جست‌وجوی استاد و پژوهشگر

• Cloud Computing
• Internet of Things
• Semantic Web
• +۳ مورد دیگر

Professor Euripides G.M. Petrakis serves as a Professor and Laboratory Director at the Technical University of Crete (TUC) within the School of Electrical and Computer Engineering. He has been a faculty member since 1999 and has directed the Intelligent Systems Laboratory since 2006. As a Senior Member of IEEE, he maintains an active research profile with over 175 publications and more than 4,000 Google Scholar citations. Education: Ph.D. in Computer Science (1993), University of Crete B.Sc. in Physics (1985), National University of Athens Professor Petrakis' research spans Cloud Computing, Internet of Things, Semantic Web, and Computer Vision. His work has evolved from early computer vision and image databases to modern information systems, semantic web technologies, and most recently cloud computing and IoT applications. His research demonstrates consistent innovation across multiple computing domains with practical implementations in healthcare, security, and smart systems. His recent publications reveal a strong focus on IoT architectures, cloud/fog computing optimization, semantic service descriptions, and real-time video processing with Apache Flink. The research shows increasing integration of blockchain for security, advanced scheduling algorithms for microservices, and semantic approaches to improve interoperability in distributed systems. Scientific Recognition: Best paper award at AINA 2024 TUC Excellence Award 2022 Keynote speaker at EIDWT-2025 Ranked in top 2% of scientists worldwide (Stanford rankings 2021-2023) Professor Petrakis has supervised numerous graduate students, resulting in over 120 co-authored papers. He has successfully secured substantial research funding, attracting more than 2.5 million euros for TUC through multiple EU and Greek government projects. His grant portfolio includes leadership roles in Horizon 2020, FP7, and national research initiatives spanning border surveillance, smart farming, healthcare systems, and semantic web technologies. As Director of the Intelligent Systems Laboratory, he leads research in cloud computing, IoT, semantic web, and computer vision. The lab has produced multiple system prototypes including IntelliSearch, Semantic Similarity tools, MedSearch, and WebSummarization systems. Current research directions focus on secure federated architectures for IoT, advanced service description frameworks, and real-time video analytics in distributed environments.

• Complex Geometry
• Kähler Geometry
• Stability of Algebraic Varieties
• +۵ مورد دیگر

Chi Li is an Associate Professor in the Department of Mathematics at Rutgers, The State University of New Jersey. Their research focuses on Complex Geometry, including canonical metrics in Kähler geometry, stability of algebraic varieties, and pluripotential theory. They hold an office in HLL-511 and can be contacted at cl1412@rutgers.edu. Research interests emphasize foundational aspects of geometric analysis with applications to algebraic structures. Recent work explores interdisciplinary applications in AI, such as anomaly detection, cross-lingual NLP, and large language model optimization. Key contributions include frameworks for domain-oriented model compression and dynamic routing in mixed LLMs. Publications span 2020–2025, addressing topics from turbulence forecasting to spatio-temporal recommendation systems. Notable trends include integration of geometric principles with machine learning methodologies. Extensive contributions to log anomaly detection (GLAD, Cat), time series meta-contrastive learning, and graph-based cross-lingual transfer. Active in developing interpretable imitation learning and uncertainty quantification techniques for in-context learning.

• Semantics
• Pragmatics
• Syntax-Semantics Interface
• +۳ مورد دیگر

Paul H. Portner is a Professor of Linguistics at Georgetown University, specializing in semantics and pragmatics with a focus on their interfaces with syntax. He holds a Ph.D. in Linguistics from the University of Massachusetts Amherst (1992) under Barbara Partee, following an A.B. in Philosophy from Princeton University (1987). His research explores mood systems, speech style particles, and the syntax-semantics interface, with funded projects on clause types and gradable modals. He has led summer schools on topics like 'Mood in Semantics and Pragmatics' (2018) and 'Tense and Aspect' (2022). Portner’s work appears in top journals like Language and Natural Language Semantics , and he authored Mood (Oxford, 2018). His funded research includes NSF grants exploring honorific meaning and speaker-addressee dynamics. Research Interests: Portner’s work centers on formal semantics and pragmatics, particularly mood variation, modality, and discourse semantics. He investigates how grammatical structures encode social relations, with contributions to understanding imperative clauses, deontic modals, and the syntax-pragmatics interface. His recent projects include a book on Social Relations in Semantics and Pragmatics (Oxford, under contract). Teaching & Outreach: Teaches courses like Semantics and Pragmatics and Syntax-Semantics Interface . Has organized summer schools at MIT, ENS Paris, and CreteLing, focusing on cutting-edge topics in linguistic theory. Advising & Grants: Co-PI on NSF grants (BCS-0234278, BCS-1053038). Advises graduate students in semantics/pragmatics and collaborates widely with researchers like Aynat Rubinstein and Miok Pak.

Jessica Kissingerمشاهده پروفایل

استاد پژوهشی

• Parasite Genomics
• Bioinformatics
• Evolutionary Genetics
• +۳ مورد دیگر

Jessica Kissinger is a Distinguished Research Professor in the Department of Genetics at the University of Georgia's Franklin College of Arts and Sciences. Her research focuses on parasite genomics, bioinformatics, and host-pathogen interactions, with emphasis on apicomplexan pathogens including Toxoplasma , Cryptosporidium , and malaria-causing Plasmodium species. Education: • A.B. cum laude, University of Chicago (1989) • Ph.D. in Molecular, Cellular & Developmental Biology, Indiana University (1995) • Postdoctoral training at NIH/NIAID, FIOCRUZ Brazil, and University of Pennsylvania Research Focus: Dr. Kissinger leads projects in comparative genomics, data integration, and systems biology of eukaryotic pathogens. Her lab develops computational tools for analyzing parasite genome evolution and host-pathogen dynamics, supported by NIH funding including the VEuPathDB resource center. Awards and Honors: University Professor, UGA (2025) Lamar Dodd Creative Research Award (2024) Fellow, AAAS (2021) Fulbright Scholar (2022) Distinguished Research Professor (2017) Current Projects: Her group combines wet-lab and computational approaches to study organellar genome evolution, gene regulation in Cryptosporidium , and multi-omics analysis of host-parasite systems through active NIH grants (R21AI180871, R01AI148667). She advises graduate students and collaborates internationally on parasitic disease research.

William Yorkمشاهده پروفایل

استاد

• Biochemistry
• Glycobiology
• Bioinformatics
• +۳ مورد دیگر

William York is a Professor of Biochemistry and Molecular Biology at the University of Georgia, with a courtesy appointment in the Computer Science department. He holds a Ph.D. from the University of Georgia (1996). His research focuses on spectroscopic and computational methods for analyzing complex carbohydrates, bioinformatics tools for glycan studies, and plant cell wall biology. He leads initiatives like GlyGen, a glycan structure repository, and develops software tools for glycomics data analysis (e.g., GRITS Toolbox). His work bridges biochemistry, informatics, and plant biology to advance understanding of carbohydrate roles in organisms and bioenergy applications. Research Interests: • Carbohydrate analysis via NMR and computational methods • Glycoinformatics and data standardization • Plant cell wall structure and biosynthesis • Development of tools for glycan annotation and archiving • Biomass utilization in bioenergy contexts Publications highlight advancements in glycan databases (GlyTouCan, GlyGen), enzymatic mechanisms (e.g., xylan acetylation), and plant polysaccharide structure-function relationships. His contributions include the MIRAGE project for glycomics data standards and collaborative frameworks like the GlySpace Alliance.

• Software Engineering
• Requirements Engineering
• Natural Language Processing
• +۵ مورد دیگر

Liping Zhao is a Senior Lecturer in Information Management. His expertise spans Software Engineering (SE), Requirements Engineering (RE), Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL). He holds a PhD and MPhil from the University of Leeds. He is a founding member of the Asian Pacific Conference on Pattern Languages of Programs and led the UK’s first multi-disciplinary service science network (2007–2010). He has received IBM Faculty Awards (2004, 2005, 2008) and a Best Tool Demo Award for TRAM (Transforming Textual Requirements into Analysis Models). He serves as an Associate Editor for Springer’s Requirements Engineering and Wiley’s Expert Systems , and guest-edited special issues on topics like Knowledge Intensive Service Systems and Problem Orientation. His research focuses on applying NLP/ML to software engineering tasks, blockchain systems, and service-oriented computing. Key contributions include a theory of pattern-based software design and datasets like FN-REQ (frame-annotated requirements) and TRAM. His work addresses challenges in requirements classification, blockchain architectures, and business problem validation through ML. Recent projects include process mining for blockchain applications, hierarchical classification of software requirements, and developing taxonomies for blockchain systems. His datasets and tools are publicly available via Zenodo and Mendeley, supporting reproducible research and industry collaboration.

Ian Holmesمشاهده پروفایل

استاد

• Computational Biology
• Genomics
• Bioinformatics
• +۴ مورد دیگر

Ian Holmes is a Professor in the Department of Bioengineering at the University of California, Berkeley. He leads the Holmes Lab, which integrates machine learning, statistical linguistics, and phylogenetics to analyze genomic data. His work focuses on RNA structure modeling, genome annotation, metagenomics, and developing open-source tools like JBrowse for genomic visualization. Research areas include computational methods for analyzing insertion-deletion events in genomes, metagenomic species distribution analysis, and collaborative web applications for genomic data interpretation. Key contributions include JBrowse 2 (a modular genome browser), CNVpytor (for copy number variation analysis), and CellScape (protein structure visualization). His research emphasizes practical tools for genomic analysis, with a focus on improving accuracy in bioinformatics workflows and enabling interdisciplinary collaboration. The Holmes Lab also explores evolutionary dynamics of genomic elements and applies statistical approaches to address challenges in molecular biology and bioinformatics.

Cresten Mansfeldtمشاهده پروفایل

استادیار

• Environmental Engineering
• Environmental Microbiology
• Bioinformatics
• +۷ مورد دیگر

Cresten Mansfeldt is an Assistant Professor in Environmental Engineering at the University of Colorado Boulder, affiliated with the Civil, Environmental, and Architectural Engineering Department. He holds a B.C.E. from the University of Minnesota (2007) and a Ph.D. from Cornell University (2013). Previously, he worked as a Research Scientist at Eawag (Swiss Federal Institute of Aquatic Science and Technology). His research focuses on microbial processes interacting with human-engineered systems, including wastewater treatment, riverine ecosystems, and bioremediation. Key interests include microbial community dynamics, contaminant biotransformation, and reactor design for resource recovery. Mansfeldt’s lab actively recruits students at all levels, emphasizing interdisciplinary approaches combining computational modeling, molecular microbiology, and environmental analytics. Research highlights include developing frameworks for wastewater-based public health surveillance, analyzing wildfire impacts on water quality, and modeling microbial community responses to environmental perturbations. Awards include the 2025 '40 Under 40' recognition from the American Academy of Environmental Engineers and Scientists, and a 2008 NSF Graduate Research Fellowship. Recent work addresses ethical considerations in wastewater sampling and integrates ecological risk assessment with synthetic biology. His publications span topics like microbial enzyme biomarkers, micropollutant fate in activated sludge systems, and lipid-accumulating algae for biofuel production. Current projects aim to optimize wastewater treatment for trace organic contaminant removal while enhancing microbial community resilience.

• Genomics
• Bioinformatics
• Comparative Genomics
• +۷ مورد دیگر

Dr. Jun Ng is a Visiting Professor at the John Curtin School of Medical Research (JCSMR) at the Australian National University (ANU). He is affiliated with the Clinical Hub for Interventional Research (CHOIR) as a visitor and is part of the Polizzotto Group. His research focuses on genomics, bioinformatics, and comparative genomics, with particular interests in structural variation analysis, marine organism genetics, and environmental adaptation mechanisms. He has contributed to projects involving genome assembly and annotation for diverse species such as oysters, reptiles, and fish. His work spans disciplines including molecular genetics, transcriptomics, and evolutionary biology, with a strong emphasis on applying genomic tools to solve biological problems. Notable projects include the development of multi-omic resources for Nicotiana benthamiana and studies on gravitropic gene expression in plants. Dr. Ng also collaborates on software tools for genomic data management, such as the easyfm suite. His publications highlight advancements in genome sequencing technologies, including long-read approaches and multi-platform comparisons. He has explored adaptation mechanisms in organisms facing environmental challenges, such as heat stress in fish and salinity tolerance in catfish. Dr. Ng’s research bridges fundamental biology with applied biotechnology, contributing to fields like aquaculture and plant science.

• Biomedical Engineering
• Machine Learning
• Signal Processing
• +۱۲ مورد دیگر

Abbas Z. Kouzani is a Professor at Deakin University's School of Engineering, specializing in Electrical and Computer Engineering. His research spans interdisciplinary domains including biomedical engineering, artificial intelligence, sensor technology, and embedded systems. Key areas: Machine Learning, Neurotechnology, Sustainable Robotics, Mental Health Analytics Recent work focuses on AI-driven solar defect detection, low-resource FPGA implementations, and 4D-printed robotic joints with reinforcement learning. Collaborations include Sui Yang Khoo, Scott D. Adams, and M. A. Parvez Mahmud.

• Data Science
• Machine Learning
• Distributed Computing
• +۴ مورد دیگر

Chris Mattmann is an academic affiliated with the University of Southern California, specializing in data science, machine learning, and high-performance computing. His work spans interdisciplinary applications in Earth sciences, climate modeling, and distributed systems. He has contributed to projects like the Earth System Grid Federation and Apache open-source software. His research emphasizes scalable data management, secure parser development, and automated machine learning systems. Education & Background: While specific educational details aren't listed, his extensive publication record in top-tier journals and conferences indicates advanced training in computer science and computational science. Research Interests: Focus areas include distributed computing infrastructure for scientific applications, machine learning for geosciences, and data-intensive systems. He explores challenges in data movement, scalable supercomputing, and open-source tools for scientific workflows. Publications: Over 150 peer-reviewed articles since 2003, with recent work on super-resolution satellite data, deep learning in geosciences, and secure parser systems. His contributions highlight advancements in both foundational computing and applied environmental science.

• Computational Pathology
• Artificial Intelligence in Medical Imaging
• Deep Learning
• +۲ مورد دیگر

B. Dislich is affiliated with the German Cancer Research Center (DKFZ), contributing to cutting-edge research in computational pathology and artificial intelligence applications for cancer diagnostics. As a Researcher, Dislich participates in developing deep learning methodologies for histopathological slide analysis. Dislich's research focuses on weakly-supervised learning pipelines for whole slide image classification, addressing critical challenges in computational pathology where ground truth annotations exist at the slide level rather than individual tiles. This work bridges AI innovation with clinical pathology needs, particularly in biomarker detection and cancer subtyping. The publications reveal a strong emphasis on methodological rigor in medical AI validation , with research spanning neural network architectures optimized for histopathological data. Dislich's contributions support the broader DKFZ mission of translating computational advances into clinical diagnostic tools. While specific advising roles or grants aren't documented in the available records, the collaborative nature of the publications (with multi-institutional co-authors including Loeffler, Muti, and Ghaffari Laleh) indicates participation in DKFZ's interdisciplinary cancer research ecosystem.

Katharina Breiningerمشاهده پروفایل

استادیار

• Artificial Intelligence
• Medical Imaging
• Computer Vision
• +۳ مورد دیگر

Katharina Breininger is an Assistant Professor (W1) for Artificial Intelligence in Medical Imaging at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), leading the AIMI@FAU Lab within the Department of Artificial Intelligence in Biomedical Engineering. She holds a doctoral degree from FAU's Pattern Recognition Lab, focusing on machine learning and deformation modeling in medical imaging. Her research emphasizes AI applications in interventional imaging and digital pathology, particularly addressing challenges in domain generalization and cross-platform compatibility. Education: PhD in Computer Science (2018), FAU Erlangen-Nürnberg, supervised by Prof. Dr.-Ing. Andreas Maier Research Interests: Computer vision and deep learning for medical imaging Domain adaptation in histopathology and interventional radiology AI-driven diagnostic tools for oncology and cardiology Labs/Teams: AIMI@FAU Lab: Focuses on AI in biomedical engineering and medical imaging workflows Collaborations: Siemens Healthineers: Joint projects on clinical imaging applications Johns Hopkins University: Collaborations on tomographic reconstruction

Milosh Jovanovikjمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Data Engineering
• Semantic Web
• +۸ مورد دیگر

Dr. Milosh Jovanovikj holds the role of Associate Professor at the Faculty of Computer Science and Engineering in Skopje, North Macedonia, and concurrently serves as a PostDoc Researcher at TU Wien in Vienna, Austria. He is also a Senior R&D Knowledge Graphs Engineer at OpenLink Software in London. His primary research focuses on Knowledge Graphs (KGs), including their lifecycle processes such as modeling, enrichment, and analytics-driven AI applications. He has contributed to over 10 international and 25 national research projects, authored 60+ publications, and co-authored 3 books. His expertise spans Data Engineering, Semantic Web technologies, Linked Data, and Applied AI. Significant contributions include developing frameworks like RDFGraphGen for RDF graph generation and PharmKE for pharmaceutical text analysis. He has led initiatives in geospatial semantic web standards (GeoSPARQL) and healthcare informatics, including predictive analytics for nephrology data. Education: PhD in Computer Science and Engineering His work bridges academia and industry, with projects like the 3DFed federation engine and Semantic Sky (a Gmail plugin). He has extensive experience in ontology development (e.g., SEOntology, VEO for CO2 emissions) and open data initiatives, including LinkedDrugs for global drug data consolidation. Active in dissemination, his articles span knowledge graph applications in music recommendation, finance sentiment analysis, and drug-disease relation discovery. He has collaborated on benchmarks like the GeoSPARQL Compliance Benchmark and Mighty Storage Challenge (MOCHA). Grants/Projects: HOBBIT, SAGE, 3DFed, LinkedDrugs He leads teams in advancing semantic web integration, cloud service platforms (Semantic Sky), and educational materials like Web Programming Basics . His labs and teams focus on AI-driven solutions for healthcare, geospatial analytics, and enterprise systems.

• Computational Biology
• Structural Biology
• Protein Structure Prediction
• +۳ مورد دیگر

Andrej Sali, PhD, is a Professor of Bioengineering at the University of California, San Francisco (UCSF), affiliated with the School of Pharmacy. His research focuses on computational methods to study protein structure and function, including predicting protein structures, analyzing macromolecular assemblies, and annotating protein functions using structural data. This work bridges genomics and medicine, enhancing the impact of structural and functional genomics. Research Interests: Dr. Sali integrates physics-based computational models and evolutionary principles to address fundamental questions in structural biology. His lab develops methods for protein structure prediction, structural genomics, and modeling dynamic biological processes. Key areas include nuclear pore complex assembly, molecular mechanisms of transporters, and integrative modeling platforms like the Integrative Modeling Platform (IMP). Grants & Funding: He has led/co-investigated numerous NIH-funded projects, including: NIH S10OD021596 (2016-2017) for high-performance computing infrastructure NIH P01GM111126 (2015-2020) on transmembrane transporter conformational cycles NIH P41RR001081 (1976-2012) for Biocomputing resources Awards & Honors: Recognized with prestigious awards such as the Zois Award (2000-2003), Irma T. Hirschl Career Award (1998-2000), and election to the National Academy of Sciences (2018). His work has been supported by grants from the Jane Coffin Childs Memorial Fund and Merck Sharp & Dohm. Labs & Teams: Leads the Sali Lab at UCSF, collaborating on cutting-edge projects such as nuclear pore complex dynamics, drug resistance mechanisms, and structural modeling of biomolecular systems.