جست‌وجوی استاد و پژوهشگر

Matthew Louis Maurielloمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Ubiquitous Computing
• Sustainability
• +۷ مورد دیگر

Matthew Louis Mauriello is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware , where he directs the Sensify Lab . He holds a PhD in Computer Science from the University of Maryland (2018) and completed postdoctoral work at Stanford University (School of Medicine, 2020; School of Public Policy & Environmental Engineering Department, 2019). Research interests span Human-Computer Interaction (HCI), Ubiquitous Computing, and User-Centered Design with applications in: Sustainability Human-Building Interaction Wearable Technology Personal Informatics Educational Game Design Mental Health Interventions Recent publications highlight trends in stress monitoring (skin-like biosensors, workplace wellbeing), energy auditing (thermography systems), and educational technology (block-based programming tools for teachers). His work appears in ACM CHI, ACM Human-Computer Interaction, and Building and Environment. Scientific awards include: Best Paper Honorable Mention, CHI 2016 Best Paper Honorable Mention, CHI 2015 Best of WebSci'18 Teaching at University of Delaware encompasses courses like Educational Game Design Operating Systems Advanced Web Technologies Computing for Social Good with a focus on project-based learning and systems thinking.

Robert Westمشاهده پروفایل

دانشیار

• Natural Language Processing (NLP)
• Machine Learning
• Computational Social Science
• +۴ مورد دیگر

Robert West is an Associate Professor at EPFL (École polytechnique fédérale de Lausanne) in the School of Computer and Communication Sciences , leading the Data Science Lab (dlab) . His research focuses on Natural Language Processing , Machine Learning , and Computational Social Science , analyzing human-generated data from the web, social media, and online platforms. Education : PhD in Computer Science (2016) - Stanford University MSc in Computer Science (2010) - McGill University BSc in Computer Science (2007) - Technische Universität München Research Interests : West develops algorithms for analyzing large-scale web data, with emphasis on multilingual NLP , social network analysis , and AI ethics . His work bridges machine learning with social science to understand digital human behavior. Scientific Awards : ICWSM’22 Adamic–Glance Distinguished Young Researcher Award Google Faculty Research Award Facebook Research Award Multiple Outstanding Paper Awards at ICWSM and WWW Advising & Grants : He advises 12 PhD students and has secured funding from the Swiss National Science Foundation , Swiss Data Science Center , and industry partners. His lab maintains collaborations with Microsoft Research and CROSS . Labs & Collaborations : West leads the Data Science Lab at EPFL, which focuses on web-scale data analysis , privacy-preserving machine learning , and AI for social good . The lab develops tools like Wikispeedia and Quotebank for public data exploration.

Maja J Matarićمشاهده پروفایل

استاد

• Socially Assistive Robotics
• Human-Robot Interaction
• Assistive Technology
• +۷ مورد دیگر

Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.

Aniket Kitturمشاهده پروفایل

استاد

• AI-Augmented Cognition
• Collective Intelligence
• Social Computing
• +۷ مورد دیگر

Aniket (Niki) Kittur is a Professor in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University's School of Computer Science. His research focuses on AI-augmented cognition, exploring how humans and computational systems can partner to accelerate knowledge acquisition and innovation. With over 100 peer-reviewed publications and 17 best paper awards or honorable mentions, Dr. Kittur has established himself as a leader in human-computer interaction and social computing. Dr. Kittur's research spans multiple interconnected areas focused on enhancing human cognition through technology. His work on crowd-augmented cognition examines how crowds and computation can collectively enhance human intellect. In social computing, he investigates how sociotechnical architectures can motivate and coordinate large groups for complex tasks. His research in data visualization and sensemaking explores how people collect, organize, and make decisions with online information. Most recently, his work has shifted toward LLM-augmented cognition, investigating how humans and large language models can work together in partnership to achieve better decisions and greater creativity than either could alone. Dr. Kittur's publications reveal a consistent trajectory toward increasingly sophisticated human-AI collaboration systems. Early work focused on crowdsourcing complex tasks (CrowdForge, CrowdSynthesis), then evolved to knowledge acceleration systems (Knowledge Accelerator, Fuse), and has recently centered on LLM-integrated cognition (Selenite, InkSpire, BioSpark). His research consistently demonstrates practical impact, with systems influencing products used by millions and receiving coverage in major media outlets including Nature News, The Economist, and The Wall Street Journal. Kavli fellow NSF CAREER award recipient Allen Newell Award for Research Excellence Inductee into the CHI Academy 17 best paper awards or honorable mentions across his publications Dr. Kittur has advised numerous students, including Andrew Kuznetsov, and has secured major research funding from NSF, NIH, Google, Microsoft, Bosch, Toyota, and other organizations. His Skeema browser extension project, which addresses tab overload through innovative project-based organization, has shown remarkable user retention and represents a practical application of his research on knowledge acceleration. His work with industry partners has influenced products used by millions, including Semantic Reader, Google Shopping, and Wikipedia features.

Tim Althoffمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Human-Centered Computing
• Data Science
• +۵ مورد دیگر

Tim Althoff is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington, specializing in Artificial Intelligence and Human-Centered Computing. His research focuses on behavioral data science, combining Data Science Natural Language Processing Social Computing Human-Centered AI Ethics & Fairness to extract insights about health and well-being. Recent publications highlight advancements in: Mental health support through AI Wearable sensor health monitoring Online community analysis Reproducibility in data science Public health interventions with notable papers in ACL, Nature Machine Intelligence, and NeurIPS. Scientific recognition includes: ACL 2023 Outstanding Paper Award WWW 2021 Best Paper Award Double ICWSM 2021 Best Paper Awards SIGKDD Dissertation Award 2019 Fulbright Scholarship German National Merit Foundation Actively mentoring postdoctoral researchers and seeking PhD students in areas like neural representation learning, NLP applications to psychology, and mobile health technologies through his Behavioral Data Science Group .

Thomas Brinkhoffمشاهده پروفایل

استاد

• Geoinformatics
• Geodatabase Systems
• Spatio-temporal Data Processing
• +۵ مورد دیگر

Prof. Dr. Thomas Brinkhoff is Chair of the Institute Board and Chair of Geoinformatics at Oldenburg University of Applied Sciences. He leads the Institute for Applied Photogrammetry and Geoinformatics (IAPG) and contributes to institutions like the Association for the Promotion of Geoinformatics in Northern Germany (GiN e.V.) and the Oldenburg Research and Development Institute for Computer Science (OFFIS e.V.). Education: Diploma in Computer Science (Informatik), Universität Bremen (1990) Doctorate in Computer Science (Dr. rer. nat.), Ludwig Maximilian University of Munich (1994) Brinkhoff's research spans geodatabase systems, spatiotemporal data processing, geosensor analytics, and location-based services. His work addresses Volunteered Geographic Information (VGI), web-based geospatial visualization, and mobile data integration, with applications in traffic management and forensic science. Recent projects include ProSaDi (Digital Provenance and Collection Research) and contributions to the Laboratory for optical 3D metrology . He has served on program committees for ACM SIGSPATIAL (2002-2019), AGILE conferences (2010-2025), and editorial boards of journals like GeoInformatica and TGIS. Notable Lectures: 2024: Forensic applications of tachograph data 2023: Geoinformatics in homicide investigations 2022: Spatiotemporal analysis for sustainability projects 2015: Open geodata standards at FOSSGIS 2014: Mobile sensor data processing

Andreas Vlachosمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Dialogue Modelling
• +۱۰ مورد دیگر

Andreas Vlachos is a Professor of Natural Language Processing and Machine Learning at the Department of Computer Science and Technology, University of Cambridge, and holds the Dinesh Dhamija Fellowship at Fitzwilliam College. His research spans dialogue modeling, automated fact-checking, imitation learning, semantic parsing, biomedical text mining, and trustworthiness in AI systems. PhD in Computer Science, University of Cambridge (supervised by Ted Briscoe and Zoubin Ghahramani) Lecturer at University of Sheffield Postdoctoral roles at UCL, University of Cambridge (NLIP group, Stephen Clark), and University of Wisconsin-Madison (Mark Craven) Current research focuses on evaluating and mitigating biases in language models, advancing fact-checking methodologies, and improving model robustness through interpolation, reinforcement learning, and causal reasoning. His work integrates natural logic, knowledge graphs, and multimodal evidence for verification tasks. Recent publications address uncertainty quantification, temporal planning benchmarks, and ethical framing of NLP artifacts. Grants from ERC, EPSRC, Facebook, Google, and the Alan Turing Institute fund his research team. Collaborations include Sebastian Riedel, Stephen Clark, and Mark Craven. Key projects explore disinformation detection, long-form generation, and confidence calibration in AI systems.

Lexing Xieمشاهده پروفایل

استاد

• Machine Learning
• Social Media Analysis
• Computer Vision
• +۷ مورد دیگر

Lexing Xie is a Professor in Computer Science at the Australian National University. He leads the ANU Computational Media Lab ( http://cm.cecs.anu.edu.au ) and the ANU Integrated AI Network. His work focuses on the intersection of machine learning, social media analysis, and multimedia understanding. Dr. Xie's research broadly focuses on innovative design and use of machine learning algorithms, especially on large-scale graph data and collective behaviour. His recent work spans several key areas: Popularity in social media -- understanding, predicting, and optimization Multimedia knowledge graphs, vision and language integration Humanising machine intelligence through better understanding of social dynamics His publications reveal a strong trend toward understanding information diffusion patterns in social media, particularly through visual content. He has made significant contributions to the study of visual memes, popularity prediction using point processes, and multimodal learning that connects vision with language. His work often bridges theoretical machine learning with practical applications in social media analysis. Dr. Xie has received recognition for his research, including an Honourable Mention at CSCW 2019 for his work on attention flow in online video networks. His research has been supported by collaborations with major institutions including IBM Research and Columbia University. As an advisor, Dr. Xie has mentored numerous students who have gone on to contribute significantly to publications in top-tier conferences. His lab, the ANU Computational Media Lab, serves as a hub for interdisciplinary research connecting computer science with social sciences.

Elena Simperlمشاهده پروفایل

استاد

• Human-centric AI
• Knowledge Graphs
• Knowledge Engineering
• +۷ مورد دیگر

Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.

• Learning Analytics
• Educational Technology
• Virtual Reality Education
• +۵ مورد دیگر

Ulrik Schroeder is a Universitätsprofessor (Full Professor) at RWTH Aachen University, leading the Chair of Learning Technologies within the Faculty of Computer Science. His research focuses on the intersection of educational technology, learning analytics, and immersive technologies with particular emphasis on practical implementations in higher education settings. Professor Schroeder's research spans multiple interconnected domains in educational technology. His primary interests include Learning Analytics implementation (particularly using xAPI standards), Virtual Reality applications for education, Open Educational Resources development and conversion, and gamification approaches for programming education. He has developed several notable tools including convOERter for OER conversion, WebWriter for creating explorable explanations, and various xAPI-based learning analytics infrastructures. His work consistently bridges theoretical frameworks with practical educational applications, often focusing on computer science education contexts. Analysis of his recent publications reveals a strong trend toward integrating Learning Analytics with immersive technologies, particularly Virtual Reality environments. His research demonstrates a systematic approach to educational technology development, with emphasis on scalability, interoperability through standards like xAPI, and practical implementation in real educational settings. The work increasingly focuses on personalized learning paths, quality assurance for educational resources, and privacy-conscious data collection. Co-editor of 21. Fachtagung Bildungstechnologien (DELFI) (2023) Co-editor of Hochschuldidaktik der Informatik HDI 2018 Co-editor of DeLFI 2018 conference proceedings Professor Schroeder has supervised numerous doctoral and postdoctoral researchers who frequently appear as co-authors on his publications, indicating an active research group. His projects often involve interdisciplinary collaborations across computer science, education, and psychology. Current major initiatives include the AIStudyBuddy project for study path analysis and the development of VR classroom simulations for teacher training. His research group, the Learning Technologies Innovation Lab, develops open research tools that support various aspects of educational technology research and implementation.

Susanne Iwarssonمشاهده پروفایل

استاد

• Gerontology
• Occupational Therapy
• Public Health
• +۶ مورد دیگر

Susanne Iwarsson is a Professor in Gerontology and Care for Older People at Lund University's Faculty of Medicine, holding the Mary and Seved Ribbing Professorship since 2005. She also serves as Director of the Centre for Ageing and Supportive Environments (CASE) and Coordinator of the Swedish National Graduate School for Competitive Science on Ageing and Health (SWEAH). Her academic journey includes a PhD in Medical Science (1997) and promotions to Associate Professor (1999) and Professor (2003). She has held leadership roles such as Pro-dean of the Faculty of Medicine (2006-2011) and Coordinator of the strategic research area MultiPark (2012-2014). Her research focuses on environmental gerontology, housing accessibility, and proactive ageing strategies. Key contributions include the Housing Enabler assessment tool and studies on ageing populations' participation in society. She has supervised 18 PhD students and 6 licentiates, with ongoing supervision of 4 current PhD candidates. Major projects include the Home, Health and Disability longitudinal study (2002-present) and the UserAge program exploring user participation in ageing research. Awards include the Excellent Teaching Practitioner title (2010) and Doctor Honoris Causa. Her work addresses UN Sustainable Development Goals related to health, sustainable cities, and reduced inequalities. Collaborations span universities in Sweden, Finland, Latvia, and the U.S., with partnerships in healthcare and municipal sectors.

• Image Science
• Digital and Media Art Research
• Art History and its Media
• +۶ مورد دیگر

Oliver Grau is a Chair Professor for Image Science and a leading figure in Media Art research, affiliated with Hong Kong Baptist University (Academy of Visual Arts, Distinguished Fellow since 2023) and Danube University Krems (Chair Professor for Image Science from 2005–2022). He founded the Archive for Digital Art (ADA) and the international MediaArtHistories Conference Series , with key roles at institutions across Germany, Austria, and Australia. His work bridges art, science, and technology, focusing on immersive images, digital heritage, and emotion research. Key Positions: Director of ADA (since 2000), Founding Director of MediaArtHistories Conference Series (since 2005), PI for high-resolution digitization of the Goettweig Graphic Print Collection (2005–2017). Research Grants: Funded by DFG, Austrian Science Fund, Australian Research Council, VW Foundation (total 8.3 Mio EUR), and Erasmus+ Joint Master program (5.4 Mio EUR). Research Interests: Grau’s scholarship spans the history of media art, telepresence, artificial life, emotion research, and digital humanities. His work emphasizes the evolution of immersive visual experiences from historical art forms to digital media, integrating theoretical and practical approaches. Article Trends: His recent publications focus on digital art’s sociopolitical dimensions, archiving challenges in the digital era, and cross-disciplinary methodologies. Themes include media art conservation, web-based tools for digital humanities, and the intersection of artistic expression with contemporary global issues like climate change and surveillance. Scientific Awards: Distinguished Fellow at Hong Kong Baptist University (2023) Science Award of Lower Austria (2019) Honorary Doctorate from University of Oradea (2014) Invitations to G-20 summit, Olympic Games, and international symposia Labs & Teams: He leads the Archive for Digital Art, managing a global team of 28 staff, and co-founded the Erasmus+ Joint Master in Media Arts Cultures. His projects emphasize collaborative archiving tools (e.g., Web 2.0/3.0 archives) and large-scale digitization initiatives.

Adegboyega Ojoمشاهده پروفایل

استاد

• Digital Government
• Artificial Intelligence Governance
• Public Sector Innovation
• +۶ مورد دیگر

Dr. Adegboyega Ojo is a Professor at the School of Public Policy and Administration (SPPA), Carleton University , holding the prestigious Canada Research Chair (Tier 1) in Governance and Artificial Intelligence since 2014. His work bridges digital government , AI governance , and smart city development , with a focus on public sector innovation and policy analytics . Research Interests Smart Cities and Urban Digital Infrastructure Open Government Data and Transparency Blockchain Applications in Public Administration AI Ethics and Algorithmic Governance Electronic Participation and Citizen Engagement Publication Trends : His research emphasizes interdisciplinary approaches to digital governance, often involving data-driven policy analysis , smart city frameworks , and open data platform design . Collaborations span institutions in Ireland, Poland, and the U.S., with citations exceeding 5,200. Scientific Awards : Canada Research Chair in Governance and AI (Tier 1) Labs & Teams : Collaborates with the Insight Centre for Data Analytics (Ireland), Delft University of Technology , and United Nations University on projects like OpenGovIntelligence and BOLD (Big and Open Linked Data).

• Marketing
• Applied Economics
• Econometrics
• +۱۰ مورد دیگر

Alan Montgomery is a Professor of Marketing at Carnegie Mellon University's Tepper School of Business, where he has held a tenured position since 2018 (previously as Associate Professor from 2005-2017). He also maintains an affiliation with the Machine Learning Department at CMU's School of Computer Science, demonstrating his interdisciplinary research approach at the intersection of marketing, economics, and computational methods. Dr. Montgomery earned his educational credentials from prestigious institutions: Ph.D. in Marketing/Economics, University of Chicago (1994) MBA, University of Chicago (1994) BS in Economics, University of Illinois at Chicago (1989) His research focuses on applying advanced quantitative methods to marketing problems, with particular expertise in consumer behavior modeling, clickstream data analysis, pricing strategies, and micro-marketing. Dr. Montgomery's work bridges traditional marketing theory with computational approaches, making significant contributions to both academic literature and practical business applications. His research often involves large-scale data analysis to uncover patterns in consumer decision-making processes, with recent work exploring mental accounting, bandit algorithms, and the impact of digital phenomena like movie piracy on traditional markets. Dr. Montgomery has received notable recognition including the 1999 Mitchell Prize from the American Statistical Association for his paper "Estimating Price Elasticities with Theory-based Priors." His work has been published in top-tier journals across marketing, economics, and computer science disciplines, demonstrating the interdisciplinary impact of his research. As an educator and mentor, Dr. Montgomery has advised numerous PhD students and collaborated extensively with researchers across multiple institutions. His interdisciplinary approach has led to collaborations with computer scientists studying web browsing behavior and economists examining consumer decision frameworks. His research has been supported by various grants throughout his career, enabling extensive data collection and analysis projects. Dr. Montgomery's work spans multiple research environments, including collaborations with the Machine Learning Department at CMU's School of Computer Science. His research group likely focuses on applying computational methods to marketing problems, particularly in the areas of consumer behavior modeling, clickstream analysis, and data-driven marketing strategies. His recent work shows increasing integration of machine learning techniques with traditional marketing research methodologies.

• Information Retrieval
• Interactive Information Retrieval
• Personalisation
• +۴ مورد دیگر

Ralf Bierig joined Maynooth University's Computer Science Department in 2017, teaching topics including information retrieval, software testing, interaction design, and virtual reality. He is the programme director of the Higher Diploma in Human-Computer Interaction (HCI) and User Experience (UX). He earned his BSc (2002) from University of Furtwangen and PhD (2008) from Robert Gordon University. Research Interests His work spans information retrieval, interactive information retrieval, personalisation, information search behavior, usability (UX), and virtual reality (VR). Recent publications focus on multimodal concept indexing, hybrid IR approaches, and contextual adaptation in search systems. Publication Trends His research combines statistical semantics, graph modeling, and multimodal data analysis across academic collaborations in Austria, Germany, and international venues like ECIR and SIGIR.