جست‌وجوی استاد و پژوهشگر

Ibraheem Al-Dhamariمشاهده پروفایل

پژوهشگر

• Trustworthy AI
• Deep Learning
• Computer Vision
• +۳ مورد دیگر

Ibraheem Al-Dhamari is a postdoctoral researcher in the Software Engineering Institute at the University of Koblenz, Germany. He holds a PhD in Computer Science supported by DAAD scholarships, alongside MSc and research grants from DAAD. His primary research focuses on Trustworthy AI, Deep Learning, Medical Image Analysis, and Cellular Automata, with applications in healthcare imaging and data protection. He has contributed to projects like medical image registration algorithms and cochlear implant analysis. Al-Dhamari's academic journey includes postdoctoral work at the Institute of Software Engineering (Department 4), and he previously belonged to the Arbeitsgruppe Paulus (Active Vision Group). His work bridges computer science and medicine, emphasizing practical tools for clinical imaging challenges. He actively mentors students seeking thesis opportunities in AI and medical imaging through DAAD-funded programs. His achievements include developing ultra-fast algorithms for medical image analysis and pioneering multi-modal imaging fusion techniques. He maintains an active GitHub profile showcasing repositories like medical-image-registration-course and tutorials on deep learning and recursion. Al-Dhamari is affiliated with organizations such as the International Data Spaces Association and contributes to open-source software for medical research. Key awards include DAAD scholarships for MSc (2007), short research (2008), and PhD (2012). His research has led to innovations in cochlear duct measurement, cervical spine analysis, and cellular automata-based data mining. He remains a sought-after collaborator in interdisciplinary projects at the intersection of AI and healthcare.

• Neuromorphic Computing
• Reservoir Computing
• Reinforcement Learning
• +۳ مورد دیگر

Prof. Abigail Morrison is a Professor and Group Leader of the Computation in Neural Circuits group at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich. Her work focuses on advancing neuromorphic computing, reservoir computing, and spiking neural network simulations. She leads development of the NEST simulator and NESTML modeling language, tools critical for large-scale brain modeling. Key research areas include: Neuromorphic hardware-software co-design Biophysically plausible neural network models GPU-accelerated simulation frameworks Multi-scale brain co-simulation techniques Applications in embodied AI and neuroscience Her lab contributes to the European EBRAINS infrastructure and has pioneered methods for parallel GPU-based network construction. Recent work explores topographic neural circuit architectures for signal processing and reinforcement learning in neuromorphic systems. Notable achievements include: Development of NESTML (v8.0+) ODE-toolbox for ODE solver selection Co-design of HNC neuromorphic compute nodes Advances in dendritic computation modeling Current efforts emphasize exascale computing readiness, neuromorphic system validation, and bridging biological plausibility with computational efficiency in neural network simulations.

Johanna Senkمشاهده پروفایل

پژوهشگر

• Spiking Neural Networks
• Neuromorphic Computing
• High-Performance Computing
• +۳ مورد دیگر

Dr. Johanna Senk is a Team Leader of the Future Simulation Architectures team at the Institute for Advanced Simulation (IAS-6), part of Forschungszentrum Jülich GmbH. Her research focuses on spiking neural networks, neuromorphic computing, and high-performance computing, with an emphasis on simulation technology and reproducible science. She leads efforts to develop scalable architectures for large-scale neuronal network simulations, particularly leveraging GPU-based systems and neuromorphic hardware. Her work bridges theoretical neuroscience and computational engineering, addressing challenges such as network connectivity design, metadata standardization for scientific workflows, and optimizing simulation efficiency. Key contributions include the development of the NNMT toolbox for mean-field analysis and the beNNch framework for performance benchmarking. Senk’s team collaborates extensively on multi-area cortical models and has published extensively on topics like GPU-accelerated neuronal network construction, synaptic dynamics modeling, and the reconciliation of spiking activity with local field potentials. Her research aims to advance both computational methods and biological understanding of neuronal systems.

William Grissomمشاهده پروفایل

استاد

• Medical Imaging
• MRI Technology
• Biomedical Engineering
• +۴ مورد دیگر

William A. Grissom, PhD, is the Medtronic Professor of Biomedical Discovery and Innovation at the School of Medicine and a Professor of Biomedical Engineering at Case Western Reserve University's Case School of Engineering. He leads the Grissom Lab, which focuses on advancing MRI techniques through novel RF pulse designs, coil innovations, and computational methods to enhance imaging capabilities for ultra-high and low-field applications. His work includes developing real-time MRI-guided therapies such as focused ultrasound, ultrasound neuromodulation for pain treatment, and robotic laser thermal therapy for epilepsy. Collaborations span institutions like Vanderbilt, Stanford, and Harvard Medical School. His research is funded by NIH, DoD, and the Focused Ultrasound Foundation. Research interests emphasize maximizing MRI's informational value by integrating RF advancements with computational strategies. The lab's projects address challenges in imaging precision, real-time monitoring during interventions, and improving therapeutic targeting accuracy. Notable contributions include low-field MRI system designs, artifact mitigation in transcranial applications, and B1+ selective excitation techniques. Grissom's articles reflect a focus on cutting-edge MRI hardware, thermometry innovations, and translational applications of imaging technologies. His work bridges engineering and clinical needs, aiming to enhance diagnostic and therapeutic outcomes through advanced imaging systems.

• Programming Languages
• Program Synthesis
• Program Verification
• +۷ مورد دیگر

Jedidiah McClurg is an Assistant Professor in the Department of Computer Science at Colorado State University, with prior faculty appointments at Colorado School of Mines and the University of New Mexico. He received his Ph.D. in Computer Science from the University of Colorado Boulder in 2018, where he was a member of the CUPLV research group under the supervision of Pavol Cerny. His research focuses on programming languages, program synthesis, verification, and their applications in networking, compilers, and distributed systems. His educational background includes an M.S. in Computer Science from Northwestern University (2013) and a B.S. in Electrical Engineering from the University of Iowa (2009). He has completed internships at Microsoft Research (RiSE Group, 2014) and Rockwell Collins (2011, 2013, 2004). McClurg’s research interests include programming languages, formal verification, software synthesis, software-defined networking, compilers, and system security. His work aims to develop tools and techniques that help programmers write more secure, reliable, and efficient code, especially in safety-critical domains. He has led multiple NSF-funded projects, including FMitF and CRII grants, totaling over $1 million in funding. His recent publications span high-impact venues such as PLDI, CAV, DISC, and SOSR, with topics ranging from neural network optimization and regular expression synthesis to network program verification and FEC code generation. These works reflect a consistent trend toward automating correctness, improving performance, and enabling scalable solutions in systems and networking. NSF CRII: SHF: Foundations for Stateful Network Programming ($175,000) NSF FMitF: Game Theoretic Updates for Network & Cloud Functions ($355,000 for him) NSF FMitF: Robust Enforcement of Customizable Resource Constraints ($250,000 for him) NSF GRFP (awarded to student Lauren Baker) He has advised multiple graduate and undergraduate students, many of whom have secured positions at leading tech companies such as Google, Apple, and Amazon. He is actively involved in academic service, having served on program committees for PLDI, SOSR, CAV, and others, and as a reviewer for journals like IEEE/ACM Transactions on Networking (ToN) and ACM Transactions on Software Engineering (TSE). He also contributes to open-source research via GitHub and maintains a strong online academic presence.

• Cell Biology
• Molecular Biophysics
• Membrane Dynamics
• +۷ مورد دیگر

Helge Ewers is a Full Professor at Freie Universität Berlin, where he conducts cutting-edge research in cell and molecular biophysics. Previously, he served as a Senior Lecturer at King's College London, a Group Leader at ETH Zürich, and a Postdoctoral Fellow at CNRS Bordeaux, establishing a robust international academic profile. His research focuses on the molecular and cellular mechanisms underlying membrane organization, cytoskeletal dynamics, and unconventional protein secretion. Key areas include septin biology, super-resolution microscopy, expansion microscopy, and nanoscale imaging of cellular structures. He employs advanced techniques such as DNA-PAINT, interferometric scattering microscopy, and deep learning-based image analysis to study compartmentalization and dynamics at the plasma membrane and organelles. The recent publications highlight a strong trend in developing and applying innovative imaging technologies to address fundamental questions in cell biology. His work spans from method development (e.g., open-source microscopes, expansion microscopy variants) to mechanistic studies in membrane biophysics, cytokinesis, and neurobiology. Collaborative efforts with physicists, chemists, and computational scientists underscore an interdisciplinary approach. Scientific Awards and Recognition: Editorial contributions to special issues on septin biology in Cytoskeleton Peer reviewer for high-impact journals including Angewandte Chemie and Nature Photonics Advising and Collaborative Research: Dr. Ewers mentors and collaborates with a dynamic group of early-career scientists, including Jakob Rentsch, Amin Zehtabian, and Nadja Hümpfer. His lab fosters interdisciplinary research, combining biology with physics, chemistry, and computational modeling. While specific grant details are not listed, his sustained publication output in top-tier journals suggests active funding and research support. Laboratories and Research Teams: He leads a research group at Freie Universität Berlin focused on quantitative cell biology and advanced microscopy. His team develops and applies novel imaging tools to study membrane and cytoskeletal dynamics, contributing to both technological innovation and biological discovery.

Biagio Cosenzaمشاهده پروفایل

دانشیار

• High-performance computing
• Compiler technology
• Software optimization
• +۷ مورد دیگر

Biagio Cosenza is an Associate Professor at the Department of Computer Science, University of Salerno, Italy. He leads research in high-performance computing, compiler technology, and software optimization. Previously, he was a Senior Researcher at TU Berlin (2015-2019) and a Post-Doctoral Researcher at the University of Innsbruck, Austria (2011-2015). His educational background includes: Ph.D. from University of Salerno (2011), supervised by Prof. Vittorio Scarano Dr. Cosenza's research focuses on creating efficient programming models for heterogeneous computing systems. His work spans compiler technology, automatic performance tuning, and energy-efficient computing approaches. He has made significant contributions to SYCL-based programming models and MPI implementations, with emphasis on portability across diverse hardware platforms including GPUs and accelerators. His research often bridges theoretical computer science with practical applications in scientific computing and bioinformatics. His recent publications demonstrate a strong trend toward heterogeneous and distributed computing, with particular emphasis on energy efficiency, performance portability, and SYCL-based programming models. Many papers focus on applications in drug discovery and scientific simulations, showing how his theoretical work translates to real-world scientific problems. Dr. Cosenza has received several prestigious recognitions: Best Paper Award at the 14th BenchCouncil International Symposium (2022) Elevated to Senior Member of the IEEE (2022) Recognized as ACM Senior Member (2022) He leads multiple significant research projects including the PRIN 2022 project "LibreRT" and the EuroHPC project "LIGATE." His work has secured substantial funding from sources including the German Research Foundation (DFG), the Italian Ministry of Education, University and Research, and EuroHPC. He actively mentors students and collaborators on advanced topics in high-performance computing. Dr. Cosenza is a member of the ISIS Lab at the University of Salerno and contributes to open standards through his work with the Khronos Group and SYCL Working Group. His research group develops tools like CELERITY, a C++ SYCL-based programming model for accelerator clusters, and EMPI, an enhanced message passing interface in modern C++.

Tobias Grosserمشاهده پروفایل

دانشیار

• Compilers
• Polyhedral Compilation
• Performance Programming
• +۷ مورد دیگر

Tobias Grosser is an Associate Professor in Compiler Design at the Department of Computer Science and Technology, University of Cambridge. His research spans compilation, programming language design, and performance programming with applications to climate science, quantum computing, and hardware design. He leads an active research group focusing on making compilers more modular, predictable, and trustworthy while bridging the gap between developers and compilers. His research interests include: Compilers and polyhedral compilation Static and dynamic program analysis High-performance computing and loop optimization Domain-specific compilation for accelerators (GPU, FPGA) Formal verification for compiler correctness Machine learning applications to compiler design His recent publications demonstrate significant contributions to multi-level intermediate representations (MLIR), compiler verification using Lean, and performance modeling. His work on xDSL provides a Python-native compiler framework that enables rapid prototyping of compiler infrastructure. His research group has developed tools like FPL (Fast Presburger Library) for loop optimization in deep learning and scientific computing. Scientific awards include two Amazon Research Awards (2023-2024) for work in automated reasoning, a Google PhD Fellowship, and an Ambizione Fellowship at ETH Zurich. He has advised numerous PhD students and researchers who have gone on to positions at Google, ETH Zurich, NVIDIA, and Intel. He actively collaborates with industry through the Amazon Scholars program and hosts regular Compiler Social events in Cambridge. His research vision emphasizes connecting compiler technology with societal challenges like climate change while maintaining a strong commitment to open-source development and diversity in computer science.

Sören Totzauerمشاهده پروفایل

مدرس

• Human-Computer Interaction
• Internet of Things
• Participatory Design
• +۷ مورد دیگر

Sören Totzauer is a Lecturer (Lehrkraft für besondere Aufgaben) at the Faculty of Digital Transformation at HTWK Leipzig, where he teaches courses in computer science, including Algorithms and Data Structures, Database Management Systems, and Big Data Management. He serves as Deputy Liaison Lecturer and is a member of the IKM study commission, actively contributing to academic governance and curriculum development. His research interests span Human-Computer Interaction (HCI) , Internet of Things (IoT) , Participatory Design , E-Learning , and Game Theory . His work emphasizes user-centered and ethical approaches to technology design, particularly in domestic environments. His recent publications, presented at premier venues like CHI, DIS, and NordiCHI, reveal a consistent focus on how people interact with and make sense of sensor data in smart homes, the design of tangible interactive devices, and innovative methods for co-creation and research. His research often employs participatory and creative methods, such as probe-based studies, multisensory prototyping, and playful design tools like 'Loaded Dice'. He is actively involved in research projects such as Miteinander (2016–2020) and ZKProSachs (2009–2012), and his work has been recognized through peer review for major conferences. His commitment to teaching is further demonstrated by his certification from the Saxony University Teaching Center and his role in developing and delivering preparatory courses and e-learning modules. His academic contributions are current and ongoing, with publications and activities documented up to 2023 and 2025, respectively.

Christopher Pulteمشاهده پروفایل

پژوهشگر ارشد

• Programming Language Semantics
• Type Systems
• Concurrency
• +۳ مورد دیگر

Christopher Pulte serves as a Royal Society University Research Fellow and Affiliated Lecturer in the Computer Laboratory at the University of Cambridge, where his work bridges theoretical computer science and practical systems verification. His research specifically targets the verification challenges of low-level systems software where hardware concurrency models complicate correctness proofs. His educational foundation includes: PhD in Computer Science from University of Cambridge (supervised by Peter Sewell) Master's degree from University of Cambridge Undergraduate studies at Technical University Dortmund Pulte's research program focuses on developing formal methods for systems software verification, particularly through programming language semantics and type systems. He investigates how to reason about concurrent systems under relaxed memory models (ARM, RISC-V), creating frameworks that make verification tractable for security-critical components like hypervisors. His approach combines executable semantics with refinement typing to handle real-world complexity while maintaining mathematical rigor. Analysis of his publication trajectory reveals consistent innovation in formalizing processor memory architectures and building verification tools that scale to production systems. His work demonstrates increasing emphasis on practical applications, notably through verification of Google's pKVM hypervisor components, while maintaining strong theoretical foundations in separation logic and concurrency semantics. His scientific recognition includes: Royal Society University Research Fellowship Pulte actively contributes to Cambridge's academic mission through teaching core computer science courses including 'Hoare Logic and Model Checking' for Part II students and guest lectures on 'Multicore Semantics and Programming'. He leads development of practical verification tools like CN (for C systems verification) and rmem (for memory architecture modeling), which have gained adoption in both academic and industrial research contexts through open-source distribution. As part of the Computer Laboratory's Systems Research Group, he collaborates extensively with Peter Sewell's team on the REMS project, focusing on executable specifications for hardware/software interfaces. His current work extends these foundations to emerging architectures while improving the usability of verification frameworks for systems developers.

Harry Xuمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Computer Systems
• +۳ مورد دیگر

Harry Xu is a Professor in the Computer Science Department at the University of California, Los Angeles (UCLA), with a research focus on computer systems spanning programming languages, compilers, runtime/operating systems, distributed systems, and computer architecture. Prior to UCLA, he was an Associate Professor at UC Irvine (UCI). His current work centers on infrastructures for future cloud computing (user-defined clouds) and scalable, cost-effective AI/ML systems. Education : Ph.D. in Computer Science and Engineering from Ohio State University (2011) His research has pioneered techniques for combating software bloat, optimizing data analytics through programming language innovations, and developing systems like Yak GC, VQPy, and Niijima. He co-founded BreezeML, a startup for GenAI risk management, and has held visiting roles at Microsoft Research and IBM Watson Research Center. Recent publications include work on resource-disaggregated datacenters, cloud computing fault tolerance, and ML system scalability, presented at top venues like SOSP, OSDI, and NSDI. He has advised numerous Ph.D. and M.S. students, many of whom now hold academic or industry roles. Awards : 2018 Dahl-Nygaard Junior Prize, ACM Distinguished Scientist Harry actively contributes to academic service as a committee member and co-chair at conferences like PLDI, SPLASH, and VMCAI. He maintains the VQPy project and other open-source systems.

João Carlos Antunes Leitãoمشاهده پروفایل

دانشیار

• Distributed Systems
• Cloud Computing
• Peer-to-Peer Networks
• +۳ مورد دیگر

João Carlos Antunes Leitão is an Associate Professor in the Informatics Department at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa , and an Integrated Member of NOVA Laboratory for Computer Science and Informatics (NOVA LINCS) . His research focuses on the scalability and dependability of large-scale distributed systems, particularly in cloud computing , peer-to-peer networks , and geo-distributed environments . He leads work packages in European research projects such as TaRDIS and contributes to projects like Syncfree and LightKone. Research interests include: Scalability of distributed systems Causal consistency in geo-replicated storage Self-organizing overlay networks Edge and fog computing Searchable encryption on trusted hardware Framework development for distributed protocols Publication trends show consistent work on distributed hash tables , causal consistency , edge computing , and secure protocols . His framework Babel is designed for performant and dependable distributed protocol development with applications in self-configuration and security. Scientific awards : Best student paper at IEEE NCA13 (2013) Best Paper Award at Inforum 2018 Best Student Paper at CPDLA Track, Inforum 2023 Best Paper Award at Inforum 2011 Advising and grants : João earned his Ph.D. from Instituto Superior Técnico (IST) under Prof. Luis Rodrigues . He has supervised students like Pedro Fouto, Pedro Ákos Costa, and Nuno Preguiça. His research is supported by European projects TaRDIS , Syncfree , and LightKone . Labs and teams : João works with the Computer Systems Group at NOVA LINCS and contributes to open-source frameworks like Babel and Yggdrasil for distributed protocol development and wireless edge systems.

Arthur J. Lembo, Jr.مشاهده پروفایل

استاد

• Geographic Information Systems (GIS)
• Geo-processing and spatial analysis
• Enterprise GIS implementation
• +۷ مورد دیگر

Arthur J. Lembo, Jr. is Professor of Geography and Geoscience in the Henson School of Science and Technology at Salisbury University, where he has taught since 2007. He also serves as Technical Director of the Eastern Shore Regional GIS Cooperative, leading regional geospatial initiatives and enterprise GIS projects. Education B.S. Geography, State University of New York, College at Oneonta (1987) M.A. Geography, State University of New York at Buffalo (1989) Ph.D. Environmental Resource Engineering, State University of New York, College of Environmental Science and Forestry (1997) Research Interests Dr. Lembo’s research centers on the innovative application of advanced information technologies to geographic problem-solving. His work explores high-performance GIS through massively-parallel algorithms executed on consumer-grade gaming GPUs, enterprise-scale spatial database design, and the integration of smartphone sensors into real-time mapping workflows. Additional emphases include spatial decision support for post-disaster infrastructure assessment, crime analysis, and sustainable local food systems. Selected Research Sponsors National Science Foundation (multiple awards) W. K. Kellogg Foundation Maryland Governor’s Office of Crime Control and Prevention Maryland Department of Natural Resources USDA and NASA Scientific Awards 2018 State of Maryland Board of Regents Award for Teaching Excellence 2006 SUNY Chancellor’s Award for Excellence in Teaching 2005 NACTA Teacher of Merit 2003 CALS Faculty Innovation in Teaching Award, Cornell University 2002 & 2003 Master Teacher recognition, University of Mississippi & NASA Teaching & Outreach Dr. Lembo teaches core GIS programming and spatial-analysis courses (GEOG 204, 415, 419, 435, 619) and maintains an active extension program that provides GIS solutions for municipalities, first responders, and environmental NGOs such as The Nature Conservancy and the City of Havre de Grace. Lab & Teams He directs the Eastern Shore Regional GIS Cooperative, a university-based center that supports multi-agency geospatial data sharing and application development across Maryland’s Eastern Shore.

Francesco Arzaniمشاهده پروفایل

استادیار

• Quantum Information Science
• Quantum Optics
• Continuous-Variable Quantum Computing
• +۵ مورد دیگر

Francesco Arzani is a junior professor at INRIA Paris and a member of the QAT team within the Department of Informatics at École Normale Supérieure. He obtained his PhD from ENS/PSL and Laboratoire Kastler Brossel, followed by post-doctoral appointments at LIP6, LORIA and Freie Universität Berlin. His research sits at the intersection of quantum optics and quantum information, with a focus on continuous-variable systems, bosonic error-correcting codes and fault-tolerant quantum computation. Education: PhD in Physics, École Normale Supérieure & Paris Sciences Lettres (2018) Graduate studies in quantum optics, Laboratoire Kastler Brossel Research interests: Arzani’s work targets the theory–experiment interface of continuous-variable quantum information processing. He designs non-Gaussian resources (photon subtraction, engineered squeezing), develops bosonic error-correcting codes (notably Gottesman–Kitaev–Preskill codes) and investigates fault-tolerant architectures that remain realistic with present-day photonic technology. Key themes include universal CV gate sets, entanglement in optical frequency combs, measurement-based quantum computation and the mathematical structure of lattice codes in phase space. Publication trends: Across 20+ peer-reviewed articles and several preprints, Arzani consistently advances from abstract code design to experimental feasibility . Recent works (2022-2025) emphasize fault-tolerant thresholds and symmetry-enhanced variational algorithms, while earlier papers map out practical methods to generate and certify multimode entanglement in femtosecond-frequency-comb platforms. Scientific outreach & awards: He has delivered invited seminars at Xanadu, WACQT, NC State and numerous international workshops; serves as referee for leading quantum journals; and maintains open-source slides and posters for community use. No competitive fellowships or prizes are explicitly listed in the supplied sources. Team & grants: Arzani leads independent research funded through the INRIA Junior Professor Chair scheme and participates in the French “Défi EQIP” quantum initiative. He collaborates closely with experimental groups at Kastler Brossel, Xanadu and within the EU continuous-variable quantum community, co-supervising graduate students and post-docs in the QAT team.

• Music Information Retrieval
• Artificial Intelligence
• Audio Signal Processing
• +۳ مورد دیگر

Gerhard Widmer is a Full Professor at the Institute of Computational Perception within the Faculty of Engineering and Natural Sciences at Johannes Kepler University Linz (JKU). He leads research at the LIT Artificial Intelligence Lab and serves as principal investigator for major projects including the FWF-funded Cluster of Excellence "Bilateral Artificial Intelligence" (2024-2029) and the EU project "Whither Music?" (2022-2026), focusing on AI applications in music cognition and performance analysis. His research spans Music Information Retrieval (MIR) with emphasis on computational modeling of musical expressivity, audio processing, and machine learning applications. Key areas include sound event detection, music transcription, language-based audio retrieval, and modeling of expressive musical performances using deep learning techniques. His work bridges artificial intelligence with musicology to develop systems capable of understanding and generating human-like musical expressions. Analysis of recent publications (2024-2025) reveals a strong trend toward diffusion models for audio generation/manipulation, robustness studies in music emotion recognition, and efficient architectures for sound event detection. There is significant focus on multimodal approaches integrating audio with textual descriptions, knowledge distillation for model compression, and real-time processing solutions for symbolic music analysis and score following. No specific scientific awards are documented in the provided materials. Professor Widmer has supervised 8 research works and manages multiple funded projects: Cluster of Excellence "Bilateral Artificial Intelligence" (FWF, 2024-2029): Investigating human-AI collaborative intelligence "Whither Music?" (EU, 2022-2026): Exploring AI's impact on musical creativity CoMIRVA: Developing music information retrieval visualization tools Sony-CSL project (2021-2024): Industry collaboration on music cognition He directs the Institute of Computational Perception at JKU and is central to the LIT Artificial Intelligence Lab, maintaining active collaborations with the International Society for Music Information Retrieval (ISMIR) community through conferences, shared datasets, and open-source tools like Partitura for symbolic music processing.