جستجوی استاد راهنمای دانشگاهی

Josien Pluimمشاهده پروفایل

استاد

• Medical Image Analysis
• Image Registration
• Image Segmentation
• +۱۲ مورد دیگر

Josien Pluim is a Full Professor of Medical Image Analysis at Eindhoven University of Technology (TU/e), where she leads the Medical Image Analysis group and serves as vice-dean of the Department of Biomedical Engineering. She also holds a part-time professorship at the University Medical Center Utrecht. Her research is centered at the intersection of artificial intelligence and clinical medicine, with strong affiliations to EAISI (Eindhoven Artificial Intelligence Systems Institute) and the EAISI Health initiative. Her academic background includes a Master's in Computer Science from the University of Groningen (1996), specializing in Scientific Computing and Imaging, followed by a PhD (2001) from the Image Sciences Institute at UMC Utrecht on multimodality image registration using mutual information. She advanced from assistant to associate professor at UMC Utrecht before joining TU/e as a Full Professor in 2014, with a concurrent part-time appointment at UMC Utrecht since 2015. Pluim’s research interests span medical image analysis, including image registration, segmentation, detection, and deep learning, with clinical applications in neurology and oncology. She investigates both methodological development and real-world clinical translation. Recent work emphasizes generative AI for synthetic data, robustness in deep learning models, and super-resolution techniques for brain MRI. Her publications reveal a strong trend toward addressing data scarcity, generalization, and evaluation in medical AI, particularly through simulation and diffusion models. She has co-authored over 250 peer-reviewed papers and is recognized with prestigious fellowships: Fellow of the MICCAI Society IEEE Fellow Pluim has served in leadership roles across the academic community, including Associate Editor for journals such as IEEE Transactions on Medical Imaging , IEEE TBME , and Medical Image Analysis . She has chaired major conferences like WBIR 2006 and MICCAI 2010, and served on the Executive Board of the MICCAI Society. She actively supervises research and educational projects, including team challenges and capstone courses in medical image analysis. Her group is involved in significant collaborative research, such as the EU-funded openGTN project, which supports PhD training in generative models for medical imaging. She also contributes to scientific advisory boards, including the Hanarth Fonds.

• Machine Vision
• Supply Chain Optimization
• Optical Imaging
• +۵ مورد دیگر

Professor Sang-Heon Lee is a faculty member at the University of South Australia, affiliated with the UniSA STEM division. His research spans interdisciplinary domains including machine vision, supply chain optimization, and material science. His research interests focus on developing advanced imaging systems for food safety (e.g., aflatoxin detection in almonds), optimizing reverse supply chains for electronic waste and solar panels, and engineering nanocomposites for construction materials. He also investigates biomedical imaging techniques for mucociliary transit assessment and clinical coding methodologies. The 15 most recent publications highlight his work in multispectral/hyperspectral imaging, fuzzy logic optimization, and nanomaterials. Key trends include non-destructive food testing, sustainable e-waste management, and biomedical imaging analysis. As a research degree supervisor, he contributes to academic training in these areas. No scientific awards or lab affiliations were explicitly mentioned in the provided text.

• Greek Texts on Horse Medicine
• Byzantine Empire Studies
• Critical Edition of Classical Texts
• +۴ مورد دیگر

Anne-Marie Doyen is a distinguished academic with a Doctor of History, Art and Archeology from the University of Oxford. Her expertise spans Greek texts on horse medicine, Byzantine studies, and critical editions of classical works. Education Doctor of History, Art and Archeology, University of Oxford Her research focuses on ancient wisdom traditions, particularly the evolution of phronesis (practical wisdom) and prudence in Greek philosophy. She specializes in editing and translating Greek veterinary texts, such as the Parisinus Graecus 2244 , exploring their content, transmission, and historical context. Recent publications highlight her work on Louvain’s classical scholarship traditions, abridging ancient texts, and analyzing Apsyrtos of Clazomenae’s contributions. Though not explicitly listed, her activities include organizing international symposia and presenting at conferences on classical literature and veterinary history since 2006.

• Plant Breeding and Genetics
• Quantitative Genetics
• Sustainable Crop Production
• +۷ مورد دیگر

Dr. Fawad Ali is an Advance Queensland Industry Research Fellow at Griffith University's Centre for Planetary Health and Food Security, specializing in environmental sustainability and management. His research focuses on sustainable crop production systems with particular expertise in tropical fruits, rice, and coffee breeding. Education: PhD in Plant Breeding and Genetics, Southern Cross University (2016-2021) MSC (Hons) in Plant Breeding and Genetics, University of Agriculture Faisalabad (2010-2012) BSC (Hons) in Plant Breeding and Genetics, University of Agriculture Faisalabad (2006-2010) Dr. Ali's research spans plant breeding, quantitative genetics, and environmental remediation, with emphasis on developing sustainable agricultural systems that address food security and environmental challenges. His work integrates molecular biology, field trials, and computational approaches to improve crop resilience and quality. His publication record reveals strong focus areas in environmental remediation (particularly arsenic and heavy metal contamination), tropical fruit breeding (papaya and citrus), and stress-responsive crop improvement. Recent work demonstrates innovative approaches combining microbial solutions with plant systems for pollution mitigation. Awards & Recognition: Best Poster Award at TropAg 2019 Qualified Person (QP) certification for Intellectual Property and Plant Breeding Rights (IP Australia, 2022-2025) Dr. Ali actively supervises doctoral research, currently serving as Associate Supervisor for genomic platform development in Australian papaya. His funded research includes the $646,000 Advance Queensland Industry Research Fellowship project 'Invigorating the Coffee Industry in Tropical North Queensland' and the 'National Papaya Breeding and Evaluation Program' ($1.5M). He collaborates extensively with industry partners to translate research into practical agricultural solutions, particularly in specialty coffee and tropical fruit production. His laboratory work encompasses plant tissue culture, molecular biology techniques, field-based breeding trials, and environmental remediation experiments, with strong emphasis on industry-relevant outcomes and consumer preferences.

Haim Dubossarskyمشاهده پروفایل

مدرس

• Natural Language Processing
• Artificial Intelligence
• Historical Linguistics
• +۳ مورد دیگر

Haim Dubossarsky is a Lecturer in Computer Science at the School of Electronic Engineering and Computer Science , Queen Mary University of London , and an Affiliated Lecturer at the Language Technology Lab , University of Cambridge. His work bridges Natural Language Processing (NLP) , Artificial Intelligence (AI) , and interdisciplinary studies in linguistics , cognitive neuroscience , and mathematical modeling . Dr. Dubossarsky's research explores semantic change and language variation through computational methods, focusing on: Detecting historical and contemporary linguistic shifts Integrating neurocognitive insights into NLP systems Developing interpretable AI models for language tasks Recent publications highlight his contributions to multilingual NLP , word-in-context (WiC) tasks , and robust semantic analysis . His work includes collaborations on hate speech detection , topological representations , and temporal modeling in language evolution. Dr. Dubossarsky leads projects funded by: UKRI AI Hub (£1,026,205, 2024–2029) RJ Riksbankens Jubileumsfond (£381,511, 2022–2027) Innovate UK (£320,887, 2024–2025) He supervises PhD students at Queen Mary's Centre for Human-Centred Computing , including Alaa Bazaid , Roksana Goworek , and Dina Pisarevskaya , working on topics like multilingual polysemy disambiguation and language variation analysis .

• Artificial Intelligence
• Horticulture
• Growers
• +۵ مورد دیگر

Feije de Zwart is a dedicated researcher at Wageningen University & Research, focusing on Horticulture Technology. With a robust presence in horticultural engineering, de Zwart contributes extensively to the fields of energy efficiency, greenhouse climate control, and sustainable crop production. Active in Artificial Intelligence and Horticulture research domains Current projects emphasize water resource management and hydrogen energy integration in greenhouses De Zwart's research spans Arid Zones , Crop Production , and Irrigation , with a strong emphasis on data-driven approaches and technological innovation in controlled-environment agriculture. Recent publications analyze energy-saving screen materials , dynamic climate control , and autonomous greenhouse systems , reflecting a trend toward AI integration and microclimate optimization.

Lindsay Fernandez-Rhodesمشاهده پروفایل

استادیار

• Genetic Epidemiology
• Health Disparities
• Obesity Research
• +۵ مورد دیگر

Lindsay Fernandez-Rhodes serves as Assistant Professor of Biobehavioral Health in the College of Health and Human Development at Pennsylvania State University, with dual affiliation at the Penn State Cancer Institute. Her research focuses on genetic and sociocultural determinants of health disparities, particularly among Hispanic/Latino populations through the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Her primary research interests span Genetic Epidemiology , Health Disparities , and Sociocultural Determinants of Obesity . She investigates how genetic ancestry interacts with acculturation, socioeconomic status, and environmental factors to influence cardiometabolic outcomes. Her work integrates multi-omics approaches with life course epidemiology to uncover mechanisms driving health inequities in minority populations. Analysis of her recent publications reveals a strong emphasis on Hispanic/Latino health across multiple domains: genomic fine-mapping ( 2023, 2025 ), epigenetic mediation of socioeconomic effects ( 2024 ), pubertal development ( 2025 ), cognitive aging ( 2023 ), and cardiometabolic disease ( 2024, 2025 ). Her methodological innovations include synthetic data applications for privacy preservation ( 2025 ) and commentary on genomic inclusion ( 2023 ). Dr. Fernandez-Rhodes actively contributes to major collaborative initiatives including HCHS/SOL, PAGE consortium, and TOPMed. Her work has secured substantial NIH funding for population genomics research, though specific grant details aren't listed in the provided text. She mentors graduate students in biobehavioral health and genetic epidemiology through Penn State's PhD programs. Her laboratory work centers on the Penn State Cancer Institute's Cancer Control program, with additional collaborations through the Center for Research on Tobacco and Health and Office for Cancer Health Equity. She utilizes HCHS/SOL data infrastructure and Penn State's biostatistics/bioinformatics shared resources for multi-omics analyses.

Yongmin Liمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Artificial Intelligence
• +۱۲ مورد دیگر

Professor Yongmin Li is a Senior Member of the IEEE and Senior Fellow of the Higher Education Academy at the Department of Computer Science , Brunel University London , within the College of Engineering, Design and Physical Sciences . His work spans multiple domains including data science, artificial intelligence, medical imaging, and foveated rendering. He has consistently been ranked in the world's top 2% scientists by Elsevier's Standardized Citation Indicators since 2020. Research Interests include Data Science Medical Imaging Computer Vision Biomedical Engineering Natural Language Processing Set-Membership Filtering Scientific Awards include 1st Place, RETOUCH Challenge (Online), MICCAI 2023 2nd Place, FeTA Challenge, MICCAI 2022 Most Influential Paper over the Decade Award, MVA 2019 Best Paper Award, Bioimaging 2018 VC Prize, Brunel University 2015

• Digital Humanities
• Philology
• Lexicography
• +۵ مورد دیگر

Christian D'AGATA is a Research Fellow at the Department of Humanities, University of Catania, conducting research on 'Philology and Digital Lexicography of 19th and 20th-Century Italian Literature' under the CHANGES (PNRR) - Spoke 3 project on Digital Verismo. His work focuses on creating digital scholarly editions of major Italian literary works through computational analysis and digital philology. His educational background includes a PhD in Interpretation Sciences from the University of Catania with a thesis on 'The Names of the Rose,' a Master's in Digital Humanities from Ca' Foscari University, and a degree in Modern Philology with a thesis on Gadamer and Eco. He completed a three-month internship at the Cologne Centre for eHumanities (CCeH). D'AGATA's research integrates philology, lexicography, hermeneutics and digital humanities methodologies to analyze literary works by Umberto Eco, Luigi Pirandello, Giovanni Verga, and other major Italian authors. His computational studies focus on textual variants, digital annotation systems, and the relationship between traditional literary criticism and digital media. He has developed specialized expertise in XML-TEI text encoding and digital edition platforms. His publication record demonstrates a consistent focus on digital scholarly editions, particularly for works like The Name of the Rose , Il fu Mattia Pascal , and Cesare Pavese's poetry. His research shows progression from theoretical foundations of digital philology toward practical implementation of hypereditions and digital archives. Member of the board of the Association for Humanistic Computing and Digital Culture (AIUCD) since January 2024 Program Committee member for the 13th AIUCD Annual Conference (May 2024) Active participant in multiple national research projects including PRIN Paves-e and POIChILIA D'AGATA actively supervises the development of digital humanities projects including the Hyperedition of Il fu Mattia Pascal within the National Digital Edition of Pirandello's Complete Works. His research team at CINUM (Center for Humanities Computing) collaborates with Mondadori publisher on these scholarly editions. He has presented his research at over 15 international conferences between 2020-2024, demonstrating strong engagement with the digital humanities community.

Adam Hirschمشاهده پروفایل

استاد

• Wills and Trusts
• Debtor/Creditor Law
• Property Law
• +۳ مورد دیگر

Adam Hirsch is a Professor at the University of San Diego School of Law , where he joined the faculty in 2013. He previously served as the William & Catherine VanDercreek Professor of Law at Florida State University. Education : PhD, 1987, Yale University JD, 1982, Yale University MPhil, 1982, Yale University MA, 1979, Yale University AB, 1976, Vassar College His research interests focus on Wills and Trusts , Debtor/Creditor Law , and American Legal History , with a particular emphasis on modernizing estate planning through electronic wills and probate law . His work bridges historical analysis with contemporary legislative challenges. Scientific Awards : George Washington Egleston Prize for best dissertation on American history Roger Traynor Fellow at Hastings College of Law Hirsch is an academic fellow of the American College of Trust and Estate Counsel and serves on the Florida Historical Commission. His publications include authoritative legal annotations and empirical analyses of wealth transfer law.

Torsten Zeschمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Educational Technology
• +۶ مورد دیگر

Prof. Dr.-Ing. Torsten Zesch serves as Deputy Scientific Director, Member of the Executive Board, and Head of the Research Professorship for Computational Linguistics at FernUniversität in Hagen since March 2022. He previously held W2 and W1 Professorships for Sprachtechnologie (Language Technology) at Universität Duisburg-Essen from 2014-2022. Zesch is also Spokesperson of the Advisory Board of the German Society for Computational Linguistics and Language Technology (GSCL) since 2024, having previously served as GSCL President from 2018-2024. Dr. Zesch completed his dissertation (Dr.-Ing.) in Computer Science at Technische Universität Darmstadt in 2009. His research spans robust language processing systems, analysis of non-standard language structures, and educational applications of language technology, with particular focus on automatic content scoring and spelling error correction for learner language. Zesch's recent publications reveal a strong focus on integrating language technology with educational applications. His work demonstrates expertise in developing practical NLP solutions for educational assessment, including transformer-based spelling error feedback systems, hierarchical automatic scoring methods, and leveraging LLMs for educational applications despite cold-start problems. He also maintains significant research in hate speech detection, particularly in multimodal contexts and visio-linguistic models. As leader of the Computational Linguistics research professorship within the CATALPA research center, Zesch directs a team investigating how language technology can support educational processes. His projects DAKODA and KISS-Pro focus on language acquisition and educational applications. He has contributed significantly to the field through numerous publications in top NLP and educational technology venues, with over 100 publications spanning from 2006 to present.

Yomna Abdelrahmanمشاهده پروفایل

استاد

• Human-Computer Interaction
• Thermal Imaging
• Usable Security
• +۶ مورد دیگر

Dr. Yomna Abdelrahman is a Professor of Usable Security and Privacy at the Bundeswehr University Munich . Her research focuses on thermal imaging for security and privacy , virtual reality usability, eye tracking , and biometric authentication . She collaborates with researchers like Florian Alt and Albrecht Schmidt on projects exploring how thermal sensing can enhance user identification and privacy awareness . Key Research Areas : Thermal Imaging, Human-Computer Interaction, Virtual Reality, Password Security, Biometric Authentication, Eye Tracking, Privacy Her recent publications address VR emotion detection , password usability , and privacy implications of thermal imaging . She has contributed to conferences like CHI, MUM, and INTERACT, often examining security-privacy trade-offs and non-invasive biometric systems . Notably, her work on thermal attacks reveals vulnerabilities in mobile authentication through thermal residue. She holds a PhD in Computer Science from the University of Stuttgart (2018), where her thesis, "Thermal Imaging for Amplifying Human Perception," laid the foundation for her later work on thermal-based interaction and cognitive load estimation . Her collaborations span diverse domains, from smart home notifications to industrial worker assistance , reflecting her interdisciplinary approach to usable security and interactive systems .

Krzysztof J. Kochutمشاهده پروفایل

استاد

• Knowledge Graphs
• Ontologies
• Semantic Web
• +۷ مورد دیگر

Krzysztof J. Kochut is a Professor in the School of Computing at the University of Georgia. His career at UGA spans from Limited Term Assistant Professor (1987–1988) to his current professorial role since 2001. He holds a Ph.D. in Computer Science from Louisiana State University (1987) and an M.S. from the University of Warsaw (1982). Education: Ph.D., Computer Science, Louisiana State University (1987) M.S., Computer Science, University of Warsaw (1982) His research focuses on knowledge graphs, ontologies, semantic web technologies, bioinformatics, distributed systems, and computational intelligence. He has developed frameworks for knowledge graph embedding, entity summarization, and semantic resource federation. Recent publications highlight knowledge graph mining, random walk-based embeddings, and relation prediction using large language models. Funded by NIH and NSF, his work addresses challenges in biomedical data integration and dark proteome annotation. Scientific Awards: Student Career Success Influencer Award 2024 Student Career Success Influencer Award 2022 Outstanding Faculty Service Award 2016 Best Paper Award 2015 Professor Kochut has received grants for projects like Annotating dark ion-channel functions using knowledge graph mining (NIH, 2021–2025) and Integrated Technology Resource for Biomedical Glycomics (NIH, 2002–2008). He leads the development of tools such as GTXplorer for glycosyltransferase analysis and participates in semantic web initiatives.

Frank Bergmannمشاهده پروفایل

پژوهشگر

• Computational Systems Biology
• Biochemical Network Modeling
• Simulation Software Development
• +۳ مورد دیگر

Dr. Frank Bergmann is a Researcher at BioQuant (Center for Quantitative Analysis of Molecular and Cellular Biosystems) within the Faculty of Biosciences at Heidelberg University. His work focuses on computational systems biology with particular emphasis on developing simulation tools and standards for biochemical network modeling. He maintains an active research profile with numerous publications spanning from 2011 to 2018 and teaches programming courses including Python and C++. His research interests center around computational systems biology, with specific expertise in biochemical network modeling, simulation software development, and systems biology standards. Dr. Bergmann has made significant contributions to the development of COPASI (Complex Pathway Simulator) and SBML (Systems Biology Markup Language), which are widely used tools and standards in the field. His work enables researchers to create, simulate, and share computational models of biological processes. Analysis of his publication record reveals a consistent focus on developing standards and infrastructure for reproducible computational biology. His work spans model representation (SBML), simulation experiment description (SED-ML), data exchange formats (SBtab), and model archiving (COMBINE). These contributions have helped establish frameworks that enable collaborative, reproducible research in systems biology across international boundaries. Dr. Bergmann actively collaborates with researchers worldwide, as evidenced by his extensive co-authorship network across multiple publications. His work bridges computer science, mathematics, and biological sciences, contributing to Heidelberg University's strong presence in molecular life sciences research.

Len Dawsمشاهده پروفایل

استاد مدعو

• Machine Learning
• Adversarial Machine Learning
• Noisy Label Learning
• +۳ مورد دیگر

Len Daws serves as an Adjunct Professor in the Department of Computer Science at Rowan University's College of Science & Mathematics while concurrently holding a Sr. Engineering Manager position at Lockheed Martin in Moorestown, NJ. With over 12 years of teaching experience across New Jersey state and community colleges, he is currently in his sixth year instructing the Computers & Society course at Rowan University, focusing on large-scale software system development and integration. His research specializes in machine learning robustness under adversarial conditions, particularly addressing noisy label learning challenges and cybersecurity threats in AI systems. Key contributions include modeling label noise dependencies across multiple annotators, developing contributor-aware defenses against backdoor attacks, and analyzing fundamental trade-offs between attack strength and detectability in adversarial settings. Analysis of his publication history reveals a consistent trajectory toward securing machine learning pipelines against sophisticated threats, with recent work emphasizing labeler-dependent noise modeling and spectral ranking techniques for truth extraction from unreliable sources. His scholarship bridges theoretical machine learning with practical defense mechanisms for real-world AI deployment.