جست‌وجوی استاد و پژوهشگر

Ana Gabriela Maguitmanمشاهده پروفایل

استاد

• Artificial Intelligence
• Information Retrieval
• Knowledge Capture
• +۷ مورد دیگر

Ana Gabriela Maguitman is a Professor in the Department of Computer Science and Engineering at the National University of the South and a researcher at Argentina's Scientific and Technical Research Council (CONICET). Her work centers on context-aware information access systems and interdisciplinary AI applications. Her research spans formal and empirical aspects of artificial intelligence with specific focus on: Context-based search and relevance propagation models Web/text mining and machine learning integration Knowledge capture systems and argumentation frameworks Distributed search architectures and data science applications Her research group operates within the Institute for Computer Science and Engineering (ICIC), receiving sustained funding from: Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) Universidad Nacional de Sur (UNS) Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CIC) Google Research Awards for Latin America Microsoft (LACCIR) She maintains active research leadership through her group's specialized focus on computational trust models and semantic evaluation frameworks while contributing to Argentina's academic computing infrastructure.

Fang Liuمشاهده پروفایل

استادیار

• Software Engineering
• Artificial Intelligence for Software Engineering
• Program Understanding
• +۳ مورد دیگر

Fang Liu is an Assistant Professor at the School of Computer Science & Engineering, Beihang University, China. She has made significant contributions to the field of software engineering, particularly in the intersection of artificial intelligence and software development practices. Dr. Liu received her Ph.D. in Computer Science from Peking University (Sep. 2017 - Jul. 2022), supervised by Prof. Zhi Jin and Prof. Ge Li. Prior to that, she earned her B.S. in Computer Science from Chongqing University (Sep. 2013 - Jul. 2017). Her research interests focus on AI for Software Engineering, including program understanding and generation, program repair, and applications of Large Language Models to software development tasks. Dr. Liu teaches Compiler Technology as a compulsory course at Beihang University (Fall 2024) and Programming in Cangjie Language as an elective course (Spring 2025). Her recent publications demonstrate a clear trend toward leveraging large language models for various software engineering tasks, with a particular emphasis on code editing, program repair, and code translation. Her research spans both theoretical advancements in model architectures and practical applications to real-world software development challenges, with numerous publications in top-tier venues like ASE, ICSE, and FSE. Distinguished Paper Award at ICPC'20 for "A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning" Dr. Liu actively participates in the software engineering research community as a program committee member for major conferences including ASE, FSE, and ICSE. Her work has significant implications for improving developer productivity, software quality, and the integration of AI technologies into the software development lifecycle.

• Health Informatics
• Electronic Patient Records
• Healthcare Workflow Systems
• +۴ مورد دیگر

George Vassilacopoulos is a Professor at the University of Piraeus, Greece, where he holds multiple leadership roles including Director of the Health Informatics Laboratory, Director of the Post-graduate Programme in Digital Systems and Services, and Deputy President of the University Council. He previously served as Vice Rector of Academic Affairs and Chairman of the Department of Digital Systems for over a decade. His professional experience spans private and public sectors, including roles as a Health Informatics advisor to the Greek Ministry of Health, board member of major hospitals, and advisor to the National Emergency Medical Service. He holds a PhD from the University of London. His research focuses on electronic patient records, healthcare workflow systems, service-oriented healthcare architectures, and healthcare security, with a particular emphasis on interoperability, big data analytics, and mobile health solutions. His recent publications emphasize advancements in holistic health records, cloud-based healthcare systems, and privacy-preserving access mechanisms. He has contributed to numerous national and EU-funded projects, authored four books, and serves on editorial boards for academic journals and conferences. Key recognitions include his Fellowship with the British Computer Society and leadership in international organizations like the Workflow Management Coalition and IMIA.

John Paul Shenمشاهده پروفایل

استاد

• Modern Processor Design
• Instruction-Level Parallelism
• Dependable Computing
• +۳ مورد دیگر

John Paul Shen is a Distinguished Service Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), based at the Silicon Valley campus. With over three decades of experience in academia and industry, he has held prominent roles including founding director of Nokia Research Center-North America Lab (2007–2012) and director of Intel’s Microarchitecture Research Lab (2000–2006). His academic career includes a tenured professorship at CMU’s ECE Department from 1990–2000 and a return to CMU in 2015 as a tenured professor. Education: Ph.D. in Electrical Engineering, University of Southern California M.S. in Electrical Engineering, University of Southern California B.S. in Electrical Engineering, University of Michigan Research Focus: Modern Processor Design: Specializes in superscalar processors, instruction-level parallelism (ILP), and microarchitecture validation tools like VMW (Visualization-Based Microarchitecture Workbench). Neuromorphic Computing: Develops energy-efficient temporal neural networks (TNNs) and CMOS implementations for sensory processing. Edge AI: Focuses on low-precision accelerators, sparsity exploitation, and real-time data analytics for edge devices. Dependable Computing: Leverages idle processor resources for error-checking and fault tolerance. Awards & Impact: Recipient of multiple teaching awards during his CMU tenure. Supervised 17 Ph.D. students and dozens of M.S. students, with notable contributions to compiler design and parallel computing. Authored two influential textbooks, including Modern Processor Design: Fundamentals of Superscalar Processors , used at Stanford. Generated over 100 patents and 200+ papers at Nokia and Intel, with a focus on mobile computing and hardware architecture innovations. Labs & Collaborations: Founded and led the Nokia Research Center-NAL, advancing mobile Internet and computing. Directed Intel’s Microarchitecture Research Lab, advancing IA32/IA64 processor designs. Current research at CMU Silicon Valley focuses on neuromorphic systems, wearable computing, and real-time data analytics.

Bentley Oakesمشاهده پروفایل

استادیار

• Digital Twins
• Model Transformations
• Software Engineering
• +۶ مورد دیگر

Bentley Oakes is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a Ph.D. (2018) and M.Sc. (2015) from McGill University, and a B.Sc. (2013) from the University of Manitoba. His research focuses on Digital Twins , Model Transformations , and Knowledge Representation for cyber-physical systems. Ph.D. in Computer Science, McGill University, Canada M.Sc. in Science, McGill University, Canada B.Sc. in Computer Science, University of Manitoba, Canada His work bridges Model-Driven Engineering and Artificial Intelligence to advance the rigorous development of digital twins. Key research areas include: Digital Twin Engineering : Frameworks for systematic development, reporting, and validation. Knowledge Representation : Ontologies and contracts for modeling domain expertise. Model Transformations : Symbolic execution and debugging of ATL/DSLTrans transformations. Verification : Formal methods for cyber-physical systems and co-simulations. Oakes has published extensively in MODELS , MSR , TOSEM , and SoSyM . His recent studies on rationale extraction in open-source software and DevOps approaches for built assets highlight interdisciplinary innovations. He has been recognized for Outstanding Reviewing Contributions , receiving multiple Best Reviewer Awards at leading software engineering venues. At Polytechnique Montréal, he teaches courses such as: INF6900AE : Scientific and Technical Communication I INF7900AE : Scientific and Technical Communication II LOG6953FE / LOG6310E : Digital Twin Engineering LOG8371E : Software Quality Engineering

Costas Vassilakisمشاهده پروفایل

استاد

• Information systems
• Semantic web technologies
• Service-oriented architectures
• +۴ مورد دیگر

Costas Vassilakis is a Professor in the Department of Informatics and Telecommunications at the University of Peloponnese, serving as Dean of the Faculty of Economics and Technology since 2019. He holds a PhD from the University of Athens (1995) and has held academic roles since 2005, including Associate Professor and Visiting positions. His research focuses on information systems, semantic web technologies, and cultural informatics, with contributions to projects like Virtual Museums and SmartGov. He leads initiatives in digital cultural heritage, cybersecurity, and smart agriculture. Notable projects include Experimedia Blue for personalized cultural experiences and Cyber-Trust for IoT security. Active in teaching, he has instructed courses on operating systems, software engineering, and real-time systems. He contributes to academic governance, including roles in the University Council and strategic planning units. His work bridges technology and cultural preservation, emphasizing interdisciplinary innovation. Education: PhD in Informatics, University of Athens (1995); MSc equivalent in Informatics, University of Athens (1990). Research Interests: Focuses on recommenders systems, collaborative filtering optimization, cybersecurity frameworks, and AI applications in agriculture. Active in cultural heritage digitization, museum technologies, and VR systems. Recent Projects: Includes TripMentor (tourism platform), PaloAnalytics (market analytics), and Rehabotics (rehabilitation robotics). Leads EN.I.R.I.S.S.T., a national infrastructure for maritime and logistics research. Awards: No explicit awards listed, but recognized through extensive project leadership and academic roles.

Silke Coemansمشاهده پروفایل

پژوهشگر ارشد

• Neurolinguistics
• Primary Progressive Aphasia
• Bilingualism
• +۶ مورد دیگر

Silke Coemans is an FWO Research Fellow and PhD candidate in Neurolinguistics at the Faculty of Arts and Philosophy, Vrije Universiteit Brussel, affiliated with the Brussels Centre for Language Studies and Department of Linguistics and Literary Studies. Her work bridges neuroscience, linguistics, and aging research, focusing on bilingualism's impact on neurodegenerative diseases. Education: Master in Biomedical Sciences: Neurosciences, University of Antwerp (2016-2018) PhD in Neurolinguistics (in progress), Vrije Universiteit Brussel Her research centers on Primary Progressive Aphasia (PPA), bilingualism, and transcranial Direct Current Stimulation (tDCS) interventions. She investigates how cerebellar tDCS combined with language therapy affects neural pathways and executive functions in bilingual PPA patients, exploring potential protective effects of bilingualism against dementia symptoms. Current projects examine the "linguistic cerebellum" in phonological processing. Recent publications reveal a concentrated focus on tDCS applications for bilingual aphasia rehabilitation across neurodegenerative and post-stroke contexts, alongside methodological contributions through systematic reviews on idiom comprehension in aphasia. Scientific Awards: PhD Day Brussels Centre for Language Studies: Best Poster Award (2022) Funded by the Research Foundation - Flanders (FWO), Coemans leads project FWOTM1214 (2024-2027) on cerebellar involvement in language processing and collaborates on the Primary Progressive Aphasia Scientific Research Network (2025-2029). Her grant portfolio emphasizes neurostimulation techniques for language rehabilitation in multilingual populations. She operates within the Brussels Centre for Language Studies research ecosystem, collaborating with Prof. Stefanie Keulen's team on neuroimaging and language therapy protocols for PPA, with active participation in international stuttering research symposia and methodology workshops.

Peer Neubertمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Dr. Peer Neubert is a Professor and Head of the Intelligent Autonomous Systems (INTAS) Working Group at the University of Koblenz. He is affiliated with the Department of Computer Visualistics (Department 4) and serves as Head of the Institute of Computational Visualistics. His academic roles include membership in the Department Council and Library Committee of FB4. His research focuses on robotics, computer vision, and autonomous systems, with particular emphasis on visual place recognition, SLAM, hyperdimensional computing, and adaptive navigation in dynamic environments. Neubert's work spans theoretical advancements and practical implementations, such as benchmarking systems (e.g., HS3-Bench), efficient algorithms (FETCH, LocalSPED), and sensor-based solutions (HealthWalk). His team addresses challenges in long-term navigation, environmental adaptation, and data-efficient learning. Collaborations include external PhD students like Kenny Schlegel and projects like MineSweeper, demonstrating interdisciplinary impact. His contributions are reflected in over 50 publications since 2007, covering topics from hyperspectral segmentation to biomedical applications. While no formal educational details are provided, his extensive research output and leadership roles underscore his expertise in computational visualistics and autonomous systems.

Joseph Le Rouxمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Optimization
• +۳ مورد دیگر

Joseph Le Roux is an Associate Professor at the University of Paris 13, affiliated with the LIPN laboratory. His research focuses on Natural Language Processing (NLP), Machine Learning (ML), and their applications to optimization problems. He has supervised multiple PhD students, including Yash Kankanampati, Nicolas Floquet, and Francesco Demelas, among others. Le Roux's work emphasizes dependency parsing, attention mechanisms, and optimization techniques in NLP. His research has been published in top venues such as NAACL, ICML, and EMNLP. He also contributes to academic service, including roles as an Action Editor for ARR and a member of the TAL journal's editorial board. His teaching responsibilities include courses on neural networks, generative models in NLP, and programming for AI. He co-manages the Data Science hub at LIPN and leads research projects like SemiAmor (ANR CE23-2023-0005) and ParSiTi (ANR-16-CE33-0021). Le Roux's academic contributions span over two decades, with a PhD in 2007 and an HDR (Habilitation) in 2024. His lab collaborations include work on XMG, a metagrammar compiler, and projects addressing challenges in social media NLP and MIP solving via ML.

• Information Retrieval
• Data Analytics
• Machine Learning
• +۹ مورد دیگر

Shane Culpepper is an Adjunct Professor in the School of Computing Technologies at RMIT University, where he also serves as Director of the Centre for Information Discovery and Data Analytics and a Vice-Chancellor's Principal Research Fellow. His research focuses on building efficient search systems, measuring answer quality, and human-driven data science transformation of heterogeneous data. Key areas include algorithms, machine learning, distributed computing, and statistical modeling. Teaching interests span space-efficient data structures, data compression, bioinformatics, natural language processing, and combinatorics. His research interests include information retrieval, artificial intelligence, and computational theory. Supervision projects include topics like query performance prediction, inferential risk measures, and efficient cascade ranking. Over 100 research outputs are listed, with recent work on query optimization, multimodal feature extraction, and trajectory data analytics. Collaborations and a personal website ( https://www.culpepper.io/ ) highlight active engagement in the academic community.

Ullrich Martinمشاهده پروفایل

استاد

• Railway Engineering
• Transport Systems
• Fault Diagnosis
• +۷ مورد دیگر

Ullrich Martin is a Professor and Head of the Institute of Railway and Transport Engineering at the University of Stuttgart, Germany. His work spans railway systems, infrastructure modeling, and transport policy. Key areas include fault diagnosis, simulation-based optimization, and capacity evaluation. Contact: Pfaffenwaldring 7, 70569 Stuttgart, Germany Office Hours: By agreement Research Trends: Recent publications focus on GAN-based data augmentation for railway fault detection, high-speed maglev systems optimization, and early instability detection in ballast tracks. His team explores discrete element modeling, operational risk analysis, and machine learning applications for track condition monitoring. Infrastructure Innovation: He drives digitalization in railway planning through graph-based knowledge databases and automated compliance tools. Projects address dwell time forecasting, electromagnetic suspension design, and accessibility solutions like the Sinn²-App for visually impaired passengers. Operational Modeling: His work includes tabu search algorithms for dispatching, reinforcement learning for timetable calibration, and multi-scale simulation frameworks. He investigates interactions between track irregularities and vehicle dynamics, with a focus on safety and efficiency.

• Formal Verification
• Software Engineering
• Computer-Aided Verification
• +۵ مورد دیگر

Zvonimir Rakamaric is a Professor in the Department of Computer Science at the University of Utah. His primary research focuses on formal methods, software verification, and numerical analysis, with an emphasis on ensuring correctness and reliability in software systems. He leads efforts in developing tools and techniques for verifying complex systems, including formal verification of floating-point arithmetic, compiler optimizations, and concurrent/distributed systems. Key Roles: Formal Methods Researcher, Software Verification Specialist, Floating-Point Arithmetic Expert Affiliations: University of Utah School of Computing Research interests span formal verification tools (e.g., SMACK, Dafny), static analysis, and numerical error analysis. His work addresses challenges in safety-critical systems, including embedded software, high-performance computing, and compiler optimizations. Collaborations include institutions like Sandia National Labs and Microsoft Research. Publications emphasize rigorous methods for analyzing floating-point precision, equivalence checking, and tool development for formal verification. His work bridges theoretical foundations with practical tool implementations, contributing to open-source verification frameworks widely adopted in academia and industry.

Peter M. Chenمشاهده پروفایل

استاد

• Operating Systems
• Distributed Systems
• Virtualization
• +۵ مورد دیگر

Peter M. Chen is the Arthur F. Thurnau Professor in the Department of Electrical Engineering and Computer Science (EECS) at the University of Michigan, part of the College of Engineering. He leads research in operating systems, distributed systems, and persistent memory technologies. His work includes foundational contributions to virtualization (e.g., ReVirt), reliable memory systems (Rio), and non-volatile memory semantics. He is a member of the Software Systems Lab and collaborates with the Computer Engineering Lab. Education and affiliations: Ph.D. in Computer Science (implied through career trajectory), affiliated with EECS and multiple labs at U-M. His research interests span speculative execution, security in distributed systems, and high-performance storage. He has advised over 20 graduate students, many of whom have contributed to seminal papers in systems research. Awards include the Arthur F. Thurnau Professorship and multiple best paper awards at top conferences like OSDI and SOSP. His work on ReVirt pioneered virtual machine logging for intrusion analysis, and Rio revolutionized reliable memory caching. Current projects focus on persistent memory programming models and wear management in NVM technologies. Key grants and teams: Active in NSF-funded projects on persistent memory systems and security. Collaborates with industry through partnerships in cloud computing and mobile systems optimization. His lab develops open-source tools like Rio and Vista, emphasizing practical system implementations alongside theoretical contributions.

Jan Carlsonمشاهده پروفایل

استاد

• Software Engineering
• Embedded Systems
• Model-Based Development
• +۵ مورد دیگر

Jan Carlson is a Professor at Mälardalen University's School of Innovation, Design and Engineering, specializing in the Division of Computer Science and Software Engineering. His primary focus is on software engineering, particularly model-based and component-based development of embedded systems. He earned his M.Sc. from Linköping University (2000) and a doctoral degree from Mälardalen University (2007) with a thesis on event pattern detection for embedded systems. Research interests include allocation optimization, timing analysis, code generation, real-time systems, and safety-critical component reuse. His work often addresses challenges such as cache-aware response time analysis, limited preemption scheduling, and integration of GPU components in embedded systems. He has contributed to projects like SCALL (a component allocator for heterogeneous systems) and Rubus (a GPU-aware component model). His research also explores continuous integration practices in model-based development and decision support systems for component selection. Key contributions include studies on architectural change management, ontology development for systems of systems, and tools for consistency checking between system models and implementations. He has authored over 80 publications, with recent work focusing on performance prediction, resource utilization, and safety-critical system integration. No notable awards are mentioned, though his extensive publication record highlights significant academic impact. Jan Carlson has advised numerous students and research teams but no explicit student names are listed in the provided text. His work is closely tied to industrial collaboration, addressing real-world challenges in automotive, railway, and smart industry domains. He actively participates in workshops and conferences, such as MARCH and ModComp, to advance model-driven engineering practices.

Azalea Raadمشاهده پروفایل

پژوهشگر

• Program Logics
• Separation Logic
• Weak Memory Concurrency
• +۱۲ مورد دیگر

Azalea Raad is a researcher at Imperial College London, actively contributing to the fields of programming languages, formal methods, and concurrency. She has a strong presence in top-tier academic conferences such as POPL, PLDI, SPLASH, and ICFP, serving in key roles including program committee member, session chair, and organizing committee member across multiple tracks and co-located events. Her research interests center on weak memory concurrency, non-volatile memory, program logics, separation logic, concurrent reasoning, and verification . She has pioneered work in incorrectness logic and under-approximate reasoning , enabling scalable bug detection in concurrent and persistent systems. Her work bridges formal theory with practical systems challenges, particularly in memory models and semantics for C/C++ and assembly-level concurrency. The recent publications highlight a strong trend toward formalizing memory persistency , extending memory models , and developing logical frameworks for bug detection . The keywords across her work include concurrency, verification, program logics, and systems correctness, with sub-fields spanning separation logic, incorrectness logic, TSO, RDMA, and crash consistency. Her research increasingly focuses on scalable and compositional methods for analyzing unsafe libraries and binaries. She has contributed to academic service through organizing workshops such as O'Hearn Fest , The Future of Weak Memory , and Incorrectness , and has co-chaired the Student Research Competition at POPL. While no grants are explicitly mentioned, her leadership in multiple conference tracks suggests active involvement in funded research and student mentorship. Azalea Raad leads or contributes to collaborative research teams focused on formal semantics and verification tools, often working within frameworks like Isabelle/HOL and developing new logical systems for program analysis. Her personal website, https://www.SoundAndComplete.org , serves as a hub for her research outputs and projects.