جست‌وجوی استاد و پژوهشگر

Gotthard Meinelمشاهده پروفایل

پژوهشگر ارشد

• Geoinformatics
• Remote Sensing
• Land Use Monitoring
• +۵ مورد دیگر

Gotthard Meinel is a Senior Fellow at the Leibniz Institute of Ecological Urban and Regional Development (IOER) since 2023, with a distinguished career spanning over three decades in geoinformatics and spatial analysis. Previously, he served as Head of the Research Department for Spatial Information and Modeling (2009-2022) and held various leadership positions within the institute since joining in 1992. Meinel received his education at the Technical University of Dresden, graduating in Information Technology in 1981. He pursued postgraduate studies in biomathematics and earned a specialist mathematician degree between 1981-1992, culminating in his promotion (PhD equivalent) in 1987. His research focuses on geoinformatics, particularly remote sensing image processing and the automated analysis of large geospatial datasets. Meinel specializes in monitoring land-use developments and building stock through advanced spatial analysis methods. His work encompasses the development of indicators and visualization technologies for understanding settlement patterns and open space dynamics. With expertise spanning computer science, mathematics, and spatial analysis, Meinel has made significant contributions to the field of land use monitoring in Germany. Analysis of Meinel's recent publications reveals a strong focus on land use monitoring systems, spatial data infrastructure, and the integration of survey and geospatial data. His research increasingly emphasizes interdisciplinary approaches, combining urban planning, environmental science, and data science to address complex spatial challenges. Key trends include the development of comprehensive monitoring frameworks, analysis of building stock characteristics, and exploration of sustainable land use practices across Germany. Meinel has led or participated in numerous significant research projects including the Social-Spatial Research Data Infrastructure (SORA), the Research Database for Non-Residential Buildings (ENOB:DataNWG), OpenGeoEdu, and the Competence Center for Scalable Data Services and Solutions (ScaDS). These projects demonstrate his leadership in developing innovative spatial data infrastructures and analytical approaches. As project leader and principal investigator, Meinel has supervised numerous research initiatives and likely mentored students and junior researchers, though specific advisees are not documented in the provided materials. His work has significantly influenced spatial planning practices and land use monitoring methodologies in Germany. Meinel's research is closely associated with the IOER Monitor, a comprehensive spatio-temporal research data infrastructure for settlement and open space development in Germany. His team has developed sophisticated methodologies for analyzing land use change, building stock dynamics, and urban structure through the integration of topographic data, remote sensing, and statistical approaches.

• Software Security
• Software Engineering
• Cybersecurity
• +۳ مورد دیگر

Wei Huo is a researcher at the Institute of Information Engineering, Chinese Academy of Sciences, specializing in software security and engineering. His work focuses on vulnerability detection, program analysis, and cybersecurity across diverse systems including cloud infrastructure, firmware, and web applications. His research interests encompass Software Security , Program Analysis , Binary Analysis , and AI-driven security techniques . He develops practical tools for identifying vulnerabilities in Kubernetes ecosystems, baseband firmware, and binary code, with emphasis on real-world applicability in industrial contexts. Analysis of his publications (2019-2025) reveals a consistent focus on empirical security studies and tool development. Key trends include cloud-native security (Kubernetes), firmware analysis (printers/baseband), and AI-enhanced binary similarity detection, demonstrating progression from component-level to system-level security challenges. While no specific awards are documented in the source material, his contributions to top venues like ASE, ICSE, and ISSTA reflect significant impact in software engineering research. His work bridges academic rigor with practitioner-oriented solutions, particularly in vulnerability management and automated testing. Wei Huo actively contributes to the security research community through publications addressing critical infrastructure vulnerabilities, though details about student supervision or grant funding are not available in the provided text.

• Remote Sensing
• Forest Ecology
• Terrestrial Laser Scanning
• +۳ مورد دیگر

Mark Danson is a Professor at the University of Salford's School of Science, Engineering & Environment, specializing in remote sensing and forest ecology. His research focuses on developing terrestrial laser scanning technologies for vegetation analysis and ecological monitoring. He leads work on the Salford Advanced Laser Canopy Analyser (SALCA) system and contributes to global environmental databases like Globe-LFMC. His research explores vegetation structure measurement, lidar technology development, and ecological applications of remote sensing. Key interests include forest canopy analysis, plant moisture estimation, wildfire risk assessment, and climate change impacts on ecosystems. Recent work advances 3D forest modeling and validation of satellite-derived ecological parameters. The publication record demonstrates consistent focus on terrestrial laser scanning methodologies and forest applications. Research trends show progression from instrument development (dual-wavelength lidar systems) toward large-scale ecological validation studies and global dataset creation for climate monitoring. Danson leads technology development initiatives including the SALCA instrument design and calibration. Collaborative work appears through international projects like the Global Ecosystem Dynamics Investigation validation studies.

Seif Haridiمشاهده پروفایل

استاد

• Parallel Computing
• Distributed Computing
• Cloud Computing
• +۴ مورد دیگر

Seif Haridi is a Professor at KTH Royal Institute of Technology in Stockholm, Sweden, specializing in parallel and distributed computing systems. He holds dual roles as Chair-Professor of Computer Systems and Chief Scientific Advisor at RISE SICS. His research integrates systems engineering with theoretical foundations, focusing on programming systems, distributed computing, and big data technologies. Key contributions include co-designing SICStus Prolog, the Mozart Programming System, and Apache Flink, as well as leading the development of HOPS, a European big data platform awarded the IEEE Scale Prize 2017. He has led major EU projects like EIT-Digital’s cloud computing initiative and co-founded startups such as LogicalClocks and HiveStreaming. His teaching includes courses on distributed algorithms and peer-to-peer computing at KTH. Notable awards include the European Data Science Technology Innovation 2019. His work spans systems like HOPS, Flink, and Kompics, emphasizing scalability and robustness in distributed environments. Current projects include CDA (Continuous Deep Analytics) and ExtremeEarth for geospatial data analysis. Research interests include distributed algorithms, consensus protocols, and cloud-native systems. His lab’s contributions to scalable storage (e.g., HopsFS) and stream processing (Apache Flink) highlight his impact on both academia and industry.

Andrew Pavloمشاهده پروفایل

دانشیار

• Databases
• Distributed Systems
• Data-Intensive Computing
• +۳ مورد دیگر

Andrew Pavlo is an Associate Professor of Databaseology in the Computer Science Department at Carnegie Mellon University , part of the School of Computer Science . His research focuses on database systems, particularly self-driving architectures, transaction processing, and large-scale analytics. He is a member of the CMU Database Group and Parallel Data Laboratory. His awards include the NSF CAREER (2019), Sloan Fellowship (2018), and ACM SIGMOD Jim Gray Dissertation Award (2014). He co-founded OtterTune, a database tuning startup, though it later ceased operations. Current research interests emphasize autonomous database systems, query optimization, and distributed computing. Recent publications (2024) highlight work on self-driving DBMS, null representation in columnar formats, and UDF optimization techniques. Awards: NSF CAREER Award (2019) Sloan Fellowship (2018) ACM SIGMOD Jim Gray Dissertation Award (2014) Advising: Mentors students in database systems, including Sam Arch, Wan Shen Lim, and William Zhang. Labs/Teams: Leads the Database Group and collaborates with the Parallel Data Laboratory.

Hannah Haynieمشاهده پروفایل

استادیار

• Linguistic Diversity
• Language Prehistory
• Language Change
• +۳ مورد دیگر

Hannah Haynie is an Assistant Professor in the Department of Linguistics at the University of Colorado. Her research focuses on linguistic diversity, language prehistory, and language change with a specialization in North American languages, particularly those of the California region. She holds a PhD from the University of California, Berkeley, and completed postdoctoral fellowships at Yale University and Colorado State University. Dr. Haynie employs interdisciplinary methods combining linguistic analysis with approaches from geography, ecology, and evolutionary biology to investigate how linguistic diversity emerges from spatiotemporal language change processes. Her work addresses competing pressures shaping language dynamics and integrates computational tools to analyze cross-linguistic data. Her recent articles explore topics such as language complexity in societies of strangers, genealogical constraints on linguistic diversity, and the origins of Uto-Aztecan languages. She has also examined drivers of global land ownership patterns and cultural pathways to social inequality. Her research contributes to understanding the interplay between cultural evolution and environmental adaptation.

Hugo Ledouxمشاهده پروفایل

پژوهشگر

• 3D Geoinformation
• Urban Data Science
• Remote Sensing
• +۳ مورد دیگر

Hugo Ledoux is an academic affiliated with the Faculty of Architecture and the Built Environment at Delft University of Technology, specializing in Urban Data Science. His research focuses on 3D geospatial modeling, including CityGML standards, terrain analysis, and automated reconstruction of urban structures. He has contributed to projects like the DeltaDTM coastal terrain model and the cjdb database solution for CityGML. Education: Not explicitly detailed in text, but inferred through academic roles and publications. Research interests emphasize 3D geoinformation systems, remote sensing applications, and urban data science. His work addresses challenges in 3D city models, building reconstruction, and geospatial validation tools like Val3dity. Recent efforts include improving global terrain models using ICESat-2 and GEDI lidar data. Publications span automated building reconstruction workflows, terrain accuracy assessments, and semantic-guided facade modeling. Awards include the Best Presentation at 3DGeoInfo 2020 and the U.V. Helava Award for Best Paper in 2011. Ledoux has supervised 4 academic works and actively participates in conferences, editorial activities, and open-source software development for geospatial applications. Labs/Teams: Involved in TU Delft’s 3D geoinformation research, contributing to tools like 3dfier and CityJSON for 3D data interoperability.

Fatemeh Vafaeeمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Systems Biology
• +۵ مورد دیگر

Associate Professor Fatemeh Vafaee is a leading researcher at the University of New South Wales (UNSW) , holding appointments as Associate Professor in the School of Biotechnology and Biomolecular Sciences (BABS) and Deputy Director (Science) of the UNSW AI Institute . She previously served as Deputy Director of the UNSW Data Science Hub (uDASH) and has held academic positions at the University of Toronto and the University of Sydney. PhD in Artificial Intelligence from University of Illinois at Chicago Postdoctoral Fellowships at University of Toronto and University of Sydney Founded the AI-Enhanced Biomedicine Laboratory in 2017 Her research focuses on deploying advanced AI techniques to address biomedical challenges through: Biomarker Discovery for cancer and neurodegenerative diseases Single-Cell Multi-Omics data integration and analysis Computational Drug Repositioning and network pharmacology Multi-Omics Data Fusion and temporal network modeling Recent publications demonstrate expertise in liquid biopsy development , single-cell imaging , and AI-driven cancer diagnostics . Her methodological contributions include novel deep learning architectures for omics data analysis and graph neural networks for drug synergy prediction. Scientific accolades include: Winner, Women in AI Asia-Pacific Health Award (2023) Runner-Up, WAI-APAC Innovator of the Year (2023) Top 10 Women in AI in Asia-Pacific (2023) Australian Bioinformatics and Computational Biology Society Research Excellence Award (2023) She supervises PhD candidates across computational biomedicine and AI in healthcare , with significant grant achievements exceeding $17M in competitive funding, including schemes from ARC Discovery , NHMRC , and Medical Research Future Fund .

Bin Guoمشاهده پروفایل

استادیار

• Parallel and Distributed Computing
• Graph Algorithms
• Graph Mining
• +۵ مورد دیگر

Bin Guo is an Assistant Professor at the Computer Science Department of Trent University (since Jan. 2024) and an Adjunct Assistant Professor at the Computing & Software Department of McMaster University. He holds a PhD in Computer Science from McMaster University (2023) and an MSc in Applied Computer Science from Winnipeg University (2018). His research focuses on parallel/distributed computing, graph algorithms, and computer security for data analytics, with notable contributions to federated k-core decomposition and secure distributed algorithms. He teaches courses in database systems, operating systems, and computer security at Trent University and has taught at McMaster University. Education: PhD in Computer Science, McMaster University (2023) MSc in Applied Computer Science, Winnipeg University (2018) Research Interests: Parallel and Distributed Computing Graph Algorithms and Mining Computer Security & Privacy Federated Learning Concurrent Data Structures Advising & Grants: Current advisees: Gregory Prouty, Michael Abiona, Syed Zarif Past advisees: Igor Jardim-Martins, Issec Lee Funding sources: Graduate Teaching Assistantships, Research Fellowships, Trent University Research Development Grants Labs & Teams: Leading research projects in parallel graph algorithms and federated security algorithms Collaborating with McMaster University on PhD/Master's co-supervision

• Machine Learning Systems
• Differential Privacy
• Adversarial Robustness
• +۳ مورد دیگر

Mathias Lecuyer is an Assistant Professor at the University of British Columbia (UBC), Department of Computer Science, where he leads the Systopia research group. His research focuses on trustworthy AI systems, including differential privacy, adversarial robustness, and causal machine learning. He holds a PhD from Columbia University and was a postdoctoral researcher at Microsoft Research. Education: PhD in Computer Science, Columbia University Postdoctoral Researcher, Microsoft Research (New York) Research Interests: Privacy-preserving machine learning (Differential Privacy) Certified adversarial robustness via randomized smoothing Causal inference for model generalization Systems for privacy and security in AI Awards: SOSP Distinguished Artifact Honourable Mention (2024) Google Research Award Supervised Students: PhD: Qiaoyue Tang, Saiyue Lyu, Frederick Shpilevskiy MSc: Mishaal Kazmi, Shadab Shaikh, Shiqi He Undergrad: Alain Zhiyanov, Jessica Bator, Ryan Shar, Eric Xiong, Joel Hempel Labs/Teams: Member of UBC S&P, TrustML, and CAIDA research groups.

• Semantic Web
• Internet of Things
• Stream Reasoning
• +۵ مورد دیگر

Pieter Bonte is a FWO Senior postdoctoral fellow and IMEC Postdoctoral researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology. His research focuses on Semantic Web technologies, stream reasoning, and Internet of Things applications. His research interests span Semantic Web, Internet of Things, Stream Reasoning, Knowledge Graphs, Context-aware Systems, RDF Processing, Linked Data, and Healthcare Informatics. His work bridges theoretical semantic technologies with practical applications, particularly in healthcare and IoT domains. Bonte's publication record shows a strong focus on streaming data processing, with numerous papers on Streaming Linked Data, context-aware query derivation, and semantic reasoning frameworks. His research demonstrates a progression from foundational semantic web technologies toward practical implementations in healthcare and IoT applications, with an increasing emphasis on privacy considerations and efficient processing techniques. His work frequently involves collaborations with Femke Ongenae, Filip De Turck, and other researchers at Ghent University and IMEC, indicating strong institutional research networks. His publications appear in respected venues including the Journal of Web Semantics, Semantic Web Journal, and various conference proceedings in the semantic technologies field.

Mikhail J. Atallahمشاهده پروفایل

استاد

• Information Security
• Algorithms
• Quantum Computing
• +۴ مورد دیگر

Mikhail J. Atallah is a Distinguished Professor of Computer Science at Purdue University, affiliated with the Department of Computer Science under the College of Science. He has been a faculty member since Fall 1982. His research focuses on information security, algorithms, and quantum computing. He holds ACM and IEEE Fellowships and has received prestigious awards such as the 2015 CCS Test of Time Award and the 2017 Arden L. Bement Jr. Award. Education: PhD (1982), MS (1980) in Electrical Engineering and Computer Science from Johns Hopkins University; BE (1975) in Electrical Engineering from the American University in Beirut. Research Interests: Includes cryptographic protocols, secure computation, privacy-preserving techniques, and theoretical foundations of algorithms. He has pioneered work on key management and multi-party computation, with applications in secure data outsourcing and authentication systems. Publications: Over 250 papers, including influential works on secure outsourcing of computations, privacy-preserving data analysis, and cryptographic algorithms. Recent trends highlight advancements in biometric authentication, manufacturing security, and lightweight cryptography. Awards: Test of Time Awards (CCS 2015, ACSAC 2021), Purdue’s highest scientific honor (Bement Award), and multiple industry-recognized accolades. Advising: Mentored over 20 PhD students, many of whom have become prominent in academia and industry (e.g., Michael T. Goodrich, Danny Z. Chen). Labs/Teams: Active in cybersecurity research groups at Purdue, contributing to projects on secure manufacturing, collaborative design, and privacy-enhancing technologies.

Dominik Moritzمشاهده پروفایل

استادیار

• Human-Centered Machine Learning
• Data Science
• Interactive Systems
• +۶ مورد دیگر

Dominik Moritz is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University and Machine Learning researcher at Apple. He leads the Data Interaction Group and develops systems for interactive data visualization. Ph.D. in Computer Science from University of Washington (2019) B.S. in Computer Science from Hasso Plattner Institute (2013) His research focuses on: Human-Centered Machine Learning Data Visualization Toolkits Interactive Systems Design Accessibility in Visual Analytics Scalable Web-Based Visualization Recent publications address visualization design knowledge formalization (Draco), cross-filtering frameworks (Mosaic), and accessibility evaluation (Chartability). He has received Best Paper Honors at VIS and EuroVis conferences. Professional Collaborations: Co-founder of Vega-Lite visualization grammar Collaborations with Jeff Heer, Bill Howe, Jock MacKinlay Projects with Microsoft Research and Google Research

Tobias Blankeمشاهده پروفایل

استاد

• Artificial Intelligence
• Digital Humanities
• Big Data Ethics
• +۷ مورد دیگر

Professor Tobias Blanke is a leading scholar at the University of Amsterdam and the Institute for Logic, Language, and Computation , with additional affiliation as Visiting Professor of Social and Cultural Informatics at King’s College London. His work bridges artificial intelligence and humanities disciplines. PhD in Computer Science and Political Philosophy Director of DARIAH (2012–2016) Head of Digital Humanities Department at KCL (2016–2019) Blanke’s research focuses on artificial intelligence and big data applications within the human sciences, emphasizing ethical implications such as: Predictive policing systems Algorithmic othering Platform monopolization Computational genealogy XML retrieval frameworks His recent publications demonstrate increasing interdisciplinary collaboration in digital humanities , with key partnerships at the Open Data Institute , TacticalTech , and British Library . While no formal awards are listed in available materials, his leadership in infrastructural projects like the European Holocaust Research Infrastructure highlights significant contributions to the field. Blanke maintains active teaching and research roles, leading initiatives like the International Artificial Intelligence PhD Academy courses for social sciences. His technical expertise spans: XML retrieval systems NoSQL database applications Algorithmic governmentality Digital publishing frameworks

• Human-Computer Interaction
• Artificial Intelligence
• Creativity Support Tools
• +۳ مورد دیگر

Joel Chan is an Affiliate Assistant Professor in the Department of Computer Science at the University of Maryland, specializing in human-computer interaction and artificial intelligence research with applications in scholarly communication and design innovation. His work bridges computational systems and human cognitive processes to enhance knowledge work. His research portfolio emphasizes: Scholarly sensemaking and knowledge synthesis infrastructure Generative AI for hypothesis exploration and analogical reasoning Cross-disciplinary translation tools using computational linguistics Biologically inspired design systems and creativity support Human-AI collaboration in visual data analysis and programming Recent publications (2023-2025) demonstrate a decisive shift toward integrating large language models into scholarly workflows, particularly for structured hypothesis exploration and cross-domain analogical inspiration. His systems like CausalMapper and AnalogiLead exemplify practical implementations that transform theoretical frameworks into usable tools for researchers and designers. Building on foundational work in analogical innovation (2010-2022), Chan's research trajectory shows consistent evolution from studying example-based problem-solving to developing AI-augmented environments that mitigate cognitive limitations in complex knowledge tasks, with significant implications for academic practice and creative industries.