Aamir Anwar is a researcher affiliated with the University of West London , focusing on interdisciplinary applications of artificial intelligence, machine learning, and human-computer interaction. His work bridges technology with education, healthcare, and cybersecurity, as evidenced by his publications on topics like emotion-aware online learning , malware detection in IoT devices , and smart systems for people with disabilities . Research Interests : Machine Learning, Sentiment Analysis, Online Learning, EEG Signal Processing, Smart Systems, Healthcare Informatics. Key Collaborations : Co-authored studies with researchers in cybersecurity, nursing education, and neuromarketing. Publication Trends : Recent articles span 2021–2024, emphasizing AI in education (emotion detection), deep learning for cybersecurity , and health-focused technologies (frailty assessment, seizure prediction).
Katarzyna Wac is a researcher at the University of Geneva affiliated with the Faculty of Economics and Management and the Information Science Institute . Her work bridges Digital Health , Mobile Computing , and Human-Computer Interaction , focusing on leveraging wearable devices, smartphones, and AI for health and quality of life (QoL) quantification. Research Themes: Digital biomarkers for Alzheimer's and migraines, QoL assessment via ubiquitous computing, peer- and self-reported behavioral data, and QoE of mobile applications. Labs: Leads the mQoL Lab , a platform for interactive, mobile, and wearable-based studies. Her recent publications explore Transformer models for health data analysis, social robots in homecare, and ethical frameworks for digital mental health. She has contributed to standards for proxy-reported QoL measures and personalized drug delivery systems in digital health. The multimodal integration of emotional signals and context-aware QoS/QoE provisioning for m-health services are recurring technical themes. Key collaborations include the MobiHealth project and COPD24 , translating future internet technologies into telemonitoring solutions. Her work spans from foundational studies on mobile cognition to applied ambulatory assessment of affect and health risks.
Hariharan Subramonyam is an Assistant Professor (Research) at Stanford University's Graduate School of Education and Computer Science (by courtesy) . He serves as the Ram and Vijay Shriram Faculty Fellow at the Institute for Human-Centered AI (HAI) and is a core faculty member of Stanford HCI . His research bridges Human-Computer Interaction (HCI) and the Learning Sciences , focusing on augmenting human learning through AI via cognitively informed design practices, co-design with learners/educators, and transformative AI-enabled learning experiences. His work emphasizes ethical AI, responsible design, and human values in technology. He earned a PhD in Information from the University of Michigan under Eytan Adar. Current projects include Script&Shift (layered interfaces for LLM writing), AltCanvas (accessible image editing for BVI users), and CogGen (AI tutoring systems). His teaching includes EDUC 432: Designing Explorable Explanations and CS 448B: Data Visualization . Key Research Areas Cognitively Informed AI Systems Human-AI Collaborative Writing Accessible Generative AI Tools Ethical AI Frameworks Interactive Learning Environments Awards & Grants Best Paper Award (CHI 2025) Honorable Mention Award (CHI 2025) HAI Hoffman Yee Grant (2024) Cover Story in Interactions Magazine (2024) Collaborative Networks Co-organizing CHI 2025 Tools for Thought Workshop Contributor to UIST 2024 Dynamic Abstractions Workshop Advising PhD students across Stanford, Georgia Tech, and Duke Collaborations with institutions including University of Michigan, National University of Singapore, and Technical University Munich
Dr. Erik Linstead is an Associate Professor and Senior Associate Dean at Chapman University, affiliated with the Fowler School of Engineering, School of Pharmacy, and George L. Argyros College of Business and Economics. His expertise spans Machine Learning, GPU Programming, Autism Spectrum Disorder, Assistive Technologies, Predictive Analytics, and Virtual Reality. Education: Bachelor of Science, Chapman University Master of Science, Stanford University Ph.D., University of California, Irvine Dr. Linstead's research integrates machine learning with diverse domains, including autism treatment, environmental monitoring, and software engineering. His recent publications focus on coral reef health, land surface temperature trends, and embedded machine learning systems. His scholarly work includes collaborations in remote sensing, medical informatics, and neurodiversity support. Articles highlight his interdisciplinary approach, applying AI to ecological challenges (e.g., Red Sea coral reefs, Nile Basin droughts) and human-centered technologies (e.g., VR therapy for autism, medication adherence analysis).
Dr. Stevan Rudinac is a Researcher at the University of Amsterdam's Faculty of Economics and Business , Section Business Analytics . His work focuses on interactive learning systems and multimodal data analysis, particularly in urban contexts and multimedia modeling. Education: PhD in Multimedia and Information Retrieval from Delft University of Technology (2013). Research Interests: Stevan specializes in multimedia modeling , hypergraph learning , and interactive video search . He develops frameworks for scalable analysis of social networks, urban imagery, and large multimodal datasets, bridging machine learning with practical applications in city planning and financial social media. Recent Trends: His 2024-2025 publications highlight large language model optimization , diffusion model evaluation , and dynamic graph embedding for meme stocks. Collaborative projects include the CASTLE 2024 dataset and Exquisitor , a system for 100 million image exploration. Labs & Teams: He contributes to the Business Analytics group at UvA, collaborating with Prof. Marcel Worring and Dr. Björn Þór Jónsson. He co-organized the UrbanMM'21 workshop and participates in ACM Multimedia and MMM conferences.
Marcelo Worsley is the Karr Family Associate Professor in Computer Science and Learning Sciences at Northwestern University's School of Education and Social Policy (SESP). His research focuses on promoting STEM education for underserved populations through hands-on, project-based learning. He holds a PhD and MS in Learning Sciences and Computer Science from Stanford University, along with dual bachelor's degrees in Chemical Engineering and Portuguese. His work emphasizes inclusive learning technologies, multimodal learning analytics, and fostering agency in students to address real-world challenges. Research Interests: Worsley’s research spans four core areas: (1) designing meaningful hands-on learning experiences; (2) extracting and analyzing multimodal data; (3) developing naturalistic interfaces for education; and (4) bridging engineering education with conceptual change. His Technological Innovations for Inclusive Learning and Teaching (tiilt) Lab aims to address inequities in education by co-designing tools with teachers and learners. Grants & Projects: Worsley has led initiatives such as Multimodal Learning Analytics (funded by NSF EAGER) and PE++ , integrating computer science with physical education. His projects often involve intergenerational making, refugee youth engagement, and culturally responsive computing. Publications: His work appears in journals like Journal of Learning Analytics and conferences such as ICLS and EDM. Recent themes include AI in education, embodied learning in games like Minecraft, and leveraging sports for computational thinking.
Jun Shen is a Professor at the School of Computing and Information Technology, University of Wollongong. He specializes in computational intelligence, cloud computing, and big data applications, with a focus on AI-driven solutions for real-world challenges in transport systems, healthcare, education, and environmental management. He has secured over 40 research grants totaling AU$4.5 million and supervised 26 completed PhD projects. His work spans interdisciplinary areas including bioinformatics, smart manufacturing, and digital health. Research interests include bio-inspired algorithmic optimization, AI in arts/media, and edge computing for IoT systems. He has pioneered research centers in applied computing since 2014 and holds editorial roles in top journals like IEEE Transactions. As an IEEE Distinguished Lecturer, he actively promotes AI ethics and interdisciplinary collaboration. Recent publications emphasize adversarial machine learning defenses, UAV systems, and multimodal data fusion. His supervision includes projects in intelligent transport systems, cloud computing, and e-learning. Grants include projects on resilient energy systems and UAV geolocation verification. Leadership roles include leading over 20 researchers and chairing conferences. He advocates for digital transformation in public services and has conducted fieldwork at MIT, UCI, and Georgia Tech.
Morten H. Christiansen is the William R. Kenan, Jr. Professor of Psychology at Cornell University and holds a concurrent position as Professor of Cognitive Science at Aarhus University's School of Communication and Culture and the Interacting Minds Centre. His research focuses on the interplay between biological and environmental factors in language evolution, acquisition, and processing. Key methodologies include computational modeling, neuroimaging, and experimental psychology. He is an elected member of Denmark’s and Norway’s Royal Academies of Sciences and a Fellow of the Association for Psychological Science and Cognitive Science Society. His work spans over 250 papers and four edited volumes, with his monograph The Language Game (2022) proposing a novel theory of language emergence through improvisation. Research interests emphasize multiword chunking, statistical learning, and individual differences in language processing. Current projects explore Danish language challenges, computational models of cultural evolution, and the impact of large language models (LLMs) on human cognition. Christiansen directs the Cognitive Science of Language Lab, teaches undergraduate and graduate courses (e.g., PSYCH 2150: Psychology of Language), and collaborates internationally on projects like the Danish Gigaword Corpus. His recent work highlights language as an emergent system shaped by interactive and ecological pressures.
Bailey Kacsmar is an Assistant Professor in the Department of Computing Science at the University of Alberta and an Alberta Machine Intelligence Institute (Amii) Fellow. Her research focuses on developing human-centered privacy solutions, combining technical privacy mechanisms (e.g., private machine learning, secure computation) with user perception studies and usability evaluations. She holds a PhD and MMath in Computer Science from the University of Waterloo. Education: PhD in Computer Science, University of Waterloo Masters of Mathematics (MMath), University of Waterloo Research Interests: Privacy-preserving machine learning and AI User-centric privacy design Cryptography for private computation Usability of privacy-enhancing technologies Recent Work Trends: Her publications emphasize practical privacy solutions, including private set intersection protocols, differential privacy in machine learning, and user comprehension of privacy mechanisms. Awards: 2025 U of A Award for Outstanding Mentorship in Undergraduate Research Honorable Mention for CRA Outstanding Undergraduate Researcher Award (Jialiang Yan) Teaching & Advising: Courses include Cryptography for Digital Privacy and Privacy, Cryptography, Network Security. Advises graduate students and undergraduate researchers on privacy-preserving technologies. Emphasizes ethical and human-centered approaches in advising. Labs & Teams: Leads the PUPS (Practical Usable Privacy and Security) Lab, focusing on interdisciplinary privacy research spanning technical design, usability, and societal impact.
Parker VanValkenburgh is an Associate Professor of Anthropology and Associate Professor of Archaeology and the Ancient World at Brown University. His research employs archaeological methods to address anthropological questions, focusing on colonialism and imperialism's impacts on Indigenous people and environments in the Peruvian Andes. He directs the Brown Digital Archaeology Laboratory and co-directs several major projects including the Paisajes Arqueológicos de Chachapoyas (PACha) project and GeoPACHA (Geospatial Platform for Andean Culture, History and Archaeology). His educational background includes: PhD from Harvard University (2012) MA from University of London (2005) MPhil from University of Cambridge (2004) BA from Stanford University (2003) VanValkenburgh's research focuses on the long-term impacts of colonialism and imperialism on Indigenous people and environments in the Peruvian Andes. Through studying architecture, ceramics, environmental datasets, and archival documents, he explores how relationships between people, institutions, and environments transform during imperial histories. His work emphasizes how survival and resilience strategies developed by communities dealing with empires are passed down across generations. He applies digital methodologies, particularly GIS, to map and analyze social, political, and environmental change in space and time, while also critically examining how digital mediation transforms archaeological practice. His recent publications reveal a strong trend toward integrating advanced computational methods with archaeological research. There's a clear emphasis on using AI, machine learning, and remote sensing technologies to enhance archaeological survey and analysis in the Andes. His work spans traditional archaeological topics like landscape, ceramics, and colonial architecture with cutting-edge digital approaches including vision foundation models, point cloud processing, and semi-supervised learning for identifying ancient urbanization patterns. His scientific achievements have been recognized with numerous awards: John Carter Brown Faculty Fellow (2023-24) Meenakshi Narain Excellence in Research Mentoring Award (Brown University, 2023) William G. McLoughlin Award for Excellence in Teaching in the Social Sciences (2021) Cogut Center for the Humanities Faculty Fellowship (2018) American Council of Learned Societies Fellowship (2017) VanValkenburgh has successfully secured substantial research funding for multiple projects. His Paisajes Arqueológicos de Chachapoyas (PACha) project has received NSF funding through 2025, while his GeoPACHA initiative has garnered support from ACLS and SPARC grants. He also co-directs the 'Mapping Historical Trauma in Tulsa, 1921-2021' project. His teaching portfolio includes courses on Geographic Information Systems, cartography, critical digital archaeology, and the archaeology of the Andean region, for which he received Brown's prestigious teaching award. He directs the Brown Digital Archaeology Laboratory, which serves as a hub for integrating digital methodologies with archaeological research. His collaborative network includes scholars from institutions like Vanderbilt University (Steven Wernke) and the University of Tulsa (Alicia Odewale), reflecting his commitment to interdisciplinary research that bridges archaeology, anthropology, and digital humanities.
Deborah McGuinness is a Professor of Computer Science, Cognitive Science, and Industrial and Systems Engineering at Rensselaer Polytechnic Institute (RPI), holding the Tetherless World Senior Constellation Chair. She leads research in semantic web technologies, ontology engineering, explainable AI, and applications in health and environmental informatics. Her work emphasizes semantic technologies to enhance human-machine collaboration through knowledge representation and reasoning. Education: B.S./B.A. (Computer Science & Mathematics, Duke University, 1980), M.S. (Computer Science, UC Berkeley, 1981), Ph.D. (Knowledge Representation, Rutgers University, 1997). Research interests include: ontology creation/evolution, commonsense AI, machine learning fairness, clinical decision support systems, knowledge graphs for scientific data, and policy modeling. Recent work focuses on AI explainability, semantic data dictionaries for public health surveys, and leveraging knowledge graphs for personalized health recommendations. Her publications span semantic web standards, AI commonsense benchmarks, clinical informatics applications, and policy frameworks. Notable projects include the Explanation Ontology for user-centered AI and the CHEAR Data Repository for environmental health research. McGuinness has pioneered semantic technologies for data integration across diverse domains like nanomaterials science and stroke care policy analysis.
Asta Zelenkauskaite is a Professor of Communication and Graduate Faculty Member in the Department of Communication at Drexel University. She is affiliated with the Center for Science, Technology, and Society. Her research focuses on social media dynamics, misinformation, and digital communication practices, employing mixed-methods approaches to analyze emergent online behaviors. She holds a PhD in Mass Communication from Indiana University (2012). Education: PhD in Mass Communication, Indiana University, 2012 Research Interests: Social media research and user-generated content analysis Emergent online practices and ideological influence Disinformation, inauthentic behaviors, and post-truth challenges Macro- and micro-level studies of digital media landscapes Recent Work Trends: Dr. Zelenkauskaite’s recent publications emphasize AI’s role in content analysis, disinformation mitigation strategies, and cross-cultural climate change narratives. Her work bridges social science, information science, and linguistics to address societal challenges like vaccine hesitancy and digital misinformation. Awards/Grants: No specific awards listed, but her research has been supported by interdisciplinary grants focusing on AI ethics and digital media governance. Labs/Teams: Active in Drexel’s Center for Science, Technology, and Society, collaborating on projects addressing technology’s societal impacts. Her work often involves international partnerships, particularly in Eastern European contexts like Lithuania.
Prof Noel O'Connor is a Full Professor at Dublin City University's School of Electronic Engineering, specializing in cutting-edge research at the intersection of artificial intelligence (AI), medical imaging, robotics, and smart city technologies. His work spans applications such as cardiac MRI reconstruction, robotic manipulation using reinforcement learning, and the development of the Smart DCU Digital Twin for autism-friendly university environments. Research interests include AI-driven medical diagnostics, multimodal data fusion, and adaptive systems. His contributions to cardiac MRI reconstruction and transformer-based medical imaging analysis reflect a strong focus on healthcare innovation. He also explores ethical AI practices to reduce social bias in foundation models. Recent work emphasizes smart infrastructure projects, such as optimizing parking recommendations for electric vehicles and enhancing accessibility through digital twin frameworks. His research often integrates real-time sensor data and multi-agent systems to address complex urban challenges. No scientific awards are listed. Collaborations include the ASU-DCU International Research Program on Sensors and Machine Learning. Advising details and grant information are not explicitly provided.
Seth Polsley is an Assistant Professor in the Jeffrey S. Raikes School of Computer Science and Management at the University of Nebraska-Lincoln. His academic home resides in the School of Computing, where he bridges intelligent systems design with human-computer interaction to enhance educational and universal computing experiences. BS in Computer Engineering (2014) - University of Kansas MS (2017) & PhD (2023) in Computer Engineering - Texas A&M University His research explores: Intelligent tutoring systems Brain-computer interfaces Accessible educational technologies Machine learning for child development assessment Sketch recognition in STEM learning Recent publications demonstrate expertise in tactile learning interfaces, sketch-based developmental assessment, and equitable AI systems. Key disciplines span Human-Computer Interaction, Machine Learning, and Educational Technology. Scientific recognition includes: James Blackiston Memorial Graduate Fellowship Sigma Xi Research Award With professional experience at Lexmark International and MIT Lincoln Lab, Polsley combines practical engineering with educational innovation. His work on sketch-based tools and wearable systems addresses both technical and societal challenges in computing.
Shaun M. Dougherty is a Professor and Department Chair of Measurement, Evaluation, Statistics, and Assessment (MESA) at Boston College's Lynch School of Education & Human Development. He directs the Catholic Education Research Initiative and serves as a Strategic Data Project (SDP) Faculty Adviser at Harvard University's Center for Education Policy Research. His work bridges academia and policy, focusing on equity and effectiveness in career and technical education (CTE), educational accountability systems, and regression discontinuity methodologies. Dougherty holds an Ed.D. in Quantitative Policy Analysis from Harvard University. Education: Ed.D., Harvard University, Quantitative Policy Analysis Research Interests: Dougherty's research emphasizes education policy analysis , causal program evaluation , and CTE program impacts . He examines how CTE can address human capital development while addressing systemic inequities related to race, class, gender, and disability. His work integrates advanced statistical methods (e.g., regression discontinuity designs) with policy implementation studies in K-12 systems and postsecondary transitions. Grants & Awards: PI: $647,499 grant from Institute for Education Sciences (2020–2025) Co-PI: $1.7 million grant from Institute for Education Science (2022–2026) Co-PI: $250,000 grant from Institute for Education Sciences (2019–2021) His awards include the Outstanding Reviewer (2017, 2020) and Outstanding Research Paper (2020) from leading journals. Labs & Teams: Leads the MESA department's research initiatives and collaborates with the Catholic Education Research Initiative and Harvard's SDP program. His work engages with states and large districts on applied policy analysis, including Massachusetts, Michigan, and Connecticut.
