جستجوی استاد راهنمای دانشگاهی

Kavin Narasimhan is an Assistant Professor at the Centre for Interdisciplinary Methodologies (CIM) at the University of Warwick. His research focuses on complexity science and computational modelling for public policy, employing agent-based modelling and futures studies methodologies. He holds a PhD in Computer Science from Queen Mary University of London (2016) and a B.E. in Computer Science and Engineering from Anna University, India. He was awarded Fellow of The Higher Education Academy (FHEA) in 2021. Previously, he served as a Research Fellow at the University of Surrey’s Centre for Research in Social Simulation (CRESS) between 2015-2023. His teaching responsibilities include convening the IM939 module on Data Science principles and contributing to courses like IM952 (Big Data Research) and IM949 (Data Visualization in Policy). Key research grants include leadership roles in the CAPTURED project (2024-2025) exploring UK green economy transitions and co-investigator roles in ESRC-funded projects on AI and climate adaptation. His work emphasizes participatory methods for knowledge co-production with stakeholders and citizens. Recent publications highlight his contributions to climate policy adaptation, pandemic model engagement, and modular model frameworks like ESSA@work. His computational models address water governance (WATERING), energy demand practices (HOPES), and transboundary dam impacts. He actively engages in science communication through YouTube and public workshops, such as the 2021 ‘Empowering Communities to Fight Climate Change’ event. Professional recognition includes the NCRM Reproducibility Bursary (2022) and ESRC Policy Fellowship (2022). His research bridges computational methods with social science theory, aiming to inform equitable policy design through participatory and complexity-aware approaches.

• Complexity Science
• Computational Modelling for Public Policy
• Agent-based Modelling
• +۵ مورد دیگر

Dr. Rob van Gent is a Researcher at the Mathematical Institute within the Faculty of Science at Utrecht University. His work focuses on the history of astronomy, celestial cartography, and historical scientific instruments. He has contributed extensively to studies of star catalogs, medieval astronomical instruments like astrolabes, and the evolution of celestial maps from antiquity to modern times. Key research interests include the analysis of historical star atlases (e.g., Cellarius' Harmonia Macrocosmica), cross-cultural astronomy transmission (e.g., Al-Sufi's influence), and the digitization of historical astronomical resources. He served on the editorial board of KNAW Press from 2009 to 2010, reflecting his engagement in scholarly publishing. With over 44 publications, van Gent explores topics ranging from ancient eclipse records to the origins of telescopic technology. His work bridges historical documentation with modern astronomical practices, particularly through projects like the IAU Working Group on Star Names. He actively contributes to public understanding of astronomy history through publications and digitization efforts of rare celestial maps and instruments.

• History of Astronomy
• Celestial Cartography
• Historical Scientific Instruments
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Omri Abend is an Associate Professor at The Hebrew University of Jerusalem, affiliated with the School of Computer Science and Engineering and serving as Chair of the Department of Cognitive and Brain Sciences. His research lies at the intersection of Computational Linguistics, Natural Language Processing, and Cognitive Science, with a focus on semantic representation and language acquisition modeling. His primary research interests include: Computational modeling of child language acquisition Semantic representation frameworks, particularly Universal Conceptual Cognitive Annotation (UCCA) Statistical learning and machine translation Unsupervised grammar learning and lexical relation induction Cross-lingual and cross-domain alignment in language models Evaluation methodologies for NLP systems His recent publications demonstrate a strong trend toward analyzing large language models (LLMs), exploring human-like patterns in AI, improving evaluation metrics, and applying NLP to humanitarian domains such as Holocaust testimony analysis. His work combines theoretical linguistic insights with practical machine learning applications. Scientific awards include: Outstanding Paper Award at ACL 2017 Area Chair Award for Best Paper in the Track at ACL 2023 He has supervised and collaborated with numerous researchers and students across projects in semantic parsing, machine translation, and cognitive modeling. His work has been supported by community-wide initiatives such as the MRP shared tasks, which he co-organized. He also leads research on ethical AI, open human feedback, and the computational analysis of historical narratives. Omri Abend leads several research teams focused on: The development and application of the UCCA framework for semantic annotation Cross-lingual and cross-domain knowledge representation in LLMs Computational modeling of language acquisition Evaluation and improvement of NLP systems Application of NLP to digital humanities and historical testimony analysis

• Computational Linguistics
• Natural Language Processing
• Semantic Representation
• +۹ مورد دیگر

Dr. José Miguel Rojas is a Lecturer in Software Testing at the University of Sheffield's Department of Computer Science. He holds a PhD from the Technical University of Madrid and has held roles including Research Associate at the University of Sheffield and Lecturer at the University of Leicester. His research focuses on automated software testing, search-based techniques, and education in software engineering. Education: PhD in Software and Systems (Technical University of Madrid, 2013). Research Interests: Automated test generation, mutation testing, empirical software engineering, and teaching methodologies for testing. He leads the development of tools like EvoSuite and Code Defenders , which advance unit test generation and education through gamification. Key Publications include work on test suite generation effectiveness, mutation testing games, and accessibility testing for mobile apps. Awards include ACM Distinguished Paper Awards for contributions to testing methodologies. Grants: PI on EPSRC-funded projects like 'Accelerating Software Development using Gamification' and Co-PI on the UKRI Trustworthy Autonomous Systems Node. Labs/Teams: Active in the Testing Research Group and contributes to the Code Defenders educational platform.

• Automated Software Testing
• Search-Based Software Engineering
• Empirical Software Engineering
• +۳ مورد دیگر

Dr. Esra Suel is an Associate Professor in City Modelling at the University College London's Centre for Advanced Spatial Analysis (CASA) since 2024. She holds a part-time role as Senior Scientist at ETH Zurich's Future Cities Lab. Her expertise spans urban systems, environmental health, and geomatic engineering. She earned a PhD in Urban Systems and Transport Planning from Imperial College London (2016), and holds degrees from Sabanci University and the University of Michigan. Research Interests: Dr. Suel focuses on the intersection of urban environments and health, leveraging street-view imagery and machine learning to assess greenspace impacts on cardiovascular health, mental well-being, and urban inequality. Her work also explores transport equity, air quality modeling, and sustainable city indicators. Recent studies include large-scale slum mapping in Africa and global urban health benchmarking tools. Key Contributions: Her 2025 studies link greenspace exposure to depression risk reduction in US women and reveal cardiovascular health disparities through street-level analysis. Earlier work pioneered air quality estimation via satellite imagery in data-scarce regions. She co-developed KidSat, a poverty-mapping dataset using satellite imagery. Awards: MRC Rutherford Fellowship (2018) Labs: CASA's Urban Analytics Lab, Future Cities Lab (ETH Zurich) Grants: Wellcome Trust-funded Healthy Cities project, MRC funding Her interdisciplinary approach bridges geospatial technologies with public health, contributing to UN Sustainable Development Goals 3 and 11.

• Urban Planning
• Environmental Health
• Transportation Engineering
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Stéphane MAAG is a Professor at Telecom SudParis, associated with the SAMOVAR research laboratory. His work focuses on formal methods for protocol validation, network security, and distributed systems monitoring. He has contributed to advancing testing methodologies for mobile ad-hoc networks (MANETs), IoT protocols, and wireless communication systems. His research integrates machine learning techniques for automation and has been applied to web testing frameworks and ERP systems. Key research areas include protocol performance evaluation, trust management in networks, and curriculum design for computer science ethics. His work spans both academic surveys (e.g., European ethics education studies) and technical innovations (e.g., proactive interoperability solutions for wireless routing). Publications emphasize practical applications of formal methods, with over 50 peer-reviewed articles in journals like International Journal of Ethics Education , Computer Communications , and IEEE Transactions . His work bridges theoretical foundations with real-world systems like ODOO ERP and SIP protocols.

• Network Protocol Validation
• Formal Methods in Software Engineering
• Mobile and Wireless Networks (MANETs/IoT)
• +۳ مورد دیگر

Alexa T. McCray, PhD , is Professor of Medicine at Harvard Medical School and Beth Israel Deaconess Medical Center, and a co-founder of the Department of Biomedical Informatics (DBMI). She has played a transformative role in national biomedical informatics infrastructure through leadership at the National Library of Medicine and NIH. Institution: Harvard Medical School, Beth Israel Deaconess Medical Center Leadership: Co-Founder, Department of Biomedical Informatics Research Focus: Knowledge representation, data interoperability, undiagnosed diseases, research culture Major Projects: Undiagnosed Diseases Network (UDN), UMLS, ClinicalTrials.gov Dr. McCray's research centers on overcoming persistent challenges in the curation, dissemination, and exchange of scientific and clinical information. Her work spans knowledge representation, biomedical discovery infrastructure, and patient engagement in rare disease research. She has pioneered efforts in health data standardization, interoperability, and the ethical and practical dimensions of open science. The recent publications highlight a strong trend in patient-centered research, particularly in rare and undiagnosed diseases, genomic medicine, and health literacy. Her work increasingly integrates informatics with patient experience, data sharing ethics, and collaborative science. Themes include natural language processing, cohort resource mapping, and research culture reform, reflecting a broad impact across biomedical informatics and translational science. Scientific Awards and Honors: Elected to the National Academy of Medicine (2001) Fellow, American Association for the Advancement of Science Fellow, American College of Medical Informatics Fellow, International Academy of Health Sciences Informatics Chair, NASEM 2018 consensus study on Open Science by Design Immediate past chair, NASEM Board on Research Data and Information Dr. McCray has served as Co-Principal Investigator on major NIH-funded projects including the Undiagnosed Diseases Network Coordinating Center. She has advised numerous researchers and contributed to national policy discussions on data sharing and research integrity. Her leadership in academic publishing and scientific debate has shaped the field of medical informatics. She has led and contributed to major labs and teams, including the development of national resources such as ClinicalTrials.gov and the UMLS at the National Library of Medicine. At Harvard, she is affiliated with the Department of Biomedical Informatics and has collaborated extensively across institutions through the Undiagnosed Diseases Network and other consortia.

• Biomedical Informatics
• Knowledge Representation
• Clinical Information Exchange
• +۱۲ مورد دیگر

Jose-Luis Machado is an Associate Professor in the Department of Biology at Swarthmore College. His research focuses on temperate and tropical forest ecology , integrating plant physiological processes with community dynamics to study biodiversity maintenance and ecosystem functioning. Education: Ph.D. in Forest Resources, University of Minnesota M.S. in Botany, University of Vermont B.S. in Biology, Universidad de Los Andes, Colombia Research Interests: Comparative analysis of carbon, water, and nutrient cycling in forest ecosystems Physiological and demographic responses of understory seedlings to resource limitations Ecological impacts of invasive species like Japanese knotweed and Norway maple Development of digital herbarium tools for biodiversity research Key Publications: 2008 - Metabolic scaling in forest ecosystems (Ecology Letters) 2006 - Plant respiration and size relationships (Nature, Tree Physiology) 2003 - Grassland/savanna functional group differences (New Phytologist) 2002-2004 - Undergraduate-driven pedagogical research on soil-plant-atmosphere stoichiometry Collaborative Projects: Smithsonian Tropical Research Institute (long-term carbon budget studies) Community Population Ecology Lab at Pontificia Universidad Javeriana Multidisciplinary GIS initiatives in Crum Woods

• Biodiversity
• Temperate Forest Ecology
• Tropical Forest Ecology
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Lukasz (Luke) Ziarek serves as Associate Dean for Academic Affairs and Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His work bridges theoretical computer science with practical systems engineering, focusing on real-time capabilities in distributed environments and safety-critical applications. His educational foundation includes a PhD in Computer Science from Purdue University (2011) and a BS in Computer Science from the University of Chicago (2003). Ziarek's research centers on formal verification of distributed protocols , real-time systems engineering , and mobile/embedded computing . He pioneers session type theory for IoT security, develops real-time variants of Android (RTDroid) and Standard ML (RTML), and investigates UAV software reliability. His work consistently addresses the tension between theoretical guarantees and practical system constraints in concurrency, timing, and security. Recent publications (2022-2025) reveal three dominant trajectories: formal methods for rate-based session types in IoT protocols, performance analysis of visual SLAM systems for robotics, and security vulnerabilities in embedded platforms like ARM TrustZone. These threads converge on ensuring correctness and timeliness in resource-constrained distributed systems. His scientific accolades include the IEEE Region One Technological Innovation Award (2023) and NSF CAREER Award (2018), reflecting dual excellence in research and education. IEEE Region One Technological Innovation (Academic) Award, 2023 President Emeritus and Mrs. Meyerson Award for Distinguished Undergraduate Teaching and Mentoring, 2022 NSF CAREER Award, 2018 SEAS Early Career Teacher of the Year, 2016 Halstead Award for Outstanding Research in Software Engineering, 2009 Intel Fellowship, 2008 GAANN Fellowship, 2004 Ziarek directs significant research initiatives including a $900K NSF UAV infrastructure project (as PI) and a $1.7M MRI grant for connected vehicle testing. His funding portfolio spans real-time systems, compiler design, and pocket-scale data management, emphasizing collaborative, interdisciplinary approaches to software reliability. CRI:CI-New UAV Infrastructure ($900K, PI 31%) NSF CAREER: Real-time Object-Oriented Systems ($500K, PI 100%) MRI: iCAVE2 Vehicle Testing ($1.7M, co-PI 14%) III: Just-in-Time Data Structures ($499K, co-PI 50%) II-EN: MLton Compiler Research ($606K, PI 63%) He leads an open-source ecosystem including RTDroid (real-time Android), Multi-MLton (parallel SML compiler), and BlueSeal (Android security analyzer), fostering community-driven advances in systems software.

• Concurrency and Parallelism
• Real-time Systems
• Distributed Systems
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Kashif Rajpoot is a Professor of Medical AI and Deputy Head of the School of Computer Science at the University of Birmingham Dubai. He is actively engaged in research at the intersection of artificial intelligence and medicine, with a focus on medical image analysis, cardiac electrophysiology, computational pathology, and data science. His educational background includes a PhD in Engineering Science from the University of Oxford (2009) and an MSc in Digital Signal & Image Processing from De Montfort University (2003). His research interests span the development of AI-driven solutions for medical diagnostics and analysis. Key areas include automated interpretation of whole slide images in pathology, signal processing in cardiac electrophysiology, and biomarker discovery for neurological and metabolic disorders. His work combines computational modeling with experimental validation in biomedical contexts. The recent publications reflect a strong trend toward integrating deep learning and signal processing in healthcare, particularly in digital pathology and cardiovascular imaging. His contributions include software tools like ElectroMap for high-throughput cardiac data analysis and methodological advances in NMR and histology image analysis. Unleashing the potential of AI for pathology: challenges and recommendations (2023) Validation of plasma protein glycation and oxidation biomarkers for autism (2023) Automated analysis of NMR spectra (2023) Handcrafted histological transformer for whole slide images (2023) High-resolution optical mapping in preclinical models (2022) Kashif Rajpoot has published over 60 papers in top-tier journals and conferences. His scientific contributions include interdisciplinary collaborations in AI for healthcare, cardiac imaging, and biomarker research. While specific grant details are not listed, his publication record suggests active funding and research leadership. He has contributed to open-source software development and methodological innovation in medical AI. He is involved in research teams focusing on medical AI, cardiac electrophysiology, and computational pathology, often collaborating with experts in pathology, cardiology, and biochemistry. His lab likely supports projects in AI-driven diagnostics, image analysis, and biomedical data science.

• Medical AI
• Medical Image Analysis
• Cardiac Electrophysiology
• +۷ مورد دیگر

Professor Richard Lucas holds a Sêr Cymru Research Chair in the Department of Geography and Earth Sciences at Aberystwyth University. He has previously held academic and research positions at the University of New South Wales, the Australian Federal Government, and Swansea University. His research focuses on Earth observation and ecosystem dynamics, particularly in terrestrial and coastal environments. His expertise lies in utilizing satellite remote sensing to quantify ecosystem responses to climatic and anthropogenic changes. Key research areas include forest biomass estimation, mangrove monitoring, land cover change detection, and environmental sustainability. He has developed innovative frameworks such as the Earth Observation Data for Ecosystem Monitoring (EODESM) and leads the national Living Wales project for land cover monitoring. His recent publications highlight a strong trend in using multi-source Earth observation data—especially Landsat, Sentinel, and GEDI lidar—for global and regional environmental assessments. These works span topics such as mangrove resilience under tropical cyclones, habitat mapping, soil moisture analysis, and biomass modeling, reflecting a cohesive focus on sustainable ecosystem management through advanced remote sensing. Professor Lucas leads several externally funded research projects with agencies including the European Space Agency, the Welsh Government, and the Australian Research Council. Notable initiatives include CCI-BIOMASS, EO4AgroClimate, and the Global Mangrove Watch. His datasets, such as the Australia's Mangrove Portal and Plant Biomass Library, are publicly available and widely used in the scientific community. He has contributed significantly to policy-relevant science, with research impacting coastal land use policy and supporting UN Sustainable Development Goals, particularly those related to climate action and life on land. His work has been featured in media outlets and policy documents, demonstrating broad societal impact. Professor Lucas is actively involved in international collaborations and scientific outreach, regularly presenting at workshops and conferences such as Living Coasts and Dynamics Coasts. He mentors researchers and contributes to editorial and peer-review activities, further strengthening the scientific community in Earth observation and environmental informatics.

• Remote Sensing
• Earth Observation
• Ecosystem Dynamics
• +۱۰ مورد دیگر

Marco Pizzolato is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing with a focus on Magnetic Resonance Imaging (MRI), particularly diffusion MRI and biophysical modeling. He is also affiliated with the inter-departmental Microstructure & Plasticity (MAP) research group and has held visiting positions at the University of Verona, EPFL, and DRCMR. His educational background includes a PhD in Signal and Image Processing from INRIA Sophia Antipolis, a Master’s in Bioengineering from the University of Padua, and a Bachelor’s in Biomedical Engineering from the same institution. He previously served as an Assistant Professor at DTU and was a postdoctoral researcher under the Marie Curie COFUND Eurotech programme. Dr. Pizzolato's research centers on image and signal denoising, inverse problems, optimization, diffusion MRI, tractography, and Monte Carlo simulations. He actively contributes to the development of microstructural models for brain imaging, with applications in neurodegenerative diseases and brain connectivity. His work aligns with UN Sustainable Development Goals, particularly in advancing education and health through imaging technology. The recent publications reflect a strong trend in advancing diffusion MRI techniques, including ACID imaging, microscopic propagator modeling, myelin integrity mapping, and multi-scale white matter organization. These works emphasize biophysical accuracy, model validation, and integration across imaging modalities and species. Magna Cum Laude , ISMRM 2020 Magna Cum Laude , ISMRM 2022 First Place , Macaque Validation Challenge at ISBI 2018 First Place (Overall and HCP) , IronTrack Challenge 2019 (MICCAI) MICCAI Student Travel Award 2015 He has supervised PhD students such as Thøgersen, T. L. and Corral Bolaños, M. in projects related to microstructure MR imaging and myelin mapping. He has also been involved in significant grants and collaborative projects, including the Multimodal Microstructure-Informed Connectivity (MMINCARAV) initiative between Inria and EPFL, and the Sinergia consortium for Brain Communication Pathways . He co-organized multiple international events, including the MICCAI CDMRI workshops and challenges (2019–2021), and the ESMRMB Leaps in Microstructure Imaging workshop (2024). Dr. Pizzolato is an active member of the scientific community, serving as an editor for MICCAI workshop proceedings, a reviewer for major journals and conferences, and an invited speaker at ISMRM 2025. He leads and participates in several ongoing research projects at DTU focused on quantitative imaging, myelin mapping, and MRI-based connectivity, demonstrating sustained research leadership and external funding success.

• Magnetic Resonance Imaging (MRI)
• Diffusion MRI
• Image and Signal Denoising
• +۱۰ مورد دیگر

Cassia Trojahn is a permanent Lecturer at the University of Toulouse 2 Jean Jaurès , affiliated with IRIT - UMR 5505, Department of Mathematics and Computer Science. Her career spans institutions in France, Portugal, Brazil, and the Netherlands, with roles including Expert Engineer at Joseph Fourier University and Post-Doc at INRIA Rhône-Alpes. Education Semantic Web, Ontology Alignment, Business Intelligence (University of Toulouse) Functional Programming (Haskell, Scala), Information Extraction (Pierre Mendès University) Graph Theory and Complexity (University of Évora) Research Interests : Knowledge representation and semantic web technologies Ontology alignment methodologies (argumentation, complex alignments, holistic approaches) Earth observation data integration with contextual information Open science and FAIR data principles Argumentation frameworks for mapping reconciliation Query rewriting with complex correspondences Advising : Co-supervised 5 PhD theses across France and Brazil, including: Jordane Dorne (2018-2021) - Earth observation semantic change detection Élodie Thiéblin (2016-2019) - Complex ontology alignment Roger Granada (2011-2015) - Hierarchical relations extraction Projects : Participated in international (CAMELEON, MULTIFARM) and European (EFFECTOR, CANDELA, SEALS) projects focused on multilingual ontology alignment, maritime situational awareness, and semantic earth observation data analysis.

• Knowledge Representation
• Ontology Engineering
• Semantic Web
• +۶ مورد دیگر

Sebastián Ferrada is an Assistant Professor at the Data & Artificial Intelligence Initiative of Universidad de Chile. He also serves as Young Researcher at the Institute for Foundational Research on Data (IMFD) and Collaborating Researcher at the National Center for Artificial Intelligence Research (CENIA). His research focuses on Knowledge Graphs, with special emphasis on extraction, management, and applications for querying, browsing, and AI systems. His academic background includes: PhD in Computer Science (2021), Universidad de Chile MSc in Computer Science (2017), Universidad de Chile BEng in Computer Science (2017), Universidad de Chile Sebastián's research explores several key areas: Multimedia Databases with applications to Wikimedia Commons images Graph Databases and Knowledge Graphs construction Federated Data Management across heterogeneous RDF sources SPARQL query extensions for similarity-based operations Graph data management and compression techniques His recent publications demonstrate strong trends in knowledge graph construction, similarity-based querying, and efficient graph data management. These works combine theoretical advancements with practical implementations in real-world systems like IMGpedia and MillenniumDB. Scientific achievements include: Best Paper Award at CoopIS 2023 Best Demonstration Award runner-up at SIGMOD/PODS 2024 Best Student Paper (Resources Track) and Best Poster at ISWC 2017 First prize in CLEI 2017 for his Master's thesis Sebastián currently leads the Fondecyt project on graph data management and contributes to the U-Inicia project on AI processes in graph databases. He serves on the editorial board of Transactions on Graph Data and Knowledge.

• Knowledge Graphs
• Graph Databases
• Multimedia Databases
• +۳ مورد دیگر

Prof. Dr. rer. nat. habil. Stephan Kopf is a faculty member at the Faculty of Spatial Information, where he holds the Professorship in Informatics and Geoinformatics. He actively contributes to research in geographic information systems (GIS), computer graphics, computer vision, and multimedia technologies. His academic leadership roles include serving as Dean and as a member of the Faculty Council, with advisory roles in the Senate. His research spans crowd simulation , image/video retargeting , augmented reality platforms , and interactive learning systems . He focuses on algorithm development for GIS, temporal effects in re-captured video, and scalable solutions for classroom interactivity. His work frequently integrates machine learning, mobile computing, and geospatial data. For teaching, he oversees courses such as Internet Technologies, Informatics, and Programming in degree programs like Geoinformatics/Management and Surveying. He supervises theses involving programming-centric topics like mobile app development , VR applications , and astronomical analysis of geospatial data .

• Geoinformatics
• Computer Graphics
• Computer Vision
• +۵ مورد دیگر