جست‌وجوی استاد و پژوهشگر

Deborah Palmerمشاهده پروفایل

استاد

• Bilingual Education Policy
• Dual Language Bilingual Education (DLBE)
• Teacher Preparation for Linguistically Diverse Contexts
• +۶ مورد دیگر

Deborah Palmer is a Professor and Chair in Equity, Bilingualism & Biliteracy at the University of Colorado Boulder Faculty Associate with the BUENO Center for Multicultural Education Affiliate Faculty in the Department of Ethnic Studies and CLASP Program Educational Background: Ph.D. in Education (Language, Literacy & Culture, 2004, UC Berkeley) M.A. in Education (Language, Literacy & Culture, 2000, UC Berkeley) B.A. in Anthropology with Humanities Honors (1991, Stanford) California Multiple Subject K-12 Teaching Credential (1992, Mills College) Research Interests focus on Critical analysis of bilingual education policy and politics Equity in dual language bilingual education (DLBE) programs Teacher preparation for linguistically diverse contexts Language ideologies and power dynamics in schools Intersection of language, race, and identity in educational settings Recent Publications include co-edited volumes Critical Consciousness in Dual Language Bilingual Education (2023, Routledge) Gentrification and Bilingual Education (2023, Lexington) Teacher Leadership for Social Change in Bilingual Education (2018, Multilingual Matters) and over 20 peer-reviewed articles and book chapters on topics ranging from translanguaging to anti-Black racism in DLBE. Current Research Projects include Caminos hacia el bilingüismo : High school student-led research on multilingual youth advocacy Transformative Inquiry : Teacher action research for CLD Master's students Critical Consciousness in DLBE : Multi-year ethnography on equitable bilingual education Teaching spans Undergraduate & Master's courses on bilingual methods, family engagement, and CLD research Doctoral seminars on qualitative methods and language-power dynamics

Mubashara Akhtarمشاهده پروفایل

پژوهشگر ارشد

• Natural Language Processing
• Multimodal Machine Learning
• AI Safety
• +۳ مورد دیگر

Mubashara Akhtar is a Research Fellow at ETH Zurich (ETH AI Center) and a visiting researcher at the University of Cambridge. She completed her PhD in Natural Language Processing at King's College London under Prof. Elena Simperl and Dr. Oana Cocarascu. Her research focuses on multimodal approaches for fact-checking, AI safety, and benchmarking for large language models. She has held internships at Google DeepMind and contributed to projects like the Croissant dataset documentation format. Education: PhD in Informatics (King's College London), MSc and BSc in Computer Science (TU Wien) Research Interests include multimodal machine learning, knowledge graphs, and ethical AI. Her work bridges NLP, computer vision, and data science to improve automated fact-checking systems and responsible AI practices. Key awards include the Best Short Paper Award at DEEM 2024 and King’s Research Impact Award for multimodal fact-checking. She actively contributes to conferences like NeurIPS, ACL, and EMNLP, co-leading initiatives such as the FEVER workshop and the Croissant project.

• Artificial Intelligence
• Cybersecurity
• Recommender Systems
• +۷ مورد دیگر

Eugenio DiSciascio is a Full Professor and Scientific Coordinator at the Department of Information Engineering (DEI) of the University of Bari. His research spans Artificial Intelligence, Cybersecurity, Recommender Systems, and Semantic Technologies with a focus on Trustworthy AI principles. He leads projects in healthcare informatics, user modeling through Brain-Computer Interfaces (BCI), and multimodal learning frameworks like Ducho 2.0. Key research areas include explainable AI for medical diagnosis (e.g., Alzheimer’s detection), ethical AI frameworks such as POLARIS, and adversarial defenses in recommender systems. He organizes international events like ICWE 2022 and workshops focused on cybersecurity and BCI applications. His work integrates interdisciplinary approaches, combining machine learning with neuroimaging, wearable devices, and regulatory compliance. Recent publications emphasize multimodal recommendation systems, cybersecurity in AI models, and human-centric AI development. Ongoing projects include NeuroSense (EEG-based emotion detection) and ARIEL (BCI-driven emotional support systems). He contributes to standards for trustworthy AI through frameworks like POLARIS, addressing ethical, legal, and social implications of AI technologies. DiSciascio’s lab, SisInf Lab, explores intelligent systems in software engineering, big data, and IoT. His work bridges theoretical advancements with real-world applications in healthcare, cybersecurity, and user-centric technologies.

• Artificial Intelligence
• Computer Vision
• Human-Computer Interaction
• +۵ مورد دیگر

Dian Tjondronegoro is a Professor in the Department of Computer Science at Griffith University's School of Information and Communication Technology. With over 120 publications spanning from 2002 to 2025, Professor Tjondronegoro has established a significant research presence in artificial intelligence, computer vision, and human-computer interaction. Professor Tjondronegoro's research interests center around affective computing, multimedia systems, and responsible AI development. Their work bridges technical innovation with practical applications in healthcare, public safety, and education. Recent research has increasingly focused on ethical AI implementation, privacy-preserving technologies, and sustainable computing practices, reflecting a growing concern for the societal impact of technological advancements. Analysis of the publication trends shows a clear evolution from foundational work in facial expression recognition and video processing toward more complex systems integrating AI ethics, privacy considerations, and human-centered design principles. The research demonstrates strong interdisciplinary collaboration across computer science, healthcare, and social sciences. Professor Tjondronegoro has collaborated extensively with researchers including Vinod Chandran (19 publications), Ligang Zhang (19 publications), Wei Song (18 publications), and Yi-Ping Phoebe Chen (15 publications), among others. Their work appears in prestigious venues including IEEE Transactions, ACM journals, and major conferences in multimedia and computer vision. Current research directions include the TOAST Framework for ethical AI integration, privacy-preserving video surveillance systems, and collaborative approaches to bridge knowledge gaps in AI adoption among innovation champions. These projects reflect a commitment to developing technologies that balance innovation with social responsibility.

Ivan Hernandezمشاهده پروفایل

دانشیار

• Industrial-Organizational Psychology
• Nonhuman Animal Rights
• Equity in Work Settings
• +۳ مورد دیگر

Dr. Ivan Hernandez is an Associate Professor of Industrial-Organizational Psychology at Virginia Tech, directing the Computational Outreach Lab. He holds roles as a College of Science Diversity Fellow and Data Science Faculty Fellow, and affiliates with the Center for the Future of Work Places and Practices. His research focuses on expanding labor rights to nonhuman animals, promoting workplace equity, and developing computational tools for worker support. Education: Ph.D. Social/Organizational Psychology, University of Illinois at Urbana-Champaign (2015) M.S. Applied Measurement, University of Illinois at Urbana-Champaign (2014) M.A. Social Psychology, University of Illinois at Urbana-Champaign (2012) B.S. Psychology (Minor: Statistics), University of Florida (2009) Research Interests: Dr. Hernandez advocates for nonhuman animal rights within workplaces and society, emphasizing ethical labor considerations. He also explores computational methods to address workplace disparities and improve equity through data-driven strategies. Recent work includes winning the 2023 SIOP Machine Learning Competition for innovative approaches in labor rights. Awards: 2023 SIOP Machine Learning Competition Winning Team Leader Teaching and Advising: Teaches courses like PSYC 2084 (Social Psychology) and PSYC 6014 (Quantitative Methods). Currently accepting students interested in nonhuman animal rights advocacy in workplaces. Advises via email with a specific subject line. Labs & Teams: Leads the Computational Outreach Lab, focusing on applying data science to workplace challenges and advocating for ethical labor practices.

• Artificial Intelligence
• Information Theory
• Computational Creativity
• +۳ مورد دیگر

Lav R Varshney is an Associate Professor with joint appointments in Electrical and Computer Engineering, the Siebel School of Computing and Data Science, Industrial Engineering, Neuroscience, and Digital Agriculture at the University of Illinois. His research spans artificial intelligence, information theory, computational creativity, and quantum computing. He leads projects in neuroengineering and digital agriculture through affiliations with the Beckman Institute and NCSA. With 271+ publications, his recent work includes quantum channel communication (2025), AI evaluation benchmarks (2025), and multimodal language models (2025). His research has examined societal aspects including technology adoption dynamics and privacy-enhancing technologies for public service.

Xing Xiaمشاهده پروفایل

مدرس ارشد

• Human Capital
• Education
• Health Economics
• +۳ مورد دیگر

Dr. Xing Xia is a Senior Lecturer at Yale-NUS College, affiliated with the Lee Kuan Yew School of Public Policy. Her research focuses on applied microeconomics, examining human capital, education, health, and labor market dynamics. She investigates decision-making processes related to educational and health investments, the impact of modern labor markets on educational institutions, and household/firm responses to globalization and climate change. Her work spans Singapore, the Philippines, Bangladesh, and the USA. Dr. Xia holds a B.A. in Economics and B.S. in Mathematics from Wuhan University, and a Ph.D. in Economics from Columbia University. Her academic expertise includes Chinese foreign policy, Southeast Asian security, and U.S.-China relations. She is reachable at xing.xia@yale-nus.edu.sg and maintains a professional website at xingxia.weebly.com . Dr. Xia’s research emphasizes practical policy implications, with a focus on bridging theoretical economic models with real-world applications in developing and developed nations. Her work often integrates interdisciplinary perspectives to address complex socio-economic challenges.

• Scene Graphs
• Generative Models
• Unsupervised Learning
• +۳ مورد دیگر

Azade Farshad is a Lecturer and researcher at the Technical University of Munich (TUM), affiliated with the Chair of Medical Informatics Applications under Prof. Nassir Navab. Her work focuses on advanced computer vision techniques applied to medical imaging and surgical robotics, with expertise in generative models, meta-learning, and scene graph-based systems. She actively contributes to research projects like MIGS (Meta Image Generation from Scene Graphs) and FedAP (Federated Learning for Non-IID Data), and leads initiatives in medical augmented reality and surgical data science. Her teaching portfolio includes courses such as Computer Aided Medical Procedures , Medical Augmented Reality , and Deep Learning for Medical Applications . She supervises master’s theses on topics like meta-learning, semantic image manipulation, and robust machine learning models, with notable students including Caghan Koksal and Sraddha Das. Azade is professionally active in the computer vision and medical imaging communities, serving on the executive committees of the British Machine Vision Association (BMVA) and Women in MICCAI (WiM). She co-organized workshops at CVPR and ICCV, and reviews for top conferences like CVPR, NeurIPS, and MICCAI. Her research labs include the DHM (Deutsches Herzzentrum München), IFL Lab, and NARVIS Lab, where she explores applications in generative AI, surgical data science, and vision-language systems. Key contributions include Y-Net (a medical image segmentation framework) and DisPositioNet (for semantic image manipulation).

Geoffroy Peetersمشاهده پروفایل

استاد

• Audio Signal Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Geoffroy Peeters is a Full Professor at Télécom Paris since 2018, affiliated with the Signal, Statistics and Learning (S2A) team within the Image, Data, Signal (IDS) department of the Laboratoire Traitement et Communication de l'Information (LTCI) . He received his PhD (2001) and Habilitation (2013) in audio signal processing from University Paris-VI . Education : PhD in Computer Science (2001), HDR (2013) from University Paris VI; Master in electronic engineering (1995) from Polytechnique Louvain-la-Neuve His research focuses on signal processing and machine learning (including deep learning) applied to audio and music data analysis , covering areas such as: Timbre description and audio feature extraction Singing voice detection and source separation Beat/downbeat/tempo estimation Chord/key/multi-pitch estimation Music structure/summary analysis Audio identification and auto-tagging Corpus creation and evaluation methodologies With over 200 publications and several patents, his work contributed to the ISO MPEG-7 audio standard . He has held leadership roles in academic conferences including: Co-general-chair: DAFx-2011, ISMIR-2018 Co-program-chair: ISMIR-2019 ISMIR Board member (2016-2017, 2018-2019) Elected ISMIR President (2022-2023) IEEE Task Force on Computational Audio Processing His teaching focuses on signal processing , deep learning , and music information retrieval through various projects and workshops.

Matthew Davisمشاهده پروفایل

دانشیار

• Literacy studies
• Composition theory and pedagogy
• Writing transfer
• +۴ مورد دیگر

Matthew Davis serves as an Associate Professor in the English Department at the University of Massachusetts Boston, where he also directs the Center for Society & Media and co-edits the journal Composition Studies . His academic work bridges composition theory, digital rhetoric, and writing pedagogy with a distinctive focus on knowledge transfer across contexts. His educational foundation includes a PhD from Florida State University, an MA from North Carolina State University, and a BA from the University of Kansas. These credentials underpin his expertise in writing studies and curriculum development. Dr. Davis's research centers on writing transfer —how students apply writing knowledge across academic, professional, and personal contexts—and digital rhetoric , particularly how display technologies reshape composing practices. His work explores materiality in multimodal texts , collaborative learning frameworks , and pedagogical design for transfer-oriented writing instruction. Recent publications demonstrate increasing engagement with post-truth discourse challenges and spatial design in digital composition. His publication trajectory reveals a sustained investigation into writing transfer mechanisms (2018-2022), digital rhetoric evolution (2016-2022), and programmatic curriculum design (2011-2015). Co-authoring frequently with Kathleen Yancey and other writing studies luminaries, he has developed influential frameworks like the 'Teaching for Transfer Curriculum' while examining material dimensions of composing in the digital age. No scientific awards are documented in the provided materials. As an educator, Davis teaches undergraduate courses including Freshman English, Digital Culture and Composition, and Advanced Nonfiction Writing, plus graduate seminars in composition pedagogy and digital writing. His directorship of the Center for Society & Media involves interdisciplinary collaboration on media-related projects, while his editorial role with Composition Studies reflects significant service to the field. Though specific grant details aren't listed, his extensive publication record and program development work at Florida State University indicate robust research activity. The Center for Society & Media functions as his primary research hub, fostering projects that connect writing studies with media literacy, public discourse, and digital citizenship through faculty-student collaborations and community partnerships.

• Systems Engineering
• Computational Social Science
• Natural Language Processing
• +۹ مورد دیگر

David A. Broniatowski is a faculty member in the Department of Engineering Management and Systems Engineering at the George Washington University's School of Engineering and Applied Science. His research spans systems engineering, computational social science, cognitive science, and public health, with a focus on analyzing social media to understand misinformation, decision-making, and public health communication. His research interests include systems engineering, natural language processing, fuzzy-trace theory, public health informatics, social media analytics, and misinformation detection. He investigates how people process risk and make decisions online, particularly in health-related contexts such as vaccine hesitancy and pandemic response, using computational models grounded in cognitive theory. His recent publications demonstrate a strong trend in analyzing the spread of misinformation, particularly during the COVID-19 pandemic, using NLP and machine learning. He has developed tools for measuring gist in text, detecting biases and prejudice online, and evaluating the impact of content moderation policies. His work frequently involves large-scale analysis of Twitter data and collaboration with experts in public health and computer science. Notable scientific contributions include: Developing the Twitter Social Mobility Index to measure social distancing. Creating the GisPy tool for measuring gist inference in text. Leading the creation of a large, annotated corpus of COVID-19 tweets. Applying fuzzy-trace theory to model online information spread. He has advised or collaborated with numerous researchers and students on projects related to bot detection, narrative analysis, causal reasoning in social media, and the impact of foreign influence operations. His work is supported by interdisciplinary grants focused on public health surveillance, cognitive modeling, and social computing. Dr. Broniatowski leads or is a key member of a research team that integrates systems engineering principles with data science to address complex societal challenges, particularly in the domain of public health communication and online behavior.

Hasan Kurnazمشاهده پروفایل

دانشیار

• Turkish Education
• Educational Sciences
• Reading Comprehension
• +۳ مورد دیگر

Hasan Kurnaz is an Associate Professor at the Department of Turkish and Social Sciences Education , Nizip Faculty of Education , Gaziantep University . With a career spanning institutions like Inonu University and Siirt University, his expertise lies in Turkish language education, reading comprehension, and vocabulary teaching. PhD in Turkish Education (2018), Inonu University MA in Turkish Education (2013), Inonu University BA in Turkish Language Teaching (2009), Erciyes University His research focuses on critical reading , literacy strategies , media literacy , and educational technology . He has developed assessment tools like the Critical Reading Self-Efficacy Scale and Intrinsic Reading Motivation Scale , contributing to educational measurement. Kurnaz's publications include 11 book chapters and 15 peer-reviewed articles analyzing Turkish textbooks, reading education paradigms, and PISA literacy trends. His work often explores intersections between student motivation , cognitive strategies , and educational policy in language teaching contexts. He has supervised three graduate theses on topics including EBA usage by teachers , values education in literary works , and relationship between writing attitude and skill . His conference presentations address contemporary issues like teaching Turkish to Syrian refugees and media literacy for teacher candidates .

Anja C. Rodenمشاهده پروفایل

استاد

• Thoracic Pathology
• Surgical Pathology
• Mediastinal Tumors
• +۵ مورد دیگر

Anja C. Roden, MD is a Professor at Mayo Clinic College of Medicine , Department of Laboratory Medicine and Pathology, Anatomic Pathology. Board certified in anatomic and clinical pathology, she specializes in thoracic pathology with expertise in mediastinal tumors, lung tumors, malignant mesothelioma, interstitial lung diseases, and pulmonary transplant pathology. Clinical Roles : Medical Director, Immunostains Laboratory Research : 190+ peer-reviewed manuscripts, 40+ book chapters, Co-editor of "Mediastinal Lesions" and "Pulmonary Pathology" atlases Leadership : Past President, International Thymic Malignancy Interest Group; Current Chair, Thymic Tumor Subgroup, IASLC; Vice-Chair, European Society of Pathology Education : 2009: Surgical Pathology Fellowship, Mayo Clinic 2008: Anatomic & Clinical Pathology Residency, Mayo Clinic 1992: Medical Degree, Technical University of Dresden Research Focus spans mediastinal neoplasms, malignant mesotheliomas, biomarker development (diagnostic/predictive/theranostic), interstitial lung diseases, and pulmonary transplant pathology. Recent work emphasizes AI integration in ILD diagnosis, direct patient-pathologist interactions in transplant medicine, and molecular characterization of thoracic tumors. Scientific Awards : 2017: President's Pulmonary Pathology Society Innovation Award 2020: Best Author Award, Pathology Outlines Professional Activities : Active in clinical guideline development (WHO thoracic tumors 2021), serves on multiple international committees including the European Lung Cancer Congress Program Committee, Pulmonary Vascular Disease Steering Committee, and International Mesothelioma Panel. Regularly contributes to peer-review processes across major journals.

Yuning Dingمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Educational Technology
• Automatic Essay Scoring
• +۳ مورد دیگر

Yuning Ding is a PhD Student and Research Assistant in the junior research group 'EduNLP' at the Research Center CATALPA (Center of Advanced Technology for Assisted Learning and Predictive Analytics), FernUniversität in Hagen, since January 2022. Her work focuses on Natural Language Processing applications for educational technology, specifically developing systems for automatic essay scoring and generating formative feedback for learners and summative feedback for teachers. Her educational background includes: M.Sc. in Applied Cognitive and Media Science with Specialization in Cognition & Artificial Intelligence at University of Duisburg-Essen (2017-2019) B.Sc. in Applied Cognitive and Media Science at University of Duisburg-Essen (2014-2017) B.A. in Communications at University of International Relations, Beijing (2009-2013) Ding's research centers on leveraging NLP to enhance writing education through AI-driven assessment and feedback systems. Her work bridges computational linguistics and pedagogy, with particular emphasis on argument mining, cohesion analysis, and cross-lingual content scoring. She investigates how transformer models and multi-task learning can improve the reliability and educational value of automated writing evaluation, while addressing critical issues like fairness and adversarial vulnerability in scoring systems. Her research demonstrates how NLP can provide actionable insights for both students and educators in writing development. Analysis of her publication trends reveals a strategic progression from foundational work on content scoring and error analysis toward sophisticated integrated systems. Recent work emphasizes multimodal feedback generation, argument-cohesion integration, and cross-lingual transfer, with increasing focus on real-world implementation challenges including fairness, robustness, and user experience. Her research spans multiple languages and educational contexts, reflecting a commitment to globally applicable educational technology. Within CATALPA, Ding actively collaborates across disciplines through the center's vibrant knowledge-sharing culture. She participates in project presentations and colloquia that facilitate cross-pollination of ideas between computer science, linguistics, and educational theory. Her work on the DARIUS corpus and FEAT-writing system demonstrates tangible contributions to educational resource development and interactive learning environments.

Hsing Kenneth Chengمشاهده پروفایل

استاد

• Economics of Information Systems
• Electronic Commerce
• Supply Chain Management
• +۳ مورد دیگر

Hsing Kenneth Cheng is the John B. Higdon Eminent Scholar Chair and Professor of Information Systems and Operations Management at the University of Florida’s Warrington College of Business, where he also serves as department chair. He previously served on the faculty at the College of William and Mary from 1992 to 1998. Education PhD – Computers and Information Systems, University of Rochester, 1992 MS – Business Administration, University of Rochester, 1988 MBA – Institute of Management Science, National Chiao-Tung University, 1983 BS – Electrical Engineering, National Chiao-Tung University, 1981 Research Interests Professor Cheng investigates the intersection of Internet technologies with software development and marketing, the economics of information systems, electronic commerce, supply-chain management, and high-profile information-systems policy debates such as network neutrality. Recent Research Directions His recent publications reveal a strong focus on digital platforms, blockchain-enabled financing mechanisms, the financial sustainability of IoT ecosystems, and the influence of AI and augmented reality on online shopping behavior. Collectively, these works advance understanding of platform governance, user behavior, and policy implications in the digital economy. Scientific Recognition & Service While no specific medals or fellowships are explicitly listed, Professor Cheng holds or has held senior-editorship roles at Decision Support Systems , Information Systems Research , Pacific Asia Journal of the Association for Information Systems , and the Journal of the Association for Information Systems , among others. He has been a recurring faculty mentor for doctoral consortia and research workshops in Asia and the U.S., and has chaired best-paper award committees for the Workshop on e-Business. Doctoral Advising & Industry Engagement Recent PhD graduates and current advisees include Qili Wang, Maxim A Terekhov, Xinyu Zang, Youhyun Lee, Jeongwoo (Jay) Lee, Mariia Petryk, Xiang Wan, and Yuan Zhang. He has collaborated with The World Bank and organized industry-oriented tracks at premier conferences such as the International Conference on Information Systems. Labs & Teams As department chair, Professor Cheng leads the Information Systems and Operations Management Department, fostering interdisciplinary research in digital platforms, supply-chain analytics, and policy studies. His mentorship and editorial roles further extend the collaborative network of doctoral students and international scholars working on emerging technology and market-design questions.