جست‌وجوی استاد و پژوهشگر

Zheng Yuanمشاهده پروفایل

مدرس ارشد

• Educational Technology
• Language Acquisition
• Multilingual NLP
• +۳ مورد دیگر

Dr. Zheng Yuan is a Senior Lecturer (Associate Professor) in Natural Language Processing at the School of Computer Science, University of Sheffield. He holds affiliated positions at the University of Cambridge and King's College London, and is a Fellow of Trinity College, Cambridge. His research focuses on NLP applications in education, healthcare, and multilingual systems. Education: PhD in Natural Language Processing, University of Cambridge MPhil in Advanced Computer Science, University of Cambridge BSc(Eng) from Queen Mary University of London Research: Dr. Yuan's work spans educational NLP, multilingual systems under low-resource conditions, and explainable machine learning. His group develops technologies for grammatical error correction, automated assessment, and cross-lingual applications, with significant contributions to computer-assisted language learning and computational creativity. Publications: Recent works (2023-2025) demonstrate strong focus on educational NLP, multilingual systems, and LLM evaluation. Key themes include grammatical error correction for code-switched languages, creativity assessment frameworks, and robust evaluation methods for large language models across diverse linguistic contexts. Awards: Winning systems at SemEval-2021 and CoNLL-2014 Fellowship at Trinity College Cambridge Fellow of Higher Education Academy Grants & Advising: Principal Investigator for Royal Society grant 'Large Language Models as Agents for Intelligent Language Tutoring' (2025-2027). Actively supervises PhD students in NLP and machine learning, welcoming new research collaborations. Affiliations: Member of Alan Turing Institute (Data-Centric Engineering), King's Institute for AI, and ACL committees. Organizes major NLP workshops including ACL/NAACL BEA workshops and AIED tutorials.

Larry P Heckمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Artificial Intelligence
• +۷ مورد دیگر

Larry P. Heck is a Professor with a joint appointment in the School of Electrical and Computer Engineering and School of Interactive Computing at the Georgia Institute of Technology. He holds the Rhesa S. Farmer Advanced Computing Concepts Chair and is a Georgia Research Alliance Eminent Scholar . Education: BSEE, Texas Tech University (1986) MSEE, Georgia Institute of Technology (1989) PhD EE, Georgia Institute of Technology (1991) His research focuses on conversational AI , dialogue systems , and machine learning applied to natural language processing and speech recognition . He pioneered early industrial applications of deep learning in speech processing and has contributed to advancements in multimodal interaction, knowledge distillation, and real-time question answering systems. Recent publications emphasize moral reasoning in AI , multimodal dialogue , and large-scale dataset creation for conversational systems. His work bridges language modeling , sensor fusion , and ethical AI through innovations in contextual reasoning and interface masking. Scientific Distinctions: IEEE Fellow (2020) IEEE Signal Processing Society Best Paper Award Academy of Distinguished Engineering Alumni, Georgia Tech (2017) Distinguished Engineer Award, Texas Tech University (2017) Fellow, National Academy of Inventors (2025) He has secured significant funding from DARPA and NSA for speaker recognition systems and has led cutting-edge research at institutions including Microsoft, Google, and Samsung. His lab focuses on conversational systems and deep learning for speech and multimodal data.

• Digital Humanities
• Visual Culture
• Computational History
• +۵ مورد دیگر

Dr. Thomas Smits is a faculty member at the Faculty of Humanities of the University of Amsterdam , specializing in Digital Humanities , Visual Culture , and Computational History . His research bridges artificial intelligence with historical image analysis, focusing on media history, colonial visual representations, and algorithmic approaches to archival studies. Recent publications highlight his work on multimodal datasets, generative AI in protest memory reconstruction, and the ethical implications of machine learning for historical research. Smits employs computational methods like CLIP and computer vision to analyze large-scale visual collections, including magic lantern slides, historical advertisements, and news images. Key research areas: Digital Humanities, Visual Memory, Algorithmic Analysis, Colonial Media, Gender Studies, Historical Epistemology. Methodological focus: Stochastic modeling, multimodal machine learning, distant reading of visual datasets, and AI-driven archival enhancement.

Theodore Cohenمشاهده پروفایل

استاد

• Tuberculosis
• Infectious Disease Epidemiology
• Mathematical Modeling
• +۶ مورد دیگر

Dr. Theodore Cohen is a Professor of Epidemiology (Microbial Diseases) at the Yale School of Public Health. His primary research focus is tuberculosis, with particular interest in understanding how TB drug-resistance and medical comorbidities such as HIV frustrate current efforts to control epidemics. His work includes mathematical modeling, fieldwork, and analysis of programmatic data. Education: DPH, Harvard School of Public Health (2006) MPH, University of North Carolina, Chapel Hill (2001) MD, Duke University (2001) BA in Neuroscience, Oberlin College (1996) Dr. Cohen's research interests span tuberculosis epidemiology, drug resistance, HIV-TB co-infections, mathematical modeling of infectious diseases, and health disparities in TB outcomes. His work focuses on developing more effective approaches to limit TB morbidity through targeted interventions and improved understanding of transmission dynamics. He examines racial and ethnic disparities in TB incidence and outcomes, particularly among US-born populations. Analysis of Dr. Cohen's recent publications (2022-2025) reveals a strong focus on tuberculosis epidemiology, with particular attention to health disparities, cost-effectiveness of interventions, and the impact of comorbidities like HIV and diabetes on TB outcomes. His work frequently employs mathematical modeling and analysis of large datasets to understand TB transmission dynamics and evaluate intervention strategies across diverse populations in the United States. Scientific Awards: Elected member, Connecticut Academy of Science and Engineering (2022) NIH New Innovator Award (2009) Merck Manual Scholar, Duke University School of Medicine (2001) Alpha Omega Alpha, Duke University School of Medicine (2000) Senior Scholarship Recipient, Duke University School of Medicine (2000) Dr. Cohen's research program is currently funded by NIH and US CDC Awards. His work includes multiple NIH-funded projects, including a R01 grant focused on evaluating health and economic effects of targeted strategies in TB/HIV epidemics (2014-2018), participation in the MIDAS Center for Communicable Disease Dynamics (2014-2019), and projects with the Bill and Melinda Gates Foundation on TB modeling and drug dosing optimization. Dr. Cohen leads the Ted Cohen Group (T Cohen Lab) at Yale, which focuses on infectious disease epidemiology, particularly tuberculosis. His lab conducts research on TB transmission dynamics, mathematical modeling of epidemics, and analysis of programmatic data to inform public health interventions. The lab is part of the Yale Institute for Global Health and the Yale-UPR Integrated HIV Basic and Clinical Sciences Initiative.

• Astronomy
• Astrophysics
• Machine Learning
• +۵ مورد دیگر

Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.

Martin Hebartمشاهده پروفایل

استاد

• Visual Perception
• Computational Cognitive Neuroscience
• Quantitative Psychiatry
• +۵ مورد دیگر

Martin Hebart is a Professor for Computational Cognitive Neuroscience and Quantitative Psychiatry at Justus Liebig University Giessen and an Independent Max Planck Research Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. His work bridges cognitive neuroscience, computer science, and psychology to explore visual perception, object recognition, and computational models of brain function. PhD in Psychology from Bernstein Center for Computational Neuroscience Berlin (2014) M.Sc. and B.Sc. in Neuro-cognitive Psychology from Ludwig Maximilian University Munich His research integrates psychophysics , neuroimaging (fMRI, MEG), and machine learning to decode how visual input transforms into stable object representations and how these insights inform psychiatric conditions like hallucinations. Articles highlight his focus on computational models , neural network alignment , and large-scale behavioral-neuroimaging datasets (e.g., THINGS-data). His group’s work spans from basic visual cognition to translational applications in psychiatry. Scientific awards include postdoctoral fellowships from the National Institute of Mental Health (2016) and Alexander von Humboldt Foundation (Feodor Lynen, 2016), alongside doctoral and study scholarships. He leads a multidisciplinary team at the intersection of JLU Giessen’s Medical Department and MPI, mentoring students in visual neuroscience , AI-driven modeling , and clinical applications .

Lisa Hultmanمشاهده پروفایل

استاد

• Peace and Conflict Research
• International Relations
• Civil War Studies
• +۵ مورد دیگر

Lisa Hultman serves as a Professor at Uppsala University's Department of Peace and Conflict Research, where she leads groundbreaking research on peacekeeping operations, civilian protection, and conflict dynamics. Her work bridges academic rigor with practical policy implications for international peace and security institutions. Professor Hultman's research focuses on the empirical analysis of UN peacekeeping effectiveness, particularly examining how different mandate configurations impact violence against civilians and local conflict trajectories. Her work demonstrates sophisticated methodological approaches, frequently utilizing geocoded data and large-N quantitative analyses to assess peacekeeping outcomes at subnational levels. Key contributions include developing innovative datasets like the Geocoded Peacekeeping Operations (Geo-PKO) and examining the economic dimensions of peacekeeping deployments on local development. Her publication record reveals consistent engagement with critical questions in peace and conflict studies, with recent work exploring mandate complexity in UN operations, the relationship between peacekeeping and civilian protection norms, and forecasting models for political violence. Her research often involves extensive collaboration with leading scholars in the field, resulting in publications in top political science journals including the American Political Science Review , American Journal of Political Science , and Journal of Peace Research . Professor Hultman's influential 2019 book "Peacekeeping in the Midst of War" (co-authored with Jacob Kathman and Megan Shannon) synthesized years of research on peacekeeping effectiveness. Her work has been widely cited and referenced in both academic literature and policy discussions, demonstrating significant real-world impact on understanding how international interventions can effectively protect civilians and reduce violence in conflict zones.

Aleda M. Leisمشاهده پروفایل

عضو هیئت علمی

• Epidemiology
• Public Health
• Chronic Diseases
• +۸ مورد دیگر

Aleda (Allie) M. Leis, PhD, is a Research Assistant Professor in the Department of Epidemiology at the University of Michigan School of Public Health. Her work bridges chronic and infectious disease epidemiology, with a focus on cardiometabolic outcomes following viral infections. Education: PhD in Epidemiological Science, University of Michigan (2022) MS in Biostatistics, Drexel University (2015) BS in Mathematics, St. Bonaventure University (2013) Research Interests: Dr. Leis investigates how viral infections like influenza and COVID-19 interact with metabolic and cardiovascular diseases across the lifespan. Key areas include aging, women's health, bone health, and precision health initiatives using large datasets such as the Study of Women’s Health Across the Nation (SWAN) and CDC respiratory surveillance programs. Projects: She leads the Surveillance of Respiratory Infections’ Sequelae (SunRISE) program, contributes to the AI & Digital Health Innovation network, and co-investigates vaccine effectiveness in the Michigan-Ford Initiative (MFIVE). Her work utilizes electronic health records and longitudinal cohorts to explore post-viral health impacts. Contact: Email aledat@umich.edu for collaboration or media inquiries.

• Experimental High-Energy Particle Physics
• CP Violation Studies
• B-Physics and Strange Quark Physics
• +۴ مورد دیگر

Roger William Lewis Jones is a Professor and Head of the Department of Physics at Lancaster University . His career spans experimental high-energy particle physics, QCD research, and global computing infrastructure development for large-scale scientific projects like ATLAS and the Rubin Observatory. ATLAS experiment (LHC) for CP violation studies in B-physics NA62 experiment for strange quark physics LEGEND collaboration for neutrino research Leadership in GridPP and Worldwide LHC Computing Grid Research Focus : Experimental particle physics with emphasis on CP violation, QCD dynamics, and data-intensive computing systems. His work bridges hardware development (e.g., tracking detectors) and software innovation (e.g., Grid computing farms across UK institutions). Recent Publications highlight precision measurements in jet physics, Higgs decays, and searches for new particles like heavy neutral leptons. Articles span 2025 with collaborations on ATLAS and NA62, focusing on detector calibration, cross-section analysis, and beyond-Standard-Model signatures. Leadership Roles : Chair of NorthGrid Management Board Former Chair of STFC Particle Physics Advisory Panel (2019-2022) Chair of Institute of Physics Head of Department Forum Steering Committee (2019-2024) Key contributor to GridPP and Worldwide LHC Computing Grid

Grant Van Hornمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Robotics
• +۲ مورد دیگر

Grant Van Horn is an Assistant Professor at the University of Massachusetts Amherst, affiliated with the College of Information and Computer Sciences. He specializes in computer vision and machine learning, focusing on applications in biodiversity and conservation. His work underpins popular tools like iNaturalist, Seek, and Merlin Bird ID. Prior to UMass, he held roles at AWS and the Cornell Lab of Ornithology. Education: PhD in Computer Science, California Institute of Technology (2019) MS in Computer Science, University of California San Diego (2014) BS in Computer Science, University of California San Diego (2012) Research Interests: Grant’s research bridges computer vision and machine learning to create systems that integrate human expertise and large datasets for environmental conservation. Key areas include wildlife species identification, acoustic monitoring, and ecological modeling. His work emphasizes leveraging technology for public engagement and scientific impact. Articles & Trends: Recent publications focus on audio geolocation, species range estimation, and satellite imagery analysis, reflecting his commitment to advancing tools for biodiversity conservation. His work often combines citizen science data with machine learning innovations. Awards: Computing Research Association Outstanding Undergraduate Researcher Honorable Mention (2012) Ben P.C. Chou Doctoral Prize (2019) Fast Company’s 2021 Recognition Advising & Labs: Grant advises students in computer science and conservation technology through the Computer Vision Research Laboratory. He has collaborated on projects like the iWildCam dataset and systems for salmonid counting in sonar data.

Peter Lambertمشاهده پروفایل

دانشیار

• multimedia signal processing
• visual communication
• computer graphics
• +۲ مورد دیگر

Peter Lambert is a full-time Associate Professor at Ghent University – imec (Belgium), affiliated with the Internet Technology and Data Science Lab (IDLab) where he coordinates the MEDIA research team since 2013. His academic background includes a Master's degree in Science (Mathematics) and Applied Informatics from Ghent University, followed by a Ph.D. in Computer Science from the same institution in 2007. Prior to his current role, he served as a Technology Developer at Ghent University (2010-2013). Lambert's research focuses on: Multimedia signal processing and visual communication systems Computer graphics and computational geometry Augmented and virtual reality (AR/VR) technologies Video compression and perceptual quality assessment Multimedia security and digital watermarking His recent publications (2024-2025) demonstrate strong emphasis on real-time multimedia systems, VR/AR applications, perceptual quality metrics, and multimedia security. Research trends include deep learning-based video forensics, light field rendering optimizations, perceptual hashing techniques, and adaptive video streaming solutions. As leader of the IDLab-MEDIA team, Lambert oversees research on emerging visual media formats with applications in immersive experiences. The team develops technologies like OpenDIBR (real-time light field renderer) and maintains datasets such as SILVR (Synthetic Immersive Large-Volume Plenoptic Dataset).

Kristopher Micinskiمشاهده پروفایل

استادیار

• Programming Languages
• Static Analysis
• Formal Methods
• +۴ مورد دیگر

Kristopher Micinski is an Assistant Professor in the Electrical Engineering and Computer Science Department at Syracuse University. His research focuses on scalable program analysis, static analysis, and formal methods applied to computer security and privacy. He holds a PhD in Computer Science from the University of Maryland and a BS in Computer Engineering from Michigan State University. Education: PhD, Computer Science, University of Maryland at College Park BS, Computer Engineering, Michigan State University Research Interests: His work bridges theory and application of program analyses, emphasizing scalable static analysis frameworks, Datalog optimization for distributed systems, and security applications. Recent efforts include GPU-accelerated Datalog engines and large-scale malware analysis pipelines like Assemblage. Grants & Projects: NSF PPoSS Large: $1M grant for declarative analytics DARPA V-SPELLS: $400K for legacy software optimization Assemblage: $350K DoD grant for malware classification Teaching: He teaches undergraduate and graduate courses on programming languages (CIS352) and formal methods (CIS700), with materials publicly available on YouTube.

Moo Chungمشاهده پروفایل

استاد

• Computational Neuroimaging
• Topological Data Analysis
• Brain Networks
• +۵ مورد دیگر

Moo Chung is a Professor of Biostatistics and Medical Informatics at the University of Wisconsin-Madison, affiliated with the School of Medicine and Public Health. He holds additional appointments in the Department of Statistics and the College of Letters and Science. Chung earned his Ph.D. in Mathematics and Statistics from McGill University under Professors Keith J. Worsley and James O. Ramsay. His research focuses on computational neuroimaging, leveraging MRI, fMRI, and DTI to study brain dynamics through topological and geometric methods. Key areas include persistent homology, brain network analysis, and statistical modeling of high-dimensional imaging data. He has pioneered methods like hyper-network construction and exact topological inference for paired brain networks, addressing computational challenges in analyzing large-scale neuroimaging datasets. Chung’s work integrates advanced mathematical techniques such as Hodge Laplacian, spectral graph theory, and Wasserstein distances to analyze brain connectivity. He has secured NIH funding for projects like the Brain Initiative (2017-2020) and current grant MH133614 (2023), focusing on geometric data analysis and topological dynamics. His contributions include three books on brain imaging and network analysis, with ongoing research on topological data analysis applications. Awards: Vilas Associate Award (2013-2014), NIH Brain Initiative Award, Editor's Award (2011) Labs/Teams: Leads brain imaging workshops globally, including Seoul National University (2024) and POSTECH (2024), and organizes conferences like ISBI and MICCAI special sessions. Grants: NIH EB022856 (Brain Initiative), MH133614 (2023), and collaborations with institutions like Vanderbilt University and University of Chicago. Chung actively mentors students and postdocs in biomedical data science, offering fellowships through the CIBM program. His group maintains a Google mailing list for brain image analysis discussions and hosts regular seminars on methodological advancements.

• Natural Language Processing
• Text Generation
• Machine Learning
• +۱ مورد دیگر

Zihao Fu is a Researcher at the Oxford Internet Institute (OII), University of Oxford, where he served as a Postdoctoral Researcher from March 2024 to April 2025, focusing on the Trustworthiness Auditing for AI project. Previously, he was a Research Associate (PostDoc) at the University of Cambridge's Language Technology Lab under Prof. Nigel Collier. His research emphasizes Natural Language Processing, Text Generation, Machine Learning, and Biomedical Applications. Education includes a Ph.D. from The Chinese University of Hong Kong (supervised by Prof. Wai Lam) and a visiting student period at Tsinghua University's NLP Lab. He has substantial experience with large-scale distributed algorithms in Alibaba Cloud's PAI platform. Research interests span NLP, biomedical applications, and AI ethics, with notable contributions to datasets like BAND and frameworks like OxonFair. His work addresses challenges in text generation repetition, parameter-efficient fine-tuning, and algorithmic fairness.

Paul Goodingمشاهده پروفایل

استاد

• Digital Humanities
• Library and Information Science
• Digital Libraries
• +۳ مورد دیگر

Paul Gooding is a Professor of Library Studies and Digital Scholarship at the University of Glasgow. His research focuses on digital library collections' impact, reuse in Digital Humanities, and user behavior analysis. He holds a BA in English Literature (University of East Anglia), MA in Library and Information Studies (UCL), and a PhD in Digital Humanities (UCL). Research interests include digital collections evaluation, legal deposit frameworks, and AI applications in cultural heritage. Notable publications include Historic Newspapers in the Digital Age (2016) and co-editing Electronic Legal Deposit (2020). He leads projects like Digital Library Futures (AHRC-funded) and the Global Dataset of Digitised Texts Network. Recent articles explore topics such as 'Slow AI' principles, HTR in heritage contexts, and inclusive AI requirements for Indigenous knowledges. His work bridges library studies, digital humanities, and ethical technology. Fellowships include the Higher Education Academy and Royal Historical Society. He serves as Associate Editor for Digital Scholarship in the Humanities and AHRC Peer Review College member.