جست‌وجوی استاد و پژوهشگر

Zhenman Fangمشاهده پروفایل

دانشیار

• Hardware Acceleration
• Computer Architecture
• Big Data Computing
• +۷ مورد دیگر

Dr. Zhenman Fang is an Associate Professor in the School of Engineering Science (Computer Engineering Option) and Associate Member in the School of Computing Science at Simon Fraser University, Canada. He founded and directs the HiAccel Lab, focusing on accelerator-rich architectures. His PhD (2014) is from Fudan University, China, with 15 months spent at the University of Minnesota. Prior to SFU, he was a Staff Software Engineer at Xilinx (2017-2019) and a postdoc at UCLA (2014-2017). His research spans: Hardware acceleration for ML, big data, genomics, and HPC FPGA-based customizable computing and near-data processing Compiler/runtime systems for heterogeneous platforms Performance/reliability optimization of accelerator-rich systems His recent publications (2024-2025) focus on FPGA acceleration for machine learning (e.g., on-device training, quantization), computational chemistry, image/video compression, database systems, and reconfigurable computing, demonstrating cross-domain applications of specialized hardware. Awards & Honors: Best Paper Awards: FPL 2024, MEMSYS 2017, TCAD 2019 Best Paper Nominations: ICCAD 2025, FCCM 2025, HPCA 2017, ISPASS 2018 SFU Research Excellence Horizon Award (2025) NSERC Alliance, CFI JELF, and Xilinx University Awards He advises 20+ PhD/Master's students in HiAccel Lab, focusing on accelerator design. Major grants include NSERC Alliance (2020) and CFI JELF (2019). The lab operates a 10-node cluster with FPGA/GPU infrastructure.

Thomas R Deanمشاهده پروفایل

استاد

• Software Transformation
• Web Application Security
• Network Protocol Security
• +۵ مورد دیگر

Dr. Thomas R Dean is a Professor in the Department of Electrical and Computer Engineering at Queen's University in Kingston, Ontario, Canada, and holds an additional appointment as an Adjunct Associate Professor at the Royal Military College of Kingston. His academic career spans several decades with consistent publication output through 2020, demonstrating active engagement in research and scholarship. His work bridges theoretical computer science with practical security applications, particularly in network protocols and web applications. Dean's research interests focus on software transformation techniques, web application evolution, and network security. His expertise includes software transformation, web site evolution, security of network applications, air traffic control systems, and language formalization. His work demonstrates a consistent thread connecting software engineering principles with security applications, particularly in developing techniques for intrusion detection systems and secure protocol implementations. His publications reveal a strong emphasis on practical applications of theoretical concepts, with numerous collaborations across academic and industrial settings. Analysis of Dean's recent publication record (2014-2020) shows a clear concentration in three interconnected areas: network security protocols, software transformation techniques, and model-based engineering approaches. His work on intrusion detection systems using constraint satisfaction methods appears consistently across multiple publications, demonstrating this as a core research thread. The publications also reveal growing interest in automotive software systems, particularly AUTOSAR implementations and Simulink model analysis, reflecting adaptation to emerging industry needs. Scientific recognition includes: Best paper award at CASCON'04 for Practical Language-Independent Detection of Near-Miss Clones Dean maintains active research collaborations, particularly with colleagues at Queen's University including M.H. Alalfi, J.R. Cordy, and F.T. Imam, as evidenced by co-authorship across multiple publications. His work spans both theoretical contributions and practical tool development, including parser generators, constraint engines, and intrusion detection systems. His research has been supported by publications in reputable venues including CASCON, IEEE conferences, and journals like Software Practice and Experience. Dean leads The Compass Group research team, focusing on software security and transformation techniques. His lab work emphasizes practical applications of software engineering principles to real-world security challenges, particularly in network protocols and web applications. The research approach combines formal methods with practical implementation, resulting in tools and frameworks that address specific security vulnerabilities in modern software systems.

Georgette Dalمشاهده پروفایل

استاد

• Constructional Morphology
• Productivity in Linguistics
• Corpus Linguistics
• +۵ مورد دیگر

Georgette Dal is a Full Professor at the University of Lille, affiliated with the Faculty of Humanities and the Language Sciences Department (UMR 8163 - STL: Savoirs, Textes, Langages). Her research focuses on constructional morphology , morphological productivity , and usage-based linguistics , with a strong emphasis on corpus analysis and digital resources like the Démonette-2 database. She led the ANR DEMONEXT project (2017-2022) to develop morphological databases for speech therapy applications. Research Themes : Constructional morphology, productivity, corpus linguistics, lexematic morphology Projects : FRANLEX (1997-2003), MorTAL (2000-2003), DEMONEXT (2017-2022) Her work bridges theoretical morphology with applied linguistics , particularly in speech therapy and language education . She has collaborated extensively with computational linguists and psycholinguists, contributing to debates on the autonomy of morphology , category boundaries , and the role of analogy in lexical construction. Recent studies include the morphological analysis of French adjectives in -eux and the development of participatory research frameworks for clinical partnerships. Her advocacy for internet-based data has transformed French morphological research methodologies.

• Data Integration
• Machine Learning
• Schema Matching
• +۵ مورد دیگر

C. Koutras is a researcher at the Data-Intensive Systems group within the School of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His work focuses on data integration, schema matching, and machine learning applications in modern data systems. Research Areas: Data Integration, Schema Matching, Machine Learning, Data Lakes, Graph Neural Networks, Biomedical Data Systems Collaborations: Active collaborations with researchers including R. Hai, A. Katsifodimos, and M. Jarke. Recent work includes developing tools like Amalur and Valentine , which address challenges in data lake integration and scalable schema matching. His research leverages large language models and graph-based techniques for biomedical and distributed data environments. Despite significant contributions to data integration and machine learning, no explicit scientific awards or part-time status are documented in the provided materials. His 2024 dissertation at TU Delft highlights expertise in modern data challenges.

• Mutation Testing
• Model Validation
• Software Engineering
• +۹ مورد دیگر

Dr. Eng. Joanna Strug is a lecturer at the Department of Automation and Computer Science within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. Her research focuses on software testing methodologies, machine learning applications in test automation, and database technologies. Specialization in mutation testing and fault injection Expertise in UML/OC validation and business process testing Active researcher in relational and non-relational database modeling Recent research trends indicate a focus on database technology performance analysis, including: Comparative benchmarking of relational vs. NoSQL databases Cost optimization in mutation testing using machine learning Structural similarity applications for test classification Validation frameworks for service-oriented architectures Model-based testing of business processes Bytecode-level mutant classification Her work appears in prominent venues including: Information Systems Architecture and Technology Artificial Intelligence and Soft Computing Journal of Engineering International Conference on Software Engineering (ENASE)

Steven Kayeمشاهده پروفایل

پژوهشگر ارشد

• Language documentation and description
• Nakh-Daghestanian linguistics
• Morphosyntactic typology
• +۳ مورد دیگر

Steven Kaye is a Research Fellow in the School of Literature and Languages at the University of Surrey, affiliated with the Surrey Morphology Group. His work focuses on understudied Caucasian languages, particularly within the Nakh-Daghestanian family. He holds a DPhil (2015) and MPhil (2009) in Linguistics from the University of Oxford, alongside a BA (Hons) in Classics and Modern Languages (2006). His research explores morphosyntactic typology, language documentation, and Indo-European comparative linguistics. Current projects include AHRC-funded 'External Agreement' investigating syntactic structures in Northern Caucasus languages and prior ANR-funded work on Northern Talyshi. He has conducted fieldwork in Zilo, Russia, and contributed to linguistic databases. Publications emphasize agreement systems in Andi and historical analyses of Caucasian linguistic works. His work bridges field-based research with theoretical linguistics, contributing to broader understanding of global language structures.

Jyothi Veduradaمشاهده پروفایل

استادیار

• Compilers
• Program Analysis
• High-Performance Computing
• +۳ مورد دیگر

Jyothi Vedurada is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad). Her research focuses on compilers, program analysis, high-performance computing (HPC), and software engineering. Prior to joining IIT Hyderabad, she was a postdoctoral researcher at Microsoft Research Lab in Bangalore and worked as a Software Engineer at Hewlett Packard in Chennai. Her research spans four major areas: Compiler Optimizations : Developing global compiler optimizations for CPU-GPU heterogeneous systems to enhance performance across varied hardware environments. ML for PL : Leveraging AI to overcome scalability and semantic challenges in program analysis, with applications in bug detection, API misuse recommendation, and algorithm description generation for Jupyter notebooks. Parallelization : Designing efficient GPU algorithms for tasks like Approximate Nearest Neighbour search and subgraph isomorphism optimization, alongside developing the Tensor Transposition Library for GPUs (TTLG). Concurrency Testing : Creating systematic testing frameworks for concurrent systems, including language-agnostic libraries and mock storage systems to validate weak isolation levels in databases. Scientific Awards & Recognition : Distinguished Artifact Award at ECOOP 2025 Google Research exploreCSR Award (2021) Tata Consultancy Services PhD Fellowship ACM SIGAI, SIGPLAN, and IEEE Travel Grants Advising & Collaborations : Supervising 11 PhD and MTech students, including Soumik Kumar Basu and Karthik V, with projects spanning compiler optimizations, HPC, and AI-driven software analysis. Collaborating with institutions like Microsoft Research and IIT Madras.

Christina Khnaisserمشاهده پروفایل

استادیار

• Learning Health Systems
• Temporal Databases
• Health Informatics
• +۳ مورد دیگر

Christina Khnaisser is an Assistant Professor in the Department of Computer Science at the University of Sherbrooke, specializing in data modeling for healthcare systems. Her work bridges computer science, medicine, and data management to advance learning health systems. Her educational background includes: M.Sc. in Software Engineering from the University of Sherbrooke (2016) Ph.D. in Medical Informatics from Université Paris Cité (with cotutelle agreement at University of Sherbrooke) (2019) Visiting Professor at Libera Università di Bolzano, Italy (2021-2022) Dr. Khnaisser develops historical data models that provide unified, temporally annotated views of health data. Her research focuses on tracking data evolution and provenance to accelerate diagnosis, optimize treatments, ensure care continuity across institutions, and improve clinical decision-making. She integrates computer science, mathematics, philosophy, and medical knowledge to create semantically rich data frameworks for reusable health analytics. Her interdisciplinary approach combines temporal database theory with practical healthcare applications, emphasizing cost-effective clinical studies through robust data infrastructure. Current work targets ontological modeling and data warehouse solutions for learning health systems.

Lisa Ingermannمشاهده پروفایل

پژوهشگر

• Comics Studies
• Children's and Young Adult Literature
• Literary Didactics
• +۲ مورد دیگر

Lisa Ingermann serves as a Researcher in the Department of German Studies at the University of Rostock's Faculty of Arts and Humanities. Holding a Master of Arts in German, she maintains her office at Kröpeliner Str. 57, Room 350, and is contactable via lisa.ingermann@uni-rostock.de. Her role encompasses research support and academic contributions to German literary studies with emphasis on pedagogical applications. Her research program centers on Comics Studies, Children's and Young Adult Literature, and Literary Didactics. Ingermann investigates how visual narratives—particularly comics—enhance language comprehension and historical education. Her work analyzes representations of National Socialism, archetypal figures like the 'evil old woman,' and innovative teaching methods including concrete poetry and language-development games. This research directly informs her development of classroom materials for German language instruction. Analysis of her 2020-2024 publications reveals consistent focus on comics as pedagogical tools across historical and contemporary contexts. She frequently collaborates with colleagues like Andrea Struck and Tina Michaelis on adaptations of works ranging from The Diary of Anne Frank to Roald Dahl's literature. Her scholarship bridges literary theory with practical classroom applications, particularly in German as both first and second language education. In addition to her research, Ingermann actively reviews children's and young adult literature for the GEW's Youth Literature and Media Working Group (AJuM), contributing critical assessments through their online database at www.ajum.de. Her ongoing work demonstrates commitment to advancing literary education through multimodal approaches.

• Answer Set Programming
• Logic Programming
• Knowledge Representation
• +۲ مورد دیگر

Wolfgang Faber is a researcher at Vienna University of Technology (TU Wien) specializing in Knowledge-Based Systems within the Faculty of Informatics. Holding the position of Privatdozent, he has completed his habilitation and is qualified to teach at the university level. His academic work centers on Answer Set Programming (ASP), Logic Programming, and Knowledge Representation, with significant contributions to theoretical foundations in these fields. Dr. Faber's research spans multiple areas of computational logic: Answer Set Programming and its theoretical underpinnings Epistemic logic programs and equivalence properties Knowledge representation and reasoning systems Nonmonotonic reasoning formalisms Integration of logic programming with external data sources His publication history reveals a sustained focus on theoretical aspects of ASP, with particular emphasis on program equivalence concepts (strong equivalence, uniform equivalence), computational complexity analysis, and applications to knowledge representation. Over two decades, his research has evolved from foundational work in disjunctive logic programming to specialized topics in epistemic reasoning within ASP frameworks. Dr. Faber has led and participated in numerous research projects including START (2014-2022) on Uniform Equivalence of Epistemic Logic Programs, SemDat (2012-2016), and multiple projects related to hybrid knowledge bases and Answer Set Programming from 2005-2015. His collaborative research extends across European institutions, evident through extensive co-authorship with researchers like Thomas Eiter and Stefan Woltran. While specific awards aren't documented in the available information, his sustained research output and leadership in multiple projects indicate significant recognition within his field. Dr. Faber has made substantial contributions to major systems in the field, most notably the DLV system for knowledge representation and reasoning, which has influenced both academic research and practical applications of Answer Set Programming.

Eline Visserمشاهده پروفایل

پژوهشگر ارشد

• Language documentation
• Language typology
• Austronesian languages
• +۵ مورد دیگر

Eline Visser is a Research Fellow at Uppsala University's Department of Linguistics, funded by the Wenner-Gren Foundations. She specializes in the endangered languages of eastern Indonesia, particularly Kalamang (Papuan) and Uruangnirin (Austronesian), and leads the Mapping Bomberai project (2024-2026) documenting understudied languages of the Bomberai peninsula. Her work bridges academic research with community-led language preservation initiatives. Her educational background includes: PhD in Linguistics from Lund University (2020), with a dissertation on Kalamang grammar Visser's research centers on language documentation and typology, with deep expertise in Austronesian and Papuan languages of eastern Indonesia. She investigates grammatical relations, narrative structures, prosody, and language contact phenomena through rigorous fieldwork. Her methodological contributions include integrating legacy materials with new field data and developing mobile dictionary apps for community use. She actively engages with ethical considerations in language documentation and promotes digital tools for endangered language preservation. Her publications from 2015-2025 reveal consistent focus on eastern Indonesian languages, particularly grammatical relations in Kalamang/Uruangnirin and methodological innovations in field linguistics. Key trends include the interplay between legacy data and new fieldwork, narrative analysis in Papuan languages, and applying computational approaches to language documentation. Her collaborative work spans syntax, phonology, and discourse analysis across diverse language families. Her scientific recognition includes: Wenner-Gren Fellowship for the Mapping Bomberai project Visser leads the Wenner-Gren-funded Mapping Bomberai project (2024-2026), supporting fieldwork on multiple Bomberai peninsula languages including Bedoanas, Erokwanas, Geser-Gorom, and Mbaham. She collaborates with researchers from Google on applying large language models to grammar reading and audio processing, and supports Wancho language documentation in India. Her community-oriented work includes developing mobile dictionary apps for Kalamang and Uruangnirin speakers. She is an active member of the 'Serial Verb Constructions across modalities' research group at the University of Amsterdam and previously contributed to the 'Where does grammar come from?' group. Her earlier work included the ExSynOp project at UiT The Arctic University of Norway on Scandinavian prosody, demonstrating her cross-linguistic research scope.

Georg Gottlobمشاهده پروفایل

استاد

• Database Theory
• Web Data Processing
• Query Languages
• +۱۱ مورد دیگر

Georg Gottlob is a Professor of Informatics at the University of Oxford and an Adjunct Professor at Vienna University of Technology (TU Wien). He is a Fellow of St John's College, Oxford, and focuses on algorithms and complexity in areas like database theory, constraint satisfaction, and computational logic. His work bridges theoretical foundations and practical applications, including web data extraction and quantitative finance. Education: Engineer and Ph.D. in Computer Science from TU Vienna (1979, 1981) Previous Positions: Full Professor at TU Vienna (1988-2006), Director of Christian Doppler Laboratory for Expert Systems (1989-1996), McKay Professor at UC Berkeley (1999) Research Interests: Gottlob specializes in graph/hypergraph-based problem decomposition methods for tractable instances of NP-hard problems, with applications in database query optimization, constraint satisfaction, and combinatorial auctions. His work spans database theory, AI, and computational complexity. Article Trends: Recent publications emphasize knowledge graph construction from financial data (2022), complexity analysis in logical frameworks (2021), and foundational work in guarded existential rules (2014). Themes include AI-driven data extraction, computational complexity, and logic programming. Scientific Awards: Fellow of the Royal Society (2010) Ada Lovelace Medal (2017) Wittgenstein Award (1998) Honorary Doctorates (University of Calabria, Klagenfurt) Advising and Leadership: Supervised numerous students and directed industry-funded projects like the Christian Doppler Laboratory. Co-founded Lixto Corporation and established the Oxford-Man Institute of Quantitative Finance (2006). Served as Editor-in-Chief of Artificial Intelligence Communications and on editorial boards of major journals.

Akhtar Aliمشاهده پروفایل

استادیار

• Data Science
• Data Analytics
• Big Data
• +۷ مورد دیگر

Dr. Akhtar Ali is an Assistant Professor at the Department of Computer and Information Sciences, Northumbria University. With over 20 years of experience in academia, he has specialized in database systems, data mining, and health informatics. He holds a PhD from the University of Manchester (2003) and has developed innovative programs like the MSc Data Science. Education: PhD in Computer Science (2003), University of Manchester MSc in Computer Science (1995), University of Peshawar Research Interests: Focuses on data science, big data management, healthcare optimization, and database migration. His recent projects include using data mining for population health prediction and redesigning healthcare service delivery models. Key Contributions: Led KTP projects on GIS for Gibraltar and healthcare process redesign. Developed MSc programs in Data Science and Information Science with Data Analytics. Supervised numerous students across BSc, MSc, and PhD levels. Awards: No specific awards listed, but recognized for contributions to database and health informatics research. Teaching & Administration: Over 20 years of teaching experience in database systems, data warehousing, and software design. Authored modules like 'Principles of Data Science' and 'Research Methods.'

• Music Processing
• Music Information Retrieval
• Audio Signal Processing
• +۱ مورد دیگر

Prof. Dr. Meinard Müller is a Professor at Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), leading the Chair of Semantic Audio Signal Processing within the International Audio Laboratories Erlangen (a joint institute with Fraunhofer IIS). He specializes in Music Processing, Music Information Retrieval, Audio Signal Processing, and Motion Processing. His work bridges fundamental research and practical applications in music technology, including audio decomposition, source separation, and computational musicology. Research Interests: Focus on algorithmic methods for music analysis, audio feature extraction, and real-time audio processing. Teaching: Supervises a large group of doctoral and master’s students, offering courses on audio processing and music technology. Awards: Recognized as an IEEE Fellow (2020) and ACM Senior Member (2020). His research group develops open-source tools like the FMP Notebooks and libfmp, and maintains datasets such as the Wagner Ring Dataset and Dagstuhl ChoirSet. He actively contributes to conferences like ISMIR and ICASSP, with over 200 publications in top-tier journals and conferences.

Maria Rute Vilhena Costaمشاهده پروفایل

دانشیار

• Linguistics
• Terminology
• Lexical Innovation
• +۵ مورد دیگر

Maria Rute Vilhena Costa is an Associate Professor with Habilitation at the Departamento de Linguística within the Universidade NOVA de Lisboa , affiliated with the Centro de Linguística da UNL (CLUNL) . She specializes in lexicography, terminology, and lexical innovation, with a focus on multilingual language resources and cultural heritage studies. She supervises PhD students and actively participates in international research networks. Education: PhD in Linguistics (Universidade NOVA de Lisboa, 2001). Research Interests: Her work centers on lexical markup frameworks, terminological methodology, ontology construction, and the documentation of Portuguese borrowings in Asian languages (CHAMUÇA project). She explores computational linguistics tools for lexical innovation and cross-linguistic studies. Key Contributions: Over 100 peer-reviewed publications (articles, conference papers, book chapters), including foundational work in linked data language resources and terminological integration. Active in editorial roles and international conferences. Labs/Teams: Leads the CLUNL research group and collaborates with global partners on projects like CHAMUÇA and ENEOLI.