Dr. Joanna Goode is a Sommerville Knight Professor and Department Head of Education Studies at the University of Oregon's College of Education. Her research focuses on equity, access, and inclusion in K-12 computer science education, leveraging her experience as a former high school CS teacher. She has led multiple National Science Foundation-funded projects and co-authored the influential book Stuck in the Shallow End: Education, Race, and Computing (MIT Press, 2008/2017). Education: PhD in Education, Urban Schooling, University of California, Los Angeles (2004) MEd in Mathematics Education, University of California, Los Angeles (1998) BS in Applied Mathematics with Computing specialization, University of California, Los Angeles (1997) Joanna's research explores how educational policies and practices can transform computer science education through culturally responsive pedagogy, teacher professional development, and justice-oriented curriculum design. Her work addresses systemic barriers in urban schools, emphasizing collaboration between teachers, researchers, and policymakers to democratize computing knowledge. Recent publications highlight trends in equity-focused computing education, including justice-oriented curriculum co-design, colonialism in technology, identity-inclusive pedagogy, and the integration of societal and technical aspects in teacher training. She has pioneered electronic textiles in classrooms to promote inclusive learning environments and examines the role of AP Computer Science courses in shaping student career paths. Joanna's grants and collaborations focus on expanding K-12/university partnerships, supporting experienced CS teachers, and developing scalable models for equity-based professional development. Her work bridges the gap between policy, practice, and social justice in computing education.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۷۰۶-۷۲۰ از ۱۱٬۲۲۳ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Kanstantsin Tsedryk is an Associate Professor at the University of Waterloo's Department of French Studies, specializing in second language acquisition and French language didactics. He has extensive experience in developing internet-based French language resources and teaching full-time since 2008. Education: BA from Minsk State Linguistic University (2003), MA in French Studies from Western University (2004), PhD in French Studies from Western University (2014) His research focuses on grammatical structure acquisition in second languages, French pedagogy, and computer-assisted language learning. He has contributed to virtual French grammar presentations and interactive exercises, including co-founding one of the best French grammar websites. Publications highlight his work on clitic pronouns in French L2 acquisition, sociolinguistic variation, and online course development. While no explicit scientific awards are mentioned, his contributions to French grammar education and digital pedagogy are significant. He has taught full-time at the University of Waterloo, with expertise in virtual presentations (Flash/PDF) and self-correcting grammar exercises. His pedagogical innovations include diagrammatic grammar explanations and syntactic transformations for language learners.
Professor Toman Barsbai of the School of Economics at the University of Bristol specializes in development economics with a focus on international migration and cultural behavior. His research combines experimental and observational micro-level data from fieldwork and archives. Lead researcher at Malengo initiative Affiliated with J-PAL and French Collaborative Institute on Migration Member of Philippines' Department of Migrant Workers expert council His work examines migration's economic implications through two core themes: (1) international migration dynamics and (2) cultural behavior economics. Recent studies include labor migration's impact on democratic diffusion, financial literacy training for migrants, and cross-species behavioral convergence. Publications in Science , American Economic Journal: Applied Economics , and Journal of Development Economics demonstrate methodological rigor through randomized controlled trials. Media coverage in BBC, Science, and World Bank Development Impact Blog highlights real-world policy relevance.
Juha Kasperi Tolvanen serves as an Assistant Professor in the Department of Economics and Finance at Tor Vergata University of Rome, teaching Master's-level courses including Game Theory and Industrial Organization, Industrial Organization, Microeconomics 2, and Strategy and Information since completing his PhD at Princeton University in 2016. His academic profile bridges theoretical rigor with practical applications in economic systems. His research investigates how information asymmetries and strategic communication shape social outcomes across two domains: industrial organization examines how minor informational advantages distort market structures and cause failures, while political economy analyzes anti-establishment parties' use of ambiguity to destabilize democracies. Tolvanen uniquely combines theoretical modeling with operational data from corporate partnerships to quantify the economic costs of information flows. Recent publications (2022-2025) reveal consistent exploration of information dynamics through high-impact studies in the RAND Journal of Economics, Management Science, and American Political Science Review. His work spans decentralized markets, algorithmic recommendations, political platforms, and demand estimation, demonstrating methodological versatility through experimental designs and empirical analyses of strategic behavior in markets and elections. No scientific awards or fellowships were documented in the source materials. Tolvanen actively mentors graduate students through course instruction and research supervision, while collaborating with companies to address real-world implications of information economics. Although specific grant details remain unreported, his applied research approach leverages day-to-day corporate operational data to translate academic insights into business solutions. He operates within Tor Vergata University of Rome's Department of Economics and Finance, with collaborative networks evidenced by co-authored publications spanning international institutions. His current work extends into moral hazard measurement, historical economic analysis, and strategic communication through active working papers.
Jayneel Parekhمشاهده پروفایل
پژوهشگر ارشد
Jayneel Parekh is a Postdoctoral Researcher in the MLIA (Machine Learning and Artificial Intelligence) team at ISIR (Institut des Sciences et Industries du Réel), Faculty of Science, Sorbonne University, working with Prof. Matthieu Cord. His research focuses on understanding and enhancing large multimodal models, with applications across audio, visual, and multimodal domains. Parekh completed his PhD at LTCI, Telecom Paris under Prof. Florence d'Alche and Prof. Pavlo Mozharovskyi, researching neural network interpretability applied to image and audio data. He earned his undergraduate degree in Electrical Engineering from IIT Bombay, where he worked with Prof. Preeti Rao and Prof. Yi-Hsuan Yang on Speech-to-Singing conversion. His research spans neural network interpretability, audio processing, computer vision, and multimodal models, with emphasis on explainable AI. His work demonstrates a consistent trajectory from foundational audio/image interpretability methods to cutting-edge large multimodal model analysis, showing increasing complexity and impact across NeurIPS, ICML, and ICCV publications. L2I paper awarded 2nd prize for STIC Best Scientific Contribution 2023 Top Reviewer at NeurIPS 2023 Parekh actively contributes to the academic community through workshop organization (ICCV on Explainable Computer Vision, ELLIS Unconference on Robustness/Fairness/Explainability) and presentations at institutions including IIT Jodhpur, Deezer Research, and IBM Research. His collaborative network spans MPI Informatics, TU Darmstadt, TU Munich, and Télécom Paris.
Hans Vernooij is a Lecturer in Farm Animal Health at the Faculty of Veterinary Medicine, Utrecht University. He specializes in statistical methods and data science applications in veterinary epidemiology and animal health. His areas of expertise include: Statistical methods for veterinary research Applied Data Science in Life Sciences Epidemiological modeling Machine learning applications in animal health Vernooij has extensive experience in developing statistical models for animal health applications. His research focuses on applying advanced statistical techniques and data science methods to solve problems in veterinary epidemiology and farm animal health. He has particular expertise in Random Forest models, as demonstrated during his sabbatical at the Human Sciences Research Council in Pretoria where he developed a model for HIV status prediction based on demographic information and knowledge of HIV prevention from large-scale survey data. His publication record shows consistent contributions across veterinary epidemiology, with recent work emphasizing machine learning applications and big data analytics in animal health surveillance. The research demonstrates a clear trajectory from traditional statistical methods toward more advanced data science approaches. Vernooij is actively involved in teaching and mentoring: Teaches statistics to Bachelor students at the veterinary faculty Supports PhD candidates and Master students during data analysis phases of their research Provides statistics education for the Master of Epidemiology program at the Julius Centre of University Medical Centre
Jin Yunshuiمشاهده پروفایل
دانشیار
Jin Yunshui is an Associate Professor at the Media Experiment and Practice Teaching Center within Tongji University's School of Art and Media. He holds a PhD in Digital Design and Technology from the University of the Arts London (2022) and has extensive experience in digital animation, interactive media, and immersive technologies. Education PhD in Digital Design and Technology (2017-2022), University of the Arts London, UK MFA in Media Art and Design (2011-2012), Bauhaus University Weimar, Germany Master of Arts (2010-2013) and Bachelor of Animation (2006-2010), Tongji University Research Interests Jin's work spans virtual reality (VR) , augmented reality (AR) , serious games , cultural heritage digitization , 3D visualization , and natural user interfaces . He focuses on applying immersive technologies to education, mental health, and historical preservation. Research Trends His recent publications highlight comparative studies of VR/AR systems, immersive education applications, and ethical design of interactive media. Key themes include digital storytelling , user engagement metrics , and technological frameworks for generative art . Scientific Awards 金曦奖-创新印象艺术奖 (2022) The Rookies奖沉浸式媒体组冠军 (2019) 全国计算机设计大赛一等奖 (2009) 同济大学优秀教师 (2018) Grants & Projects Jin leads major initiatives like the Shanghai Educational Research Project on Mental Health Intervention (2024), Ministry of Education's National Golden Course in Shadow Puppetry (2023), and international collaborations with Brunel University on creative industries (2023). Labs & Teams He heads the Non-planar Imaging Laboratory at Tongji and contributes to the Forever Project with Holocaust survivor holography (2017).
Ariel Chanمشاهده پروفایل
دانشیار
- Experiential Learning
- Virtual Reality (VR)/Augmented Reality (AR) in Education
- Data Science in Engineering Education
- +۳ مورد دیگر
Ariel Chan is an Associate Professor in the Department of Chemical Engineering and Applied Chemistry at the University of Toronto, Faculty of Applied Science and Engineering. She is cross-appointed to the Institute for Studies in Transdisciplinary Engineering Education & Practice (ISTEP) and serves as the Principle Investigator of the Re-Engineering Education (Re3) Research group. Ph.D. in Chemical Engineering from Queen’s University Postdoctoral Fellowship at Agriculture Canada Registered Professional Engineer (P.Eng.) in Ontario Her research focuses on three domains: Assisted-Learning Technology (VR/AR and virtual labs), Data Analytics for Student Success (machine learning and language complexity analysis), and Sustainable Laboratory Practices (Life Cycle Analysis in biodiesel production and nutritional initiatives). She has developed over 40 inquiry-based lab projects and a virtual lab tour with immersive safety training. Recent trends in her publications include integrating VR/AR for remote experimentation , data science for equity in education , and sustainable chemical processes . Her work often combines chemical engineering principles with pedagogical innovation. Scientific Awards Northrop Frye Award (2023) Bill Burgess Teacher of the Year Award (2023) Wighton Fellowship (2022) Diran Basmadjian Teacher of the Year Award (2019) Dean’s Emerging Innovation in Teaching Professorship (2018-2021) Technology Enhanced Active Learning (TEAL) Fellowship (2018-2021) NSERC Postdoctoral Fellowship (2009-2011) Chan accepts graduate students and leads the Unit Operations Laboratory modernization project, emphasizing accessible, inclusive, and sustainable education through immersive technology and data-driven curriculum design.
Seyyed A. Hosseiniمشاهده پروفایل
استاد پژوهشی
- Multiphase fluid flow in porous media
- Geological carbon storage (CO2 sequestration)
- Reservoir engineering
- +۴ مورد دیگر
Seyyed A. Hosseini is a Research Professor at the Bureau of Economic Geology (BEG), Jackson School of Geosciences, University of Texas at Austin . His work focuses on subsurface fluid dynamics with applications to geological carbon storage (CO 2 sequestration) and underground hydrogen storage . Education: Ph.D. in Petroleum Engineering (University of Tulsa, 2008) M.S. in Biotechnology (Sharif University of Technology, 2005) B.S. in Chemical Engineering (University of Isfahan, 2002) Research Interests include: Multiphase fluid flow in porous media Pressure-pulse testing for CO 2 monitoring Reservoir engineering fundamentals Machine learning for subsurface energy projects Geomechanical impacts of fluid injection Environmental risk assessment for CO 2 and hydrogen storage Article Trends reveal his expertise in developing applied methodologies for CO 2 and hydrogen storage, emphasizing machine learning integration , 3D modeling , and fault leakage detection . Recent work explores deep learning workflows and microfluidic experiments for subsurface energy systems. Grants and Funding PI on a $1.5M DOE/NETL grant (2015) to study brine extraction for CO 2 storage pressure management Collaborative Initiatives include the SMART program for machine learning in CCS and partnerships with institutions in Mississippi, Texas, and the Gulf Coast . His research extends to laboratory experimentation following BEG's facility upgrades.
Mariela A. Rodríguez, Ph.D., is a Professor in the Department of Educational Leadership and Policy Studies at The University of Texas at San Antonio (UTSA), where she also serves as a Leadership Fellow for Student Success in the College of Education and Human Development. Her work emphasizes leadership practices that foster equitable learning environments for culturally and linguistically diverse students, with a focus on social justice and mentorship frameworks. Dr. Rodríguez has held prominent roles in national educational organizations, including Vice President of Division A at the American Educational Research Association (2021–2024) and President of the University Council for Educational Administration (2017–2018). She was appointed Co-Editor of the American Educational Research Journal in 2024 and received the Jay D. Scribner Mentoring Award (2021) for her work with graduate students and emerging scholars. Her research explores the intersection of social justice, guerrilla pedagogy, and leadership development, particularly for Latinas and immigrant faculty in academia. Recent publications (2024) include studies on horizontal mentoring and decolonial approaches to transforming schools through guerrilla pedagogy. Earlier work (2019–2017) addresses dual language immersion, English learner support, and organizational renewal in educational institutions. Awards: Jay D. Scribner Mentoring Award (2021) Leadership Roles: Co-Editor, American Educational Research Journal (2024–present) Vice President, AERA Division A (2021–2024) President, UCEA (2017–2018) Key Research Themes: Equity-Oriented Leadership Culturally Responsive Practices Mentorship for Underrepresented Groups Decolonial Educational Reform
Katharina Dobsمشاهده پروفایل
پژوهشگر
Dr. Katharina Dobs is a faculty-level researcher at Justus Liebig University Giessen, based in the Department of Psychology and Sports Science and soon moving to the Department of Mathematics & Computer Science. She leads the Visual Cognition & Computational Neuroscience (VCCN) Lab, where she integrates state-of-the-art machine-learning models with human behavioural and neural data to decipher the computations underlying rapid visual scene and face perception. Education & Career: While explicit degree details are not provided, Dr. Dobs currently holds a prestigious LOEWE Start-Professorship and an ERC Starting Grant (DEEPFUNC), underscoring her leading role in computational vision research. Research Interests: Computational principles of human visual perception Functional organisation of the visual cortex Deep neural network models of object and face recognition Integration of facial form and motion cues Temporal dynamics of face perception using MEG and fMRI Across her recent publications, a clear trend emerges toward leveraging deep convolutional networks to explain category-selective responses in the human brain, particularly for faces. Her work repeatedly demonstrates how artificial networks trained on ecologically relevant tasks spontaneously develop brain-like functional specialisation, providing computational evidence against domain-specific expertise hypotheses. Scientific Awards & Funding: ERC Starting Grant “DEEPFUNC” LOEWE Start-Professorship Supervision & Collaboration: Dr. Dobs currently supervises PhD students Elaheh Akbarifathkouhi and Hilal Nizamoglu. She co-leads multiple SFB (Collaborative Research Centre) projects, including Project S “Deep Learning: Unleashing the Potential” with Prof. Roland Fleming and Project C9 “Factors influencing categorical face processing” with Dr. Benjamin de Haas. The VCCN Lab is additionally affiliated with the CRC Cardinal Mechanisms of Perception, the research cluster The Adaptive Mind, the Center for Mind, Brain and Behavior, and the Center for Applied Computer Science and Data Science (ZAD).
Leanne M. Currie is an Associate Professor at the UBC School of Nursing , part of the University of British Columbia's Faculty of Applied Science. Her work bridges nursing practice with health informatics, focusing on technology-mediated stigma reduction, usability design, and equity in digital health platforms. Nursing Informatics Health Information Technology Virtual Health Systems Stigma Reduction in Digital Platforms Equity, Diversity, and Inclusion (EDI) in Technology Community and Rural Health Equity Her recent research explores EHR compatibility, mHealth adoption, and the social determinants of critical illness recovery. She develops tailored digital tools for patient self-management and integrates Indigenous knowledge frameworks into health informatics curricula. Her work emphasizes human-centered design, safety in clinical technology, and cross-sectoral collaboration. Dr. Currie's publications highlight partnerships with healthcare providers to address technology-related safety events, co-design of person-centered apps, and the impact of digital tools on nurse emotional exhaustion. She actively contributes to defining anti-stigma design guidelines and advancing fair classification systems in health equity.
Jim McKinley is a Professor of Applied Linguistics at University College London (UCL), specifically within the IOE - Culture, Communication & Media. His career spans 25+ years across the UK, Japan, Australia, Uganda, and the US, focusing on the interplay between globalization, language education, and higher education. Education : PhD from Victoria University of Wellington, MA and BA (Hons) from the University of Sydney and Susquehanna University, respectively. His research bridges applied linguistics and higher education studies, emphasizing English Medium Instruction (EMI), teacher training, and the teaching-research nexus. Funded by the Economic and Social Research Council (ESRC), British Academy, British Council, and John Fell Fund, he explores linguistic challenges in EMI and Content and Language Integrated Learning (CLIL). Recent publications address EMI policy in Ethiopia/Poland/Japan, academic literacy in EMI, and systematic review methodologies. He is Editor-in-Chief of System and co-Editor of Cambridge Elements: Language Teaching . Scientific Awards : Senior Fellow of the Higher Education Academy (2020-present), Honorary Research Fellow at the University of Oxford (2021-2023). Leadership Roles : Former Director of Studies for PhD in Education at UCL, Head of Programme, and leadership in academic organizations.
Steven C. Grambow is an Associate Professor and Associate Chair of Education in the Department of Biostatistics & Bioinformatics at Duke University School of Medicine. He serves as Director of Duke’s Clinical Research Training Program (CRTP) and Co-Director of the Duke Clinical and Translational Science Institute (CTSI) Workforce Development Pillar. With over two decades of experience in graduate education, he has trained more than 1,000 physician-scientists in statistical methods while developing innovative programs for clinical research education across various delivery formats. His work focuses on creating pathways into clinical and translational research through partnerships with institutions like North Carolina Central University and Durham Technical Community College. Grambow actively explores AI integration into biostatistical workflows and leads initiatives in faculty development, active learning models, and cross-disciplinary collaboration frameworks. As a collaborative statistical scientist, his research spans observational studies, randomized trials, and epidemiologic investigations addressing public health challenges including amyotrophic lateral sclerosis (ALS), post-traumatic stress disorder (PTSD), and cardiovascular risk reduction. His recent publications highlight innovations in biostatistical education, AI applications, and community-engaged research models. Scientific Awards: American Statistical Association teaching honors Duke University teaching honors Grambow has secured significant grants from NIH, Department of Defense, and University of Colorado-Denver for projects spanning statistical methods in cardiovascular disease research, patient-focused drug development resources, and multi-component lifestyle interventions. He actively mentors through Duke’s educational programs and leads quantitative collaboration units in academic healthcare settings.
- Social Informatics
- E-Government
- E-Democracy
- +۹ مورد دیگر
Georgios Lappas is a Professor of Information Technology with emphases on Social and Political Informatics at the Department of Communication and Digital Media, University of Western Macedonia. He serves as Head of the Department, Director of the Digital Media and Strategic Communication Laboratory, and Vice-Director of the MSc Programs "Public Discourse and Digital Media" and "Digital Games and Multimedia Development". He is also a member of the Regional Council for Research and Innovation of the Region of Western Macedonia. Professor Lappas holds a PhD in Computer Science and an MSc in Applied Artificial Intelligence. His academic career spans numerous research contributions and leadership roles within the university and research community. His primary research interests focus on Social Informatics, E-Government, E-Democracy, Online Politics, Human-Computer Interaction, Digital Marketing, Online Reputation Management, Web Mining, Opinion Mining, Artificial Intelligence, Web Intelligence, and Social Network Analysis. His work bridges computer science with social and political sciences, particularly examining how digital technologies impact governance, political communication, and social interactions. Professor Lappas has published extensively, with over 100 papers in international journals, conference proceedings, and book chapters. His recent work examines social media campaigns in political contexts, citizen engagement with digital government services, and the application of emerging technologies like augmented reality in various sectors. His publications appear in prestigious journals such as New Media and Society, Journal of Information Technology and Politics, Local Government Studies, and International Journal of Electronic Governance. He has served as Program Committee member in more than 130 international conferences and on editorial boards of journals including Journal of Information Technology and Politics, International Journal of Entertainment Technology and Management, and Journal of E-Government. Professor Lappas has chaired or co-chaired four international conferences, served on organizing committees for seven conferences, acted as publicity chair for two conferences, and chaired sessions at over 20 international conferences. Professor Lappas has participated in numerous national and EU-funded projects. Currently, he coordinates the "Wine Live Label Innovative Augmented Reality Applications in Wine Product Labeling" project under the "Research-Create-Innovate" program, and leads work package 5 of the "AGRO-TOUR" project focused on mixed reality applications for promoting mountain trails in Western Macedonia. He teaches courses including Human-Machine Communication, Digital Marketing and Online Entrepreneurship, Online Reputational Management, E-Government, E-Democracy and Political Campaigns on the Internet, Special Issues on Social Informatics, and Big Data and Web Intelligence.