جست‌وجوی استاد و پژوهشگر

• Gender Studies
• Postcolonial Criticism
• Media Studies
• +۶ مورد دیگر

Prof. Dr. Sandra Ponzanesi is a full Professor at Utrecht University's Department of Media and Culture Studies, leading the Graduate Gender Programme. Her interdisciplinary research bridges postcolonial theory , gender studies , media studies , and digital humanities , with a focus on Italian colonial history, European migration, and postcolonial cinema. PhD in Comparative Literary Studies and Gender Studies (Utrecht University) MA in English and Commonwealth Studies (University of Sussex, UK) MA in Modern Languages and Literature (University of Bologna, Italy) Her work explores how digital technologies reshape European integration through digital diasporas and connected migrant networks. Recent projects like "Virtual Reality as Empathy Machine" examine VR's role in humanitarian communication, while the completed ERC-funded CONNECTINGEUROPE project investigated digital migration's impact on citizenship. Key publication themes include postcolonial cultural industries , transnational women intellectuals , and digital affective belonging . She has co-edited 10+ volumes and guest-edited special issues in Popular Communication , Transnational Screens , and Postcolonial Studies . ERC Consolidator Grant (2014) NWO Internationalization Grant EU 7th Framework Program grant As founder of Utrecht's Postcolonial Studies Initiative and organizer of international conferences, she connects scholars across migrant communities , activist networks , and digital humanities to reimagine Europe's postcolonial future.

• Natural Language Processing
• Machine Learning
• AI Ethics
• +۵ مورد دیگر

Arnav Arora is a PhD Fellow at the Department of Computer Science , University of Copenhagen (DIKU), specializing in Natural Language Processing . His work focuses on ethical AI, bias detection, and societal impacts of language models. Email: aar@di.ku.dk Location: Universitetsparken 1, 2100 København Ø Arnav's research explores fine-grained value alignment in language models, harmful content detection , and cross-cultural differences in AI responses. His work bridges technical NLP advancements with social responsibility, including dual use ethical frameworks and community value analysis . Key publication trends include: 2025: Bias mitigation through BiasGym framework 2024: Factcheck-Bench benchmark development 2023: Thorny Roses dual use analysis 2022: Cross-cultural value probing methods 2020: Multi-hop fact checking systems Arnav contributes to the Software, Data, People & Society (SDPS) section, collaborating with interdisciplinary teams on projects involving language model evaluation and societal impact mitigation . His work often addresses real-world AI deployment challenges through academic-industry partnerships.

Raul Castro Fernandezمشاهده پروفایل

استادیار

• Data Management
• Data Science
• Databases
• +۶ مورد دیگر

Raul Castro Fernandez is an Assistant Professor of Computer Science at the University of Chicago, where he researches data ecology, a concept he created to study how data shapes our world and how we can shape it back. He is the faculty co-lead of the Data Science Institute's Data Ecology Research Initiative and a member of ChiData, the data systems research group at the University of Chicago. He is also co-founder and Chief Research Officer at invocate and co-runs Chicago Data Night, a forum connecting industry and academia in Chicago. Castro Fernandez's research focuses on data ecology, data discovery, data markets, and data integration. He develops both theory and systems that help people and organizations find, evaluate, and use data effectively. His work often uses techniques from data management, statistics, and machine learning. He has pioneered concepts in data market design, understanding the economics of data, and building platforms to support markets of data. His research on data ecology frames how data moves through and transforms technological, economic, and social systems—and how to design interventions to make those ecosystems more valuable, equitable, and resilient. His publications reveal a strong focus on data markets, data discovery, and LLM applications for data management. Recent work includes Pneuma (leveraging LLMs for tabular data), Solo (data discovery using natural language), and Nexus (correlation discovery for spatio-temporal data). His research spans theoretical foundations of data value to practical systems for data sharing and discovery. SIGMOD Test of Time Award (2023) NSF CAREER Award (2024) Sloan Research Fellowship (2025) Castro Fernandez has advised numerous PhD, Master's, and undergraduate students who have gone on to pursue PhDs at institutions like University of Washington and Stony Brook, joined companies like Google, Anthropic, and Citadel, or founded startups. His teaching includes courses on The Value of Data, Ethics in Data Science, and Introduction to Databases. He serves on program committees for major conferences including SIGMOD, VLDB, and CIDR, and has been recognized as a Distinguished Reviewer by multiple venues.

Mitra Bokaei Hosseiniمشاهده پروفایل

استادیار

• Legal Compliance
• Natural Language Processing
• Privacy
• +۳ مورد دیگر

Mitra Bokaei Hosseini is an Assistant Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA), part of the College of Sciences. She holds a Ph.D. in Computer Science from UTSA, an M.S. in Information Technology from K.N. Toosi University of Technology, and a B.S. in Information Technology from Qazvin Islamic Azad University. Her research focuses on legal compliance, natural language processing (NLP), privacy, and software engineering, with an emphasis on regulatory compliance frameworks, privacy policy analysis, and automated tools for policy adherence. Her work bridges NLP techniques with practical applications in software development and mobile security. Key research trends in her articles include privacy policy analysis, automated extraction of regulatory requirements, and the use of machine learning (e.g., few-shot learning, large language models) to align code with privacy policies. Her work addresses challenges in disambiguating policy ambiguities, identifying third-party entities, and ensuring compliance in mobile applications. No scientific awards are explicitly mentioned. Her advising record and grants are not detailed in the provided texts. She may be affiliated with research teams or labs focused on privacy and NLP, though specifics are not listed.

John Willoughbyمشاهده پروفایل

استاد

• U.S. Economic History
• European Economic History
• Political Economy
• +۵ مورد دیگر

John Willoughby is a Professor of Economics at the College of Arts & Sciences, American University. He holds a PhD from the University of California at Berkeley, an MA from Cambridge University, and a BA in History from the University of Michigan. His research focuses on U.S. and European economic history, political economy, international economic policy, and the political economy of higher education in the Middle East and Gulf regions. Professor Willoughby has extensive international experience, including creating an undergraduate economics program at the American University of Sharjah in the UAE and teaching as a visiting professor at the American University in Cairo. His work critically examines capitalist structures, labor issues, and the intersection of education and geopolitics. He is affiliated with the Union for Radical Political Economics, the Review of Radical Political Economics Editorial Board, and the Middle East Studies Association. His publications explore topics such as authoritarian capitalist states, gender dynamics in labor markets, and the global expansion of higher education systems. Recent research trends include analyzing the political economy of the Gulf region, the impact of colonial legacies on language policies, and the role of worker empowerment in socialist models. He has also authored Remaking the Conquering Heroes: The Social and Geopolitical Impact of the Early American Occupation of Germany (2001).

Xujie Siمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۵ مورد دیگر

Xujie Si is an Assistant Professor in the Department of Computer Science at the University of Toronto. He is also a faculty affiliate at the Vector Institute and an affiliate member at Mila - Quebec AI Institute, holding a Canada CIFAR AI Chair. Previously, he served as an Assistant Professor at McGill University's School of Computer Science. Education: Ph.D., Computer and Information Science, University of Pennsylvania (advised by Mayur Naik) M.S., Computer Science, Vanderbilt University B.E. (with Honors), Nankai University Research Focus: His work bridges AI and program reasoning, emphasizing the integration of statistical and logical methods. Key areas include: Static analysis and verification using deep learning/reinforcement learning Neuro-symbolic systems for urban simulation (e.g., LogiCity) Automated theorem proving via LLMs and symbolic reasoning Program repair and compiler fuzzing Recent Article Trends: Recent work focuses on synergizing LLMs with symbolic reasoning (e.g., Olympiad inequality proving), advancing SAT solving with graph neural networks, and applying neuro-symbolic methods to Euclidean geometry formalization. Awards: Canada CIFAR AI Chair (2023) Lab/Teams: Leads research teams exploring program analysis, neuro-symbolic AI, and formal verification at the University of Toronto and Vector Institute.

Nidhi Rastogiمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Data Science
• +۷ مورد دیگر

Nidhi Rastogi is an Assistant Professor at the Department of Software Engineering within the Golisano College of Computing and Information Sciences (GCCIS) at Rochester Institute of Technology (RIT). She leads the AI4Sec Research Lab, which focuses on data-driven AI solutions for cybersecurity, emphasizing interpretability and practical applications. Her research interests span Cyber Threat Intelligence, Artificial Intelligence, Graph Analytics, and Healthcare Analytics. Education: Ph.D. in Computer Science (2018), Rensselaer Polytechnic Institute M.S. in Computer Science (2008), University of Cincinnati Bachelor of Information Technology (2003), University of Delhi Research Interests: Transdisciplinary work in cybersecurity, AI, heterogeneous networks, and graph analytics. She develops systems for threat intelligence, explainable AI, and security monitoring. Notable projects include the CyNER library for cybersecurity NER, TINKER framework for open-source CTI, and personal health knowledge graphs. Awards & Mentoring: Students advised include Le Nguyen (1st place at UPSTAT23), Tanvirul Alam (IEEE SP Travel Grant), and Dipkamal Bhusal. Recent recognitions include program committee roles for ACM CCS'24 and ACSAC'24. Labs & Collaborations: The AI4Sec Lab collaborates with federal agencies, national labs, and enterprises. Current projects address autonomous vehicle security, healthcare analytics, and systemic cyberattack detection using graph-based methods.

• Corpus Linguistics
• Applied Linguistics
• Theoretical Linguistics
• +۳ مورد دیگر

Professor Tony McEnery is a Distinguished Professor of English Language and Linguistics at Lancaster University, where he has held various senior roles, including Dean of the Faculty of Arts and Social Sciences (2008–2014) and Head of the Department of Linguistics and English Language (2000–2005). His research focuses on corpus linguistics, applied linguistics, and sociolinguistics, with notable contributions to corpus-based analyses of historical medical discourse, media representation of Islam, and swearing in English. He has led major research projects, including the ESRC Centre for Corpus Approaches to Social Science (CASS) and the Trinity Lancaster Corpus. McEnery has secured over £10 million in research funding and holds visiting professorships at institutions worldwide, including Zhejiang University of Media and Communications and Shanghai International Studies University. He is a Fellow of the Academy of Social Sciences, Trinity College London, and the Royal Society for the Arts. Education: No explicit details provided, but his career trajectory implies advanced degrees in linguistics. Research Interests: Corpus linguistics applications in theoretical and applied linguistics, historical language analysis, and language as a socially situated phenomenon. McEnery’s work extends to interdisciplinary collaborations, including projects with the Environment Agency and the Home Office. His teaching includes summer schools in corpus linguistics and a Futurelearn MOOC, reaching tens of thousands globally. He advises on research funding for international bodies like the Irish Research Council and the Qatar National Research Foundation. Grants and Awards: Queen’s Anniversary Prize (2015), Changjiang Chair (2021), and multiple fellowships. Current grants include the Lancaster-Northern Arizona corpus and the Trinity Lancaster Corpus projects. Advising and Labs: Supervises postgraduate students in linguistics and collaborates with teams like the ESRC CASS Centre and UCREL (University Centre for Computer Corpus Research on Language).

Marzyeh Ghassemiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Healthcare
• +۶ مورد دیگر

Marzyeh Ghassemi is an Associate Professor at MIT in the Department of Electrical Engineering and Computer Science (EECS) and the Institute for Medical Engineering & Science (IMES). She also holds a Canadian CIFAR AI Chair and is a faculty member at the Vector Institute. Her affiliations include the Jameel Clinic and CSAIL. Dr. Ghassemi's work focuses on ethical AI, algorithmic fairness in healthcare, and mitigating bias in medical datasets. She has pioneered projects analyzing racial disparities in end-of-life care, vocal disorder diagnosis using accelerometers, and improving subgroup robustness in machine learning. Education: PhD in Computer Science, MIT MSc in Biomedical Engineering, University of Oxford (Marshall Scholar) B.S. in Computer Science and Electrical Engineering, New Mexico State University (Goldwater Scholar) Research Interests: Her work bridges AI and healthcare, emphasizing fairness, reproducibility, and ethical deployment. Key areas include: - Algorithmic Fairness: Addressing biases in medical imaging and clinical decision systems. - Bias Mitigation: Developing methods to decorrelate sensitive information from predictions. - Health Equity: Studying disparities in end-of-life care and organ procurement. - Generative AI: Applications in mental health and medical imaging. Publications: Her recent work highlights challenges in vision-language models (e.g., handling negation), regulatory gaps in health AI, and bias reduction techniques. These efforts aim to ensure AI systems are both accurate and equitable in clinical settings. Awards: Herman L. F. von Helmholtz Career Development Professorship CIFAR Azrieli Global Scholar MIT Tech Review’s 35 Innovators Under 35 Canada Research Chair Leadership & Impact: She co-chaired the NeurIPS Workshop and founded the Association for Health Learning and Inference. Her projects like Quantifying Racial Disparities in End-of-Life Care reveal systemic biases in ICU treatments. She advocates for transparent AI deployment through frameworks like FUTURE-AI and TRIPOD+. Labs & Teams: Leads MIT’s HealthyML group, collaborating on projects such as voice misuse detection, federated learning for medical imaging, and AI-driven mental health prediction.

Tria Blu Wakpaمشاهده پروفایل

استادیار

• Native American Studies
• Indigenous Performance and Dance
• Carceral Studies
• +۸ مورد دیگر

Tria Blu Wakpa is an Assistant Professor in the Department of World Arts and Cultures/Dance at UCLA's School of the Arts and Architecture. Her work bridges academia and community engagement, focusing on decolonizing methodologies to examine Indigenous peoples' practices in confinement contexts. Education: Ph.D. and M.A., Ethnic Studies, UC Berkeley M.F.A., Creative Writing, San Diego State University B.A., English with Film, Oklahoma State University (summa cum laude) Research Interests: She explores dance, athletics, and yoga through Indigenous frameworks, analyzing their roles in education, incarceration, and performance. Her work emphasizes community collaboration, particularly with tribal experts, and critiques colonial structures. Awards & Recognition: 2023 Gerald Kahan Scholar’s Prize (American Quarterly article) Fulbright Association’s Selma Jeanne Cohen Dance Lecture Awardee (2023) Fellowships: Ford Foundation, Hellman Fund, UC Postdoctoral Program Community Engagement: Co-Founder/Editor-in-Chief of Race and Yoga journal. Serves on LA Cultural Affairs Commission, LA Unified School District’s American Indian Parent Committee, and Fernandeño Tataviam Education Committee. Teaches at tribal, carceral, and public institutions.

Brian Y. Chenمشاهده پروفایل

دانشیار

• Bioinformatics
• Structural Biology
• Computational Biology
• +۵ مورد دیگر

Dr. Brian Y. Chen is an Associate Professor and Doctoral Program Director in the Department of Computer Science & Engineering at Lehigh University. His research focuses on bioinformatics, structural biology, and machine learning applications in computational biology. He holds a Ph.D. in Computer Science from Rice University and B.A. degrees in Mathematics and Computer Science from Rutgers University. Dr. Chen's work emphasizes developing algorithms to analyze protein structures, protein-protein interactions, and ligand binding mechanisms. He has contributed to tools like DeepVASP-S and MechPPI, which explain molecular interactions and predict binding specificity. His recent projects include Alzheimer’s disease diagnosis using multimodal data and containerization frameworks for bioinformatics software. He previously served as a postdoctoral researcher in Barry Honig's Lab at Columbia University, where he contributed to the Center for Computational Biology and Bioinformatics. His research spans structural bioinformatics, computational methods for protein function prediction, and interdisciplinary applications in medicine and materials science. Key achievements include a nomination for Outstanding Mentorship (2017) and collaborative projects funded by the Army Research Lab and Lehigh University. His lab explores cutting-edge AI techniques for biomedical problems, including interpretable machine learning models and scalable bioinformatics pipelines.

• Social Network Analysis
• Network Science
• Data Science
• +۷ مورد دیگر

Giacomo Fiumara is an Associate Professor at the University of Messina, Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences. He holds academic rank since October 2021. Previously, he served as a Permanent Researcher (2008–2021) and secondary school teacher (1997–2008). He earned a Doctorate in Physics (1993) and a Degree in Physics (1989), both from the University of Messina. He is an associate member of the Accademia Peloritana dei Pericolanti and qualified as an associate professor in INF/01 and ING-INF/05 sectors. His research focuses on social network analysis, network science, data science, criminal networks, knowledge representation, bioinformatics, and computational modeling. He has supervised over 170 theses and advised PhD students in Mathematics and Computational Sciences. Key collaborations include work with Prof. Pasquale De Meo on criminal networks and complex systems, and international projects with institutions in the US, UK, China, and Australia. Teaching includes courses on Algorithms, Data Structures, Bioinformatics, and Machine Learning across Computer Science, Engineering, and Medical programs since 2000. He also contributed to international programs at Lviv Polytechnic, Birzeit University, Cluj-Napoca, and Murcia. His editorial roles include Associate Editor of IEEE Access and Academic Editor of Complexity. He holds a patent for predictive analysis of criminal organizations' social structures and has received FFABR research funding. Key awards include FFABR funding (2017) and recognition in the FFABR Unime 2020 II edition. He organized conferences like Crimenet 2014 and participated in high-profile events such as the 2022 Complex Networks conference in Palermo, presenting on quantum walks for criminal network analysis.

Melanie Jacksonمشاهده پروفایل

پژوهشگر

• Multidisciplinary Art
• Bio-technology
• Sociopolitical Art
• +۳ مورد دیگر

Melanie Jackson is an artist and researcher affiliated with the Royal College of Art (RCA), School of Arts & Humanities. Her practice spans multidisciplinary storytelling, focusing on bio-technocapitalism, milk’s sociopolitical roles, and toxicology. She holds a PhD from the University of Reading and has exhibited globally, including solo shows at Grand Union and Primary. Jackson’s research projects include 'Deeper in the Pyramid' and 'Hellmouth,' exploring bio-economies and material science. She is an external examiner at Leeds, UEL, and Camberwell College of Arts, and advises on the SPACEX EU-funded project. Awards include the AHRC Doctoral Award (2016–18) and Jerwood Drawing Prize (Winner). Education: PhD (University of Reading), RCA, LCC, Byam Shaw Key Collaborations: Esther Leslie, Arts Catalyst, Delfina Foundation Her work critiques technological and biocapitalist systems through sculpture, animation, and performance. Recent projects like 'Hellmouth' merge toxicology with digital systems, while 'Deeper in the Pyramid' examines milk’s cultural and economic significance. Jackson’s art navigates contradictions between complicity and critique, using provisional aesthetics to address complex socio-ecological issues.

Mohit Mendirattaمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Computer Graphics
• +۳ مورد دیگر

Mohit Mendiratta is a PhD student in Computer Science at the Universität des Saarlandes and a Researcher at the Max-Planck-Institut für Informatik, Germany. He is part of the Visual Computing and Artificial Intelligence department (Department 6) under the Graphics, Vision & Video group led by Prof. Dr. Christian Theobalt. His research focuses on advancing computer vision, machine learning, and computer graphics, particularly in areas like 3D human avatars, text-driven editing, and video semantic segmentation. Education includes a Master's in Visual Computing from Universität des Saarlandes (2018–2021) and an undergraduate degree in Electronics and Electrical Engineering from KIIT, Bhubaneswar, India (2013–2017). He has held roles such as Research Assistant at the Max Planck Institute and Fraunhofer Institute, and industry experience as an Associate Software Engineer at Zentron Labs. His research interests span developing novel techniques for photorealistic 3D avatars, text-based editing systems, and zero-shot semantic segmentation using diffusion models. He collaborates on projects like AvatarStudio and TEDRA, advancing applications in virtual reality and human-computer interaction. Mohit contributes to the Saarbrücken Research Center for Visual Computing and is affiliated with the International Max Planck Research School on Trustworthy Computing. His work bridges theory and practical applications in AI-driven visual computing.

Pamela Beachمشاهده پروفایل

دانشیار

• Teacher Education
• Professional Development of Educators
• Online Learning Environments
• +۴ مورد دیگر

Pamela Beach is the Associate Dean, Research and Associate Professor of Language and Literacy at Queen’s University’s Faculty of Education. She holds an MA and PhD in Child Study/Developmental Psychology from the University of Toronto. With nearly a decade of elementary teaching experience, her research focuses on leveraging online and multimedia resources to enhance teacher education and professional development. Key projects include SSHRC-funded studies on teachers’ self-directed online learning, analysis of web analytics for literacy PD platforms, and cross-cultural studies of literacy practices in Montessori and Reggio Emilia schools. Her expertise spans early literacy development, critical literacy integration, and the use of technologies like eye-tracking and virtual classrooms in teacher training. She leads the Literacy Education Research Team, collaborating on projects such as integrating music into literacy education and evaluating virtual classroom tools for teacher candidates. Beach is also the author of Promoting Language and Early Literacy Development (2024), a practical guide for educators and caregivers. Current roles include supervising graduate students in the Language and Literacy program and overseeing research initiatives as Associate Dean. Her work bridges research, practice, and policy to improve literacy instruction and teacher learning in diverse educational contexts.