جست‌وجوی استاد و پژوهشگر

Aaqib Saeedمشاهده پروفایل

استادیار

• Human-Centric AI
• Federated Learning
• Self-Supervised Learning
• +۳ مورد دیگر

Aaqib Saeed is an Assistant Professor in the Department of Industrial Design at Eindhoven University of Technology. His research focuses on Human-Centric AI, Federated Learning, Self-Supervised Learning, and Audio Understanding, with applications in Personal Health. He holds a PhD (cum laude) from TU/e and an MSc (cum laude) from the University of Twente. Education: PhD in Computer Science (cum laude), TU/e (2021) MSc in Computer Science (cum laude), University of Twente (2018) Research Interests: Development of robust federated learning frameworks for decentralized data Self-supervised learning for audio and physiological signal analysis AI-driven solutions for healthcare monitoring Key Contributions: DeltaMask: Reducing communication overhead in federated fine-tuning FedNS: Mitigating noisy decentralized data in federated learning Labeling Chaos to Learning Harmony: Handling label noise in FL Professional Experience: Visiting Industrial Fellow, University of Cambridge (2023) Research Scientist, Philips Research (2019–2023) Research Internships: Google Research, TNO/EIT Digital Awards: UT Scholarship (MSc) Cum Laude awards for both PhD and MSc Labs/Teams: EAISI Health, EAISI Foundational, Computational Design Systems.

Anton Bergمشاهده پروفایل

پژوهشگر ارشد

• Cognitive Science
• Computer Vision
• Religious Studies
• +۷ مورد دیگر

Anton Berg is a Postdoctoral Researcher at the University of Helsinki, affiliated with the Department of Digital Humanities within the Faculty of Arts and the Helsinki Institute for Social Sciences and Humanities (HSSH). He is also a member of the methodological unit at HSSH, focusing on interdisciplinary research at the intersection of cognitive science, religious studies, and artificial intelligence. His educational background spans computer science, cognitive science, and religious studies, enabling him to bridge technical and humanistic approaches to AI. His research primarily investigates how commercial image recognition systems interpret and categorize religious content, exploring issues of bias, representation, and the datafication of religion. Berg's research interests include computer vision systems, automatic image recognition, machine and deep learning, large language models, and the relationship between religions, worldviews, and values related to AI technologies. He particularly focuses on inequality issues, the datafication of religion, the datafication of societies, the social scientific study of religion, and the cognitive science of religion. His work combines technical analysis of AI systems with social scientific perspectives on religion and technology. His recent publications demonstrate a strong focus on examining biases in commercial image recognition services, particularly regarding religious content, with significant contributions to understanding representational silence and racial biases in these systems. He has also conducted important work on pandemic psychology, contributing to large-scale international studies on COVID-19 responses across 69 countries. Berg has been actively involved in numerous academic activities, including presentations at international conferences on topics such as computer vision in religious studies, mediatized religious populism, and biases in image recognition services. His research has been presented at venues including the International Association for the Cognitive Science of Religion. His teaching areas include religious studies, cognitive science, data science, and religion and technologies, reflecting his interdisciplinary approach to understanding the relationship between digital technologies and religious phenomena.

• Computer Vision
• Robotics
• Medical Imaging
• +۴ مورد دیگر

Yuhao Chen is a Research Assistant Professor at the University of Waterloo, specializing in cutting-edge research at the intersection of computer vision, robotics, and healthcare. His work focuses on 3D reconstruction, food tracking, medical imaging, and AI-driven solutions for nutrition analysis and sports analytics. He has contributed to benchmark datasets like NutritionVerse, MetaGraspNet, and FoodVerse, advancing applications in robotic grasping, dietary intake estimation, and human-object interaction analysis. Research interests include egocentric video analysis, real-time 3D reconstruction, zero-shot learning, and multi-task learning. His projects often integrate Gaussian splatting, photometric SLAM, and diffusion models to solve complex problems in food tracking, medical image segmentation, and sports player motion analysis. Recent work highlights include FoodTrack for dietary monitoring and RepViT-MedSAM for medical image segmentation. Yuhao Chen’s innovations span robotics, healthcare, and AI, with a focus on practical applications such as automated nutrition assessment, robotic bin picking, and athlete performance analysis. His research emphasizes scalable frameworks and physically informed 3D reconstruction methods to address real-world challenges in health, sports, and automation.

• Bioinformatics
• Structural Biology
• Computational Biology
• +۳ مورد دیگر

Martin Steinegger is a researcher affiliated with Johns Hopkins School of Medicine and previously held roles at institutions such as the Max Planck Institute for Biophysical Chemistry and Technical University of Munich. His research focuses on bioinformatics, protein structure prediction, and computational methods for analyzing large genomic datasets. He has contributed to tools like MMseqs2, ColabFold, and Foldseek, advancing fields like metagenomics and structural biology. His work emphasizes scalable algorithms and open-source software development. Education includes a Master of Computer Science from Ludwig-Maximilians-Universität München (2013-2014) and a Ph.D. from Technical University of Munich (2014-2018). He has also held visiting scholar positions at Seoul National University, Centre for Genomic Regulation, and University of California, San Francisco. Key research interests revolve around protein structure prediction, metagenomic analysis, and developing machine learning frameworks for biological data. His publications highlight innovations in protein language models, structural phylogenetics, and database management systems. Notable contributions include the AlphaFold Protein Structure Database, MMseqs2 sequence search tool, and ColabFold for accessible protein folding predictions. His work bridges computational methods with biological discovery, addressing challenges in structural biology and genomic data interpretation.

• Machine Learning
• Bayesian Optimization
• Gaussian Processes
• +۴ مورد دیگر

Ti John is a Research Fellow at Aalto University's Department of Computer Science within the School of Science. He is affiliated with Professor Marttinen's research group and the Probabilistic Machine Learning group led by Professor Samuel Kaski. His work connects with the Finnish Center for Artificial Intelligence (FCAI) and the Helsinki Institute for Information Technology (HIIT). Dr. John's research focuses on machine learning, particularly Bayesian optimization, Gaussian processes, and point process models. His work spans theoretical developments in neural processes and practical applications in healthcare analytics and large language models. He has made significant contributions to equivariant neural processes, causal mediation analysis in healthcare, and interpretability of additive models. His publication record shows consistent output with 17 publications between 2021-2024, including multiple papers at top AI conferences like NeurIPS, ICML, and ICLR. His research demonstrates strong interdisciplinary connections between statistical modeling, artificial intelligence, and healthcare applications. Active reviewer for NeurIPS, ICLR, AISTATS Reviewer for Journal of Machine Learning Research Member of Finnish Center for Artificial Intelligence project Dr. John has been actively contributing to the machine learning community through peer review and conference participation, demonstrating expertise across multiple subfields of artificial intelligence and statistical modeling.

Luca Barraمشاهده پروفایل

استاد

• Media Studies
• Television History
• Transnational Media Circulation
• +۵ مورد دیگر

Luca Barra is Full Professor of Television and Digital Media at the Department of Arts, University of Bologna. His research focuses on media studies, particularly television history and contemporary evolution, transnational circulation of content, serialization, and comic/humorous genres. He has coordinated the Master's Degree in Information, Cultures and Media Organization since 2021 and serves as editor-in-chief of VIEW. Journal of European TV History and Culture. University of Bologna, Department of Arts Research areas: Television History, Transnational Media, Digital Transformation, Italian TV Production Barra's work examines the international mediation of ready-made TV formats, Italian streaming partnerships, and the cultural implications of digital television. His recent articles analyze dystopian narratives, sitcom reception in Italy, and the redefinition of celebrity during the pandemic. He contributes to academic discourse through editorial roles in journals like SERIES and Comunicazioni Sociali. His publications include monographs on Italian television programming, sitcoms, and co-edited volumes exploring European premium TV fiction and digital media frameworks. Barra has led research projects such as ATLas and F-ACTOR, and collaborates with international institutions including Brown University and NECS.

• Natural Language Processing
• Large Language Models
• Soft Robotics
• +۴ مورد دیگر

Peiyi Wang is an Assistant Professor at Peking University's School of Electronics Engineering and Computer Science, Institute for Artificial Intelligence. With strong research output spanning both natural language processing and robotics, Wang maintains significant collaborations with Southern University of Science and Technology and National University of Singapore, particularly in soft robotics research with Professor Cecilia Laschi. Additionally, Wang is actively involved with DeepSeek-AI, contributing to several major language model initiatives including DeepSeek-R1 and DeepSeek-V2. Peking University, School of EECS, Institute for Artificial Intelligence (Primary) Southern University of Science and Technology (Collaborative) National University of Singapore (Collaborative) DeepSeek-AI Research Organization Dr. Wang's research spans two primary domains with significant intersection points. In natural language processing, Wang focuses on large language model reasoning capabilities, mathematical verification, uncertainty estimation, and preference alignment. The robotics work centers on soft robotics, particularly origami-inspired designs, strain-based modeling, and control systems for continuum manipulators. These domains converge in Wang's work on vision-language models, embodied AI, and multimodal reasoning systems. Recent work demonstrates particular innovation in mathematical reasoning verification (Math-Shepherd), soft robotic control systems, and red teaming frameworks for language model safety. Wang's publication record shows remarkable productivity, with over 40 publications between 2021-2025 across top-tier venues including ACL, EMNLP, CVPR, and IEEE Transactions on Robotics. The work demonstrates consistent progression from foundational NLP tasks to increasingly sophisticated multimodal and reasoning systems. The most recent publications (2024-2025) show particular emphasis on mathematical reasoning verification, soft robotics control, and language model safety evaluation. While specific awards aren't documented in the provided materials, Wang's work has clearly gained significant recognition through acceptance at top-tier conferences and collaborations with leading researchers in both NLP and robotics fields. Wang's research demonstrates strong interdisciplinary connections, bridging theoretical NLP work with practical robotics applications. The work with DeepSeek-AI suggests active industry collaboration while maintaining strong academic research output. Current research directions appear focused on improving language model reasoning reliability while developing novel soft robotic systems that can interact safely and effectively with complex environments.

Derrick R. Spiresمشاهده پروفایل

دانشیار

• Early Black Print Culture
• Citizenship Studies
• African American Intellectual History
• +۳ مورد دیگر

Derrick R. Spires serves as Associate Professor of English in the College of Arts & Sciences at the University of Delaware, specializing in early Black print culture, citizenship studies, and African American intellectual history. His scholarly mission centers on recovering the rich imaginative worlds African-descended people generated through print media and how these imaginings facilitated material change, spanning from tragicomic expressions to mundane daily practices. Spires' research interrogates how Black writers articulated expansive, practice-based theories of citizenship through robust print networks including newspapers, the Colored Conventions movement, and ephemeral publications. His work reveals the centrality of seriality, pseudonymity, and collaborative performance in Black political thought, demonstrating how print culture enabled Black communities to navigate and reshape citizenship frameworks despite systemic exclusion. He examines how early African American literature cultivated aesthetic sensibilities that sustained resistance and community building. Analysis of his 2016-2024 publications reveals consistent thematic threads: the material conditions of Black bibliography, gendered dimensions of political expression, and the performance aspects of print culture. His scholarship increasingly engages with digital humanities methodologies while maintaining deep archival rigor, particularly regarding Dorothy Porter's bibliographic mission and liberation bibliography frameworks. Key publications map connections between early Black social media practices and contemporary digital activism. Spires' accolades include: Modern Language Association Prize for First Book (2020) St. Louis Mercantile Library Prize (2020) National Endowment for the Humanities Fellowship Ford Foundation Fellowship Social Science Research Council Fellowship Mellon/Mays Initiatives Fellowship American Antiquarian Society Fellowship His editorial leadership encompasses the Broadview Anthology of American Literature and the University of Pennsylvania Press series 'Black Print and Organizing in the Long Nineteenth Century.' Research has been supported by major fellowships examining Black print networks, though specific grant details beyond institutional fellowships aren't specified. Spires contributes significantly to recovering marginalized intellectual traditions through meticulous bibliographic work and theoretical innovation in citizenship studies.

Allison P Squiresمشاهده پروفایل

استاد

• Global Health
• Immigrant and Refugee Health
• Health Services Research
• +۷ مورد دیگر

Allison P Squires is a Professor at the Rory Meyers College of Nursing at New York University (NYU), where she also serves as the Director of the Global Consortium of Nursing and Midwifery Studies (GCNMS), an 82-country research network. She holds affiliated appointments at the Grossman School of Medicine’s Department of General Internal Medicine, the Center for Latin American Studies, and the Center for Drug Use and HIV Research. She is actively accepting PhD students and postdoctoral fellows. PhD in Nursing – Yale University MSN – Duquesne University BSN – University of Pennsylvania Post-Doctoral Fellowship – University of Pennsylvania Her research focuses on global health , immigrant and refugee health , and health services and workforce research , with particular attention to language access, health equity, and pandemic response. She is an expert in implementation science and contextual factors in healthcare delivery. Her recent work examines mental health among nurses during the pandemic, disparities in school-based mental health services, and continuity of care in home health settings. Her publications span global nursing policy , workforce planning , linguistic equity , and cross-cultural research translation . She has served as associate editor of the International Journal of Nursing Studies since 2012 and contributed to major policy initiatives, including the National Academy of Medicine’s 'Future of Nursing 2020–2030' report. Selected honors include: Distinguished Nurse Scholar in Residence, National Academy of Medicine (2019–2020) Fellow, American Academy of Nursing (2015) Outstanding Mentor Award, Academy Health (2023) Chair, Nursing Section, New York Academy of Medicine (2018–2022) Squires has advised numerous research projects and policy analyses, particularly with the World Bank and Migration Policy Institute. She has led initiatives on nursing workforce forecasting, mentoring in Sub-Saharan Africa, and language access in school and home health settings. She is a strong advocate for equitable healthcare and interdisciplinary collaboration. She leads the GCNMS, a major international research consortium, and has developed training programs in gerontology for nurse practitioners. Her work bridges clinical practice, policy, and academic research, with a strong commitment to improving care for vulnerable populations globally.

Erik Linsteadمشاهده پروفایل

دانشیار

• Machine Learning
• GPU Programming
• Autism Spectrum Disorder
• +۵ مورد دیگر

Dr. Erik Linstead is an Associate Professor and Senior Associate Dean at Chapman University, affiliated with the Fowler School of Engineering, School of Pharmacy, and George L. Argyros College of Business and Economics. His expertise spans Machine Learning, GPU Programming, Autism Spectrum Disorder, Assistive Technologies, Predictive Analytics, and Virtual Reality. Education: Bachelor of Science, Chapman University Master of Science, Stanford University Ph.D., University of California, Irvine Dr. Linstead's research integrates machine learning with diverse domains, including autism treatment, environmental monitoring, and software engineering. His recent publications focus on coral reef health, land surface temperature trends, and embedded machine learning systems. His scholarly work includes collaborations in remote sensing, medical informatics, and neurodiversity support. Articles highlight his interdisciplinary approach, applying AI to ecological challenges (e.g., Red Sea coral reefs, Nile Basin droughts) and human-centered technologies (e.g., VR therapy for autism, medication adherence analysis).

Colin Wilsonمشاهده پروفایل

استاد

• Theoretical Phonology
• Experimental Phonology
• Phonetics
• +۳ مورد دیگر

Colin Wilson is a Professor in the Department of Cognitive Science at Johns Hopkins University . He is on leave during Fall 2025. His research spans theoretical and experimental phonology, phonetics, cross-language perception/production, and computational modeling. Specialties : Theoretical phonology, phonotactics, constraint learning Techniques : Artificial grammar, probabilistic models, acoustic analysis Research Trends Recent publications focus on interpretable neural networks for morphological learning, phonetic covariation in American English stops, and cross-language speech processing. Key areas include constraint-based grammar, Bayesian inference, and phonotactic probability. Teaching History Colin has taught courses at JHU (2008-2017) and UCLA (2001-2007) including Phonology I/II, Bayesian Inference, and language processing seminars. He co-taught with Donca Steriade, Bruce Hayes, and others.

• Semantics
• Pragmatics
• Syntax
• +۲ مورد دیگر

Kyle Rawlins is a Professor in the Department of Cognitive Science at Johns Hopkins University (JHU), where he heads the Semantics Lab located in Krieger Hall 105. His research focuses on semantics, pragmatics, syntax, and their intersections, often collaborating with labs like the Van Durme Lab in Computer Science. The Semantics Lab facilitates weekly meetings for discussing research, structured as seminars or traditional lab sessions, and co-organizes projects such as the Decomp Project and MegaAttitude Project . Current lab members include PhD students Karl Mulligan and Natalia Talmina. Notable collaborators: Ilaria Frana (University of Enna), Barbara Landau (JHU), Ben Van Durme (JHU CS), and Aaron Steven White (Rochester). His research spans topics like: Questions Under Discussion (QUD) frameworks Evidentiality and bias in language Multimodal semantic parsing Decompositional semantics Pragmatic particles in Italian Recent publications analyze polar questions, neural network representations, and discourse particles. The lab maintains a mailing list for event announcements, emphasizing collaborative research in semantics and computational linguistics.

• Hybrid Intelligence
• Human-centered Generative AI
• Federated Learning
• +۱ مورد دیگر

Florian Leiser is a Professor at the Chair of Information Infrastructures (led by Prof. Dr. Ali Sunyaev) at Technical University of Munich's Heilbronn campus. His research focuses on human-AI collaboration, privacy-preserving algorithms, and explainability in machine learning systems. Current research areas include Hybrid Intelligence, Human-centered Generative AI (LLMs), Federated Learning, and Health Information Systems Recent publications demonstrate expertise in Explainable AI for medical imaging LLM hallucination detection Federated learning architectures Human-in-the-loop systems Healthcare data applications He contributes to teaching through Human-Centered Artifact Design courses Collaborative teaching roles in machine learning Supervising student projects

• Public Law
• European Union Law
• International Trade Law
• +۳ مورد دیگر

Manuel Fontaine Campos serves as Associate Professor at the Faculty of Law of the Catholic University of Portugal (UCP), where he has held directorial responsibilities since 2013 and previously served as Vice-President of UCP's Porto Regional Center (2017-2021). His academic journey includes a Law degree (1996), Master's in Political Science (1999), and Doctorate in Law (2012), all from UCP. His research focuses on Public Law , European Union Law , and International Trade Law , with particular expertise in State Aid regulation, constitutional interpretation, and EU competition policy. His publication record spans over two decades, including commentaries on Portugal's Civil Code and Constitution, analyses of EU regulatory frameworks, and historical studies of international trade regulations. Professionally, he has held visiting positions at universities in Mozambique, Macau, Spain, and Portugal, and contributes to legal discourse through scholarly publications and expert opinions. His teaching portfolio includes International Trade Law, Public Law, and European Economic Law modules across multiple UCP degree programs. As both academic and practitioner (having worked as a lawyer and legal consultant), Campos bridges theoretical scholarship with practical legal application, particularly in EU regulatory compliance and constitutional interpretation. His current work continues to influence Portuguese legal scholarship through ongoing publications and institutional leadership.

• Machine Learning
• Statistical Methodology
• Computational Biology
• +۵ مورد دیگر

Eric P. Xing is a Professor at the Language Technologies Institute of Carnegie Mellon University , and currently serves as President of the Mohamed bin Zayed University of Artificial Intelligence . His work bridges machine learning methodology with computational biology and large-scale AI systems . Research Focus: Developing machine learning theory for high-dimensional, dynamic data Building foundation models for biology (AIDO, scLong, ProteinAligner) Designing scalable AI architectures (Pollux, LLM360, PAN) Advancing interpretable and controllable NLP systems Scientific Leadership: Founded the SAILING Lab at CMU Co-chaired ICML 2014 and ICML 2019 Recipient of the Jay Lepreau Best Paper Award (OSDI 2021) Education & Mentorship: Advises PhD students across machine learning and computational biology Alumni include faculty at ETH Zurich, University of Chicago, and UC San Diego