جست‌وجوی استاد و پژوهشگر

Dinakar Jayarajanمشاهده پروفایل

دانشیار بالینی

• Marketing Analytics
• Market Dynamics
• Quantitative Modeling
• +۶ مورد دیگر

Dinakar Jayarajan is a Clinical Associate Professor of Marketing and Director of Graduate Business Programs at the Stuart School of Business, Illinois Institute of Technology. His roles include directing the Master of Business Administration (MBA), Master of Management, and M.S. in Marketing Analytics programs. He holds a Ph.D. in Business Administration (Marketing) from USC Marshall School of Business, an M.S. in Computer Science & Engineering from IIT Madras, and a B.Tech. in Computer Science & Engineering from the University of Kerala. His research focuses on applying quantitative models to marketing challenges, particularly examining interactions between new and used product markets (e.g., automobiles, groceries, online platforms). Earlier work explored computational linguistics techniques like lexical chain-based document clustering and semantic representation. He also develops innovative pedagogical methods in business education, emphasizing student autonomy and motivation. His publication trends show a transition from early computational linguistics research (2007-2009) to current marketing analytics and market dynamics studies. He advises multiple graduate programs and oversees curricula in analytics-driven business disciplines. Contact: dinakar.jayarajan@illinoistech.edu | Office: Conviser Law Center, Room 452

• Information Retrieval
• Computational Linguistics
• Knowledge Graphs
• +۵ مورد دیگر

Pei-Chi Lo serves as Assistant Professor in the Department of Information Management at National Sun Yat-sen University (NSYSU), Taiwan, where she leads research at the intersection of information retrieval, computational linguistics, and user profiling. Her work leverages knowledge graphs and large language models to advance contextual understanding systems and social media analysis. Education: PhD in Computer Science, Singapore Management University (supervised by Prof. Ee-Peng Lim) Research Focus: Dr. Lo pioneers knowledge-based information retrieval systems including contextual path generation and knowledge graph reasoning. Her computational linguistics work spans task-specific language models, Singlish (English Creole) processing, and LLM-based knowledge extraction. User profiling research examines behavior-based modeling, adaptive crowdsourcing, and social media personality analysis through community-specific language features. Publication Trends: Her 14 publications (2017-2025) reveal evolving expertise from foundational knowledge graph embeddings to contemporary LLM integration. Recent work (2023-2025) emphasizes causal reasoning with LLMs, judicial document analysis, and temporal knowledge discovery, while maintaining core strengths in contextual retrieval and low-resource language processing. Academic Leadership: Dr. Lo advises 8 Master's students across 2024-2025 cohorts and supervises undergraduate research teams. She has secured multiple competitive grants including NSTC projects on LLM-based causal reasoning (2025-2027) and temporal knowledge discovery (2024-2026), plus institutional funding for sustainable e-commerce and elderly care technology initiatives. Laboratory: Her NSYSU research lab actively recruits students for projects spanning judicial reasoning analysis, personalized travel planning systems, and Singlish processing tools, maintaining strong industry and community engagement through practical NLP applications.

Nguyen Thanh Sonمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Multimodal Deep Learning
• Knowledge Base Systems
• +۳ مورد دیگر

Nguyen Thanh Son is a Research Scientist at the Artificial Intelligence Initiative under the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. He holds a PhD in Information Systems from the School of Information Systems, Singapore Management University (SMU), where he was advised by Associate Professor Hady Lauw. His research focuses on natural language processing, opinionated text mining, and multimodal deep learning. Previously, he completed a visiting PhD program at Carnegie Mellon University (CMU) and an internship at IBM Research Lab in Dublin, Ireland. He also earned a Bachelor of Information Systems from the University of Engineering and Technology (UET), Vietnam National University, Hanoi, with academic distinctions in research. Research Interests: His work spans natural language processing, emotion recognition, knowledge base systems, and agentic AI. He has contributed to advancements in large language models, multimodal encoding, and retrieval-augmented systems. Grants & Awards: He secured a Singapore Aerospace Programme grant (SGD 360,000) as PI and co-led an A*STAR grant (SGD 6 million). His accolades include the SMU Presidential Doctoral Fellowship and top research prizes during his undergraduate studies. Labs & Teams: Active in IHPC's AI initiatives and collaborated with CMU and IBM on projects like sentiment analysis and ontology building. His work bridges academic research and industrial applications in AI.

Bo Peiمشاهده پروفایل

استادیار

• Artificial Intelligence in Education
• Educational Data Mining
• Learning Analytics
• +۴ مورد دیگر

Dr. Bo Pei is an Assistant Professor in the Instructional Technology and Learning Design & Technology program at the University of South Florida's College of Education. He leads the VISTA Lab (Visualization, Intelligence, Systems, and Technology in Education) located on the Tampa campus, focusing on interdisciplinary research at the intersection of AI, data visualization, and educational technology. His research explores: AI-driven personalized learning tools and ethical teaching enhancements Educational data mining and learning analytics methodologies Development of trustworthy and explainable AI systems for education Data visualization techniques for actionable learning insights Equitable educational technology design for diverse learners Dr. Pei has secured significant research funding including: NSF ICorps award for AI-Driven Educational Platform Florida High Tech Corridor's Early-Stage Innovation Fund NEW RESEARCHER GRANT for Viz4Edu project Building Partnerships Across Campuses grant He currently advises seven graduate students across PhD and Master's programs in Instructional Technology, Educational Measurement, Computer Science, and related fields. The VISTA Lab team collaborates on projects involving AI tutors, educational dashboards, VR learning environments, and automated literature review systems.

Stephen Amermanمشاهده پروفایل

استاد

• American Indian History
• Urbanization of Native Americans
• Education Policy
• +۳ مورد دیگر

Stephen Amerman is a Professor of History at Southern Connecticut State University, specializing in American Indian history with a focus on 20th-century urbanization, education, and Connecticut regional studies. He holds a PhD from the University of Utah/Arizona State University and has taught at Southern since 2003. His work bridges historical scholarship and public education, emphasizing Indigenous perspectives in urban contexts. Education Background: Grew up in Des Moines, IA; earned undergraduate degree in North Carolina; completed graduate studies in Utah and Arizona. Research Interests: Amerman’s research examines Native American experiences in urban schools, tribal sovereignty issues, and the intersection of education policy with cultural preservation. His award-winning monograph Urban Indians in Phoenix Schools, 1940-2000 (Univ. of Nebraska Press, 2010) analyzes federal relocation programs’ impact on Native communities. He actively engages in reviewing scholarly works on Indigenous topics for top journals like the Journal of American History and Western Historical Quarterly . Presentations: Active in academic conferences including the Western History Association and Native American and Indigenous Studies Association. Recent talks include discussions on Mohegan cultural festivals and urban Native identity in Connecticut schools.

• Audio Signal Processing
• Music Information Retrieval
• Natural Language Processing (NLP)
• +۳ مورد دیگر

Panagiotis G. Zervas is an Associate Professor at the Department of Electrical and Computer Engineering, University of Peloponnese (since 2020). His expertise spans audio signal processing, music information retrieval, and natural language processing for knowledge extraction. He teaches courses including Signals & Systems, Digital Signal Processing, and Machine Learning. His research focuses on AI-driven applications in sound analysis, music feature extraction, and multimodal information processing. Education: PhD (2007) in Electrical Engineering from the University of Patras, specializing in Greek prosody modeling for text-to-speech systems. Previous roles include Assistant Professorships at Hellenic Mediterranean University (2015–2020) and Technical Educational Institute of Crete (2008–2015). Research Interests: Natural Language Processing (NLP) for text analysis and large language models (LLMs) Audio signal processing, voice analysis, and embedded systems AI applications in job market analytics and skills frameworks Machine learning for music information retrieval Notable Projects: Principal Investigator in EU projects EU-ALMPO (2025–), Train4Blue (2025–), GROWTH4BLUE (2024–), and MICROIDEA (2024–) World Bank consultant (2023–) for AI-driven employment systems in Greece and Pacific Islands Publications in journals like 'Acoustics' and conferences like WAC 2022 and Forum Acusticum 2023 Office: Building K, Office K2.07 | Contact: pzervas@uop.gr

Július Hlaváčمشاهده پروفایل

استادیار

• Software Engineering
• Business Intelligence
• Data Mining
• +۳ مورد دیگر

Július Hlaváč serves as an Assistant Professor at the Faculty of Informatics of the Pan-European University. His work integrates theoretical knowledge with practical applications in software engineering, business intelligence, and enterprise IT architecture. Position: Assistant Professor Workplace: Institute of Applied Informatics Phone: +421 2 6820 3685 Email: julius.hlavac@paneurouni.com Hlaváč emphasizes bridging academia and industry through teaching subjects like IT Project Management , Software Engineering , and Enterprise Architecture . He has supervised over 60 diploma theses at the university. His research spans Business Intelligence , Data Mining , and Information Security , focusing on extracting hidden patterns from datasets to support decision-making. Recent publications with Juraj Štefanovič (2020) and collaborators (e.g., Ružický et al., 2020) demonstrate expertise in machine learning, medical data visualization, and enterprise IT systems. Project: GAAA Challenge (Project number: GAAA 12/2018) Laboratory: Think Future Laboratory Miscellaneous achievements: PRINCE2 Foundation certification. Active in university governance as a member of the Academic Senate and representative on the Council of Universities.

• Indigenous history
• settler colonial studies
• critical race studies
• +۵ مورد دیگر

Kristin Burnett is a Professor in the Department of Indigenous Learning at Lakehead University, where she has worked since transferring from the Department of History in August 2012. A settler scholar, she holds a PhD from York University (2006), following BA and MA degrees in History from the University of Calgary, and completed an SSHRC post-doctoral fellowship at the University of Alberta. BA and MA in History, University of Calgary PhD, York University (2006) Burnett's research centers on Indigenous history, settler colonial and critical race studies, women and gender history, and the social history of health and medicine. She critically examines systemic barriers in healthcare access, social services, and food systems for Indigenous communities in northern Ontario, with particular focus on how colonial structures perpetuate health inequities. Her work consistently bridges academic research with policy advocacy. Analysis of her 15 most recent publications (2018-2024) reveals three dominant thematic clusters: Indigenous food sovereignty (examining traditional foods, land access, and colonial disruption of food systems), healthcare access barriers (including identification systems and vaccine hesitancy), and institutional complicity in colonial violence (particularly regarding Residential Schools and Indian Hospitals). Her methodology increasingly emphasizes community-engaged research and policy-relevant scholarship. Burnett co-founded the Social Science and Aboriginal Research Group (SSARG), dissolved in 2023, and frequently collaborates with Indigenous communities and scholars like Shannon Stettner. She secured notable research funding including an SSHRC post-doctoral fellowship and a YWCA Canada contract for historical research on Residential Schools, though the latter was severely underfunded ($14,500). Her July 2025 media coverage on identification barriers in healthcare demonstrates ongoing policy impact. Her landmark 2022 report "The Role of YWCA Canada in Canada's Residential Schools and Indian Hospitals" faced a two-year embargo before public release in December 2024, highlighting institutional resistance to confronting uncomfortable colonial histories. Burnett maintains that ethical research requires centering Indigenous leadership and adequately funding community-driven work.

Ken Satohمشاهده پروفایل

استاد

• Artificial Intelligence (AI) and Law
• Logical Foundations of AI
• Juris-Informatics
• +۶ مورد دیگر

Ken Satoh is a full Professor at the National Institute of Informatics (NII) and Sokendai (The Graduate University of Advanced Studies), Japan. He leads the Center for Juris-Informatics within the Joint Support-Center for Data Science Research (ROIS-DS). Previously, he worked at Fujitsu (1981-1995) and was an Associate Professor at Hokkaido University until 2001. He holds a law degree from the University of Tokyo (2006-2009) and passed the Japanese bar exam in 2017. Roles: Director of Center for Juris-Informatics, Principal Investigator in multiple AI/Law projects Research Focus: Juris-informatics (merging informatics and law), logical foundations of AI, legal debugging, and compliance mechanisms for AI systems His work bridges AI and legal systems, including developing the PROLEG framework for legal reasoning and organizing international workshops like JURISIN. Key contributions include applying logical inference to detect legal conflicts in algorithmic governance systems and advancing AI ethics through compliance checks with regulations like GDPR. He has authored over 130 publications, including works on legal norm reasoning, multi-agent systems, and formal methods in law. His research group collaborates globally, hosting competitions like COLIEE to advance legal AI technologies.

Barbara Parkerمشاهده پروفایل

دانشیار

• Gender Studies
• Food Security
• Intersectionality
• +۴ مورد دیگر

Barbara Parker is an Associate Professor in the Department of Sociology at Lakehead University since August 2014. Her research focuses on gender, food systems, health equity, intersectionality, and critical dietetics. She holds a PhD from Charles Sturt University (Australia), an MA from Lakehead University, and a BA from the University of Manitoba. Dr. Parker's work integrates feminist theory with food studies, emphasizing intersectional analysis of marginalized groups' food experiences. She examines topics like Indigenous food sovereignty, urban Indigenous food access, and anti-colonial research methodologies. Her book Feminist Food Studies explores these themes through critical lenses. Her recent publications (2020–2024) address food pedagogy, pandemic governance, and professional socialization in dietetics education. She has conducted community-based research in Northwestern Ontario, focusing on urban Indigenous communities and school food environments. Notable research collaborations include the Recipe Exchange Project and policy analyses on wild game access for Indigenous women. Her work bridges academia with community action through participatory frameworks.

• Thermodynamics of radionuclides
• Actinide chemistry
• Nuclear waste repositories
• +۷ مورد دیگر

Prof. Dr. Vinzenz Brendler serves as Head of the Department of Thermodynamics of Actinides at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) Institute of Resource Ecology. He also holds an Honorary Professor position in Radiochemistry at the University of Applied Science Dresden (HTW) since 2008. His career at HZDR has spanned over three decades, progressing from Junior Scientist (1993-2000) to his current leadership role, with previous positions including Head of Department Surface Processes (2013-2021) and Acting Director of the Institute of Resource Ecology (2012-2013). Dr. Brendler received his Ph.D. in natural sciences from TU Bergakademie Freiberg in 1993 with distinction ("Magna cum laude") and completed his Diploma in Chemical Engineering there in 1989 with "Excellence" honors. His doctoral work focused on water activities in ternary salt systems, while his diploma research examined reaction models for activity data in lithium-zinc chloride systems. His research focuses primarily on the thermodynamics of radionuclides in aqueous solutions and at mineral-water interfaces, with direct applications to nuclear waste repositories. He possesses extensive expertise in experimental capabilities using modern analytical spectroscopic methods, including laser-induced fluorescence and X-ray absorption techniques. His work encompasses geochemical modeling, radionuclide migration studies, sorption processes, risk assessment methodologies, and database development for environmental modeling. Analysis of his recent publications reveals a consistent focus on actinide and f-element chemistry, particularly uranium, europium, and technetium systems. His research employs sophisticated combinations of experimental methods including spectroscopy, batch experiments, and computational modeling to understand complex geochemical processes relevant to nuclear waste disposal. Key themes include surface complexation modeling, redox processes, mineral-water interactions, and thermodynamic characterization under repository-relevant conditions. Agricola medal of the TU Bergakademie Freiberg for outstanding diploma work As an Honorary Professor at HTW Dresden, Dr. Brendler contributes to radiochemistry education while maintaining an active research program. His extensive publication record (over 100 papers) demonstrates significant contributions to the field of nuclear waste management. He serves on multiple advisory boards including the Technical Direction Team of the NEA Sorption Project and the Governing Board of EU framework projects. His research is supported by numerous national and international funding programs including EU R&D framework programs and German federal initiatives. Dr. Brendler leads research within the Thermodynamics of Actinides department at HZDR, collaborating with various research teams across multiple facilities including the Rossendorf Beamline at ESRF. His work integrates experimental, theoretical, and modeling approaches to address complex challenges in nuclear waste disposal safety assessment.

Padmini Srinivasanمشاهده پروفایل

استاد

• Information Retrieval
• Natural Language Processing
• Text Mining
• +۱۲ مورد دیگر

Padmini Srinivasan is a Professor in the Department of Computer Science at the University of Iowa, affiliated with the College of Engineering. Her work bridges computer science, informatics, and social applications through advanced research in information retrieval, natural language processing, and data mining. Research Interests: Her research focuses on Information Retrieval & NLP , Text and Web Mining , Biomedical Text Mining , Privacy/Security & Censorship , Social Media Analytics (particularly in political and health belief contexts), and Crowdsourcing & Games . She leads the Text Retrieval & Text Mining Group , fostering interdisciplinary research involving machine learning, human computation, and real-world data challenges. Publication Trends: Her recent work appears in top-tier venues such as SIG-IR, KDD, WSDM, ICWSM, EMNLP, JASIST, and PLOS One, reflecting sustained contributions to both foundational and applied aspects of data science. These publications span topics from ranking optimization and query modeling to social dynamics, health informatics, and ethical AI. Scientific Awards: No specific awards were mentioned in the provided text. Advising and Grants: She has advised numerous graduate students including Osama Khalid, Ingroj Shrestha, Asad Mahmood, Jonathan Rusert, and others. While grant details are not listed, her publication record in premier venues suggests consistent external funding and collaborative research activity. Labs and Teams: She leads the Text Retrieval & Text Mining Group , which conducts cutting-edge research in search technologies, text analysis, and social media understanding, often integrating crowdsourcing and game-based methods for data collection and evaluation.

Gyunam Parkمشاهده پروفایل

پژوهشگر

• Process Mining
• Action-Oriented Process Mining
• Object-Centric Process Analysis
• +۱۲ مورد دیگر

Gyunam Park is a Research Group Lead and Process and Data Scientist at Fraunhofer FIT and a Scientific Assistant at the Chair of Process and Data Science at RWTH Aachen University, a leading institution in computer science and engineering. He is actively involved in both research and teaching, contributing to the advancement of process mining, data science, and artificial intelligence. His work bridges academic research and industrial applications, particularly in SAP ERP systems and digital twins of organizations. Research Interests: Gyunam Park’s research focuses on Action-Oriented Process Mining (AOPM) , Object-Centric Process Analysis , and Responsible Machine Learning . He aims to transform process mining insights into actionable management decisions, ensuring transparency, fairness, and compliance. His work enables organizations to monitor operational constraints, generate corrective actions, and assess their impact using data-driven methods. Publication Trends: His recent publications emphasize object-centric approaches to process mining, predictive monitoring, constraint checking, and integration with AI planning. There is a strong trend toward preserving structural information in event logs, improving machine learning performance, and applying these techniques to real-world systems like SAP ERP and after-sales service processes. Scientific Awards: No awards are explicitly mentioned in the provided text. Advising and Grants: While no formal students are listed, Gyunam Park leads research projects and collaborates with industry partners such as Samsung Electronics and SAP. His projects involve root cause analysis, resource optimization, and educational data mining. He has developed open-source tools like ProAct and OCPA , indicating active grant or institutional support for software development and research dissemination. Labs and Teams: He is a core member of the Process and Data Science (PADS) group led by Prof. Wil van der Aalst at RWTH Aachen University and leads a research group at Fraunhofer FIT. These teams focus on cutting-edge research in process mining, data science, and AI, with strong industry collaborations and regular contributions to top conferences and journals.

Zahra Batool Naqviمشاهده پروفایل

مدرس

• Meat Science
• Livestock Health and Production
• Meat Tenderness
• +۱۱ مورد دیگر

Dr. Zahra Batool Naqvi is a Lecturer in Livestock Health and Production at the School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University (CSU). She holds a DVM and a PhD in Meat Science from CSU, awarded in 2022 under the John Allwright Fellowship from the Australian Centre for International Agricultural Research (ACIAR). Her academic and research work is centered on improving meat quality, particularly for low-value beef cuts. Her educational background includes: DVM (Doctor of Veterinary Medicine) PhD in Meat Science, Charles Sturt University (2022) Dr. Naqvi's research interests focus on meat science, livestock health, and agricultural extension. She investigates mechanisms to enhance meat tenderness, shelf life, and sensory characteristics using natural methods such as ginger protease (zingibain) and sous vide cooking. Her work integrates food technology with farmer engagement, particularly in rural Pakistan, where she has led extension projects to improve beef value chains. Her recent publications (2021–2024) reveal a strong focus on meat quality preservation, lipid and microbial stability, and innovative processing techniques. Themes include the use of natural antioxidants, plant-based enzymes, and fortified food products, reflecting a multidisciplinary approach bridging veterinary science, food science, and agricultural development. Dr. Naqvi has been recognized for her outreach, particularly her tribute to rural women in agriculture, highlighted in university press. While no formal scientific awards are listed, her work has generated significant citations and engagement. She actively teaches meat and veterinary science subjects and has contributed to major research projects funded by Meat and Livestock Australia (MLA) and ACIAR. Her work emphasizes knowledge transfer to farmers and end-users, combining laboratory research with field application. Though no specific lab or team name is mentioned, her collaborations include researchers from CSU and international partners, focusing on meat science and rural development initiatives.

Mingjun Zhongمشاهده پروفایل

مدرس

• Machine Learning
• Computational Statistics
• Non-intrusive Load Monitoring
• +۱۲ مورد دیگر

Dr. Mingjun Zhong is a Lecturer in the School of Natural and Computing Sciences at the University of Aberdeen. His research focuses on machine learning and computational statistics with applications in healthcare, energy systems, and medical imaging. He is actively engaged in teaching and academic service, including editorial roles in prominent journals. Position: Lecturer Institution: University of Aberdeen School: School of Natural and Computing Sciences Email: mingjun.zhong@abdn.ac.uk Dr. Zhong's research interests center on probabilistic and statistical machine learning methodologies applied to real-world data. He works on healthcare data analysis, non-intrusive load monitoring (NILM), spectroscopy, EEG/fMRI, and energy disaggregation. His methodological expertise includes variational inference, Markov chain Monte Carlo, Bayesian matrix factorization, and deep learning. He has developed lightweight and efficient neural network models for applications in medical imaging and smart grids. The most recent publications reflect a strong trend in applying advanced machine learning techniques—particularly deep learning, self-supervised learning, and capsule networks—to diverse domains such as medical diagnostics, energy disaggregation, and clinical decision support. There is a clear emphasis on developing efficient, interpretable, and robust models for real-world deployment, often addressing challenges like class imbalance, domain adaptation, and data scarcity. Scientific recognition includes: Fellow of the Higher Education Academy (FHEA) Associate Editor, Neural Processing Letters Review Editor, Frontiers in Applied Mathematics and Statistics Regular reviewer for top-tier journals and conferences in AI and machine learning Grant reviewer for multiple funding bodies Dr. Zhong advises a number of students, as evidenced by co-authorships on numerous publications. His research is supported by academic collaborations and likely external grants, though specific funding details are not mentioned. He teaches courses in Robotics, Machine Learning, and Knowledge Representation and Reasoning, contributing significantly to the curriculum in computing sciences. He is involved in interdisciplinary research, particularly through projects like ARCHERY (Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY), which integrates AI into orthopaedic care. His work bridges computer science, statistics, and domain-specific applications, demonstrating a strong commitment to impactful, application-driven research.