جست‌وجوی استاد و پژوهشگر

Cindy Grimmمشاهده پروفایل

استاد

• Robotics
• Agricultural Robotics
• Computer Graphics
• +۳ مورد دیگر

Cindy Grimm is a Professor and Graduate Program Director in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University (OSU), part of the College of Engineering. She is affiliated with the Robotics group, Human-Centered Computing, and Graphics and Visualization. Her research focuses on robotic grasping and manipulation for agricultural applications, ethics in robotics, and interdisciplinary projects such as 3D modeling, medical imaging segmentation, and bio-inspired sensor design. Education: Ph.D. in Computer Science, Brown University, 1996 M.S. in Computer Science, Brown University, 1992 B.A. in Computer Science and Art, University of California, Berkeley, 1990 Research Interests: Dr. Grimm’s work bridges computer science and robotics, emphasizing practical applications in agriculture and ethics. Key areas include robotic fruit harvesting systems, human-robot interaction, and the development of perception-driven algorithms for complex tasks like tree pruning and object manipulation. Her earlier projects explored surface modeling, bat sonar patterns, and 3D sketching interfaces. Publications: Her recent work addresses challenges in autonomous orchard management, robotic gripper design, and public understanding of service robots. Themes include precision agriculture, grasp planning, and sociotechnical aspects of robotics adoption. Awards: Recipient of the NSF CAREER Award, recognizing her contributions to robotics and interdisciplinary research. Service: Leads the Robotics graduate program at OSU, emphasizing ethical and technical training. Collaborates with the Collaborative Robotics and Intelligent Systems Institute (CoRIS) to advance robotics applications. Labs/Teams: Active in the CoRIS Institute, focusing on collaborative robotics and real-world robotic systems. Her lab develops hardware-software solutions for agricultural robotics and human-centered robotic interfaces.

Pedro U. Limaمشاهده پروفایل

استاد

• Robotics
• Multi-Robot Systems
• Autonomous Systems
• +۴ مورد دیگر

Pedro U. Lima is a Full Professor at Instituto Superior Técnico (IST), University of Lisbon, and President of the Institute for Systems and Robotics (ISR/IST), coordinating the Intelligent Robots and Systems group (IRSg). He holds a Ph.D. in Electrical Engineering from Rensselaer Polytechnic Institute (1994). His research focuses on intelligent control systems, multi-robot coordination, and human-robot interaction, with contributions to robotics competitions like RoboCup and initiatives like the European Robotics League (E.R.L.). Lima has served as Vice President of the RoboCup Federation, Trustee of IEEE Portugal RAS Chapter, and Portuguese National Delegate to the European Space Agency’s Human Spaceflight Program Board. He led the Cátedra de Excelencia sabbatical at UC3M (2010), contributing decision-theoretic approaches to human-robot interaction. His work integrates robotics with societal impact, including outreach through the Pavilhão do Conhecimento and media appearances. He coordinates large projects like euROBIN (EU Horizon Europe) and CRAI (Portugal’s PRR), advancing robotics in domains like autonomous delivery and social robotics.

Eike Schneidersمشاهده پروفایل

مدرس

• Human-Computer and Robot Interaction
• Human-AI Interaction focusing on generative AI and its impact on society
• Multidisciplinary research in collaboration with artists, medical professionals, and lawyers

Dr. Eike Schneiders is a Lecturer at the School of Electronics and Computer Science, University of Southampton. He holds a PhD in Computer Science from Aalborg University and is a recipient of the UKRI Trustworthy Autonomous Systems Hub Early Career Researcher Award. His research focuses on autonomous and AI-infused systems, investigating how to ensure their trustworthiness and responsible interaction with humans and other agents through interdisciplinary collaborations across art, law, and medicine. His recent work explores the societal impact of Generative AI, particularly examining its influence on legal services accessibility for non-experts through the REGALS project (Principal Investigator) and its effects on creative communities via the ART-I project (Co-Investigator). Dr. Schneiders emphasizes public engagement to enhance AI literacy and employs both qualitative and quantitative methods to study human-computer interaction and ethical implications. Dr. Schneiders teaches courses including COMP6251 (Web and Cloud Application Development), ELEC6259 (Research Methods and Project Preparation), and ELEC6200 (Group Design Project). His pedagogical approach integrates foundational technical skills with critical research methodologies. He has led several interdisciplinary projects including ARTificial Intelligence: Show Me a Story about AI (ART-I) and Responsible Employment of Generative AI for Legal Services (REGALS), and contributes to the Agents, Interaction and Complexity research group. His Cat Royale project received the 2024 Webby Award for Best Integrated Experience. Honors include the Best Paper Award at ACM CHI 2024, multiple Honourable Mentions at CHI and TAS Symposiums, and membership in the Foundation for Science and Technology's Future Leaders Programme.

Pablo Callejaمشاهده پروفایل

پژوهشگر ارشد

• Natural Language Processing
• Medical Informatics
• Legal Informatics
• +۵ مورد دیگر

Pablo Calleja is a Research Fellow at the Faculty of Computer Science, Polytechnic University of Madrid (UPM), where he has been a member of the Ontology Engineering Group (OEG) since March 2014. His research focuses on Natural Language Processing (NLP), medical terminology mapping, and legal domain applications. He holds a degree in Computer Engineering from San Pablo CEU University (2013) and has prior industry experience as a software developer at IECISA (2008–2011) and a collaboration grant at the Open Access Classroom, San Pablo CEU University (2011–2013). Key contributions include projects like Drugs4covid for pandemic drug discovery, TermitUp for terminological enrichment, and esT5s , a Spanish text summarization model. His work spans legal knowledge graphs, multilingual compliance systems, and NER techniques for academic content analysis. He has also explored accessibility multimedia services and semantic graph applications in tourism ( DBtravel ). Professional roles include collaboration grants at UPM and active participation in interdisciplinary projects such as SNOMED-CT annotation for medical technical sheets. Research trends emphasize cross-domain adaptation (e.g., K-Flares), data augmentation (Widaug), and multilingual NLP solutions. Advising and grants: His current position is supported by a collaboration grant at OEG. Earlier grants include work at San Pablo CEU University. No formal advisees are listed, but he contributes to collaborative research teams. Labs and teams: Core member of the Ontology Engineering Group (OEG), focusing on knowledge representation, NLP, and applied informatics in healthcare and law domains.

Allan Hanburyمشاهده پروفایل

استاد

• Information Retrieval
• Data Mining
• Natural Language Processing
• +۱۳ مورد دیگر

Allan Hanbury is a Full Professor for Data Intelligence at the Faculty of Informatics, TU Wien, and a faculty member at the Complexity Science Hub Vienna. He leads the Data Science Research Unit and serves as the Faculty Representative for financial affairs and internationalization. He holds a PhD in Applied Mathematics from Mines ParisTech and a Habilitation in Practical Informatics from TU Wien. PhD in Applied Mathematics, Mines ParisTech, 2002 Habilitation in Practical Informatics, TU Wien, 2008 Bachelor’s and Master’s in Physics and Applied Mathematics, University of Cape Town His research focuses on information retrieval, data mining, natural language processing, and information extraction, with applications in healthcare, legal, and patent domains. He has coordinated major EU projects including Khresmoi, VISCERAL, KConnect, and DoSSIER, the latter training 15 PhD students. He is co-founder of contextflow, a spin-off commercializing radiology search technology. His recent publications (2024–2022) highlight a strong trend in systematic literature review automation, neural re-ranking, large language models, and domain-specific information extraction. Key themes include improving citation screening, patient-trial matching, evaluation metrics, and dataset creation for offensive language and legal text. His work combines technical innovation with real-world impact in medical, legal, and scientific communication contexts. Allan Hanbury has received no explicitly mentioned scientific awards in the provided text. He actively supervises numerous PhD and master’s students and leads large research projects such as DoSSIER, Transparent Automated Content Moderation, and PLFDoc, funded by FWF, WWTF, and EU. His group develops tools for evidence synthesis, clinical data extraction, and legal document analysis. He also contributes to AI and data strategy in Austria and Europe. He leads the Data Science Research Unit at TU Wien and is involved in multiple interdisciplinary projects including BRISE (building regulation analysis), CDL-RecSys, and TACo, focusing on legal and scientific document processing. His work bridges academia and industry through spin-offs like contextflow and collaborations with Deutsche Telekom, Siemens, and FMA.

• Labor Law
• Digital Transformation
• Platform Work
• +۷ مورد دیگر

Antonio Aloisi is a Professor of Labor Law at IE University in Madrid, where he teaches European and Comparative Labour Law and guides students in digital regulation. He co-leads the Jean Monnet Center 'Lawtomation' and is affiliated with the 'LawAhead' Center on the Legal Profession, while also serving as a fellow at the UNESCO Chair in Ethics and Governance of Artificial Intelligence. His research focuses on the impact of digital transformation on labor markets, particularly in the gig economy and algorithmic decision-making, blending insights from labor law, data protection, and EU policy. Antonio’s work examines the dual transition of green and digital economies, advocating for governance frameworks that balance innovation with labor rights. His scholarship frequently appears in high-impact journals and is cited in policy documents, court rulings, and media, reflecting his influence on debates about platform work and AI surveillance. He has held visiting roles at institutions like NYU School of Law, Fundação Getulio Vargas, and European University Institute, and his collaborations with international bodies such as the European Parliament, ILO, and OECD underscore his global engagement. Articles by Aloisi highlight trends in algorithmic management, EU Platform Work Directive, and the socio-legal implications of AI. His work critiques the 'robocalypse' narrative, emphasizing that automation often intensifies organizational processes rather than displacing workers, while advocating for collective action and regulatory innovation. Scientific awards include the Marie Skłodowska-Curie Fellowship for the 'Boss Ex Machina' project and a research grant by the European Commission. Scientific Awards: Marie Skłodowska-Curie Fellowship (2020-2022) European Commission Research Grant

Juan F. Sequedaمشاهده پروفایل

پژوهشگر

• Knowledge Graphs
• Semantic Web
• Databases
• +۴ مورد دیگر

Juan F. Sequeda is the Principal Scientist and Head of the AI Lab at data.world, with a PhD in Computer Science from the University of Texas at Austin. He co-founded Capsenta, a spin-off from his research on semantic data virtualization. His work bridges academia and industry through roles in the Property Graph Schema Working Group, LDBC Graph Query Languages task force, and W3C standards editing. Education : PhD in Computer Science (2015) from University of Texas at Austin His research focuses on Knowledge Graphs, Semantic Web, and Ontology-Based Data Integration. He develops technologies for graph data management and semantic query processing, with applications in constitutional data analysis (Constitute.org) and enterprise data virtualization (Ultrawrap, Gra.fo, G-CORE). Recent publications analyze composable graph query languages (G-CORE, 2018) and optimize SPARQL execution on relational data (Ultrawrap, 2013). Awards include NSF Graduate Fellowship (2010-2013), ISWC2014 Best Student Paper, and 2015 Institute for Applied Informatics Best Transfer Project. Scientific Awards : NSF Graduate Research Fellowship (2010-2013) 2nd Place, 2013 Semantic Web Challenge Best Student Research Paper, ISWC2014 2015 Best Transfer and Innovation Project (Institute for Applied Informatics) UT Graduate Diversity Fellowship (2008-2009) National Instruments Scholarship (2007-2008) Intel Foundation Fellowship (2007) He actively contributes to program committees (ISWC, ESWC, WWW) and workshop organization (COLD, AMW2018 General Chair). Contact: juan@data.world (work), juanfederico@gmail.com (personal).

Daniel Hardtمشاهده پروفایل

دانشیار

• Computational Linguistics
• Natural Language Processing
• Artificial Intelligence
• +۴ مورد دیگر

Daniel Hardt serves as Associate Professor in the Department of Management, Society and Communication at Copenhagen Business School. His interdisciplinary research bridges computational linguistics, artificial intelligence, and social analysis, with particular focus on natural language processing applications and theoretical linguistic phenomena. His primary research domains include Computational Linguistics (specializing in ellipsis resolution and sluicing phenomena), Natural Language Processing (developing methods for psychographic classification and sentiment analysis), and Artificial Intelligence (examining large language model capabilities and limitations). Recent work analyzes travel behavior during crises, gender effects in evaluations, and GDPR policy comprehension through NLP techniques. His publications span top venues including Linguistic Inquiry , Tourism Management , and ACL proceedings. Hardt actively engages with practical business applications through 27 media contributions discussing AI implementation, ChatGPT transparency, and data-driven leadership strategies. His academic service includes organizing events like the 2019 "Fake News" conference at CBS and presenting at international venues including JSAI 2024. With 28 supervised academic works documented, he maintains substantial mentoring activity while contributing to public discourse on digital transformation challenges.

Danica M Ommenمشاهده پروفایل

دانشیار

• Forensic Statistics
• Computational Statistics
• Handwriting Analysis
• +۳ مورد دیگر

Danica M Ommen is an Associate Professor at Iowa State University, specializing in forensic statistics and computational methodologies. Her research bridges machine learning, handwriting analysis, and source identification frameworks. Education: Ph.D. in Computational Science and Statistics (2017), M.S. in Mathematics (2014), B.S. in Mathematics (2012), all from South Dakota State University. Affiliations: Chair of the OSAC Statistics Task Group; Vice-Chair of the ASA Advisory Committee on Forensic Science. Her work focuses on statistical modeling for forensic evidence , particularly in handwriting identification, aluminum powder analysis, and digital device forensics. Recent publications explore interpretable deep learning, synthetic data anchoring, and ensemble methods for likelihood ratios. The 15 most recent articles (2023–2025) span forensic machine learning, handwriting kinematics, multi-camera smartphone identification, and Bayesian frameworks. Keywords include Forensic Science , Machine Learning , and Computational Statistics , with subfields like Score-Based Likelihood Ratios and Smartphone Forensics .

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۴ مورد دیگر

Dr. Lea Frermann is an active researcher in computational linguistics and natural language processing, with a focus on media framing analysis, fairness in AI, and Bayesian modeling of semantic categories. Her work bridges machine learning with social science applications, particularly in political discourse and climate communication contexts. PhD in Bayesian models of category acquisition (University of Edinburgh, 2017) Key collaborations with University of Melbourne, ACL, EMNLP, and CoNLL communities Research emphasizes: Media framing analysis across cultures Explainable AI for bias detection Bayesian approaches to language understanding Word association modeling for value systems Computational methods for political discourse analysis Applications in mental health support forums Recent publications focus on large language models' limitations in hierarchical reasoning, multimodal categorization, and systematic fairness evaluation frameworks. Collaborations show strong connections with researchers like Timothy Baldwin, Trevor Cohn, and Omri Abend.

Pascal Bizarroمشاهده پروفایل

دانشیار

• Accounting Information Systems
• IT Auditing
• Information System Assurance & Control
• +۷ مورد دیگر

Pascal Bizarro, Ph.D., is an Associate Professor in the Department of Accounting and Information Systems at Bowling Green State University (BGSU), part of the Schmidthorst College of Business. He holds a Ph.D. and M.Acc. from the University of Alabama and a B.B.A. in Commercial Engineering from HEC, Liège, Belgium. A Certified Information Systems Auditor (CISA), he specializes in IT Auditing, Accounting Information Systems, and emerging technologies like blockchain. He advises BGSU's Information System Audit and Control (ISAC) programs and serves as president of the Northwest Ohio ISACA Chapter and academic board member of the Northwest Ohio IIA Chapter. Dr. Bizarro's research focuses on cybersecurity, audit technology, data privacy, and blockchain applications in accounting. His work has been published in leading journals such as ISACA Journal , Internal Auditing , and The CPA Journal . Notable contributions include studies on phishing attacks, IoT security, AI in auditing, and XBRL implementation. He has received awards including the Schmidthorst Leadership Council Faculty Excellence Award (2015) and the Primrose Family Professorship (2013–present). His professional certifications and academic leadership roles reflect his expertise in bridging accounting practices with information systems innovation.

Tamilselvan Gajapriyaمشاهده پروفایل

استادیار

• Aviation Safety
• Pilots' Selection and Training
• Human Factors in Aviation
• +۷ مورد دیگر

Tamilselvan Gajapriya is an Assistant Professor in the Department of Aviation Science at Saint Louis University, part of the School of Science and Engineering. He holds a Ph.D. in Aviation Science from Florida Institute of Technology, and master’s and bachelor’s degrees in Avionics and Electronics Engineering from Anna University, India. His research focuses on aviation safety, pilot selection/training, human factors, and physiological monitoring in flight environments. He directs the Aviation Safety, Aviation Physiology, and Ergonomics (ASAPE) Lab, which uses advanced equipment like EEG sensors and eye-tracking devices to study pilot performance under stress. Key research areas include cognitive workload assessment during emergencies, UAV privacy concerns, and consumer attitudes toward autonomous aircraft. He has published extensively in journals like Safety Science and Journal of Unmanned Vehicle Systems , with peer-reviewed work on topics ranging from pilot retention strategies to electronic chart usability. Professional affiliations include the Human Factors & Ergonomics Society and Women in Aviation International. His lab investigates physiological markers (e.g., galvanic skin response, EEG) to evaluate pilot decision-making and stress levels during simulated emergencies. Current projects explore factors influencing pilot career retention in commercial aviation and public acceptance of unmanned systems. Dr. Gajapriya collaborates with industry partners to translate research into practical aviation safety solutions.

Samuel Dahanمشاهده پروفایل

دانشیار

• Legal AI
• Dispute Resolution
• Global Work
• +۴ مورد دیگر

Samuel Dahan is an Associate Professor at Queen’s University Faculty of Law and Director of the Conflict Analytics Lab. He holds visiting faculty positions at Cornell University, Paris Dauphine University, ENA, and Harvard University. His expertise spans Legal AI, Dispute Resolution, and Global Work, with a focus on open-source platforms like OpenJustice and the Deel Lab for global employment policy. Education: MA: Sorbonne-Ecole Normale Supérieure Ulm LLM: Katholieke Universiteit Leuven PhD: University of Cambridge Research Interests: Dahan’s work integrates data science with legal challenges, including AI-driven legal tools, conflict resolution analytics, and global workforce compliance. He leads initiatives like OpenJustice, an open-source platform with over 20,000 monthly queries, and the Deel Lab for HR tech innovation. Notable Achievements: Secured $1.1M in grants (NSERC-MITACS Partnership). Published in top venues: AAAI, ICML, McGill Law Journal. Keynote speaker at the French Supreme Court Hearing, Stanford Codex, and Law Society of Ontario. Labs & Teams: Directs the Conflict Analytics Lab at Queen’s University and co-leads the Deel Lab. His teams develop tools like the Deel AI Classifier and MyOpenCourt, addressing legal challenges through data-driven solutions.

Ashok Agrawalaمشاهده پروفایل

استاد

• Computer Systems
• Distributed Algorithms
• Real-Time Systems
• +۱۰ مورد دیگر

Ashok Agrawala is a Professor in the Department of Computer Science at the University of Maryland, with joint affiliations in the University of Maryland Institute for Advanced Computer Studies (UMIACS) and the Department of Electrical Engineering. He directs the Maryland Information and Network Dynamics (MIND) Lab, a leading research group focused on real-time systems, network performance, and wireless localization technologies. Education: B.E. and M.E. in Electrical Engineering, Indian Institute of Science, Bangalore M.A. and Ph.D. in Applied Mathematics, Harvard University His research interests span computer systems, distributed algorithms, real-time operating systems, network performance modeling, traffic shaping, and indoor localization . He is renowned for pioneering the Ricart-Agrawala distributed mutual exclusion algorithm, developing the Maruti real-time operating system, and creating the Horus and Locus indoor positioning systems. His work has led to significant advances in temporal guarantees, jitter-free data delivery, and calibration-free localization. His recent publications show sustained innovation in wireless localization, context-aware computing, breath analytics, and energy-efficient IoT systems , reflecting an evolving research trajectory toward smart health and urban computing. He has authored over 200 papers and seven books, with consistent publication activity into 2024. Scientific Recognition: Fellow, IEEE Member, ACM Member, AAAS Member, Sigma Xi Agrawala has advised over thirty Ph.D. students, many of whom now lead research in academia and industry. His research has been funded by DARPA, NSF, and AFOSR, with corporate partnerships from IBM, Novell, and AT&T. He previously worked at Honeywell Information Systems, where he designed an Optical Character Reader. He has also served as a consultant to the UNDP and the Government of India, and as a technical expert in legal cases. He leads the MIND Lab, which focuses on mobile computing, wireless networks, and context-aware systems , continuing to innovate in real-time and networked systems.

• Machine Learning
• Case-Based Reasoning
• Natural Language Processing
• +۳ مورد دیگر

Nirmalie Wiratunga is a Professor in Intelligent Systems at the School of Computing , Robert Gordon University, and serves as the Associate Dean for Research . She is also an Adjunct Professor at the Norwegian University of Science and Technology (IDUN program). Her academic excellence spans over two decades in Artificial Intelligence and Machine Learning , with a focus on Explainable AI (XAI) , Case-Based Reasoning (CBR) , and Natural Language Processing (NLP) . Her research explores innovative methodologies for knowledge-rich representations to automate decision-making through CBR for Retrieval-Augmented Q&A systems and human-centered AI platforms . She co-founded Attendr.app , a spinout for student and conference attendance tracking, and leads the Artificial Intelligence & Reasoning Research Group at RGU. Recent publications (2024–2025) highlight her work on LLM hallucination detection , counterfactual explanations in finance , cross-lingual biomedical review automation , and multi-query resolution in legal domains . Themes span AI explainability , NLP , CBR , and domain-specific knowledge integration across healthcare, law, and education. Her leadership extends to organizing international workshops on XAI , digital health , and Deep Learning , and co-chairing the ICCBR 2021 and 2022 conferences. She actively contributes to program committees for ECCBR , ECML/PKDD , and IJCAI .