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Scott MacDonald is the Norma K. Regan Professor in Christian Studies at Cornell University , with a joint appointment in the Department of Philosophy and affiliated roles in the Medieval Studies Program and Religious Studies Program within the College of Arts and Sciences . He holds advanced degrees from the University of St. Andrews (BD, 1981) and Cornell University (BA, 1978; PhD, 1986).
Prof. Dr. Gunther Hellmann is a Professor of Political Science at Goethe University Frankfurt, specializing in German and European foreign policy. He serves as a Principal Investigator, Board Member, and Research Field Coordinator at the Cluster of Excellence 'Normative Orders,' and has held leadership roles such as President of the World International Studies Committee (2017–2021) and Dean of the Department of Social Sciences (2004–2005). His academic contributions include co-editorship of the Journal of International Relations (ZIB) and a visiting professorship at Johns Hopkins University’s SAIS Bologna Center. Affiliations: Goethe University Frankfurt, Cluster of Excellence 'Normative Orders,' World International Studies Committee, Aspen Institute Berlin, Transatlantic Academy Education: Political Science, History, and Philosophy at Freiburg, Munich, and Washington, D.C. Research Interests: Hellmann focuses on international relations theory, foreign policy analysis, German and European foreign policy, security and peace policy, and the transformation of global and regional orders. His work emphasizes the interplay between normative expectations and practical diplomacy, with a particular interest in transatlantic relations, strategic dilemmas, and praxis theory. Publications: His recent works examine global order challenges, pragmatism in foreign policy, and the evolution of international practices. Articles from 2024 address normative expectations, economic interdependence, and post-reunification German foreign policy. Earlier works (2022–2020) analyze praxis theory, securitization, and the relevance of theoretical political science to real-world issues. Teaching: He supervises theses and exams in international relations, requiring topics related to foreign policy theory, German/EU policy, and security studies. Students must attend his colloquium and submit detailed outlines.
پژوهشگر ارشد
Thomas Grote is a Research Fellow at the University of Tübingen's Ethics and Philosophy Lab within the Cluster of Excellence 'Machine Learning: New Perspectives for Science'. His research focuses on philosophical and ethical dimensions of artificial intelligence, particularly interpretability, fairness, and reliability in medical and social contexts. He co-supervises the Carl-Zeiss-Stiftung-funded project 'Certification and Foundations of Safe Machine Learning Systems in Healthcare' and co-organizes the 'Philosophy of Science Meets Machine Learning' conference series. Research Focus Grote's interdisciplinary work bridges philosophy of science and applied AI ethics. Key areas include: Methodological foundations of AI ethics and epistemology Clinical reliability and safety of ML systems Fairness metrics in sociotechnical healthcare systems Interpretability requirements for medical AI Computational psychiatry and evolving mental health frameworks His recent publications demonstrate strong emphasis on healthcare applications, with critical analyses of reliability in foundation models, ethical paradigms for LLMs, and rethinking evaluation methodologies at the epistemology-ethics interface.
Philip J. Ethington is Professor of History, Political Science, and Spatial Sciences at the University of Southern California's Dornsife College of Letters, Arts, and Sciences. As Co-Director of the USC Center for Transformative Scholarship and Fellow of the Los Angeles Institute for the Humanities, he bridges historical scholarship with digital innovation through projects like HyperCities. Ethington's educational background includes: Ph.D. in History from Stanford University (1989) Postdoctoral Fellowship at Harvard University's Charles Warren Center (2007-2008) Getty Scholar at the Getty Research Institute (1996-1997) His research pioneers spatial theory of history through chronographs and digital cartography, examining urban evolution from Pleistocene times to present. Key interests include global metropolis studies , visual culture , and digital humanities , with focus on Los Angeles as a case study for transnational urban dynamics. Recent publications reveal consistent exploration of spatial dimensions in historical analysis, particularly through geographic institutionalism and deep historical regionalism. His work integrates cartographic innovation with theoretical frameworks to map urban change across millennia, emphasizing institutional ecology and transnational connections. Scientific recognition includes: Nomination for USC's Steven B. Sample Teaching Award (2010-2011) USC Interdisciplinary Faculty Fellowship (2004-2005) Award-winning documentary film Visual Acoustics (2009) Ethington mentors undergraduate researchers in urban history while leading major grants including MacArthur Foundation's HyperCities project ($238,000) and NEH's Digital Humanities initiative ($248,492). His funded work develops collaborative platforms for geohistorical research and digital publishing. He co-directs the USC History Lab and Center for Transformative Scholarship, fostering interdisciplinary collaboration through the Population Dynamics Lab and HyperCities consortium for participatory urban mapping.
استادیار
Elsayed Issa is an Assistant Professor in the School of Languages and Cultures at Purdue University. Specializing in Computational Linguistics and Arabic, his interdisciplinary research bridges Natural Language Processing (NLP) with Second Language Acquisition (SLA), focusing on conversational AI and speech technology for under-resourced languages. Ph.D. in Linguistics from the University of Arizona (2023) Research integrates NLP, conversational AI, and SLA methodologies Develops tools for computer-assisted pronunciation training (CAPT) Focuses on Arabic dialectology and large language models (LLMs) His work employs Transformer architectures and end-to-end machine learning to enhance language learning systems. Recent projects include ArabiBot development and dialect identification models. He specializes in speech-to-text systems , prosody modeling , and emotional speech analysis for Arabic language learning applications.
Janice McGregor is an Associate Professor of German Studies at the University of Arizona, affiliated with the College of Humanities and the Interdisciplinary PhD program in Second Language Acquisition and Teaching (SLAT). She holds a PhD in German Applied Linguistics from Penn State and previously served as Assistant Professor of German at Kansas State University (2012–2018). Her research focuses on three core areas: ideologies in language learning/teaching, discourses around intercultural learning in study abroad, and reflexive qualitative research methods in applied linguistics. She emphasizes the importance of examining social interactions and authentic language use patterns across communities. Her work critiques traditional methodologies in study abroad research, advocating for more reflexive and decolonized approaches. Notable contributions include analyzing interactions in study abroad contexts, the role of authenticity in language learning, and the ethical dimensions of global mobility programs. Current courses include GER 244 (Real Talk: Why Language Matters) and GER 508 (Approaches to German Studies). Her research methodologies often integrate autoethnography and critical discourse analysis. McGregor’s articles consistently address themes of agency, authenticity, and methodological innovation. Recent work explores ungrading practices and the use of technology in L2 learning. She actively participates in academic discourse through her contributions to conferences like the Tucson Humanities Festival and her involvement in curricular decolonization initiatives.
دانشیار
Ying Cai is an Associate Professor in the Department of Computer Science at Iowa State University, joining in 2003 after earning his Ph.D. in Computer Science from the University of Central Florida (2002). His research focuses on AI, machine learning, data science, cybersecurity, privacy protection, and database systems. He leads projects funded by the Air Force Research Laboratory, including work on authentication data structures for rank-aware queries, requiring U.S. citizenship and expertise in linear algebra/cryptography. Dr. Cai’s work spans cybersecurity (e.g., adversarial example defense, secure secret sharing), spatio-temporal systems (e.g., traffic risk prediction, check-in time modeling), and healthcare AI (e.g., cervical spine diagnosis with transformers). His publications emphasize practical applications of ML in privacy, security, and distributed systems. Professional roles include Associate Editor for Multimedia Tools and Applications (since 2009), Co-chair for COMPSAC TAIN/NCIW symposium (2014–2017), and TPC Chair for Mobilware 2010. His service includes contributions to INFOCOM, ICDCS, and MDM conferences. Current research opportunities exist for graduate students with strong programming/math skills, particularly in cryptography and linear algebra. He emphasizes interdisciplinary work, such as bridging AI with social sciences via large language models.
Prof. Ruth King is the Thomas Bayes’ Professor of Statistics at the University of Edinburgh’s School of Mathematics. Her research focuses on applying Bayesian statistical methods to ecological and public health challenges, including population estimation for hidden groups (e.g., injecting drug users, modern-day slaves) and wildlife conservation. She develops computationally efficient techniques for analyzing large datasets, such as spatial capture-recapture models for animal populations and spatio-temporal abundance models for hidden human populations. Key projects include estimating survival rates of guillemots (30,000 individuals) and improving capture-recapture models to account for animal movement dynamics. Her work bridges statistical methodology with real-world applications, emphasizing rigorous inference and scalable algorithms. King’s academic contributions span Bayesian modeling frameworks, parameter clustering in neuroscientific data, and hierarchical centering in random effects models. She collaborates with biologists and policymakers to address conservation and public health issues. Notable recent projects include incorporating memory effects into spatial capture-recapture models and developing semi-complete data augmentation for state-space models. Her interdisciplinary approach addresses challenges in ecology, epidemiology, and computational statistics, with a focus on methodological innovation for large-scale data. Her scientific contributions are highlighted through over 100 peer-reviewed articles, including work on integrated population models, animal movement dynamics, and hidden Markov models for seabird behavior. King emphasizes the importance of statistics in uncovering hidden information within datasets, advocating for robust methodologies that ‘stand up in court’ when applied to critical real-world problems.
مدرس ارشد
Gabrielle Hodge is a Senior Lecturer in Sign Language Linguistics at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. A deaf researcher, she specializes in sociolinguistics related to deaf communities, sign languages, and multimodal communication. Her work incorporates corpus linguistics, applied linguistics, and semiotics methodologies. Education: PhD in Linguistics (Macquarie University, 2014), BA (Hons) in Linguistics (La Trobe University, 2008). Teaching includes undergraduate and postgraduate courses in sign language linguistics and sociolinguistics. She chairs the University BSL Plan Implementation Group (2024-2030) and actively supervises PhD and MSc students in deaf community research. Research focuses on accessibility, sign language corpus methods, and inclusive language theory. Notable projects include the Accessibility & Inclusion Toolkit for deaf Australians and Signing to Know & Survive , exploring deaf communication resilience. She develops training for educators and interpreters, emphasizing direct access without relay systems. Key contributions include advancing corpus-driven sign language research, analyzing deaf professionals' trust in interpreters, and creating climate change resilience resources in Auslan. Her work challenges traditional linguistic frameworks to better incorporate deaf perspectives and embodied communication practices.
Maria T. Schultheis is a Professor in Drexel University's Department of Psychological and Brain Sciences and holds a joint appointment in the School of Biomedical Engineering, Science and Health Systems. As Interim Director of Clinical Training, she oversees clinical psychology education. She earned her PhD in Clinical Psychology from Drexel University in 1998. Her research focuses on neurorehabilitation, particularly applying virtual reality (VR) technology to assess and improve driving capacity and everyday functioning in individuals with neurological disorders like traumatic brain injury, stroke, and multiple sclerosis. She has pioneered VR-based driving simulators for clinical evaluation and rehabilitation. Her work integrates clinical psychology, engineering, and transportation science, addressing cognitive, physical, and behavioral demands of driving post-neurological injury. Key projects include developing driving assessment protocols for disabled populations and investigating fatigue management in MS patients. Her interdisciplinary approach has been funded by NIH, NIDRR, and the NMSS. Notable awards include the 2007 APA Early Career Award (Division 40) and recognition from the National Academy of Neuropsychology. Schultheis leads the Applied Neuro-Technologies Lab, emphasizing ecologically valid methodologies. Over 35 peer-reviewed publications and presentations at international forums highlight her contributions. She serves on the National Research Council’s Transportation Research Board, influencing policy on neurological disorders and mobility. Grants have supported projects like VR-based financial competency assessments and understanding dual-task demands in post-concussion driving. Her research also explores decision-making competency in young adults and the neurocognitive correlates of risky driving behaviors. Collaborations with biomedical engineers and transportation specialists reflect her commitment to bridging clinical practice and technological innovation for functional recovery.
دانشیار
James Zou is an Associate Professor of Biomedical Data Science at Stanford University, with courtesy appointments in Computer Science and Electrical Engineering. His research focuses on advancing machine learning methodologies for healthcare applications, emphasizing reliability, fairness, and statistical rigor. He holds a Ph.D. from Harvard University and has held positions at Microsoft Research, Cambridge University (as a Gates Scholar), and UC Berkeley (Simons Fellow). Zou leads the Stanford Data4Health hub and is a Chan-Zuckerberg Investigator. His work spans AI-driven diagnostics, spatial transcriptomics, and ethical AI frameworks. Key achievements include the EchoNet AI system for echocardiography and foundational contributions to data valuation (e.g., Data Shapley). Awards include the Sloan Fellowship, NSF CAREER Award, and Google/Tencent AI awards. Education: Ph.D., Harvard University (2014); Postdoctoral roles at Microsoft Research, Cambridge, and Berkeley. Research Interests: Machine learning for healthcare, algorithmic fairness, interpretable AI, spatial omics, and translational bioinformatics. His lab develops tools like TextGrad (PyTorch for text agents) and frameworks for evaluating medical AI systems. Recent work addresses LLMs in peer review and clinical decision-making. Grants/Grants: Supported by NSF, Sloan Foundation, Chan-Zuckerberg Initiative, and industry partnerships (Google, Amazon, Adobe). Advises on over 20 doctoral students, many contributing to high-impact papers in Nature , Science , and top conferences (NeurIPS, ICML). Leads collaborations in cardiology, oncology, and veterinary medicine. Labs/Teams: Stanford AI Lab, Stanford Data4Health, and interdisciplinary groups in precision medicine. Active in open-source projects like FrugalML and MetaViz.
دانشیار مدعو
LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.
استادیار
Dr. Darryl Dickerson is an Assistant Professor in the Department of Mechanical and Materials Engineering at Florida International University (FIU), part of the College of Engineering. His research focuses on mechanical characterization of biological interfaces, design of bioinspired materials, and advancing inclusive engineering education practices. He holds a Ph.D. (details not explicitly provided in text). Research Interests: Dr. Dickerson’s work bridges biomechanics and biomaterials engineering with social equity in education. Key areas include: Mechanical properties of biological interfaces (e.g., bone-cartilage junctions) Development of biomaterials for tissue repair using 3D printing and electrospinning Anti-marginalization strategies in engineering education, particularly for Black and Brown students Publications Trends: Recent work emphasizes dual themes: (1) Biomedical innovation through advanced material fabrication and (2) Inclusive pedagogy addressing systemic inequities in STEM education. Notable contributions include scaffold designs for osteochondral repair and frameworks for reducing microaggressions in team-based learning. Grants and Advising: No specific grants or advisees listed in the provided text. His work appears to be grant-funded through NIH/National Science Foundation pathways common in biomaterials and education research. Labs and Teams: While not explicitly stated, his research likely involves collaborations with FIU’s Center for Engineering and Computing’s diversity initiatives and biomaterials labs focusing on tissue engineering applications.
Pascale Biron is a Professor in the Department of Geography, Urban Planning and Environment at Concordia University, Montreal. She holds a Ph.D. in Geography from Université de Montréal (1995) and has been with Concordia since 1998. Her research focuses on river dynamics, stream restoration for fish habitat, flood modeling, and climate change impacts. She specializes in hydrogeomorphology, river management in agricultural watersheds, and numerical modeling of fluvial processes. Research Interests: Her work includes river restoration strategies, flood risk assessment using LiDAR technology, and the 'river freedom' concept promoting ecosystem resilience. She collaborates closely with government agencies to translate research into practical river management policies. Professional Affiliations: Canadian Geomorphology Research Group, Canadian Association of Geographers, American Geophysical Union, GRIL (Limnology Research Group), and RIISQ (Quebec Flood Risk Network). Publications & Research: Recent studies address global salmonid biomass patterns, fluvial hazard detection via machine learning, and large-scale flood modeling. She supervises 19 graduate students in Ph.D./M.Sc. programs in Geography and Environmental Studies, focusing on topics like river confluence hydraulics and agricultural stream restoration. Grants & Funding: Active projects include river dynamics in fish habitats, flood modeling for road infrastructure vulnerability, and computational fluid dynamics simulations of river flows. She also leads research on societal dimensions of river restoration and policy frameworks for flood resilience.
استادیار
Jon Hawkings is an Assistant Professor in the Department of Earth and Environmental Science at the University of Pennsylvania School of Arts & Sciences. His research focuses on biogeochemical cycles in glacial environments, particularly the role of glacial meltwater in downstream ecosystems and coastal oceans. He investigates processes such as subglacial weathering, nutrient mobilization, and contaminant transport, with fieldwork conducted in the Arctic, Patagonia, Himalayas, and Antarctica. Education: PhD in Biogeochemistry (University of Bristol, 2015); MSci in Physical Geography (University of Bristol, 2009). Research Interests: Aqueous biogeochemistry and elemental cycles Chemical weathering and mineral dissolution Contaminant transport (e.g., mercury, arsenic) Glaciology and ice sheet dynamics Environmental impacts of glacial meltwater He collaborates on projects such as the Salsa-Antarctica subglacial lake drilling initiative. His work integrates field observations, electrochemical sensing, and lab analyses to address pressing questions in cryosphere science. Awards: None explicitly listed, but active in professional societies like the American Geophysical Union. Advising/Grants: No student advisees listed; funding sources include grants for fieldwork and analytical studies in glacial systems. Labs/Teams: Leads field research groups in remote polar and mountainous regions, emphasizing interdisciplinary collaborations between geochemistry, glaciology, and environmental science.
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