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Dokyun LeeView profile

Associate Professor

• Generative AI
• Economics of Unstructured Data
• Human-AI Collaboration
• +5 more

Dokyun Lee is a Kelli Questrom Chair Associate Professor of Information Systems and Computing & Data Science at Boston University , where he founded the Business Insights through Text (BIT) Lab and co-leads the BU Digital Business Institute Generative AI Lab . His research focuses on the responsible application, development, and impact of AI in business, particularly analyzing unstructured data (e.g., text, images) across digital consumer management, platform design, and human-AI collaboration. Education : PhD in Operations, Information & Decisions (Wharton School), MS in Statistics (Yale University), BA in Computer Science (Columbia University) His work addresses Generative AI (unintended consequences, human-integration frictions), Economics of Unstructured Data (content extraction, marketing), and AI Regulation in contexts like advertising, market competition, and creativity. Recent articles explore LLMs in corporate risk nowcasting, generative AI's effects on online communities, and interpretable deep learning for churn management. His research trends span NLP, computer vision, and causal inference, with applications in digital marketing, e-commerce, and innovation analytics. Scientific Awards : INFORMS ISS Gordon B David Young Scholar, INFORMS ISS Sandy Slaughter Early Career, CDO Magazine Leading Academic Data Leader, AMA Don Lehmann Award 2024, MSBA Teaching Award He has secured grants from Adobe, Google, Microsoft, MassMutual, and Prudential Foundation. His labs (BIT Lab, Generative AI Lab) mentor students and collaborate on AI-driven solutions for business challenges.

Christian WinklerView profile

Professor

• Artificial Intelligence
• Natural Language Processing
• User Experience
• +4 more

Christian Winkler is Professor for AI-based UX optimization and general business administration at Nuremberg Institute of Technology since 2022. With over 25 years of experience spanning entrepreneurship, enterprise architecture, and academia, he brings substantial industry expertise to his academic role. His career includes founding multiple technology companies including an internet service provider (WWL Internet AG) that went public in 1999, Querplex GmbH through management buyout in 2003, and datanizing GmbH as an NLP SaaS provider in 2017. Professor Winkler's research focuses on practical applications of artificial intelligence in business contexts, with particular expertise in natural language processing, user experience optimization, and data-driven marketing strategies. His work bridges theoretical AI research with real-world business applications, emphasizing accessibility of complex technologies. He has published extensively on language models (including BERT and LLaMA implementations), text analysis techniques, and social media data analysis for business insights. Recent publications reveal a strong trend toward optimizing large language models for practical deployment, with significant focus on analyzing user-generated content from social platforms like Instagram and WallStreetBets. His work demonstrates how NLP can extract valuable business intelligence from unstructured data sources while making advanced AI techniques accessible to non-technical business professionals. Winkler teaches E-Commerce, International Marketing Tools - Quantitative Methods, Applied User Experience, and Communication Management, reflecting his interdisciplinary approach that combines technical AI knowledge with business administration expertise. He is an active contributor to the data science community through conference presentations at events like m3 Konferenz, MLsummit, and data2day, as well as educational content for Heise Academy on Python and NLP topics.

George ChenView profile

Assistant Professor

• Machine Learning
• Healthcare
• Information Systems
• +3 more

George Chen is an Assistant Professor of Information Systems at Carnegie Mellon University's Heinz College and an affiliated faculty member of the Machine Learning Department. His research focuses on machine learning applications in healthcare and developing countries, particularly in time series analysis and forecasting. He holds a PhD in Electrical Engineering and Computer Science from MIT, where he received the George Sprowls Award for his thesis on nonparametric methods. He also advises the AgriTech startup CoolCrop, providing farmers in India with market forecasts and cold storage solutions. Education: PhD, Electrical Engineering and Computer Science, MIT (2015) SM, Electrical Engineering and Computer Science, MIT (2012) BS, Electrical Engineering and Computer Sciences & Engineering Mathematics and Statistics, UC Berkeley (2010) Research: Chen develops nonparametric machine learning methods for healthcare (e.g., predicting patient outcomes) and agricultural forecasting (e.g., crop pricing for farmers). His work emphasizes interpretable models and statistical guarantees. He recently authored a monograph on deep learning for survival analysis and co-organized the 2023 AAAI Survival Analysis Symposium. Awards: NSF Fellowship, NDSEG Fellowship, Siebel Scholarship (PhD) MIT Goodwin Medal (2015, top teaching award) George Sprowls Award for Best Computer Science Thesis (MIT) Teaching: Teaches courses on unstructured data analytics at CMU, including graduate-level machine learning and time series analysis. Previously taught at MIT and UC Berkeley, winning teaching awards at both institutions. Professional Service: Area chair for ICML, NeurIPS, and MLHC (2025). Active in organizing conferences and workshops related to survival analysis and healthcare ML. Labs/Teams: Leads research collaborations in healthcare analytics and developing-world technology through the Heinz College and CMU's Machine Learning Department.

Swapna GottipatiView profile

Associate Professor

• Artificial Intelligence
• Data Science
• Machine Learning
• +7 more

Swapna Gottipati is a Full-time Associate Professor of Information Systems (Education) and Associate Dean (Undergraduate Education) at the School of Computing and Information Systems , Singapore Management University . Holding a PhD from SMU (2014) , she specializes in text analytics, education technology, and digital business. Current focus areas: Artificial Intelligence, Data Science, Technology-Enhanced Learning Interdisciplinary applications: Health Informatics, Social Media Analytics Research Interests span text analytics, opinion mining, curriculum analytics, and digital transformation. She applies machine learning and data mining to educational systems, business processes, and health domains. Scientific Contributions: 2016 Best Paper Award (AIS SIG-ED) 2016 MOE TRF Grant 2017-2020 Conference Best Paper Nominations 2013 Best Paper Finalist (CIKM) Academic Leadership includes: Director of Undergraduate Education Co-developer of SMU-X pedagogy Founder of MyCompetencies mobile platform Organizer of curriculum analytics workshops Grant Projects include the Learning Analytics on Qualitative Student Feedback system (MOE TRF 2016) and ICDL-funded digital literacy studies. She has delivered 12+ invited talks on digital transformation in education and industry.

• Mathematics Education
• Quantitative Research Methods
• Educational Attitudes
• +4 more

Dr. Maria Pampaka is a Professor at the University of Manchester, holding joint appointments in the Manchester Institute of Education and the Department of Social Statistics. Her research focuses on mathematics education, particularly learners’ attitudes and dispositions, advanced quantitative methods, and the application of complex systems theory. She has led projects on mathematics anxiety, gender equality measurement, and longitudinal survey analysis. Pampaka employs methodologies like Rasch modeling, missing data imputation, and agent-based simulations. She has collaborated internationally on studies ranging from regional gender gaps to tourist behavior analysis. Her work contributes to UN Sustainable Development Goals related to quality education and gender equality. Her research interests span mathematics education, quantitative research methods, and social statistics. Notable projects include a systematic review of mathematics anxiety and the development of the Extended Regional Gender Gaps Index (eRGGI). She has also explored applications of machine learning in tourism and healthcare, such as predicting revisit intentions and optimizing hospital resource allocation during the pandemic. Projects: Systematic review of mathematics anxiety, eRGGI development, analysis of sexual assault survivor support needs, and requirements discovery for smart driver assistive technologies. Key methodologies: Rasch modeling, multilevel modeling, thematic analysis, agent-based simulations, and machine learning. Collaborations: Cross-disciplinary work with social scientists, engineers, and healthcare professionals internationally. Pampaka’s work bridges education, statistics, and policy, aiming to inform equitable practices in learning and societal structures. She is engaged in impact initiatives like the Good Behavior Game evaluation and policy-informed gender equality research.

Moe Thandar WynnView profile

Professor

• Process Mining
• Data Quality
• Business Process Management
• +3 more

Professor Moe Thandar Wynn is a Co-Director of QUT's Centre for Data Science and holds a Professorship in the School of Information Systems at Queensland University of Technology (QUT). She leads the Process Science Academic Program and serves as the Academic Lead of Research for the School of Information Systems. Her expertise spans Process Mining, Data Quality, and Robotic Process Automation (RPA). Prof Wynn has attracted over AUD 6 million in research funding and holds an h-index of 41 with 8700+ citations. She is a member of the Australian Research Council College of Experts (2023–2025) and has received prestigious awards including the QLD Women in Technology Excellence Award (2024). Her research focuses on formal foundations of process modeling, verification, and automation. She has contributed to international conferences as a co-chair and program committee member, and co-edited special issues on RPA and process dynamics. Prof Wynn collaborates with industries like healthcare, insurance, and agriculture to optimize business processes through data-driven insights. Current research includes privacy-preserving process mining and quality-driven event log enhancement. Education: PhD (QUT, 2006), M. Information Technology (Research, QUT) Key Projects: Hospital Capacity Optimization, Liquid Process Model Collections, Risk-Aware BPM Supervision: Over 10 completed PhD/MSc students in process mining and analytics Awards: Multiple QUT Excellence Awards, ARC College Membership Her lab focuses on advancing process intelligence and RPA, with ongoing efforts in data quality frameworks and process mining standards (e.g., IEEE XES). She actively participates in industry partnerships, such as the CRC Food Agility project, to bridge research and real-world applications.

• Natural Language Processing (NLP)
• Machine Learning
• Later-Life Health
• +7 more

Arlene Casey is a Vivensa Foundation Senior Research Fellow at the Usher Institute within the University of Edinburgh 's College of Medicine and Veterinary Medicine. With over 18 years of industry experience in pharmaceutical research and a PhD in Natural Language Processing (NLP) from Edinburgh (2020), she specializes in developing algorithms for responsible use of unstructured health data in secure environments. Roles: NLP Programme Lead and Principal NLP Data Scientist at DataLoch Education: B.Sc (Hons) in Mathematics for Business Analysis, M.Sc (Distinction), PhD in NLP Her research focuses on applying NLP and machine learning to uncover hidden patterns in clinical free-text data, particularly for understanding aging, mental health, and risk indicators. Current projects include: Proleptic Fellowship with Dunhill Medical Trust (2023-2028, £292,090): Improving prediction models for later-life syndromes SARA Project (2023, £478,762): Risk assessment in clinical free-text De-identification of narrative EHRs (2022-2023, £170,000) She leads the MSc Data Science for Health and Social Care program and actively supervises postgraduate students. Awards include the Scottish Health Innovation Conference Best Oral Presentation (2023) and Alan Turing enrichment funding (2022).

Jieyang ChenView profile

Assistant Professor

• High-Performance Computing
• Big Data Analytics and Visualization
• Distributed Machine Learning
• +1 more

Jieyang Chen is an Assistant Professor in the Department of Computer Science at the University of Oregon's School of Computer and Data Sciences, where he leads research in high-performance computing and data-intensive scientific applications. His work bridges theoretical computer science with practical solutions for large-scale computational problems. Research Focus: Developing energy-efficient algorithms for CPU-GPU heterogeneous systems Creating fault-tolerant frameworks for scientific computing Designing advanced data compression techniques with error control Optimizing distributed machine learning workflows Dr. Chen's research portfolio demonstrates a consistent focus on performance, reliability, and energy efficiency in scientific computing. His recent publications show increasing sophistication in handling scientific data through techniques like multigrid frameworks, progressive retrieval methods, and adaptive compression algorithms that preserve critical features in climate and other scientific datasets. Education: PhD in Computer Science, University of California, Riverside (2019) MS in Computer Science, University of California, Riverside (2014) BE in Computer Science, Beijing University of Technology Dr. Chen previously worked as a Computer Scientist at Oak Ridge National Laboratory before joining the University of Oregon faculty. His collaborations span national laboratories and industry partners, contributing to real-world applications in scientific computing infrastructure.

Nicolai FabianView profile

Researcher

• Digital Transformation
• Knowledge Engineering
• Artificial Intelligence
• +4 more

Nicolai Fabian is a researcher at the Faculty of Economics and Business, University of Groningen, specializing in Digital Transformation and its intersections with organizational strategy, ethics, and technology. His work addresses critical challenges in digital governance, artificial intelligence applications, and business model innovation for SMEs. Key Research Areas: Digital Transformation, Knowledge Engineering, AI Ethics, and Digital Governance. Recent Collaborations: Frequent co-authorship with scholars like Dong, Broekhuizen, and Verhoef on topics spanning cybersecurity, digital trace data, and platform dynamics. Research Trends (2022–2025): Focuses on the dual-edged impacts of digitalization, from economic value creation in SMEs to dystopian risks in AI and cybersecurity. Explores how organizations adapt to digital disruption through strategic learning, ethical frameworks, and data-driven governance. Network & Visibility: Active in international collaborations and cited across multidisciplinary domains, reflecting his engagement with global research communities.

Babatunde AnifowoseView profile

Assistant Professor

• Environmental Impact Assessment
• Oil Spill Modeling
• Water Pollution Management
• +6 more

Dr Babatunde Anifowose is an Assistant Professor at the CEES School of The Environment. He holds a PhD in Environmental Science from the University of Birmingham (2011) and advanced qualifications in Geography and Data Processing. His expertise spans Environmental Impact Assessment (EIA), oil spill modeling, water pollution management, and the application of AI/ML in environmental decision-making. Education PhD in Environmental Science, University of Birmingham (2011) MSc in Geography (Transport & Remote Sensing), University of Lagos (2007) BSc in Environmental Science, University of Lagos (2005) Diploma in Data Processing (Computer Science), University of Lagos (1997) Research Interests Anifowose focuses on sustainable natural resource exploitation, decarbonization, and EIA innovations using AI/ML. His work addresses oil spill dynamics in fluvial-marine transition zones, EIA quality assessment, and socio-environmental equity in development projects. He also explores climate change mitigation strategies in energy systems. Awards & Recognition 2020 Sustainability and Stewardship Award (Oil & Gas Industry) EPSRC Peer Review College Member (2020–present) SPE Sustainable Development Technical Section Chair (2017–present) Advisory Roles & Grants Anifowose advises on water pollution and energy infrastructure projects. His grants include funding from the Nigerian Government (PTDF) and collaborations with JICA and the AfDB. He has supervised over 4 PhD students and actively engages in peer review for Elsevier journals. Labs & Collaborations He contributes to the Data Science and Engineering Analytics Technical Section and collaborates with institutions like the British Hydrological Society and the Transportation Research Board’s Hazardous Materials Committee.

Matthias FuchsView profile

Professor

• Sustainable Tourism
• Big Data Analytics
• Circular Economy
• +4 more

Matthias Fuchs is a tenured full professor at the Faculty of Economics and Management, Free University of Bozen-Bolzano. His research focuses on sustainable tourism, big data analytics, circular economy frameworks, and strategic management in tourism destinations. He teaches courses such as M-1 Strategic Management and is actively involved in curriculum development for e-tourism and business intelligence. His work integrates quantitative methods like clustering algorithms (e.g., k-Means, DBSCAN) with qualitative analyses to address tourism challenges. Key research areas include real-time tourism monitoring via Google Maps data, socio-economic impact assessments of tourism, and post-Cartesian ontologies challenging conventional economic paradigms. He explores creativity's role in fostering innovative regions through network science and Buddhist philosophy-influenced frameworks. Publications span topics from cultural tourism sustainability in Sweden to the application of convolutional neural networks for Instagram analysis. Despite no explicit awards listed, his contributions to e-tourism curricula and big data methodologies reflect significant scholarly influence. Fuchs advocates for transformative science to align tourism with UN Sustainable Development Goals, emphasizing ethical leadership and justice-oriented socio-economic policies. Teaching responsibilities include guiding students in tourism management, strategic leadership, and destination marketing. His interdisciplinary approach bridges business intelligence, environmental science, and philosophy to address contemporary tourism challenges.

• Digital Humanities
• Text Mining
• Artificial Intelligence in Education
• +3 more

Dr. Ahmed Taiye Mohammed holds a Postdoctoral research fellowship at Linnaeus University's Department of Cultural Sciences, Faculty of Arts and Humanities in Växjö, Sweden. He earned his Master's and PhD from Northern University of Malaysia (UUM) with a thesis on text anomaly detection. His research focuses on Digital Humanities (DH), AI applications in education, and computational thinking for non-engineers. He teaches courses like Digital Humanities Research Methods, Programming for DH, and AI in Healthcare. Key research projects include InKuiS (innovative cultural entrepreneurship) and AI for ISP (supporting academic writing via ChatGPT). He collaborates with Linnaeus University Centre for Data Intensive Sciences (DISA) on e-health initiatives. Recent publications explore AI in K-12 education, automated library classification, and text mining for archaeology. His work spans AI ethics, DH methodologies, and interdisciplinary applications of computational tools. Teaching responsibilities include over 10 courses at undergraduate/master's levels, emphasizing practical skills in DH technologies. Active in developing AI-based educational tools like CHAT4ISP-AI and exploring generative AI for academic writing support. Research also involves social media ecosystems, data mining practices, and satellite image classification using SVM techniques.

Antonio Rodríguez-SánchezView profile

Associate Professor

• Explainable AI
• Computational Neuroscience
• Deep Learning
• +4 more

Antonio Rodríguez-Sánchez is an Associate Professor in the Intelligent and Interactive Systems group at the Department of Computer Science, Universität Innsbruck (since 2019). He holds a PhD from York University (2010) and has held academic roles in Austria, Canada, and Spain. His research focuses on Explainable AI, computational neuroscience, deep learning, computer vision, robotics, and medical imaging. Education: PhD in Computer Science, York University (Canada), 2010 M.Sc. in Computer Science, Universidade da Coruña (Spain), 1998 B.Sc. in Computer Science, Universidad de Córdoba (Spain), 1996 3-year Bachelor in Biology, Autonomous University of Madrid (Spain), 1998–2001 Research Interests: His work bridges AI and neuroscience, emphasizing explainable systems, medical imaging analysis, robotics, and deep learning applications. Recent trends in publications highlight advancements in healthcare AI (REM sleep disorder prediction), robotic recycling, and computer vision for environmental monitoring. Teaching & Advising: Teaches courses like Deep Learning, Computer Vision, and Algorithms. Supervises PhD/MSc students (e.g., Safoura Rezapour-Lakani, Sebastian Stabinger). Active in EU-funded projects like PaCMan (FP7-ICT) and IntellAct. Labs & Projects: Leads research in the Intelligent and Interactive Systems group, focusing on interdisciplinary AI applications. Projects include automated avalanche detection and robotic recycling systems.

Ken BarkerView profile

Professor

• Computer Science
• Data Security
• Distributed Systems
• +7 more

Ken Barker is a Professor and Director of ISPIA at the University of Calgary's Department of Computer Science within the Faculty of Science. He holds a Ph.D. from the University of Alberta (1990) and has extensive experience in industrial computer systems and database design. His research focuses on distributed systems, data privacy/security, bioinformatics, and heterogeneous systems. He has served as Dean of the Faculty of Science, Department Head of Computer Science, and Past President of the Canadian Association of Computer Science (CACS/AIC). His work emphasizes privacy-preserving technologies, blockchain applications, and event understanding systems. Barker has published over 200 peer-reviewed papers across domains like transaction systems, spatial databases, and astro-informatics. He advocates for balancing data utility with privacy through frameworks like the Privacy Policy Permission Model. His contributions include the CHRONOS event prediction system and blockchain-based platforms for secure data storage.

Zizhou PengView profile

Assistant Professor

• Consumer Digital Engagement
• Content Marketing
• Human-AI Interaction
• +7 more

Dr Zizhou Peng is an Assistant Professor in Marketing at the University of Birmingham's Birmingham Business School, joining in September 2024. He previously served as a Lecturer in Marketing at Greenwich Business School. He holds a PhD in Business & Management, an MSc in Business Analytics from Warwick Business School, and a BSc in Geophysics from the University of Edinburgh. PhD in Business & Management, Warwick Business School, 2019–2024 MSc in Business Analytics, Warwick Business School, 2018–2019 BSc in Geophysics, University of Edinburgh, 2013–2018 His research centers on consumer digital engagement, content marketing, and Human-AI interactions, with a strong focus on analyzing unstructured data such as text, image, and video using empirical quantitative methods. He explores how creative elements in brand-generated social media content influence consumer decision-making, the role of Generative AI in enhancing content creativity, and how brand logo design affects consumer perceptions of brand competency and luxury. His work aligns with the research themes of Marketing Analytics and Behavioural Science, and Analytical Marketing Insights. Dr Peng has presented his research at major academic conferences including the Association for Consumer Research (ACR), the Society for Consumer Psychology (SCP), and the Midlands Graduate School Conference (MGS), reflecting his active engagement in the marketing and consumer behavior research community. There are no listed scientific awards or publications in the provided text. Dr Peng advises no named students in the available information and there is no mention of grant funding or specific research projects beyond his thematic interests. He is not noted as part of any formal lab or research team, though his work contributes to analytical marketing research initiatives within the department.