جست‌وجوی استاد و پژوهشگر

• Digital Humanities
• Linked Data Publishing
• Ontology Services
• +۷ مورد دیگر

Jouni Tuominen is a University Researcher at the University of Helsinki, affiliated with the Helsinki Institute for Social Sciences and Humanities (HSSH), and a visiting researcher at Aalto University's Department of Computer Science. He holds a D.Sc. (Tech.) from Aalto University (2017), where his dissertation focused on ontology services for knowledge organization systems. His roles include collaboration with the Helsinki Centre for Digital Humanities (HELDIG) and the Semantic Computing Research Group (SeCo). Education: D.Sc. (Tech.) in Computer Science, Aalto University, 2017 (Dissertation: "Ontology Services for Knowledge Organization Systems") Research Interests: Jouni specializes in ontology repositories, linked data publishing tools (e.g., ONKI and LDF.fi ), semantic modeling of legacy datasets, and computational methods for digital humanities. His work emphasizes interdisciplinary projects such as WarSampo , LawSampo , and Mapping Manuscript Migrations , aiming to integrate fragmented data into unified semantic infrastructures. He collaborates with institutions to digitize and publish cultural heritage, legal, and archaeological data for public and academic use. Articles Trends: His recent publications (2023–2025) focus on semantic portals for historical and parliamentary data, ontology-driven harmonization of heterogeneous datasets, and methodologies for enhancing Linked Open Data quality and trust. Key themes include event-based modeling for war history, epistolary networks, and cross-cultural data aggregation. Scientific Awards: While Jouni has received multiple national and international honors, specific award names are not detailed in the provided text. Advising and Grants: He leads or contributes to large-scale projects like FIN-CLARIAH, ECHOES, and ARCH-ON, funded by national and international grants. His work involves open science initiatives, such as creating the ParliamentSampo data service and co-developing the SuALT citizen science platform for archaeological data. Projects emphasize collaboration with libraries, museums, and archives to advance digital humanities infrastructure. Labs and Teams: Jouni is affiliated with the Helsinki Institute for Social Sciences and Humanities (HSSH) and the Helsinki Centre for Digital Humanities (HELDIG). He collaborates internationally through initiatives like the Mapping Manuscript Migrations project and the COST Action network for Web-centred linguistic data science. Key tools developed include FindSampo (archaeological finds), BiographySampo (biographical data), and LawSampo (legal data).

• Dataset Retrieval
• Linked Data
• Decentralised Technologies
• +۴ مورد دیگر

Dr. Luis-Daniel Ibáñez is a Lecturer in Computer Science at the University of Southampton, where he leads research in dataset retrieval, linked data, and decentralized technologies. He is affiliated with the Web and Internet Science team and the Centre for Machine Intelligence. Prior to his academic role, he worked as a Research Fellow (2015–2020) and holds a PhD from the University of Nantes, France, focusing on distributed data management. His teaching includes courses on Data Science, Data Visualization, and Data Analysis. Education: PhD in Computer Science, University of Nantes, France (Distributed Data Management Team) Computer Engineering Diploma, Universidad Simón Bolívar, Venezuela Research Interests: Focuses on scalable data systems, including decentralized knowledge graphs, data marketplaces, and provenance management. His work integrates AI techniques like LLMs for automated provenance inference and explores privacy-preserving mechanisms in data sharing. Current projects include UPCAST (Universal Platform Components for Safe Data Exchange). Advising & Grants: Supervises 5 PhD students and contributes to projects funded by research councils. His team collaborates on modular data marketplace architectures and game-theoretic approaches to data monetization. Labs/Teams: Active in the Web and Internet Science group and the Centre for Machine Intelligence at the University of Southampton.

• Pathology Informatics
• Clinical Systems Engineering
• Artificial Intelligence in Diagnostics
• +۴ مورد دیگر

Peter Gershkovich is an Associate Professor of Pathology and Director of the Section of Pathology Informatics and Cancer Data Science at Yale School of Medicine. His roles include leading software development to integrate clinical technologies and improve patient care through systems engineering. He holds an MD from Altai State Medical University (1987) and an MHA from Suffolk University (1996). His research focuses on clinical informatics, AI in diagnostics, genomic data analysis, and precision medicine platforms. Notable projects include the TQuest web platform linking tumor genetics to therapies, systems for Lynch syndrome diagnosis, and AI-driven prostate cancer detection validation. During the pandemic, his team rapidly deployed SARS-CoV-2 testing software. Recent work explores organizational readiness for AI in pathology (2023), senescent cell mapping (SenNet Consortium, 2022), and systems engineering for clinical workflows. His software solutions emphasize pragmatic, impactful integration into daily clinical operations. No scientific awards are explicitly listed in the provided materials. His academic contributions include over 15 peer-reviewed publications since 2001, with a focus on pathology informatics, laboratory systems, and oncology diagnostics.

Andrea Berez-Kroekerمشاهده پروفایل

استاد

• Documentary Linguistics
• Endangered Language Preservation
• Language Technology
• +۴ مورد دیگر

Andrea Berez-Kroeker is a Professor in the Department of Linguistics at the University of Hawaiʻi at Mānoa, specializing in documentary linguistics with a focus on endangered language preservation, language technology, and reproducible research practices. She holds a PhD from the University of California, Santa Barbara. Her work bridges linguistics, archiving, and community activism, emphasizing sustainable data practices and technological infrastructure for endangered languages. Research Interests: Her research examines discourse-functional frameworks in language description, integrating field-collected data and archived materials. She advocates for reproducible research methodologies in linguistics and leads initiatives such as the Kaipuleohana Digital Language Archive. Her projects in Alaska and Hawaiʻi prioritize community-driven language preservation and education. Labs/Teams: Director of the Kaipuleohana University of Hawaiʻi Digital Language Archive, collaborating on projects like C’ek’aedi Hwnax, an Ahtna digital archive. She also participates in international conferences and workshops on language documentation and conservation. Advising & Grants: Advises graduate students in documentary linguistics and related fields. Her work includes grants focused on digital archiving, data citation standards, and curriculum development for reproducible research practices in linguistics.

Haipeng Caiمشاهده پروفایل

دانشیار

• Software Security
• Software Engineering
• Program Analysis
• +۴ مورد دیگر

Haipeng Cai is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. Previously, he served as an Assistant Professor (2016–2022) and tenured Associate Professor (2022–2024) at Washington State University. His research focuses on software engineering and security, particularly program analysis, machine learning for security applications, and multilingual software systems. He holds a PhD in Computer Science and Engineering from the University of Notre Dame (2015). Education: PhD in Computer Science & Engineering (University of Notre Dame, 2015). Research interests include: Software security and reliability of distributed systems Machine learning-driven vulnerability detection and patching Analysis of multilingual software and cross-language bugs Tools like VGX (vulnerability data generation), PyRTFuzz (Python runtime fuzzing), and PolyFuzz (multi-language system fuzzing) Notable awards include the 2025 TOSEM Outstanding Paper Award for malware detection sustainability, multiple Distinguished Reviewer Awards, and the 2022 Junior Faculty Research Award. His work has led to over 50 publications, with a focus on practical security solutions. Advising: Mentor to students like Wen (PhD 2024, now at Utah State), Xiaoqin (first PhD graduate from his lab), and current advisees Haoran, Jiawei, and Yu. Projects include grants from NSF, ONR, and the Open Technology Fund. Key contributions include tools like VulGen (vulnerability dataset generation) and FlowDist (distributed system analysis), and labs focused on AI-driven security and multilingual software engineering.

• Responsible AI
• Software Engineering
• Machine Learning
• +۳ مورد دیگر

Mr. Boming Xia is a Research Fellow at the Responsible AI Research Centre (RAIR) and the Australian Institute for Machine Learning (AIML), University of Adelaide. He holds a position within the Faculty of Sciences, Engineering and Technology. His research focuses on advancing responsible and safe AI through a software engineering lens, particularly exploring the integration of system-level practices with machine learning approaches. His work emphasizes ethical AI development, including frameworks for risk assessment, ESG (Environmental, Social, Governance) integration, and blockchain-based accountability mechanisms. Key areas of interest include AI safety, privacy protection in generative AI, and the design of transparent software supply chains using tools like SBOM (Software Bill of Materials). Xia's contributions span empirical studies on SBOM adoption, AI system evaluation frameworks, and tools like CDCAT for cross-document entity and event coreference. His research bridges theoretical AI foundations with practical software engineering methodologies to ensure AI systems are both innovative and ethically grounded.

• Programming Language Theory
• Functional Programming
• Logic Programming
• +۳ مورد دیگر

Tom Schrijvers is a Professor at the Department of Computer Science, Faculty of Engineering Science, KU Leuven. His research focuses on programming language theory, functional programming, logic programming, and computational effects. Advancing multi-stage programming with computational effects (2024–2028) Generating Educational Feedback with Program Analysis (2024–2028) Programino: An Educational Programming Platform (2023–2027) eTeacher: Interactive web-based programming education platform (2023–2025) AmPERSand: Programming Education Runtime System (2023–2026) His recent publications emphasize bidirectional transformations, effect handlers, and programming education tools. He collaborates extensively with British institutions like Imperial College London and works on the book Language Engineering in Haskell with Dr. Nicolas Wu.

Diana Bannisterمشاهده پروفایل

پژوهشگر

• Effective use of Learning Technologies
• School Development and School Improvement
• Innovation and Creativity in the Curriculum
• +۷ مورد دیگر

Diana Bannister MBE (PFHEA) is the Director of the Institute of Education and Associate Dean at the University of Wolverhampton , Faculty of Education, Health & Wellbeing. Since 2001, she has led research and development in learning technologies, school improvement, and future educational scenarios. Principal Fellow of the Higher Education Academy (PFHEA) Expert in 1:1 learning, interactive technologies, and educational change Collaborates with Ministries of Education, commercial providers, and international agencies Education: Postgraduate Certificate in Higher Education Leadership and Management (2018) MA in Education Management and Leadership (2005) B.Ed. (Honours) (1996) Research Interests: Specializes in the effective use of learning technologies , school development , mobile learning , and innovative learning spaces . Her work bridges technology integration with pedagogical improvement across global contexts. Scientific Awards: Member of the Order of the British Empire (MBE) for Services to Education (2000) Lloyds TSB Teaching Award for Creative ICT use in Primary Education (1999) Project Leadership: Directed major international projects including Living Schools Lab (2013–present) and Creative Classrooms Lab (2012–2014), observing practices in over 30 countries. Currently supports Digital Campus Transformation as a member of the Digital Academic Reference Group.

• Knowledge Representation
• Mathematical Knowledge Management
• Natural Language Processing
• +۵ مورد دیگر

Prof. Dr. Michael Kohlhase is a Professor in the Computer Science department at FAU Erlangen-Nürnberg and an Adjunct Associate Professor at Carnegie Mellon University . His work spans Computer Science and Formal Methods , focusing on Mathematical Knowledge Management (MKM), Knowledge Representation , and Natural Language Processing (NLP) in STEM domains. He leads the KWARC (Knowledge Adaptation and Reasoning for Content) research group, driving projects like OMDoc , sTeX , and MathHub . His research emphasizes modular logical foundations for mathematical knowledge and large-scale document corpora analysis, with applications in computer-supported education and semantic document systems . Collaborations include extended visits to institutions such as SRI International , University of Amsterdam , and University of Edinburgh . Key projects include developing scalable module systems for formal mathematics, theory graph models for knowledge integration, and mathematical search engines like MathWebSearch . His work bridges formal logic with practical software systems , ensuring interoperability across proof assistants , computer algebra systems , and educational tools .

Michael Hicksمشاهده پروفایل

استاد

• Programming Languages
• Computer Security
• Quantum Computing
• +۷ مورد دیگر

Michael Hicks is a Professor in the Department of Computer and Information Science at the University of Pennsylvania and an Amazon Scholar. Previously, he was a Professor at the University of Maryland (2002-2021) and Senior Principal Scientist at Amazon Web Services (2022-2025). He co-founded the Programming Languages research lab (PLUM) at Maryland and was its director, as well as Director of the Maryland Cybersecurity Center (MC2). He is a Fellow of the Association of Computing Machinery (ACM), former Chair of ACM SIGPLAN, and Editor-in-Chief of Proceedings of the ACM on Programming Languages (PACMPL). His research focuses on programming languages and their application to software security , quantum programming , and formal verification . He has pioneered dynamic software updating techniques, developed tools like Checked C for memory safety, and co-designed the Cedar authorization policy language at AWS. In quantum computing, he works on verified compilers like VOQC and Qunity to ensure reliability and correctness. His recent work trends include quantum programming languages , secure multi-party computation (e.g., Wysteria , Symphony ), and fuzz testing methodologies . He has contributed to formal verification for quantum programs and language-based security frameworks. Scientific Awards include: ACM Fellow He has advised numerous PhD and Master’s students , including James Parker, Andrew Ruef, Kesha Hietala, and Aseem Rastogi, who now hold academic and industry positions. His lab, PLUM , has been instrumental in advancing programming languages research.

Shriram Krishnamurthiمشاهده پروفایل

استاد

• Programming Languages
• Type Systems
• Formal Methods
• +۳ مورد دیگر

Shriram Krishnamurthi is a Professor in the Department of Computer Science at Brown University, specializing in programming languages, formal methods, and software education. His research focuses on language design, type systems, and pedagogical approaches to programming concepts. Recent publications highlight his work in areas such as Rust trait error debugging formal methods teaching tools automated type error telemetry document calculus design logic misconceptions in education His contributions also include program committee roles at major conferences like SPLASH, ICFP, and SIGCSE.

Sukyoung Ryuمشاهده پروفایل

استاد

• Programming Languages
• Static Program Analysis
• WebAssembly
• +۳ مورد دیگر

Sukyoung Ryu is a Professor at KAIST, focusing on programming languages and static program analysis. Her work spans JavaScript analysis, WebAssembly, Rust translation frameworks, and language specification verification. Education : Not explicitly mentioned Research Focus : Programming languages, static analysis, JavaScript, WebAssembly, Rust, Android hybrid apps, type systems Conference Roles : Co-chair (OOPSLA Review Committee, New Faculty Symposium), Committee Member (ICFP, ECOOP, ASE, PLDI, ICSE), Session Chair (SCAM, Type Systems, Keynotes) Keynote Talks : PLDI 2021, ICFP 2020, Scala 2019 Tool Development : SAFE framework, SpecTec, Wasm-R3, HybriDroid, WALA extensions Her recent publications focus on WebAssembly benchmarks, language specification verification, and memory/concurrency safety in cross-language translation. She contributes to open-source analysis tools and standards development. As a committee member and session chair for conferences like PLDI, ICFP, and SPLASH, she actively shapes research directions in programming language design and analysis. Her lab at KAIST develops tools like SpecTec for mechanized language specifications.

Ben Greenmanمشاهده پروفایل

استادیار

• Language Design
• Type Systems
• Formal Methods
• +۱ مورد دیگر

Ben Greenman is an Assistant Professor at the University of Utah's Department of Computer Science. He has affiliations with institutions including Cornell University (BS, M.Eng), Northeastern University (PhD), and Brown University (CIFellows 2020). His work spans programming language design, type systems, formal methods, and human factors in software development. His research focuses on Gradual typing and type soundness Language design with emphasis on usability Formal methods education tools Empirical studies of type system usage Recent work analyzes temporal logic misconceptions, privacy-respecting telemetry for type errors, and macro systems without traditional syntax barriers. His publications reveal trends in Gradual type migration Runtime monitoring and profiling Visual formal methods Developer-centric language design He has received the CIFellows 2020 award and serves on program committees for SPLASH, Scheme, and other conferences. His work addresses both theoretical and practical aspects of programming language design.

KC Sivaramakrishnanمشاهده پروفایل

استادیار

• Functional Programming
• Language Runtimes
• Concurrency
• +۴ مورد دیگر

KC Sivaramakrishnan is an Assistant Professor at Indian Institute of Technology Madras and concurrently serves as CTO of Tarides. He works at the intersection of programming languages and systems, focusing on concurrency, distributed systems, and OCaml runtime development. Primary Affiliation: Indian Institute of Technology Madras Co-founder: Tarides His research explores: Concurrency and parallelism in OCaml Effect handlers for modular programming Mergeable Replicated Data Types for distributed systems Weak memory models and consistency guarantees Lock-free algorithms and safe multicore programming Recent publications focus on OCaml 5.0's concurrency features, effect handler integration, and verified CRDT implementations. He contributes to compiler design, runtime optimization, and testing frameworks for multicore systems. Service roles include committee memberships in SPLASH, ICFP, OCaml, and PROPL conferences. He actively bridges functional programming with systems research through practical implementations.

Alvin Cheungمشاهده پروفایل

دانشیار

• Data Management
• Programming Languages
• Software Systems
• +۳ مورد دیگر

Alvin Cheung is an Associate Professor at the University of California at Berkeley, affiliated with the Department of Electrical Engineering and Computer Sciences (EECS). He leads the Data Systems and Foundations group, Programming Systems group, Sky Lab, and SLICE Lab, while also serving as a faculty affiliate at the Berkeley Institute for Data Science. His research focuses on integrating data management, programming languages, and software systems to develop tools for scalable data processing pipelines and improved data programming experiences. PhD students advised: Sahil Bhatia, Mick Kittivorawong, Jongseok Park Research keywords include Data Management , Programming Languages , Program Synthesis , Formal Verification , and Machine Learning . His recent work explores Verified Lifting techniques for database applications, stencil computations, and cloud systems, alongside novel programming paradigms for geospatial video analytics and speculative decoding. His publications from 2023-2025 demonstrate trends in LLM-driven code optimization , automated SQL equivalence , and neural code generation across domains like tensor operations and geospatial video systems. Notable scientific achievements include the Dahl-Nygaard Prize (2024) , VLDB Early Career Award (2023) , and CHI Best Paper Award (2021) .