazza currently leads a Vidi project funded by the Dutch Research Council (NWO) on improving low-resource language modeling through child language acquisition insights. She is also part of two national consortium projects funded by NWA-ORC initiatives: InDeep (Interpreting deep learning models for language, speech & music) and LESSEN (Low Resource Chat-based Conversational Intelligence). She supervises multiple PhD students, including two China Scholarship Council (CSC)-funded researchers working on simulating human patterns of language learning and change. Her earlier research was supported by a Veni grant (2017-2021) focused on understanding and improving the encoding of linguistic structure in Neural Machine Translation models. As head of the InClow research group, Dr. Bisazza oversees a team investigating interpretable, cognitively inspired approaches to low-resource language modeling. The group's work combines insights from cognitive science and linguistics with cutting-edge NLP techniques to develop language models that better reflect human language processing capabilities, particularly in resource-constrained settings.
Eric Oberheimمشاهده پروفایل
پژوهشگر
Eric Oberheim is a Researcher at the Department of Philosophy within the Faculty of Philosophy at Humboldt-Universität zu Berlin . He is affiliated with the DFG-Emmy-Noether Research Group: A Sensible World , focusing on philosophical and historical analyses of scientific theories and their evolution. Role : Researcher Institution : Humboldt-Universität zu Berlin Research Group : DFG-Emmy-Noether Research Group: A Sensible World His research interests center on the philosophy of science , particularly the incommensurability of scientific theories , theoretical pluralism , and the historical development of scientific concepts . He has extensively studied the works of Paul Feyerabend, Thomas Kuhn, and Karl Popper, examining their contributions to understanding scientific progress and conceptual change. Eric’s publications include analyses of Feyerabend’s intellectual trajectory, the role of falsificationism in scientific methodology, and the implications of incommensurability for theory comparison. His work often bridges historical scholarship with contemporary philosophical debates, emphasizing the dynamic and context-sensitive nature of scientific knowledge. He has contributed to edited volumes and critical discussions on topics such as scientific revolutions , nonsense in paradigm shifts , and the ethical dimensions of scientific authority . His editorial collaborations include introductions to Feyerabend’s works and co-edited collections on the philosophy of science.
Melanie Mitchell is a Professor at the Santa Fe Institute, where she conducts research at the intersection of artificial intelligence, cognitive science, and complex systems. Her work focuses on conceptual abstraction and analogy-making in artificial intelligence systems, seeking to understand the mechanisms that enable both human and machine intelligence. Mitchell received her PhD in Computer Science from the University of Michigan in 1990 and has held positions at numerous institutions including the University of Michigan, Los Alamos National Laboratory, the Oregon Graduate Institute, and Portland State University. Her research bridges the gap between theoretical understanding of intelligence and practical AI development. Her recent publications explore fundamental questions about AI understanding, reasoning capabilities, and the relationship between language models and world knowledge. She has developed novel evaluation frameworks for assessing analogical reasoning and abstraction in AI systems, challenging assumptions about what current AI can truly comprehend. Her work often examines the limitations of large language models while proposing pathways for more robust and human-like artificial intelligence. 2010 Phi Beta Kappa Science Book Award for "Complexity: A Guided Tour" Finalist for the 2023 Cosmos Prize for Scientific Writing for "Artificial Intelligence: A Guide for Thinking Humans" Senior Scientific Award from the Complex Systems Society Distinguished Cognitive Scientist Award from UC Merced Herbert A. Simon Award of the International Conference on Complex Systems Mitchell actively advises numerous PhD students and postdoctoral researchers, fostering the next generation of researchers in AI and complex systems. She has also developed educational resources including the popular online course "Introduction to Complexity" on Complexity Explorer. Her public outreach includes a Substack newsletter "AI: A Guide for Thinking Humans," Science Magazine columns, and the podcast series "The Nature of Intelligence."