جست‌وجوی استاد و پژوهشگر

Vinit Paridaمشاهده پروفایل

استاد

• Servitization and advanced service innovation
• Business model innovation and scaling
• Digitalization and artificial intelligence as enablers for innovation
• +۴ مورد دیگر

Vinit Parida is a Professor and Head of Subject for Entrepreneurship and Innovation at Luleå University of Technology, within the Department of Social Sciences, Technology and Arts, Division of Business Administration and Industrial Engineering. He serves as Associate Editor for Journal of Business Research, is a Member of Swedish ministry's high-level group on digital transformation of Swedish industry, Scientific Leader for NorrlandsNavet, and Board member for RE:Source Strategic Innovation Program. His educational background includes a Bachelor in Commerce from Delhi University (2000), an Advance Diploma in Computer Applications (2000), an MBA with specialization in Electronic Commerce from Luleå University of Technology (2005), and a PhD in Entrepreneurship from Luleå University of Technology (2010). Professor Parida's research focuses on several key areas in business and innovation. His work spans servitization and advanced service innovation , business model innovation and scaling , digitalization and AI as enablers for innovation , industrial ecosystems development , circular economy and sustainable product service-systems , organizational capabilities and routines , and entrepreneurship in resource constrained environments . His research involves collaboration with major companies including ABB, Billerudkorsnäs, Boliden, Epiroc, Ericsson, IBM, Komatsu Forest, Lindbäcks, Metso, Sandvik Coromant, SCA, Scania, Siemens, Volvo Cars, and others. Professor Parida has published over 200 works in leading international journals including Academy of Management Journal, Journal of Management, Strategic Management Journal, and Entrepreneurship Theory and Practice. His recent publications focus on AI-enabled innovation, digital business models, and entrepreneurial learning from failure, reflecting current trends in digital transformation and sustainable business practices. His scientific achievements have been recognized with several prestigious awards: Nordea Scientific Excellence Prize (2020) The Young Researcher Award for Entrepreneurship Research (2016) PhD Supervisor of the Year (2015) Award for Young Deserving Research in Entrepreneurship and Innovation (2013) Award for Excellent Research in Small Business (2010) Ranked among the 100 most productive and cited researchers in Sweden in Social Sciences by Fokus Professor Parida actively supervises PhD students, with notable advisees including Elizaveta Averina, Linus Thomson, Milad Kolagar, Lina Sundén, Anmar Kamalaldin, Angelica Löfberg, and others. He has received research funding from various sources including the Wallenberg Foundations, VINNOVA, and direct industry partnerships. His work bridges academic research with practical applications through collaborations with Swedish government ministries, the EU Commission, and numerous industry networks. He is involved in teaching courses at all levels (bachelor, master, PhD) and executive education, focusing on strategic business development, technology and innovation management, international entrepreneurship, and scientific methods. Professor Parida has also contributed to Swedish newspapers and practitioner-oriented outlets such as Ny Teknik and Dagen Industri.

William E. Spanglerمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Dr. William E. Spangler serves as Professor and Department Chair of the Accounting, Information Systems and Technology, and Supply Chain Management Department at Duquesne University's Palumbo-Donahue School of Business. With extensive industry experience at Fortune 500 companies including Unisys and Westinghouse, he bridges academic theory with real-world practice while maintaining active leadership in international academic programs across six continents. His educational foundation includes: Ph.D. from the University of Pittsburgh M.B.A. from the University of Hawaii B.A. from the University of South Florida Spangler's research program demonstrates remarkable evolution from core artificial intelligence and machine learning applications in decision support systems toward contemporary explorations of sustainability, social responsibility, and technology ethics. His work spans surgical scheduling optimization, television viewer profiling, RFID privacy concerns, and cross-cultural analysis of charitable behavior in online social networks, reflecting both technical depth and societal relevance. Recent publications increasingly examine information technology's role in corporate sustainability initiatives across global contexts. His publication trajectory reveals consistent contributions to premier journals including Management Science , Journal of Management Information Systems , and IEEE Transactions on Knowledge and Data Engineering , with growing emphasis on interdisciplinary applications connecting information systems with healthcare, marketing, and sustainability domains. Recognition for his teaching excellence includes: Duquesne University Creative Teaching Award Apple Polishing Award Palumbo-Donahue School of Business Outstanding Educator Award Kurt Rethwisch Outstanding Teaching Award As an educator, Spangler has pioneered international immersion experiences through study abroad programs across Europe, Asia, Africa, and South America while developing innovative curriculum frameworks for AI integration in business education. His professional engagement extends through active membership in the Association for Information Systems (AIS), International Association for Computer Information Systems (IACIS), Information Systems Audit and Control Association (ISACA), and Institute of Internal Auditors (IIA). Current research initiatives focus on comparative analysis of online social network influences across US, Chinese, and Indian contexts regarding charitable behavior, alongside investigations into organizational responses to consumer privacy concerns in the RFID era.

Katja Pässlerمشاهده پروفایل

پژوهشگر

• Aptitude testing
• Fairness of ability tests
• Gender differences in professional interests
• +۱۱ مورد دیگر

Katja Pässler serves as a Scientific Associate at the School of Applied Psychology at the University of Applied Sciences Northwestern Switzerland (FHNW). She has been working at the institution since October 2011 and is affiliated with the Institute for Humans in Complex Systems, which focuses on the interaction between people, technology, and organizations in the context of automation, digitalization, and technical networking. Dr. Pässler completed her doctorate at the University of Hohenheim under Prof. Dr. Heinz Schuler and studied psychology at the University of Konstanz and the University of Exeter. Prior to her current position, she worked as a research assistant at the University of Konstanz (2008-2012) and as a consultant in personnel and management consultancy (2006-2008). Her research focuses on the fundamentals of aptitude testing, including the fairness of ability tests, gender differences in professional interests, personality psychology in aptitude diagnostics, and validity studies. She also develops aptitude diagnostic procedures, particularly self-assessments available at www.self-assessment.ch. Her teaching spans Bachelor's and Master's programs in Applied Psychology, covering Differential and Personality Psychology, Questionnaire Development, and Advanced Statistical Methods, as well as continuing education programs. Analysis of her recent publications (2015-2024) reveals a consistent focus on vocational interests, aptitude diagnostics, and the integration of digital tools in career counseling. Her work bridges theoretical research with practical applications, particularly in student selection and career guidance. A significant portion of her research examines gender differences in vocational interests and STEM career choices, with several publications addressing the underrepresentation of women in technical fields. Dr. Pässler actively collaborates with colleagues like Benjamin Hell and Tamara Mitrovic on projects related to online self-assessments and their implementation in counseling practice. Her research combines quantitative methods, meta-analyses, and practical validation studies to improve the effectiveness of career guidance tools. She teaches in both degree programs and continuing education courses, including the CAS Basic Knowledge Psychology and MAS Career, Study and Career Counseling. Her work on self-assessment tools demonstrates a commitment to translating research into practical applications that benefit students and career seekers. Dr. Pässler is involved with the Institute for Humans in Complex Systems, which addresses the challenges and opportunities of human-technology interaction in increasingly automated and networked environments. Her specific contributions focus on how psychological principles can inform the design and implementation of assessment tools in digital contexts.

Paola Perucchiniمشاهده پروفایل

استاد

• Educational Psychology
• Child Development
• Intercultural Education
• +۳ مورد دیگر

Paola Perucchini is a Professor in the Department of Educational Sciences at the University of Rome III, specializing in child development, educational psychology, and environmental learning. Her work bridges early childhood education with interdisciplinary research on intercultural understanding, ADHD intervention, and sustainability pedagogy. Full Professor, Department of Educational Sciences Director of the Department of Educational Sciences Member of Academic Senate and Research Commission Her research focuses on reducing social biases, inclusive pedagogy, and the cognitive benefits of green environments. She pioneered the ODIS (Osservazione della DIScussione) framework for analyzing classroom communication and the Yesterday-Today-Tomorrow e-learning program for migration education. Recent publications (2023-2025) emphasize prosocial behavior promotion, intergroup coalition formation, and outdoor education's role in attention restoration. Earlier work (1997-2004) explores gestural development in autism and its implications for theory-of-mind cognition. She collaborates with the MuSEd – Mauro Laeng Museum of School and Education , integrating historical pedagogy with modern inclusive education strategies. Her teaching emphasizes socio-communicative teacher traits and remote learning adaptation, particularly in pandemic contexts.

Yoav Artziمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Robotics
• +۴ مورد دیگر

Yoav Artzi is an Associate Professor in the Department of Computer Science at Cornell University and a core faculty member at Cornell Tech in NYC. He serves as the Associate Faculty Director at arXiv.org and is a researcher at ASAPP. His work focuses on building systems that enable machines to interact with humans through natural language while continuously improving through dynamic interactions. Key roles include: Cornell University, Department of Computer Science Cornell Tech, NYC campus arXiv.org Associate Faculty Director ASAPP Research Scientist Education: B.Sc. from Tel Aviv University, Ph.D. from the University of Washington (advised by Luke Zettlemoyer). Research integrates NLP with robotics, computer vision, and cognitive science, emphasizing situated learning in multi-agent systems. Notable projects include the COLM conference, RecNet paper recommendation network, and LM-class educational resource. Awards include an NSF CAREER Award and paper recognitions at top venues. Research interests span automated language acquisition, situated systems, and interactive learning. Recent work explores tokenization challenges, heterogeneous cluster training, and the role of RAG systems in modern LLMs. Advises students in vision-language systems and robotics. Active in organizing workshops like InterNLP and SpLU-RoboNLP. Teaching includes advanced NLP courses (CS 5740, CS 6741). Labs focus on collaborative interaction platforms (CB2), visual reasoning benchmarks (lilGym), and multimodal learning tools. Current initiatives include launching COLM 2025 and advancing RecNet's paper discovery network.

Amel BOUZEGHOUBمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Internet of Things (IoT)
• +۵ مورد دیگر

Prof. Amel BOUZEGHOUB is a Professor at Telecom SudParis, affiliated with the SAMOVAR research center. Her work focuses on AI, IoT, and data-driven systems with applications in smart environments, robotics, and education. She has contributed to over 50 peer-reviewed publications spanning machine learning, reinforcement learning, and semantic data processing. Research Interests: Her research bridges theoretical advances in machine learning with practical applications in smart homes, autonomous systems, and educational technology. She explores topics like human activity recognition, anomaly detection in social networks, and real-time data stream processing. Recent Trends: Her 2023-2024 work emphasizes explainable AI, reinforcement learning for autonomous systems, and multi-agent frameworks for stream reasoning. Earlier contributions include IoT-based supply chain traceability and distributed human activity recognition models. Grants & Projects: Key contributions include the ANR INCOME project on multi-scale context management for IoT systems and ACMES initiatives in educational technology. Labs/Teams: Active within the SAMOVAR lab at Telecom SudParis, collaborating with international teams in AI and robotics research.

Manjunath Kamathمشاهده پروفایل

استاد

• Stochastic modeling
• Queuing theory
• Performance Modeling of Manufacturing Systems
• +۵ مورد دیگر

Dr. Manjunath Kamath is a Professor in the Department of Industrial Engineering and Management at Oklahoma State University's College of Engineering, Architecture and Technology, where he has served since 1989. He directs the Center for Computer Integrated Manufacturing Enterprises and previously led the NSF Center for Excellence in Logistics and Distribution (CELDi) as Associate Site Director (2002-2012) and Site Director (2012-2013). His academic credentials include a Ph.D. in Industrial Engineering from the University of Wisconsin-Madison (1989), a Master of Engineering in Automation from the Indian Institute of Science, Bangalore (1984), and a Bachelor of Technology in Mechanical Engineering from the Indian Institute of Technology, Madras (1982). Dr. Kamath's research centers on stochastic modeling, queuing theory, and performance evaluation of manufacturing and supply chain systems. He utilizes object-oriented modeling, Petri nets, and simulation to develop methodologies for freight movement, supply chain networks, and knowledge work environments. His work bridges analytical frameworks with practical enterprise applications, emphasizing discrete-event systems and enterprise modeling. His publication record reveals a progression from manufacturing systems to broader supply chain and logistics applications, with increasing focus on decision support tools like TISCSoft and RAQS. Recent work integrates transportation infrastructure modeling with supply chain optimization, reflecting evolving industry needs. His accolades include: Regents Distinguished Teaching Award (2013) Lockheed Martin Aeronautics Teaching Excellence Award (2013) Halliburton Excellent Teacher Award (2012, 2003) CELDi Success Award (2011) ASR Best Paper Award (2006) Phoenix Award for Outstanding Graduate Faculty (2005) Outstanding Advisor Award (2004) Pritsker Outstanding Faculty Award (1999, 1996) IIE Transactions Award (1993) As an advisor, he earned the Outstanding Advisor Award (2004) while securing five NSF grants (1993-2003) and recent funding from Oklahoma Transportation Center and ODOT. His projects produced modeling tools for manufacturing systems and supply chains, along with new graduate courses in enterprise modeling. He leads the Center for Computer Integrated Manufacturing Enterprises and has driven CELDi's industry-academic partnerships in logistics innovation for over a decade.

Dominique Pyمشاهده پروفایل

استاد

• Computer Environments for Human Learning (EIAH)
• Learner Modeling
• Cognitive Diagnosis
• +۴ مورد دیگر

Dominique Py is a Professor of Computer Science at Le Mans University since 2003, previously serving as a lecturer at the University of Rennes I from 1991 to 2003. She holds a PhD in Computer Science (1990). Her research focuses on Computer Environments for Human Learning (EIAH), emphasizing learner modeling and cognitive diagnosis, with recent interests in informatics of collapse and sustainability of EIAH systems. She currently serves as Deputy Director of the MathSTIC Doctoral School and Head of the Computer Science Master's program at Le Mans University. Her work integrates advanced computational methods with pedagogical strategies, particularly in object-oriented modeling education (e.g., the DIAGRAM system) and systemic risk education. Key themes include adaptive learning systems, teacher-student interaction metrics, and environmental implications of digital infrastructure. Her interdisciplinary approach bridges software engineering, cognitive science, and sustainability studies. Publications highlight innovative educational technologies such as UML-based learning environments and meta-indicator systems for instructional effectiveness. While no awards are explicitly listed, her sustained contributions to EIAH research and academic leadership positions reflect impactful contributions to the field. She maintains active roles in curriculum development and doctoral supervision within Le Mans University's computer science department.

• Natural Language Processing
• Information Retrieval
• Web Personalization
• +۶ مورد دیگر

Wolfgang Nejdl is a distinguished Professor at Leibniz University Hannover, working within the Faculty of Mathematics and Computer Science and affiliated with the Institute of Information Systems. With an extensive publication record spanning over two decades, he has established himself as a leading researcher in Natural Language Processing, Information Retrieval, and Web Personalization. His work bridges theoretical advances with practical applications, particularly in clinical NLP and semantic web technologies. Nejdl's research interests encompass a broad spectrum of topics including Natural Language Processing, Information Retrieval, Web Personalization, Semantic Web technologies, Machine Learning applications, Clinical NLP, and Recommender Systems. His recent work has focused on critical challenges such as clinical outcome prediction using MIMIC datasets, financial literacy evaluation of large language models, and developing resources for low-resource languages like Tigrinya. He has made significant contributions to understanding data drift in clinical applications and developing interpretable AI systems for healthcare. His publication record shows a consistent trajectory of impactful research, with recent articles demonstrating his ability to tackle emerging challenges in NLP and AI. From his foundational work on web personalization using ODP metadata to his current research on clinical NLP and low-resource language processing, Nejdl has consistently addressed important problems at the intersection of information systems and human needs. His work on stance detection incorporating toxicity and morality analysis represents innovative approaches to understanding social media discourse. Among his notable achievements are the development of the EDUTELLA P2P infrastructure based on RDF, significant contributions to boilerplate detection algorithms, and pioneering work on preventing shilling attacks in recommender systems. His research has been widely cited, reflecting its substantial impact on the fields of web science and natural language processing. Nejdl has supervised numerous students and collaborated extensively with researchers worldwide, particularly with Alexander Loeser, Jens-Michalis Papaioannou, and Paul Grundmann. His work demonstrates a consistent focus on practical applications of theoretical advances, particularly in healthcare and web technologies. He has also worked on important infrastructure projects like the L3S Research Center, contributing to the broader academic and technological ecosystem.

Jalil Boudjadarمشاهده پروفایل

دانشیار

• Cyberphysical Systems
• Digital Twins
• Embedded Systems
• +۸ مورد دیگر

Jalil Boudjadar is an Associate Professor at the Department of Electrical and Computer Engineering, Aarhus University. His research focuses on cyberphysical systems, embedded systems, and AI optimization with applications in automotive, robotics, and energy systems. Cyberphysical Systems & Digital Twins Embedded AI & FPGA Acceleration Real-Time Systems & Dynamic Scheduling Formal Methods for Safety/Security Current projects include ACCURATE (resilient manufacturing through digital twins, 2024-2026), DigiGlass (sustainable glass fiber manufacturing, 2023-2024), and Embedded AI research (2022-2025). His work bridges hardware/software co-design, machine learning, and industrial sustainability across domains like automotive, robotics, and smart manufacturing.

Timotheus Kampikمشاهده پروفایل

استادیار

• Intelligent Systems
• Automated Reasoning
• Formal Argumentation
• +۵ مورد دیگر

Timotheus Kampik is a Tenure-Track Assistant Professor at the Department of Computing Science , Umeå University , Sweden. He combines his academic work with an industry role as Principal Scientist at SAP , focusing on strategic research engagement related to intelligent processes, decisions, and transformation. Kampik's research centers on principle-based automated reasoning and the engineering of intelligent systems with applications in multi-agent systems, formal argumentation, and business process management. Kampik is a WASP Fellow supported by the Wallenberg AI, Autonomous Systems and Software Program. His work often bridges theoretical foundations with practical implementations, reflected in both his academic publications and industry contributions. He has served as co-chair for the International Workshop on Argumentation for eXplainable AI (ArgXAI) and organized sessions at major conferences like AAMAS and ECAI. Research Interests: Abstract and Quantitative Bipolar Argumentation Multi-Agent Systems Engineering Explainable AI and Human-AI Interaction Business Process Intelligence Formal Reasoning and Decision Theory Key Publications: Disagree and Commit (2025) - Argumentation-based agreements Kettle Logic in Abstract Argumentation (2024) Change in Quantitative Bipolar Argumentation (2024) Business Process Improvement with AB Testing (2024) Scientific Recognition: Best Paper Award, ICPM 2024 Best Program Committee Member Award, AAMAS 2022 Best Post-Graduate Student Paper Award, WESAAC 2020 WASP Fellowship recipient Teaching & Supervision: Lecturer for courses including Software Engineering and Artificial Intelligence at Umeå University Supervised multiple Master's and Bachelor's theses on topics like machine learning integration, human-aware planning, and deception detection Co-developed open-source agent programming libraries like JS-son

Samuel Maddenمشاهده پروفایل

استاد

• Database Systems
• Main Memory Databases
• Data Warehousing and Analytics
• +۶ مورد دیگر

Samuel Madden is the MIT College of Computing Distinguished Professor and CS Head in the Electrical Engineering and Computer Science (EECS) Department at Massachusetts Institute of Technology. He leads the Systems that Learn Initiative and co-directs both the Data Systems and AI Lab (DSAIL) and the Data Systems Group (DSG) at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). Professor Madden's research focuses on database systems, including main memory databases, data warehousing/analytics, querying video data, and machine learning for data systems. His recent projects include Palimpsest (a declarative system for optimizing AI workloads), BRAD (simplifying cloud data processing), self-organizing data containers, and VaaS (Video Analytics as a Service). His work bridges traditional database systems with emerging AI technologies, exploring how learned models can improve data management efficiency. His research has resulted in numerous influential systems including C-Store (column-oriented database), CarTel (mobile sensor network system), BlinkDB (approximate query processing), Silo (main memory transaction processing), and Datahub (versioned data platform). These projects have significantly impacted both academic research and industry database technologies. ACM Fellow (2020) SIGMOD Edgar H. Codd Innovations Award (2024) Multiple 'Test of Time' awards from VLDB, SIGMOD, SIGMOBILE, and SenSys MIT TR35 Outstanding Researcher Under 35 (2005) Sloan Fellowship (2007) NSF CAREER Award (2005) Professor Madden actively advises six current PhD students and has mentored numerous successful researchers who now hold positions at leading universities and tech companies. His lab maintains strong industry connections through the Data Systems and AI Lab, providing students with opportunities to work on real-world data challenges. As Chief Scientist of Cambridge Mobile Telematics and advisor to several database startups, he ensures his research remains grounded in practical applications while pushing the boundaries of database system design. His recent publications demonstrate a clear trajectory toward tighter integration between AI and database systems, with significant contributions in cloud data infrastructure, video analytics, and learned query optimization techniques that are shaping the next generation of data management systems.

• Artificial Intelligence
• Case-Based Reasoning
• Experience-Based Learning Systems
• +۱۲ مورد دیگر

Professor Ralph Bergmann is a distinguished academic at the University of Trier, where he holds the position of Professor of Business Information Systems since 2004. He also serves as the research group leader for Experience-Based Learning Systems (EBLS) at the German Research Center for Artificial Intelligence (DFKI) Trier branch since 2020. His academic career spans multiple institutions with appointments at the University of Hildesheim (2001-2004) and the University of Kaiserslautern (1997-2001). Dr. Bergmann's research focuses on the integration of data-oriented AI methods with semantic technologies to create hybrid AI systems. His work centers on experience-based learning systems that combine machine learning, case-based reasoning, ontologies, and knowledge graphs for modeling explicit knowledge. This research enables the redesign, adaptation, and flexible execution of processes with applications across diverse domains including Industry 4.0, construction, crisis management, service, medicine, cooking, and political argumentation. His recent publications demonstrate a strong trend toward integrating traditional case-based reasoning with modern AI techniques like large language models and knowledge graphs. The research shows increasing application in healthcare (particularly oncology and emergency response), IoT-enabled process monitoring, and argumentation analysis. His work bridges theoretical AI foundations with practical implementations across multiple industries. Professor Bergmann has led approximately 35 research projects funded by prestigious organizations including the European Union, German Research Foundation (DFG), Federal Ministry of Education and Research (BMBF), and the State of Rhineland-Palatinate. With an h-index of 40, he has authored more than 200 scientific publications including four books and 13 conference proceedings. He actively contributes to the academic community through service on editorial boards including Engineering Applications of AI and the International Journal of Intelligent Information Technologies. His leadership extends to program committees for major conferences in artificial intelligence and case-based reasoning. Professor Bergmann heads the Artificial Intelligence and Intelligent Information Systems research group at the University of Trier and leads the Experience-Based Learning Systems research group at DFKI. His teams work on multiple projects including AI-AIM (AI-based anonymization in medicine), KIAFlex (interactive AI assistance for predictive and flexible control in discharge and transition management), DZW (Digital Twin Water Management), myRPA (experience-based Robotic Process Automation), and SPELL (Semantic Platform for Intelligent Decision and Operational Support in Control Centers).

• Human-Robot Interaction
• Artificial Intelligence
• Social Robotics
• +۶ مورد دیگر

Prof. dr. M.A. Neerincx is a Professor at Delft University of Technology in the Faculty of Electrical Engineering, Mathematics and Computer Science, where he leads research in the Interactive Intelligence department. His work spans multiple interdisciplinary domains focusing on human-AI interaction, social robotics, and health informatics. His research focuses on: Human-Robot Interaction and Social Robotics Explainable AI and Inclusive Design Persuasive Technology and Behavior Change Health Informatics and Digital Health Interventions Human-AI Teaming and Collaborative Systems Cognitive Modeling and Memory Systems Neerincx's recent publications demonstrate a strong focus on ethical AI, human values in technology design, and practical applications in healthcare and emergency services. His work on human-agent teamwork, particularly around moral decision allocation and meaningful human control, has gained significant attention. In health applications, he explores digital interventions for smoking cessation, hypertension management, and cardiac health through conversational agents and social robots. His research combines technical innovation with deep consideration of psychological, social, and ethical dimensions. Through his editorial work for Interacting with Computers since 2011 and Mediamatica TU Delft since 2010, he has shaped scholarly discourse in human-computer interaction. His supervision of students like Albers, N. and Verhagen, R.S. has produced impactful research on human feedback in chatbot interventions and robot pedagogical interactions with children. His datasets reveal ongoing work in virtual coaching systems and robot-child interactions.

Julia Rayzمشاهده پروفایل

استاد

• Artificial Intelligence
• Natural Language Processing
• Knowledge Representation and Reasoning
• +۵ مورد دیگر

Julia Rayz is a Professor and Associate Department Head in the Department of Computer and Information Technology at Purdue University's Purdue Polytechnic Institute. She specializes in Natural Language Processing (NLP), Artificial Intelligence, and Knowledge Representation. Her work focuses on enabling informal human-computer communication, with a particular interest in computational humor detection and uncertainty management. Education: PhD, Computer Science and Engineering, University of Cincinnati, 2008 MS, Computer Science, University of Cincinnati, 2004 BA, Mathematics, University of Cincinnati, 1999 BS, Computer Science, University of Cincinnati, 1999 Research Interests: Natural language understanding Knowledge representation and reasoning Cognitive science Phishing detection Online predation analysis Recent grants include the TaskBot Challenge Competition (2023), SaTC-EDU AI-based Social Engineering Training (2021), and collaborative research on Robots and Sensors for Human Well-being. She leads the Applied Knowledge Representation and Natural Language Understanding Lab, advancing projects in smart home energy systems, chatbot reliability, and ethical AI.