Hoyt Long is the Andrew W. Mellon Professor in the Department of East Asian Languages and Civilizations and the College at the University of Chicago. He serves as Chair of his department and directs the Chicago Text Lab while co-directing the Textual Optics Lab. His research spans modern Japanese literature, digital humanities, media history, and cultural analytics. Modern Japanese literature Media theory and platform studies Cultural analytics and computational methods Environmental history and book history Long's recent work focuses on digital media's impact on cultural production, machine translation, and computational approaches to literary studies. His publications highlight intersections of quantitative methods with traditional criticism, including projects on Aozora Bunko, the History of Black Writing, and Japanese text mining. Scientific awards include the Andrew W. Mellon Professorship, reflecting his leadership in integrating computational methodologies with humanities scholarship. He actively collaborates on digital initiatives and contributes to editorial boards like CA: Journal of Cultural Analytics .
Emmanuel Morin is a Full Professor in Computer Science at the University of Nantes, France. He is affiliated with the Computer Science Department of Nantes Institute of Technology (IUT) and leads the Natural Language Processing (TALN) team at the Digital Sciences Laboratory of Nantes (LS2N UMR CNRS 6004). His research focuses on computational linguistics with particular emphasis on multilingualism and multimodality. His academic leadership includes serving as Head of the NLP team (2017-present), Co-responsible for the ATAL (Machine Learning and Natural Language Processing) option of the Computer Science Master (2017-present), and Director of the Nantes computer science training department (2014-present). He also co-edits the Traitement Automatique des Langues (TAL) journal and serves on the steering committee of ATALA since 2004. Current projects: Atlantic 2020, ALALA Project (2019-present), ANR ADDICTE (2017-present), and Atlanstic 2020 RAPACE Project (2016-present) Past projects: Labex CominLabs LIMAH (2014-2019), ANR CRISTAL (2012-2016), and European FP7-ICT TTC project (2010-2012) Professor Morin's research spans natural language processing with a focus on bilingual terminology extraction and comparable corpora analysis. His recent work (2020-2022) shows strategic expansion into medical informatics applications like FrenchMedMCQA, while maintaining his foundational work on domain adaptation of language models using graph-based networks. His publications demonstrate a consistent trajectory from early terminology extraction methods to contemporary applications in specialized language processing. He has supervised numerous PhD students, with current advisees including Kévin Espasa, Martin Laville, Merieme Bouhandi, and Antoine Caubrière. His past students have made significant contributions to the field of natural language processing, continuing his research legacy in academia and industry.
Andrew R. Jamieson is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center, where he leads a research team focused on developing advanced AI systems for medical education and clinical performance assessment. He was appointed in 2019 and serves as Principal Investigator of the Jamieson Group. Institution: UT Southwestern Medical Center School: School of Health Professions Department: Lyda Hill Department of Bioinformatics Academic Rank: Assistant Professor Dr. Jamieson earned his B.A. in Physics with honors (2006) and Ph.D. in Medical Physics (2012) from the University of Chicago. His early work in computer-aided diagnosis laid the foundation for his career in AI and machine learning. Education: University of Chicago (B.A., Ph.D.) Prior Experience: GE Healthcare, Big Data Analytics Startup (First Data Scientist) Dr. Jamieson's research lies at the intersection of artificial intelligence, medical education, and bioinformatics. His team leverages multimodal data—including video, audio, and text—from the UTSW Simulation Center to train frontier AI models for automated assessment of medical student performance. His work in computational image analysis spans label-free live-cell imaging, spatial biology, and highly multiplexed immunofluorescence, with applications in cancer biology and diagnostics. He has also made significant contributions to public health through the development of the UTSW COVID-19 forecast model. The most recent publications reflect a strong trend toward AI-driven medical education tools, particularly using large language models and multimodal AI for OSCE assessment. Earlier works focus on deep learning in medical imaging, dimensionality reduction, and computer-aided diagnosis in mammography. The research consistently emphasizes interpretability, automation, and clinical translation. Scientific recognition includes being featured on the cover of Cell Systems (July 2021) for work on melanoma cell analysis. His team's development of the first automatic AI grading system for medical student OSCE notes in 2023 marks a major innovation in educational assessment. Featured on cover of Cell Systems (2021) Developed UTSW COVID-19 forecast model Pioneered AI grading system for OSCE notes (2023) Dr. Jamieson is actively involved in mentoring and graduate education. He serves as Course Director for the Master’s in Health Informatics program and contributes to nanocourses at the Clinical Informatics Center. His team includes multiple advisees and collaborators working on NLP, LLMs, and AI/ML in healthcare. He is expanding his group and seeking researchers in AI, data science, and software development. His leadership in the Bioinformatics Core Facility (2018–2021) and ongoing collaborations with pathologists and radiation oncologists demonstrate strong interdisciplinary grant and project engagement. Course Director: Master’s in Health Informatics Mentor to multiple graduate students and researchers Collaborations: Pathology, Radiation Oncology, Surgery, Clinical Informatics The Jamieson Group is a dynamic, interdisciplinary research team at the forefront of applying cutting-edge AI to medical education and clinical data analysis. The lab focuses on natural language processing, multimodal learning, and computer vision, with strong ties to the UTSW Simulation Center and Clinical Informatics Center. The team develops custom pipelines for spatial biology and imaging data and is actively expanding to meet growing research demands.
Hengchen Dai is an Associate Professor of Management and Organizations and Behavioral Decision Making at the UCLA Anderson School of Management. She joined the faculty in 2017 after previously serving at Washington University in St. Louis. As co-director of the UCLA Nudge Unit and a Senior Editor for Organization Science , her work bridges behavioral science with real-world applications in healthcare, education, and business. She employs intrapersonal, interpersonal, and policy-focused frameworks to study motivation, fresh starts, and managerial interventions. Education : Ph.D. in Operations and Information Management (2015, University of Pennsylvania); B.S. in Psychology and B.A. in Economics (2010, Peking University) Her research explores behavioral change mechanisms , particularly how temporal landmarks (e.g., New Year’s resolutions) influence goal pursuit, and how social influence and policy design affect decision-making. She has published in Nature , PNAS , and Academy of Management Journal , with a focus on field experiments over lab-based approaches. Recent work analyzes choice overload in digital platforms , text-based nudges , and urgency in precommitment designs . Scientific awards include Association for Psychological Science Fellow (2024) Academy of Management MOC Division Best Paper Award (2024) Janet Taylor Spence Award (2023) Behavioral Science & Policy Association Best Publication (2023) UCLA Hellman Fellows Award (2020) She teaches executive, fully employed, and full-time MBA programs, emphasizing practical applications of behavioral research. Her work with corporations and healthcare systems demonstrates a commitment to translational behavioral science .
Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.
Carl G. Stahmer serves as Professor of English and Science and Technology Studies at the University of California, Davis, where he holds dual leadership roles as Executive Director of the UC Davis DataLab: Data Science and Informatics and Director of the English Broadside Ballad Archive—a position he assumed after 18 years as its Associate Director and Lead Developer. His research pioneers computational tools for Analytical Bibliography at scale, focusing on historical text and printed image analysis. With a career spanning since the mid-1990s, he has shaped digital humanities through foundational work with the English Short Title Catalog, NINES (Networked Infrastructure for 19th Century Studies), ARC (Advanced Research Consortium), and Project Quintessence (EEBO text analysis portal). Stahmer's initiatives have secured major funding from the Andrew W. Mellon Foundation, Alfred P. Sloan Foundation, Microsoft Research, National Endowment for the Humanities, and National Science Foundation. He teaches L-100: Digital Approaches to Bibliography & Book History, integrating his research into pedagogy. He directs the UC Davis DataLab and English Broadside Ballad Archive, fostering cross-disciplinary collaboration in digital scholarship infrastructure and data science applications for humanities research.
João Guerreiro is a Visiting Assistant Professor at ISCTE-IUL (Instituto Universitário de Lisboa) with a PhD in Marketing from the same institution. He is affiliated with the Iscte Business School, where he teaches undergraduate and master's degree courses in marketing and decision support systems, applying data mining techniques to analyze large information sets. His research expertise spans three interconnected domains: Decision Support Systems - particularly in banking and insurance sectors where he has held executive positions Neuroscience Applied to Marketing - utilizing eye-tracking and studying autonomic emotional responses to consumer stimuli Corporate Social Responsibility - examining cause-related marketing and pro-environmental behavior in tourism Dr. Guerreiro's recent publications (2020-2023) reveal a strong emphasis on immersive technologies, with multiple studies on virtual reality applications in consumer behavior, augmented reality's impact on purchasing decisions, and cross-cultural differences in digital marketing effectiveness. His methodological approach frequently incorporates text mining, sentiment analysis, and neuromarketing techniques to uncover deeper consumer insights. His industry experience in decision support systems provides practical grounding for his academic work, creating a valuable bridge between theoretical marketing concepts and real-world business applications in financial sectors.
Paul P. Maglio is a Professor of Management and Cognitive Science at the University of California, Merced, where he is affiliated with the School of Engineering and the Department of Management of Complex Systems. As one of the founders of the field of service science, he has established himself as a leading researcher at the intersection of management, cognitive science, and information systems. His work spans from theoretical foundations of service systems to practical applications of service innovation. Maglio received his bachelor's degree in computer science and engineering from MIT and earned his Ph.D. in cognitive science from the University of California, San Diego. His academic journey reflects his interdisciplinary approach that bridges technical and social sciences. His research interests focus on human-computer interaction, distributed cognition, and service science, with particular emphasis on how technology enables service innovation and value creation. Maglio's work explores how cognitive principles can inform the design of service systems and how service systems can be understood through the lens of complex adaptive systems. His research has practical applications in digital service transformation, service design, and the integration of artificial intelligence in service contexts. Analysis of his recent publications reveals a clear trajectory toward understanding service systems in the age of AI. His work increasingly examines how autonomous technologies transform human-centered service systems, with particular attention to trust in AI systems, digital service transformation, and the ethical implications of data-driven business models. The publications show a consistent focus on service science as an interdisciplinary field that connects management, information systems, and cognitive science. Maglio served as Editor-in-Chief of INFORMS Service Science from 2013 to 2018 and is the lead editor of the Handbook of Service Science, Volumes I and II. He has published over 125 papers across computer science, cognitive science, and service science domains, establishing him as a prolific contributor to these fields. As an educator, Maglio teaches courses including Technology-enabled Service, Foundations of Management of Complex Systems, Service Science, and Service Innovation. His teaching reflects his research interests and commitment to developing the next generation of service science scholars and practitioners. His work with students likely focuses on the practical application of service science principles to real-world business challenges. Maglio directs research that examines the intersection of cognitive science and service systems, with particular attention to how people interact with and through service systems. His work on epistemic actions and distributed cognition provides theoretical foundations for understanding how humans and technology collaborate in service contexts.
Morteza Zihayat is an Associate Professor and Canada Research Chair (Tier 2) in Human-Centered Artificial Intelligence at Toronto Metropolitan University. He holds dual appointments in the Faculty of Engineering and Architectural Science (Department of Electrical, Computer, and Biomedical Engineering) and the Ted Rogers School of Management. Additionally, he serves as an Adjunct Professor at the University of Waterloo in Management Sciences and is a Faculty Fellow at IBM's Centre for Advanced Studies. Dr. Zihayat's educational background includes: PhD in Computer Science from York University (2016) MSc in Computer Engineering from University of Tehran (2011) Postdoctoral Research Fellowship at University of Toronto's Faculty of Information (2017) His research lies at the intersection of AI, security, and society with a focus on building fair and transparent AI systems. Dr. Zihayat's expertise spans human-centered AI, fair information retrieval systems, and blockchain-enabled AI infrastructures. His work emphasizes creating AI systems that are accountable and designed to serve the public good, with applications in healthcare, digital media, and social networks. Dr. Zihayat has received numerous accolades including the Canada Research Chair (Tier 2) in Human-Centered AI (2024), Dean's Outstanding Scholarly, Research, and Creative Activity Award (2023), Best Short Paper Award at ECIR (2023), and IBM CAS Faculty Fellowship (2021). His research has attracted over $1.7 million in external funding from agencies such as NSERC, Mitacs, and multiple industry partners including Toronto Transit Commission, The Globe and Mail, AT&T, and IBM. Dr. Zihayat serves as Associate Editor of the Computational Intelligence Journal and is an active reviewer for top-tier venues. He is also Co-director and Co-founder of the Digital Enterprise Analytics and Leadership (DEAL) Research Center.
Olga Viberg is an Associate Professor at KTH Royal Institute of Technology, specializing in Technology-Enhanced Learning within the Division of Media Technology and Interaction Design at the School of Electrical Engineering and Computer Science. With a PhD in Informatics from Örebro University (2015), she brings extensive experience from Dalarna University (2008-2016) as a lecturer in Media Technology and Learning Sciences. Current roles: Associate Professor, Docent, Course Coordinator Key research areas: AI in Education, Learning Analytics, Privacy & Ethics Leadership roles: Editor-in-Chief of International Journal of Learning Analytics , Vice-President of SoLAR Research Focus : Viberg's work bridges AI, learning analytics, and educational design through value-sensitive approaches. Her studies address: Privacy concerns in learning analytics Cultural alignment of AI systems Self-regulated learning frameworks Trust dynamics in AI adoption Responsible data practices in education Generative AI applications in assessment Scientific Contributions : Recognized through: 2024 Google Academic Research Award Multiple conference recognitions (LAK'24, LAK'23) Leadership in international initiatives like UNESCO's online education policy Educational Impact : Directly shaping academic programs through: Coordination of Bachelor's course in Media Technology Teaching PhD courses in Learning Analytics Organizing Nordic Learning Analytics Summer Institute
Jignesh M. Patel is a Professor in the Computer Science Department at Carnegie Mellon University, where he leads research on efficient data analysis methods. His work focuses on improving both system efficiency (e.g., high-performance data algorithms) and human efficiency (e.g., user productivity with data systems). Research Focus: Patel's group specializes in database systems, query optimization, hardware acceleration, and human-data interaction. Their interdisciplinary work spans: Transactional processing and real-time analytics Query optimization techniques Hardware-algorithm co-design Natural language interfaces for data systems Memory-efficient data processing Professional Activities: Co-founded four technology companies (Paradise, Locomatix, Quickstep, DataChat). Serves on program committees for premier conferences including SIGMOD and CIDR (as co-chair). Teaches database systems courses at CMU. Awards: Received Best Paper Award at DaMoN 2010 for work on cluster efficiency.
Dr. Ramona Roller is a Researcher in Sociology at the Faculty of Social and Behavioural Sciences, Utrecht University. She is affiliated with the Chair Buskens Social Networks, Solidarity and Inequality and contributes to the Institutions for Open Societies (IOS) initiative, specifically focusing on Behaviour and Institutions and In-Equality research areas. Her research expertise spans Analytical Sociology, Experimental Sociology, Computational Humanities, Computational Social Sciences, and Network Analysis. Dr. Roller employs a complex systems perspective to study how local human interactions give rise to global group phenomena. Her work focuses on two main areas: cooperation in modern work teams and the diffusion of ideas in historical societies. In her research on contemporary teams, Dr. Roller investigates fair, productive, and sustainable cooperation through the spontaneous emergence of roles in software development teams. She is part of the SCOOP project (Sustainable COOPeration), collaborating with Rafael Wittek from Groningen and Vincent Buskens from Utrecht. On a societal level, she studies the evolution and spread of ideas during the Reformation in 16th-century Europe using letter correspondences of scholars. This interdisciplinary work involves collaboration with researchers from historiography, theology, and linguistics to address complex challenges in historical analysis. Dr. Roller applies diverse research methodologies including field studies, behavioral experiments, social network analysis, spatio-temporal modeling, and causal inference methods. Her recent publications demonstrate expertise in computational approaches to historical data, particularly in analyzing 16th-century correspondence networks and territorial concepts.
Fernando Rodriguez Jr. is an Assistant Professor at the University of California, Irvine's School of Education. He directs the Education, Technology & Culture (ETC) Lab and co-directs the IES-funded Career Pathways for Researching Learning and Education, Analytics and Data Science (CP-LEADS) program. B.A. in Psychology from California State University, Northridge (CSUN) Master's in Developmental Psychology from the University of Michigan Ph.D. in Educational Psychology from the University of Michigan Dr. Rodriguez's research integrates cognitive theories to enhance student learning. He specializes in: Learning analytics to analyze online platform data for learning behaviors Self-regulated learning and its impact on academic outcomes Social learning theories applied to peer-driven online environments (e.g., Flip, YouTube, Perusall) Dual-process theories of cognition examining critical thinking and persuasive texts His work bridges educational psychology, data science, and instructional technology to optimize digital learning experiences. Scientific recognition includes: Fellowship at the International Max Planck Research School on the Life Course Support from the NIMH-COR training program during undergraduate studies As co-director of the CP-LEADS program, he mentors emerging scholars in education data science methodologies. His research lab investigates how cognitive frameworks can inform adaptive learning technologies and collaborative digital pedagogies.
Hamid Karimi is an Assistant Professor of Computer Science at Utah State University (USU), where he leads the Data Science and Applications (DSA) lab. His research focuses on using AI and data mining for social good, including social media mining, educational data mining, and machine learning. He earned his Ph.D. in Computer Science from Michigan State University (MSU) in 2021, with a thesis on AI for social good. His interdisciplinary work includes the Teachers in Social Media project, which developed algorithms to improve PK-12 education quality. Dr. Karimi has received several awards, including the Best Paper Award at ASONAM 2018 and the International Faculty Recognition Award at USU in 2022. His research spans social media behavior analysis, misinformation detection, and fairness in machine learning. The DSA lab prioritizes practical solutions for socially impactful data science applications, such as cross-disciplinary projects in science and engineering. Education: Ph.D. in Computer Science, Michigan State University, 2021 Research Interests: Social Media Mining Educational Data Mining Graph Mining AI for Social Good Lab: Data Science and Applications (DSA) Lab, USU His work bridges theoretical data science with real-world applications, such as analyzing teacher behavior on Pinterest and leveraging GPT for scalable education tools. Dr. Karimi’s research emphasizes ethical AI practices and interpretable machine learning models.
Dr. Jiraporn Surachartkumtonkun is a Senior Lecturer in the Department of Tourism and Marketing at Griffith University. She holds a PhD in Marketing from the University of New South Wales and has academic affiliations with the Centre for Work, Organisation and Wellbeing and Griffith Asia Institute. Her research focuses on services marketing, frontline employee wellbeing, cross-cultural studies, and consumer behavior in digital contexts. She has published in top journals like the Journal of Retailing and European Journal of Marketing , and serves on the editorial board of the Australasian Marketing Journal . Education: PhD in Marketing, University of New South Wales (Australia) Master of Marketing, Thammasat University (Thailand) Bachelor of Economics, Thammasat University (Thailand) Research Interests: Combines empirical and theoretical approaches to study customer emotions, service recovery, employee diversity, and digital marketing strategies. Recent work explores AI’s impact on workplaces and consumer engagement via TikTok and social media. Teaching: Specializes in Services Marketing, Digital Marketing, and Consumer Psychology. Holds fellowship in UK Higher Education Academy (2022). Grants & Impact: Recipient of a $15,000 Queensland grant to develop growth mindset programs for Aboriginal and Torres Strait Islander students. Leading a $100,000 project on gamified career exploration for culturally diverse female students. Collaborated on a UNDP data project analyzing regional education strategies. Awards: 2022 Best Reviewer Award - Australasian Marketing Journal UK HEA Fellowship (2022)
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