جست‌وجوی استاد و پژوهشگر

Brian Vejrum Wæhrensمشاهده پروفایل

استاد

• Circular Economy
• Supply Chain Management
• Industry 4.0
• +۵ مورد دیگر

Brian Vejrum Wæhrens is a Professor at the Department of Materials and Production, Aalborg University, Denmark. He leads research in circular economy, Industry 4.0, and sustainable manufacturing systems. His work focuses on supply chain innovation, digital transformation in production, and closing material loops through advanced manufacturing technologies. Key Affiliations: Center for Industrial Production, The Faculty of Engineering and Science Projects: CIFA (Circular Factory), AAU Circular Plastics, CYCLES (Plastic Economy Transition) Research Interests: Circular Economy strategies, digital product passports, closed-loop manufacturing systems, and Industry 4.0 applications in SMEs. His work bridges theoretical frameworks with practical implementation in Danish manufacturing sectors. Publications emphasize case studies in smart production systems, automated robotics, and supply chain resilience. He actively engages with industry through advisory roles and has contributed to Danish policy discussions on sustainability and innovation.

• Human Evaluation
• Data-to-text Generation
• Natural Language Generation
• +۳ مورد دیگر

Chris van der Lee Dr. Chris van der Lee is an Assistant Professor at Tilburg University's Tilburg School of Humanities and Digital Sciences (TSHD),隶属 Department of Communication and Cognition. His work focuses on human evaluation of natural language generation systems, data-to-text generation, and reproducibility challenges in computational linguistics. He actively contributes to advancing methodologies for assessing AI-generated content and improving transparency in research practices. Research Interests Key areas include: Human evaluation frameworks for automated text generation Data-to-text generation using small datasets Reproducibility in NLP research Conversational AI and chatbot interactions Awards Best Paper Award (2019) Best Thematic Paper Award (2021) Outstanding Reviewer Recognition (2020) Collaborations Dr. van der Lee collaborates with international researchers on projects like the ReproHum initiative, investigating reproducibility barriers in human evaluations. His work also involves interdisciplinary projects, such as developing digital health assistants for medication reconciliation.

Onnig H. Dombalagianمشاهده پروفایل

استاد

• Securities Regulation
• Derivatives Law
• Financial Market Governance
• +۵ مورد دیگر

Onnig H. Dombalagian is the George Denègre Professor of Law at Tulane University, affiliated with Tulane Law School. He specializes in U.S. and international regulation of securities and derivatives markets, focusing on federal and state law interactions in corporate governance. His roles include serving as Vice Dean for Academic Affairs (2016–2020) and contributing to regulatory bodies like FINRA's National Adjudicatory Council. He holds a JD, cum laude, from Harvard Law School and an AB in Computer Science, summa cum laude, from Harvard College. Education: JD, cum laude, 1995, Harvard Law School AB in Computer Science, summa cum laude, 1992, Harvard College Research Interests: Professor Dombalagian examines regulatory frameworks for securities, derivatives, and emerging financial technologies like cryptocurrency. He explores how federal/state laws interact in corporate governance, with a focus on market integrity, self-regulatory organizations, and policy adaptation to digital finance. His work bridges legal, technological, and economic dimensions of financial markets. Key Contributions: His recent articles address cryptocurrency-based exchange-traded products (ETPs), class certification in securities litigation, digital bond trading, and automated compliance systems. These reflect a focus on regulatory challenges posed by technological innovation and market evolution. Awards: Felix Frankfurter Distinguished Teaching Award (2007) Advising & Grants: While no formal advisees are listed, his extensive regulatory roles and academic contributions imply significant mentorship in securities law and policy. His work with FINRA highlights practical engagement with industry disputes and regulatory enforcement. Labs/Teams: Engaged with Tulane Law School's research initiatives and external bodies like FINRA, contributing to adjudication and dispute resolution in financial markets.

Tai Neilsonمشاهده پروفایل

مدرس ارشد

• Journalism
• Political Economy of Digital Media
• Critical Cultural Theory
• +۳ مورد دیگر

Tai Neilson is a Senior Lecturer in Media and Major Coordinator for Journalism and Nonfiction Writing at Macquarie University's School of Communication, Society and Culture. He holds a PhD in Cultural Studies from George Mason University, an MA in Sociology from the New School for Social Research, and a BA (Honours) in Sociology and Media Studies from Victoria University of Wellington. Neilson's research explores the political economy of digital media, journalism practices, and critical cultural theory. His work investigates how digital platforms, data collection, and new capital accumulation models shape media labor. Specific interests include journalists' professional ideologies, power dynamics in media work, and intersections of technology with social justice. His research demonstrates consistent focus on digital journalism transformations, with articles examining platform regulation, AI in publishing, labor conditions, and harassment dynamics. Recent works critically analyze policy frameworks and technological impacts on news production. Faculty of Arts Teaching Award for Diversity, Inclusion and Belonging Neilson actively supervises graduate researchers in journalism, digital media, and critical theory. Current doctoral candidates include Petra Petruccio (algorithmic news curation) and Kara Ortiga (disinformation entanglements). He coordinates collaborative projects including 'AI/Journalism/Distributed Ethics' and has developed inclusive pedagogical initiatives like Australia's first autism-friendly journalism course featured on ABC's The Assembly .

Terence Broadمشاهده پروفایل

مدرس ارشد

• Generative AI
• Computational Creativity
• Artistic Applications of Machine Learning
• +۵ مورد دیگر

Terence Broad is a Senior Lecturer at the Creative Computing Institute, University of the Arts London, and Acting Course Leader of the MSc Applied Machine Learning for Creatives. He is currently completing a PhD at Goldsmiths, University of London. His work bridges art and technology, focusing on generative AI, computational creativity, and the use of machine learning as artistic materials. His research has been exhibited globally at venues like The Whitney Museum of American Art and SIGGRAPH conferences. Education: MSci Creative Computing from Goldsmiths, University of London (2012–2016). Research interests include expressive manipulation of deep generative models, exploring the latent possibilities of 'black-box' systems, and ethical considerations in AI art. He has pioneered methods like 'Network Bending' for creative model customization. Key achievements include winning the ICCV Computer Vision Art Gallery Grand Prize (2019) and serving on the SIGGRAPH jury (2021). His work is part of Geneva's contemporary art collection and has been featured in media like The Independent and Vox. Professional activities include organizing conferences like IGGI 2020 and reviewing for journals like Leonardo and ACM Transactions on Image Processing. He actively participates in exhibitions, artist talks, and academic workshops.

Morgan A. Grayمشاهده پروفایل

استاد مدعو

• Criminal Procedure
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Morgan A. Gray is an Adjunct Professor of Law at the Thomas R. Kline School of Law of Duquesne University. His research focuses on the intersection of law and artificial intelligence, particularly in criminal procedure, machine learning applications for legal document analysis, and systems to improve access to justice. He holds a B.A. from Thiel College (2016) and a J.D. from Duquesne University (2019), and is currently pursuing a Ph.D. in Intelligent Systems at the University of Pittsburgh. Education: B.A., Thiel College, 2016 J.D., Thomas R. Kline School of Law of Duquesne University, 2019 Ph.D. Candidate (Intelligent Systems), University of Pittsburgh Gray's work emphasizes interpretable machine learning models in legal contexts, including automated identification of legal factors and user-centric AI explanations. His scholarship bridges computational methods with legal practice, addressing challenges like predictive model transparency and equitable legal access. Professionally, he served as a judicial clerk for the Commonwealth Court of Pennsylvania (2019-2021) and is admitted to practice law in Pennsylvania and the Western District of Pennsylvania federal court. His research and development efforts aim to create tools that make legal systems more accessible through technological innovation.

Amna Mirzaمشاهده پروفایل

استادیار

• Language and Reading Development
• Learning Disabilities in English Language Learners (ELLs)
• Multilingual Literacy and Orthographies
• +۳ مورد دیگر

Dr. Amna Mirza is an Assistant Professor in the Faculty of Education at Mount Saint Vincent University. Her research focuses on language and reading development, learning disabilities in English Language Learners (ELLs), and the impact of genetics on conditions like Dyslexia. She collaborates with institutions like Wilfrid Laurier University and Brock University on interventions for multilingual literacy improvement. Dr. Mirza also runs teacher training programs internationally, emphasizing literacy principles. She holds a PhD in Developmental Psychology from Wilfrid Laurier University and supervises graduate students at MA/PhD levels. Her office is located in Seton 579, and she can be reached at Amna.Mirza@MSVU.CA. Her work examines reading profiles in diverse orthographies (e.g., Urdu, English) and evaluates vocabulary-based interventions for ELLs. Current projects explore how enriched literacy programs affect 2nd/3rd graders with/without learning disabilities. She also investigates AI ethics, digital transformation, and Industry 4.0 implications across governance and climate change. Education: PhD in Developmental Psychology (Wilfrid Laurier University) Research Collaborations: Wilfrid Laurier University, Brock University International Projects: Teacher training programs on literacy principles Supervision: Accepting MA/PhD students in Education Dr. Mirza’s research bridges educational psychology and technological advancements, addressing both foundational learning challenges and societal impacts of digitalization. Her recent work spans AI-driven governance systems, circular economy opportunities, and ethical challenges in AI applications.

• Evolutionary Computation
• Multi- and Many-Objective Optimization
• High-Dimensional Visualization
• +۳ مورد دیگر

Dr. Amin Ibrahim is an Associate Teaching Professor in the Faculty of Business and Information Technology at Ontario Tech University, specializing in evolutionary computation, optimization, and machine learning. He holds a PhD and MASc in Computer Engineering from Ontario Tech University and a BASc in Computer Engineering from the University of Toronto. His research focuses on multi- and many-objective evolutionary algorithms, high-dimensional visualization, and applying optimization techniques to big data challenges. He has won two Teaching Excellence Awards at Ontario Tech University (2008 and 2018) and contributed to peer-reviewed journals, book chapters, and conferences. Education: PhD in Computer Engineering, Ontario Tech University MASc in Computer Engineering, Ontario Tech University BASc in Computer Engineering, University of Toronto Research interests span evolutionary algorithms, machine learning applications, and optimization-driven solutions for complex systems. Recent work includes electric vehicle infrastructure planning and resilient supply chain design. His articles address multi-objective optimization, risk management, and sustainable transportation. Awards and Honors: Teaching Excellence Award (2008, 2018) Graduate Continuing Scholarship (2008) Graduate Entrance Scholarship (2007) Professional Involvement: Session chair at IEEE World Congress on Computational Intelligence (2016), workshops on cybersecurity and supply chain management, and contributions to IBM CASCON (2008). Active in the Business Analytics & AI Research Group, focusing on transforming data into actionable insights for business decision-making. Teaches courses ranging from cryptography to discrete mathematics and business analytics.

Sophie Borweinمشاهده پروفایل

استادیار

• Political Economy
• Political Behavior
• Public Policy
• +۶ مورد دیگر

Sophie Borwein is an Assistant Professor of Political Science at the University of British Columbia, affiliated with the Department of Political Science in the Faculty of Arts. She holds a Ph.D. from the University of Toronto (2020). Her research focuses on political economy, political behavior, and public policy, with two key areas: the impact of local contexts on political preferences and responses to economic disruption caused by technology versus other labor market shocks. She has published on Canadian social policy, immigration policy, and place identity. Her work examines how technological changes (e.g., AI, automation) influence public attitudes, policy demands, and electoral behavior. She also investigates urban-rural policy divides and municipal identity. Borwein teaches courses such as Quantitative Methods in Political Science and Advanced Topics in Canadian Politics . Her recent research highlights themes like fiscal federalism in healthcare, the political implications of AI, and the socio-economic effects of automation. She explores how information about trade-offs shapes public support for policies addressing job loss. Her work often bridges comparative politics with Canadian-specific contexts, emphasizing empirical rigor and interdisciplinary approaches. Borwein’s articles span topics from acoustic analysis of political speech to policy transformation in Canada. She collaborates on projects analyzing the microfoundations of attitudes toward AI and globalization, as well as the gender dimensions of technological change. Her research contributes to understanding how place-based identities and economic anxieties shape contemporary politics.

Christopher O'Neillمشاهده پروفایل

پژوهشگر ارشد

• Automation
• Biopower
• Facial Recognition
• +۲ مورد دیگر

Christopher O'Neill is a Research Fellow at the Alfred Deakin Institute for Citizenship and Globalisation, Deakin University. His research examines automation, facial recognition, and biopower, with emphasis on ethical, social, and political implications in contemporary societies. He holds a PhD from the University of Melbourne (2020) and has held positions at Monash University, Harvard University, and IRCAM-CNRS in Paris. His work intersects philosophy, media studies, and technology ethics. Recent publications analyze conspirituality in online scams, facial recognition in gambling regulation, pandemic automation, and Foucauldian critiques of information theory. His research addresses governance challenges in emerging surveillance technologies and automated systems.

Christopher Turnerمشاهده پروفایل

مدرس ارشد

• Business Analytics
• Digital Manufacturing
• Industry 4.0
• +۵ مورد دیگر

Dr. Christopher Turner is a Senior Lecturer in Business Analytics with a focus on research in human-centric manufacturing, Industry 5.0 automation, and explainable AI. He is affiliated with the cross-University People-centred AI Institute and the IEEE Task Force on Process Mining. His work bridges advanced technologies like the Metaverse and machine learning with practical applications in logistics and maintenance systems. Education: MSc, MSc, PhD Research interests include business analytics, data mining, machine learning, digital manufacturing, and sustainable distributed manufacturing. Recent publications emphasize the integration of extended reality (XR) in production systems and frameworks for explainable AI. With over 100 peer-reviewed publications and 5,600 citations (H-index 30), his research has significant impact. Notable projects include the AUTONOM initiative (collaborating with Network Rail) and a Knowledge Transfer Partnership (KTP) with Basemap, developing logistics management software. Teaching responsibilities include the MSc module Operations Management and Digital Services within the Operations and Supply Chain in the Digital Era and Entrepreneurship programs.

• Digital Responsibility
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Thomas Arnold is a Postdoctoral researcher at Technische Universität Darmstadt, specializing in Digital Responsibility, Natural Language Processing, and Machine Learning. His work focuses on developing automated tools for measuring corporate digital responsibility activities and detecting machine-generated text across multiple domains and languages. He actively participates in initiatives like Semeval tasks and has contributed to frameworks like M4 and M4gt-bench for evaluating black-box text generation systems. His research spans advanced motif analysis in text-induced networks, hierarchical data summarization, and privacy-preserving text rewriting (DP-rewrite). Notable projects include QUEST, an educational tool leveraging engaging storytelling for interactive quizzes, and EmpiriST, a robust tokenization and POS-tagging system for diverse text genres. Publications highlight trends in ethical AI, corporate strategy evaluation, and cross-domain NLP challenges. Recent work emphasizes transparency in AI systems and the intersection of digital ethics with corporate governance. He is affiliated with TU Darmstadt's Department of Computer Science (implied through research focus) and maintains professional profiles on LinkedIn. No specific awards or grants are listed in the provided data.

• Medical Informatics
• Machine Learning in Healthcare
• Predictive Modeling in Medicine
• +۳ مورد دیگر

Thomas Lasko is an Associate Professor holding dual appointments in the Department of Biomedical Informatics and the Department of Computer Science at Vanderbilt University. His work focuses on advancing machine learning and computational methods to address critical challenges in healthcare, particularly leveraging electronic health records (EHR) for disease prediction, risk stratification, and clinical decision-making. Lasko’s research spans areas such as predictive modeling for chronic diseases (e.g., COPD, systemic lupus erythematosus), multimodal data integration (e.g., imaging and EHR), and improving the generalizability of clinical models across healthcare institutions. His academic contributions emphasize scalable solutions for large-scale EHR analysis, including lightweight natural language processing (NLP) models for document classification and contrastive learning approaches for patient-level representation. Lasko has also pioneered methods for uncovering latent disease signatures using probabilistic independence and has developed tools like pyPheWAS for phenome-disease association studies. His work frequently intersects with clinical practice, aiming to translate algorithmic advancements into actionable clinical decision support systems. Lasko’s recent research trends highlight a focus on longitudinal data analysis, model calibration drift mitigation, and explainable AI (XAI) for enhancing trust in medical AI systems. While his articles emphasize technical innovation, they consistently ground methodologies in real-world healthcare challenges, such as optimizing lung cancer screening protocols and identifying comorbidity patterns in autoimmune diseases. Despite his prolific output, no formal scientific awards or student advising records are explicitly mentioned in the provided texts. He collaborates across disciplines, integrating expertise from computer science, biomedical informatics, and clinical medicine to tackle problems such as automated patient acuity determination and novel disease subtyping. Ongoing work includes refining multimodal fusion techniques for pulmonary nodule classification and developing synthetic data frameworks to improve model robustness in resource-limited settings.

Jake Goldenfeinمشاهده پروفایل

مدرس ارشد

• Platform Regulation
• Data Governance
• Digital Surveillance
• +۵ مورد دیگر

Jake Goldenfein is a Senior Lecturer at Melbourne Law School and a Chief Investigator in the ARC Centre of Excellence for Automated Decision-Making and Society. His research focuses on platform regulation, data governance, digital surveillance, and automated decision-making systems. He authored the monograph Monitoring Laws (2019) and has contributed to critical analyses of facial recognition technology, AI governance frameworks, and the ethical dimensions of automated systems. Before joining Melbourne Law School, Goldenfein was a Postdoctoral Research Fellow at Cornell Tech’s Digital Life Initiative. His work bridges legal scholarship with technological critique, emphasizing how law constructs data economies and shapes digital rights. Recent projects include submissions to parliamentary inquiries on AI, social media regulation, and privacy in automated systems. His research outputs span policy submissions, academic articles, and interdisciplinary studies, addressing themes such as algorithmic transparency, human-in-the-loop systems, and the intersections of labor rights with automated decision-making. Goldenfein’s writing often critiques corporate influence in digital rights advocacy and explores the societal implications of emerging technologies. Key contributions include analyses of facial recognition’s privacy risks, critiques of AI ethics commodification, and proposals for regulatory frameworks balancing innovation with accountability. His work is informed by both academic rigor and practical policy engagement, aiming to shape legal responses to technological change.

Loup Cellardمشاهده پروفایل

پژوهشگر ارشد

• Algorithms and Data Centres
• Ecological Impacts of Automated Decision-Making
• Science and Technology Studies
• +۳ مورد دیگر

Loup Cellard is a Postdoctoral Research Fellow at the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) at the University of Melbourne, affiliated with Melbourne Law School. His research focuses on the ecological impacts of data centres and automated decision-making (ADM), drawing on science and technology studies (STS) and materialist media studies. He holds a PhD from the University of Warwick (UK), where his thesis explored algorithmic transparency through ethnographic fieldwork at France's Etalab open data initiative. Before joining ADM+S, he worked as a data visualisation designer at Sciences-Po Paris and EPFL Lausanne, and as an editor for the design criticism journal Strabic . His current project examines environmental challenges of data centre cooling infrastructures in Marseille, France. He has authored policy-relevant white papers on algorithmic transparency cited in Algorithm Watch's reports and contributed to interdisciplinary collaborations across law, computer science, and social sciences. Active in cross-national research networks, Cellard's work bridges technical practices with societal implications of ADM systems, emphasizing ethical governance and policy innovation.