Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.
Prof. Torsten Wolfgang Kuhlen serves as a Universitätsprofessor at RWTH Aachen University, leading the Teaching and Research Area for Virtual Reality and Immersive Visualization within the Department of Computer Science. He is affiliated with Chair of Computer Science 12 (High Performance Computing), the Visual Computing Institute, and remains an integral part of the RWTH IT Center where his research group operates one of the world's largest Virtual Reality laboratories including the 30 sqm aixCAVE visualization chamber. The group maintains strong connections with Computational Science & Engineering Division, National High Performance Computing Center for Computational Engineering Science (NHR4CES), and VR in Science and Industry Network NRW e.V. Prof. Kuhlen's research spans virtual reality, immersive visualization, and multimodal 3D user interfaces with applications across simulation science, production technology, neuroscience, and medicine. His work combines basic research on advanced methods and algorithms with interdisciplinary collaborations involving RWTH Aachen institutes, Forschungszentrum Jülich, and industry partners. Recent publications demonstrate strong focus on audiovisual perception, immersive analytics, collaborative virtual environments, and practical VR applications in education and manufacturing. His research group has produced significant work on listening effort in virtual environments, immersive authoring techniques, and VR applications for scientific visualization. Notable projects include VRScenarioBuilder for automated vehicle testing and applications in monitoring additive manufacturing processes. The group actively participates in major conferences including IEEE VIS and EuroVis, with several award-winning contributions. Prof. Kuhlen has advised PhD students including Martin Bellgardt who recently completed his doctoral degree on "Increasing Immersion in Machine Learning Pipelines for Mechanical Engineering". The research group maintains state-of-the-art VR infrastructure including the aixCAVE facility which is open to all RWTH research groups.
Guofang Li is a Professor in the Department of Language and Literacy Education at the Faculty of Education, affiliated with the Centre for Early Childhood Education & Research (CECER). Her work centers on bilingual development and literacy education within multicultural contexts, particularly focusing on Chinese-Canadian communities. Her research interests include: Early bilingual development Family literacy practices Early literacy instruction methodologies Early education for minority learners Teacher education for multilingual classrooms Analysis of her 2021-2025 publications reveals a concentrated focus on Chinese-Canadian children's bilingual development, examining home literacy environments, digital technology impacts, and pandemic-related disruptions. She consistently advocates for equity-focused approaches in superdiverse educational settings, emphasizing translanguaging practices and critical perspectives on linguistic justice. Scientific Awards: No awards explicitly mentioned in source materials Advising and Grants: No specific student names or grant information provided in source materials Labs and Teams: Centre for Early Childhood Education & Research (CECER): An interdisciplinary hub facilitating collaborative research between academics, educators, and community partners focused on advancing evidence-based early childhood education practices through longitudinal studies and community-engaged projects.
Dr. Martha Sidury Christiansen is a Professor of Applied Linguistics/TESOL at the University of Texas at San Antonio , where she serves in the College of Education and Human Development . She is the Principal Investigator of Project RESPETO , a NSF-funded initiative exploring racial equity in engineering education. Her work spans sociolinguistics, digital literacies, and raciolinguistic analysis, with a focus on transnational multilingual communities. Born in Veracruz, Mexico Ph.D. in Foreign/Second Language Education (Ohio State University, 2013) M.A. in English Composition (Indiana University, 2007) B.A. in English Language Teaching (Universidad Veracruzana, 2002) Her research examines how transnational youth navigate digital spaces through multiliteracies , challenges Western academic writing norms via Mexican decolonial methodologies , and investigates raciolinguistic intersections in identity formation. The 15 most recent publications reveal a strong focus on digital communication , transnationalism , and critical pedagogy across journals like TESOL Quarterly and Language@Internet . 2023-2025: Expanding raciolinguistic frameworks in digital contexts 2021-2022: Analyzing multimodal identity construction 2019-2020: Exploring Mexican bilinguals' online language use She has received multiple honors including ACUE Fellow (2023), Fulbright Scholar (2017), and Faculty Leadership Fellow (2021-2022). Her presentations at conferences like ICOLLITE and DDVM Lab highlight her expertise in critical sociolinguistic awareness and digital discourse analysis . Dr. Christiansen actively consults for nonprofits on linguistic equity and multilingual education .
Chanchal K. Roy is Professor of Software Engineering/Computer Science at the University of Saskatchewan and Co-Director of the Software Research Lab. He leads an NSERC CREATE graduate program on Software Analytics Research and co-leads the Data Management group for an NSERC CFREF project on Food Security, with over 170 publications cited 6,000+ times. His research centers on software clone detection using the widely adopted NICAD system, software evolution, empirical studies, and AI-driven software analytics. Recent work integrates large language models for code generation, clone detection in the AI era, and developer interactions with tools like ChatGPT, emphasizing practical applications in maintenance and analytics. Analysis of his 15 most recent publications reveals a strong trend toward AI/ML integration in software engineering: 12 of 15 articles (2025) explore LLMs, quantum computing, or deep learning for tasks like bug localization, code snippet generation, and feature-toggle analysis. Key themes include empirical validation of AI tools, Stack Overflow data mining, and cross-domain frameworks for Society 5.0. His scientific awards include: Most Influential Paper Awards (SANER 2018, ICPC 2018) Outstanding Young Computer Science Researcher Award (CS-Can/Info-Can, 2018) New Researcher Award (University of Saskatchewan, 2019) New Scientist Research Award (College of Arts and Science, 2019) As lead of the NSERC CREATE program and CFREF data group, he mentors graduate students in software analytics while securing major grants. He actively serves on program committees for ASE, ICSE, and FSE, reviewing journals and organizing workshops on clone detection and empirical methods. His lab focuses on real-world applications in food security data management and software evolution. The Software Research Lab, co-directed by Roy, drives projects like NICAD and the NSERC CREATE initiative, emphasizing open-source contributions and industry collaboration. Current efforts include quantum-SE integration and AI-augmented maintenance tools under the CFREF food security mandate.
Pascale Trevisiol Okamura is an Associate Professor in Language Sciences and Language Teaching at Sorbonne Nouvelle University, affiliated with the DILTEC research team (EA 2288). Her primary role includes teaching language acquisition and foreign language didactics within the UFR of Literature, Linguistics, and Didactics (LLD). She co-heads the Master 2 program in Language Teaching (FLE/FLS) and holds administrative roles in departmental councils and educational committees. Education Background: Lecturer at Sorbonne Nouvelle University since 2015 Previously taught at Université de Poitiers (2010–2015) and Université Paris 8 (2007–2010) French teaching assistant at Hokkaido University, Japan Research Focus: Specializes in third language acquisition (L3), crosslinguistic influence, and the interface between language acquisition and didactics. Key themes include: Discourse construction in L3 French Input processing and initial language exposure Development of teaching materials for FLE Plurilingual practices among language teachers Current projects involve multilingualism in primary education, Tamil-speaking learners' L3 French acquisition, and reflexive training in research. Teaching & Supervision: Co-supervises doctoral research on topics such as L3 French acquisition in Chinese contexts, translinguistic discourse influences, and plurilingual teacher practices. Teaches advanced courses on language acquisition theories and FLE methodology. Labs/Teams: Member of the Second Language Acquisition Network (ReAL2) and part of the DILTEC team, focusing on language didactics and multilingualism research.
David Lillis is an Associate Professor in the School of Computer Science at University College Dublin (UCD). His research focuses on Natural Language Processing (NLP), Artificial Intelligence (AI), and their applications in legal and forensic contexts. He leads projects like CeADAR (Ireland’s Applied AI Center) and the Transpire project, collaborating with organizations such as Corlytics and the Department of Enterprise, Trade and Employment. He holds adjunct roles as a Guest Professor at Beijing University of Technology’s Data Mining and Security Lab and has been a Fulbright Scholar at the University of New Haven’s Cyber Forensics Research and Education Group. Education: B.A. (Hons) in Law and Accounting, University of Limerick Higher Diploma in Computer Science, UCD M.Sc., Ph.D. in Computer Science, UCD Professional Certificate in University Teaching & Learning, UCD Research Interests: Legal AI, digital forensics, machine learning, multi-agent systems, and information retrieval. Recent work includes NLP for regulatory analysis, crop yield prediction via neural networks, and AR-driven decision support systems. Grants & Projects: Principal Investigator: Transpire (AI Platform for Regulation) SFI Funded Investigator: CONSUS (Crop Optimization) PI: CeADAR Technology Centre Teaching roles include Deputy Programme Director for Software Engineering at Beijing-Dublin International College (BDIC) since 2014. Labs & Groups: UCD Forensics and Security Research Group, ML-Labs (SFI Centre for ML Training), and the Data Mining and Security Lab (BJUT).
Dr. Sajedul Talukder is an Assistant Professor in the Department of Computer Science at The University of Texas at El Paso (UTEP), directing the SUPREME Lab. He holds a Ph.D. in Computer Science from Florida International University (2019) and has held prior faculty positions at Southern Illinois University (2021-2024) and Pennsylvania Western University (2019-2021). Education: Ph.D. in Computer Science, Florida International University (2019) M.S. in Computer Science, Florida International University (2018) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2014) Research Interests: Focuses on cybersecurity, privacy-enhanced machine learning, and AI-driven solutions for social good. Key areas include: Security and privacy in online systems Abuse detection in social networks Quantum security and distributed systems Federated learning for healthcare and industrial IoT His work emphasizes practical applications like AI for nuclear plant cybersecurity and mitigating sockpuppet attacks. Recent Article Trends: Recent publications highlight advancements in federated learning frameworks (e.g., SAFARI, FLASH), context-aware emotion detection (CAMERA), and AI-driven nuclear facility security (ContextGPT, AML-TIN). These contributions address privacy, scalability, and real-time threat monitoring. Awards & Grants: $500K NRC grant (2024) for AI-driven nuclear plant cybersecurity NSF CISE CRII Award ($157K) for sockpuppet defense IMEC/NIST grant ($99K) for industrial IoT security Best Paper Awards (ICEEICT 2014, ACM SAC 2022) Advising & Labs: Mentored over 40 students (K-12 to Ph.D.), including 2 recent M.S. graduates. Leads SUPREME Lab and affiliated with UTEP AI Institute and NSF IDEAS Center. Active in program committees for ASONAM, ICWSM, and CHI.
Morgan G. Ames is an Assistant Adjunct Professor at the UC Berkeley School of Information and serves as Associate Director of Research for the Center for Science, Technology, Medicine & Society. She chairs the Designated Emphasis in Science and Technology Studies and is affiliated with multiple research centers including the Algorithmic Fairness and Opacity Working Group, the Center for Science, Technology, Society and Policy, and the Berkeley Institute of Data Science. Her educational background includes a Ph.D. in Communication with a minor in Anthropology from Stanford University (2013), an M.S. in Information Management and Systems from UC Berkeley (2006), and a B.A. in Computer Science from UC Berkeley (2004). Prior to her academic career, she worked as a researcher at Google, Yahoo!, Nokia, and Intel. Ames researches the ideological origins of inequality in the technology world, with a focus on utopianism, childhood, and learning. Her work critically examines how technology design practices shape identities and social structures. Current projects include 'Seeing Like a Valley: the Moral Visions of Silicon Valley,' 'Algorithms in Culture,' and 'Countercultures of Technology Use.' She has published extensively on One Laptop per Child, Minecraft, and the social implications of algorithmic systems. Her publication record shows a consistent focus on the cultural dimensions of technology, particularly examining how utopian visions shape technology design and implementation. Recent work increasingly addresses algorithmic systems and their cultural impacts, while maintaining her longstanding interest in educational technology and youth technology practices. Ames has received significant recognition for her scholarship, including: 2020 Best Information Science Book Award 2020 Sally Hacker Prize 2021 Computer History Museum Prize She advises students on interpretive research methods, particularly ethnography, and serves on doctoral committees though cannot be a primary advisor for PhD students. Her research has been supported by multiple interdisciplinary collaborations, including the 'Algorithms in Culture' conference series she co-organized through the Center for Science, Technology, Medicine & Society. Ames leads the 'Seeing Like a Valley' research collective that brings together scholars from across UC Berkeley and Silicon Valley to examine how the region's industrial practices shape moral visions that influence global technological development and social values.
Yiming Yang is a Professor at the Language Technologies Institute and Machine Learning Department within the School of Computer Science at Carnegie Mellon University , where he has held faculty positions since 2003. His research spans foundational and applied aspects of machine learning , artificial intelligence , and scientific computing . Professor, Carnegie Mellon University (2003–Present) Associate Professor, Carnegie Mellon University (1996–2003) Yang's research focuses on LLM-based problem-solving agents , combinatorial optimization , and scalable oversight frameworks . His work explores diffusion models, Langevin dynamics, and Fourier neural operators for NP-hard problems, while advancing reinforcement learning techniques for self-play supervision and principle-driven fine-tuning of large language models. Recent publications highlight his contributions to code synthesis , PDE solving , and multi-agent reinforcement learning . Key methodologies include demonstration-guided control, retrieval-augmented reasoning, and test-time scaling laws. His team has developed frameworks like FEEDER for efficient in-context learning and μTransfer-FNO for zero-shot hyperparameter transfer in PDE solvers. Notable scientific achievements include: Best Student Paper Runner Up (2013) Best Theoretical Paper Award (1994) Best Theoretical Paper Award (1993) Yang has mentored over 20 PhD students and postdocs, including Shengyu Feng , Zhiqing Sun , and Aman Madaan , across domains like graph learning , extreme multi-label classification , and language model alignment .
Demirdache Hamida is a Full Professor of Linguistics at Nantes University and Director of the Nantes Linguistics Lab (LLING UMR 6310, CNRS). She holds a PhD from MIT (1991) and Habilitation à diriger des recherches from Nantes University (2003). Her research focuses on syntax-semantics interfaces, linguistic diversity, and formal syntactic theory with emphasis on Semitic languages and under-represented languages like Salish. She has pioneered experimental methodologies to probe logical form syntax, particularly in studies of temporal anaphora, distributivity, and quantification. Leadership roles: Founded LLING lab in 2004, elevated to CNRS status in 2016 Research grants: Coordinator of ANR-DFG projects (2022-2025), CHILL serious game initiative (2018-2021) Awards: Palmes académiques (2011), Descartes-Huygens Prize (2003), multiple PEDR/PES excellence awards Her experimental work bridges theoretical syntax and empirical child language studies, with recent focus on cross-linguistic variation in telicity and scalar implicatures. Supervised 15 PhD theses (including 3 double-doctorates) and 54 master’s theses. Active in international research networks including the Van Riemsdijk Foundation and Carnot Cognition Institute. LLING lab specializes in formal linguistics with particular expertise in: syntax-semantics interfaces, multilingualism, and experimental methods. Current projects investigate Boolean connectives (FRAL project), heritage language maintenance (AThEME EU project), and logical language acquisition through game-based learning (Cool Boole School).
Nicholas Henriksen is an Arthur F. Thurnau Professor and Professor of Spanish & Linguistics at the University of Michigan, where he has held faculty positions since 2012. His research focuses on laboratory phonology, experimental phonetics, sociophonetics, and intonational grammar in Spanish and other Romance languages. Notable projects include studies on sound change in Andalusian and Patagonian Spanish, bilingualism (Afrikaans-Spanish), and second language speech learning. He directs the Michigan Speech Production Lab and co-leads initiatives integrating gender-diverse language into Romance curricula. Henriksen earned a PhD in Linguistics from Indiana University (2010), MA in Hispanic Linguistics (2006), and BA in Spanish/Mathematics from Rutgers (2003). His teaching spans undergraduate and graduate courses in Spanish linguistics, sociolinguistics, and phonetics, emphasizing applied research and pedagogical innovation. He has received prestigious awards, including the LSA Early Career Award (2021) and the Class of 1923 Teaching Award (2018). His research has been funded by grants from the University of Michigan ADVANCE Program and the Humanities Collaboratory, supporting projects like From Africa to Patagonia: Voices of Displacement . Collaborations include work with scholars in Argentina, South Africa, and Spain, examining language contact, heritage language maintenance, and sociolinguistic identity. Publications span over 30 peer-reviewed articles and book chapters, with a focus on phonetic variation, intonation, and bilingualism. He mentors graduate students in experimental phonetics and sociolinguistics, with advisees contributing to studies on Andalusian Spanish, heritage language acquisition, and voice quality.
Jodi Schneider is an Associate Professor at the University of Illinois Urbana-Champaign , with affiliate appointments at the Beckman Institute , Health Care Engineering Systems Center , European Union Center , and Center for Health Informatics . She directs the Information Quality Lab and focuses on the science of science through argumentation and evidence analysis. PhD in Informatics (National University of Ireland, Galway) M.S. in Library and Information Science (UIUC) M.A. in Mathematics (UT-Austin) B.A. in Liberal Arts (St. John's College) Her research examines how scientific controversies persist through citation patterns, the role of knowledge brokers in public policy, and information quality in biomedical contexts. She has developed semantic frameworks for micropublications and knowledge maintenance in digital libraries. Recent publications include citation integrity studies in Scientometrics , retraction indexing in STI Conference , and argumentation mining in Human Language Technologies . Collaborative projects span institutions like Harvard Radcliffe Institute and RWTH Aachen . NSF CAREER Award IMLS Early Career Award Senior Member, Association of Computing Machinery Marie Curie Fellow She advises graduate students in information quality and knowledge representation , with funding from the Alfred P. Sloan Foundation , NIH , and European Commission . Her lab develops tools to combat scientific misinformation and improve public health informatics .
Thomas Pasquier is an Assistant Professor in the Department of Computer Science at the University of British Columbia, affiliated with the Systopia Lab and UBC Security & Privacy Group. His research focuses on digital provenance, system auditing, intrusion detection, and performance optimization. He investigates systems security through provenance graph analysis, developing practical frameworks for intrusion detection (including PROVNET and Kairos) and provenance summarization tools. His work combines machine learning with systems research to enhance cybersecurity transparency. Recent Publications (2022-2025) Provenance-based intrusion detection systems analysis Whole-system provenance for practical security eBPF kernel extension security enhancements LLM-driven provenance summarization Research code quality assessment Scientific Awards Incredible Instructor Awards Amazon Science Research Award He supervises graduate students in systems security research and teaches courses on security & privacy and operating systems. His lab welcomes diverse students for thesis-based research opportunities.
Rachel Pottinger is a Professor in the Department of Computer Science at the University of British Columbia within the Faculty of Science. She has been at UBC since 2004, progressing from Assistant Professor to Associate Professor in 2012 and to full Professor in 2021. She is affiliated with research centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action) and DFP (Designing for People), and is part of ICICS (Institute for Computing, Information and Cognitive Systems). Her research focuses on data management, particularly semantic data integration, metadata management, and making data more accessible and understandable to users. She leads the Data Management and Mining Lab and has supervised numerous doctoral and master's students. Her work addresses three main areas: helping people understand and explore their data, managing data not well supported by databases, and coordinating data across multiple databases. Her recent publications demonstrate strong trends in database usability, data provenance visualization, query recommendation systems, and building information modeling integration. Her work bridges theoretical database concepts with practical human-centered applications, particularly in making complex data systems more accessible to non-expert users. UBC Computer Science Department Faculty Teaching Award 2013 Computer Science Department Teaching Award 2010 CS Department Teaching Award Denice Denton Emerging Leader Award 2007 Pottinger has supervised numerous PhD and Master's students, with research focusing on data provenance, database usability, and data coordination. She has been involved in significant research projects related to data lakes, open data navigation, and query recommendation systems. Her current research explores table annotation and discovery in data lakes, query refinement for aggregation queries, and query prediction based on past user behavior. She is actively involved in the academic community, serving as Secretary-Treasurer for SIGMOD, on the VLDB Journal editorial board, and as a member of the Computing Research Association's Board of Directors. She previously served as General Co-Chair of SIGMOD 2020 and as Associate Head for the Undergraduate Program of the Department of Computer Science from 2018-2020.
