جست‌وجوی استاد و پژوهشگر

• Educational Technology
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Adrián Domínguez Díaz is an Assistant Professor at the University of Alcalá's Department of Computer Science. He specializes in educational technology, cybersecurity, and artificial intelligence applications. His research focuses on gamification in education, dark web content analysis, and machine learning methodologies. He is affiliated with the PMI (Intelligent Mobile Platforms) and TIFyC (Information Technologies for Training and Knowledge) research groups. He earned his Ph.D. from the Universidad de Alcalá in 2018 with a thesis on gamification and social networks' impact on academic performance. His work bridges computer science with pedagogical innovation, emphasizing data-driven solutions for education and cybersecurity challenges. Research interests include: - AI-driven content analysis (ChatGPT, GPT-3.5) - Dark web threat detection and classification - Gamification strategies for student engagement - Sustainability in high-performance computing His recent publications (2023–2025) highlight advancements in automated content analysis, cybersecurity threat modeling, and gender detection algorithms. No scientific awards have been explicitly noted. Advising: Supervised theses on gamification and e-learning (e.g., 2018 thesis). No grants listed, but active in collaborative projects like μDevOps. His research groups develop mobile technologies and educational platforms.

• Computer Science
• Artificial Intelligence
• Cybersecurity
• +۷ مورد دیگر

Luis de Marcos Ortega is a Full Professor at the Department of Computer Science, University of Alcalá. He belongs to the TIFyC research group (Information Technologies for Training and Knowledge), focusing on interdisciplinary intersections of computer science, education technology, and cybersecurity. He holds a PhD from the University of Alcalá (2009), with a thesis on adaptive educational content sequencing using AI agents. His research interests span Artificial Intelligence applications (e.g., ChatGPT for automated analysis), Cybersecurity (dark web threat patterns, malware detection), Education Technology (gamification, mobile learning usability), and Interdisciplinary studies (gender representation in academia, editorial board dynamics). Recent work emphasizes AI-driven solutions for content analysis, dark web monitoring, and healthcare IT security. Key contributions include methodological frameworks for gender detection via AI, optimization of dark web datasets for OpenAI processing, and UML profiles for accessible web design. His publications also address usability guidelines for mobile apps, continuous authentication systems (e.g., JBCA architecture), and gamification in MOOCs and classroom environments. He has collaborated on projects like the μDevOps platform for cyber ranges, the ProTego healthcare security initiative, and the ECO iMOOC gamification experiment. His work frequently bridges technical innovation with societal impact, emphasizing accessibility, ethical AI, and academic equity.

Ingo Weberمشاهده پروفایل

استاد

• Business Process Management
• Process Mining
• Software Architecture
• +۵ مورد دیگر

Prof. Dr. Ingo Weber is a Full Professor at the Technical University of Munich (TUM) in the Department of Information System Development and Operation within the TUM School of Computation, Information and Technology. He also serves as Director of Digital Transformation and ICT Infrastructure at the Fraunhofer-Gesellschaft. Previously, he held a full professorship at TU Berlin (2019–2022) and spent a decade in Australia researching at CSIRO, NICTA, and UNSW. His research focuses on Business Process Management (BPM), Process Mining, Blockchain technology, Software Architecture, DevOps, and AI Systems Engineering. Weber has authored/co-authored influential books including DevOps: A Software Architect's Perspective (Addison-Wesley, 2015) and Engineering AI Systems: Architecture and DevOps Essentials (2025). Education & Career - PhD in Semantic Methods for Business Process Modeling (University of Karlsruhe, 2009) - SAP Research parallel role during doctoral studies - Tenured Professorships at TU Berlin and TUM Research Interests Weber's work bridges academic theory and industrial applications. Key areas include: - Blockchain-based process execution (Caterpillar framework on Ethereum) - AI-driven DevOps practices - Scalable transaction creation in blockchain systems - Sustainability-oriented process analysis (SOPA framework) - Generative AI for large process models Awards - Two-time BPM Best Blockchain Paper Award (2019/2022) - ISSRE Best Paper (2015) - CSIRO/NICTA Excellence Awards (2015–2018) - EDOC 2023 Best Paper Grants & Labs - Leads Fraunhofer's digital transformation initiatives - Collaborates with industry partners like Commonwealth Bank (Australia) - Active in EU/CSIRO-funded blockchain research projects Key Contributions - Pioneered blockchain-based BPM systems (Caterpillar) - Defined blockchain pattern taxonomies - Developed tools like BLF (Blockchain Logging Framework) - Advocates for responsible AI engineering practices

Hong Jin Kangمشاهده پروفایل

مدرس

• Active Learning
• Artificial Intelligence
• Software Engineering
• +۳ مورد دیگر

Hong Jin Kang is a Lecturer in the School of Computer Science at The University of Sydney. His research focuses on improving developer productivity through human-centric AI tools, particularly in Active Learning and AI-driven Software Engineering. Prior roles include postdoctoral fellowships at UCLA and a PhD at Singapore Management University (SMU), advised by Prof. David Lo. His work spans vulnerability detection, program transformation, and software supply chain security, with practical industry impact through CVE discoveries and deployed techniques. Education : PhD in Computer Science, Singapore Management University (2023) Postdoctoral Research, University of California, Los Angeles (UCLA) Research Interests : Active Learning for code analysis and vulnerability management AI and ML integration into software development tools Cybersecurity in software supply chains Program transformation and legacy code modernization His publications address challenges in automated tool development, including vulnerability identification (e.g., CHRONOS), code model compression, and adversarial specification mining. Recent work emphasizes sustainability in AI and human-in-the-loop systems. Awards : Distinguished Reviewer Award for ICSE 2025 Advising & Grants : Actively mentoring PhD students in software engineering and AI, with a focus on curiosity-driven candidates. His research is supported by collaborations with industry and academic institutions. Labs/Teams : Pioneers tools like Coccinelle4J for Java program transformation and collaborates on projects such as VulCurator and HERMES for vulnerability analysis.

Joshua Mandelمشاهده پروفایل

مدرس

• Biomedical Informatics
• Health Information Technology
• API Development
• +۷ مورد دیگر

Joshua Mandel, MD, is a Lecturer on Biomedical Informatics (Part-time) at Harvard Medical School's Department of Biomedical Informatics within the Faculty of Medicine. He is also the Chief Architect at Microsoft Healthcare and Project Lead for Sync for Science, contributing significantly to national health IT standards and API ecosystems. His research interests lie at the intersection of medicine and technology, focusing on Biomedical Informatics , Health Information Technology , and API Development for clinical data interoperability. He is particularly passionate about building tools and interfaces that empower software developers new to the healthcare domain, supporting innovation in Learning Health Systems and Digital Health . Joshua Mandel plays a key role in national health IT policy as a member of the Health IT Standards Committee. His work on the SMART Health IT platform and the Blue Button REST API has advanced open standards for accessing electronic health records. He bridges academia and industry, driving forward initiatives like Sync for Science to enable secure research use of clinical data. He earned his S.B. in Computer Science and Electrical Engineering from the Massachusetts Institute of Technology and his M.D. from Tufts University School of Medicine. His career uniquely combines clinical medicine, software development, and health policy leadership. Joshua Mandel leads major technology initiatives including: SMART Health IT – Open platform for health app development Sync for Science (S4S) – Enabling research access to EHR data Blue Button REST API – National standard for patient data access Microsoft Healthcare API strategy – Cloud-based health data platforms

Foyzul Hassanمشاهده پروفایل

استادیار

• Software Engineering
• Machine Learning
• Continuous Integration (CI)
• +۷ مورد دیگر

Foyzul Hassan is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan-Dearborn , where he focuses on improving software development productivity through research in Continuous Integration (CI) , Build Systems , Program Repair , and Software Engineering for Machine Learning (SE4ML) . Education : Ph.D. from the University of Texas at San Antonio (2020), M.Sc. from United International University, B.S. from Military Institute of Science and Technology. His research spans automated build processes , CI/CD pipelines , VR software optimization , and security vulnerability analysis . He has developed tools like HireBuild (history-driven build script repair) and RUDSEA (Dockerfile updates via environment analysis). Recent publications (2025–2023) highlight trends in ML DevOps adoption , technical debt in build systems , and automated testing for VR applications . His work has been published in top venues like ASE , ICSE , ESEM , and journals such as TOSEM . Scientific Awards : NSF CRII Grant (2022–2026), multiple NSF Travel Awards (2019, 2018), UTSA CS Outstanding Achievement Award (2019), Alvarez Grad Fellowship (2017), etc. He has advised research projects on build failure prediction , cross-project compatibility testing , and automated Java project building , with collaborations across institutions and industry partners like Microsoft Research.

Zheng Songمشاهده پروفایل

استادیار

• Distributed Systems
• Edge Computing
• Middleware
• +۷ مورد دیگر

Zheng Song is an Assistant Professor in the Department of Computer and Information Science at the University of Michigan–Dearborn College of Engineering and Computer Science . He holds two PhDs: one in Distributed Systems and Software Engineering from Virginia Tech (2020) and another in Wireless Networking and Mobile Computing from Beijing University of Posts and Telecommunications (2015). His research focuses on middleware solutions for edge computing , service-oriented architecture , and distributed systems . PhD, Virginia Tech (2020) PhD, Beijing University of Posts and Telecommunications (2015) MS, China Agricultural University (2009) BS, China Agricultural University (2007) Zheng's research spans edge computing , distributed systems , privacy-preserving algorithms , and computer science education . His work includes QoS-consistent edge services , microservice orchestration , and AI-driven birdwatching applications like Robin , which was featured in multiple 2025 publications. Recent publications highlight Zheng's expertise in machine learning (IEEE SMC'25), web service integration (Empirical Software Engineering, 2025), and edge computing frameworks (IEEE Edge'19 Best Paper, NSF CRII grant 2021). His 15 most recent works demonstrate leadership in QoI-aware systems , privacy , and innovative teaching methodologies . NSF CRII Research Grant (2021) Best Paper Award, IEEE Edge 2019 Distinguished Paper Award, IEEE ICDCS 2024 2nd Place, ACM Student Research Competition 2015 CECS Teaching Excellence Award 2025 Zheng mentors students in MQTT middleware , serverless computing , and generative AI in education . His Pervasive Computing Lab has produced impactful projects like Robin (Best Senior Design Project 2025) and Blaze (fire safety system). Former students have been admitted to Georgia Tech , University of British Columbia , and UM-Ann Arbor .

Mira Meziniمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Distributed Systems
• +۳ مورد دیگر

Mira Mezini is a Professor of Computer Science at Technical University of Darmstadt (TU Darmstadt), Germany. She leads the Software Technology Lab and is co-spokesperson for the Excellence Cluster Reasonable Artificial Intelligence . Mezini serves on the board of the National Research Center for Applied Cybersecurity ATHENE and co-directs hessian.AI, the Hessian Center for Artificial Intelligence. Her academic leadership includes past roles as Dean of Computer Science (2013-2014) and Vice President of TU Darmstadt (2014-2019). PhD in Computer Science, University of Siegen Assistant Professor, Northeastern University (USA) Visiting Professorships: Lancaster University (UK), Università della Svizzera Italiana (Switzerland) Research Interests : Mezini develops programming systems for reliable distributed software and AI, focusing on large-scale module concepts, adaptability, and extensibility. She creates intelligent software development environments leveraging web-based resources to automate programming rules and patterns. Her work spans automated API misuse detection , session types , and foundational code models . Scientific Contributions : Mezini has (co)authored over 200 peer-reviewed publications, including 15 recent representative works on: Modular multi-language analysis (2024) Secure distributed programming models (2023-2024) Effect systems for concurrency (2023) Reactive programming frameworks (2018-2024) Formal verification of cryptographic APIs (2018) Core languages for cloud computing (2016) ACM Fellow ERC Advanced Grant (2012) AITO Dahl-Nygaard Senior Prize (2025) Horst Görtz IT Security Award (2014, second prize) IBM Eclipse Innovation Awards (2005, 2006) Google Research Award (2017) Leadership : Mezini has chaired major conferences (OOPSLA, ECOOP, ICSE) and served on panels including the European Research Council Consolidator Grant, ACM SIGPLAN Executive Committee, and DFG Senate. She mentors through the SIGPLAN long-term program and contributes to DEI initiatives at conferences like SPLASH. Labs & Collaborations : Leads the Software Technology Lab at TU Darmstadt. Collaborates with institutions including EPFL (session types), ETH Zurich (language design), and Carnegie Mellon University (code analysis). Her teams focus on decentralized systems, API security, and programming language foundations.

Will Crichtonمشاهده پروفایل

استادیار

• Programming Languages
• Human-Computer Interaction
• Type Systems
• +۴ مورد دیگر

Will Crichton is an Assistant Professor of Computer Science at Brown University. His research bridges programming language theory and cognitive psychology to improve developer experience, particularly in Rust and type systems. He has developed tools like Flowistry (Rust IDE plugin) and Argus (trait error debugger) used by over 100,000 developers. Education: PhD from Stanford University (2022), advised by Pat Hanrahan and Maneesh Agrawala Prior Roles: Postdoctoral researcher with Shriram Krishnamurthi at Brown University His research focuses on: Type Systems: Creating usable type-level programming frameworks like Tyrade Rust Ecosystem: Ownership models, trait error debugging, and learning tools Human Factors: Applying cognitive psychology to programming language design Key contributions include: Interactive visualizations for Rust (AquaScope) Scientific programming workshops and educational materials Foundational work on security type systems and session types in Rust

• Logic Programming
• Computational Logic
• Abstract Interpretation
• +۳ مورد دیگر

Baudouin Le Charlier is a researcher with a focus on computational logic, programming languages, and system security. He has led multiple research projects, including sequential analysis under Unix, automated IT resource monitoring, and abstract interpretation for declarative languages. His work spans 1992–2008, with a strong emphasis on logic programming and formal semantics. Key Research Areas: Logic Programming, Abstract Interpretation, Data Stream Processing, Unix Systems, and Programming Language Interoperability. Notable Projects: Asax (Sequential Analysis), Survauto (IT Monitoring), COMPULOG-Net (Computational Logic Network), ABILE (Abstract Interpretation Tools). His 15 most recent publications (1995–2008) highlight trends in declarative semantics, interoperability mechanisms, and distributed audit analysis. These works often intersect with constraints, tools, and formal modeling.

Declan Gilheanyمشاهده پروفایل

استاد

• Organic Chemistry
• Inorganic Chemistry
• Organophosphorus Chemistry
• +۷ مورد دیگر

Professor Declan Gilheany is a Full Professor at the School of Chemistry, University College Dublin (since 2014). With academic positions spanning Queens University Belfast (1980-81), St. Patrick's College Maynooth (1983-92), and a Fulbright scholarship at MIT (1988-90), he has contributed significantly to organophosphorus chemistry and asymmetric synthesis . His research group has produced over 82 original articles and secured €7.6M in funding, with a breakthrough commercialized via Celtic Catalysts Ltd. His work on enantioselective Grignard synthesis and Wittig reaction mechanisms remains foundational. Education : B.Sc. (1978, First Class, Queen's University Belfast); Ph.D. (1983, Queen's Foundation Student, Queen's University Belfast) His research focuses on chiral phosphorus compounds , asymmetric catalysis (Rh turnover >100,000), and enantioselective synthesis of complex molecules like vitamin E and antihistamines. He pioneered dynamic resolution of P-stereogenic phosphorus and challenged traditional d orbital involvement in bonding theories. His asymmetric Appel reaction and 7-membered ring synthesis methodologies have broad industrial applications. His recent publications emphasize stereomutation mechanisms , phosphonium salt dynamics , and enantioselective ligand design . The Wesley Cocker Award (2008) and Royal Society of Chemistry Fellowship (2014) highlight his academic impact. He has supervised 36 PhDs and 10 PDRAs, with current teams of 6 PhDs and 3 PDRAs. Professional Leadership : Served on Forfas Technology Foresight Panel (1998), Enterprise Ireland IRCC (2006-08), and EU Marie Curie ITN Program (2012-date). Chair of the Royal Society of Chemistry (2015-2018) and external examiner for PhDs across four countries.

Alessandro Midoloمشاهده پروفایل

استاد مدعو

• Code Refactoring
• Software Testing
• Parallel Computing
• +۳ مورد دیگر

Alessandro Midolo is an Adjunct Professor of Computer Science at the Department of Mathematics and Computer Science (DMI) of the University of Catania, Italy. His research focuses on code refactoring, software testing, and parallel computing, with a particular emphasis on improving source code quality and automating robustness injections into distributed systems. Research Interests : Code Refactoring Software Testing Parallel Computing Source Code Quality Mining Software Repositories Software Maintenance Recent Publications highlight advancements in distributed application robustness, automated test generation, Java stream refactoring, and parallel code transformation. His work bridges theoretical insights with practical tools for developers. Contact : alessandro.midolo@unict.it

Nicolas Rayمشاهده پروفایل

استاد

• Geospatial Analysis
• Spatial Data Infrastructure
• Global Health
• +۲ مورد دیگر

Nicolas Ray is a Professor at the Institute of Global Health , University of Geneva. His research focuses on Geospatial Analysis , Spatial Data Infrastructure , and Global Health , particularly in low-resource settings and during disasters. His work integrates Environmental Science and Modelling and Simulations to address healthcare accessibility, snakebite epidemiology, and disaster response. He has developed tools like the inAccessMod R package and promotes open-source software for geospatial health planning. Recent publications highlight applications of geospatial methods in Africa , Nepal , and Cameroon , emphasizing One Health approaches, climate-health linkages, and sustainable healthcare policy.

• Formal analysis
• Software testing
• Programming languages
• +۶ مورد دیگر

Alastair Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he has been a faculty member since 2011. He leads the FastPL research group (formerly Multicore Programming Group), focusing on formal analysis, software testing, and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson earned his BSc (First Class Honors) in Computing Science and Mathematics from the University of Glasgow in 2003, followed by a PhD in Computing Science from the same institution in 2007 under Alice Miller. His academic journey includes positions as an EPSRC Postdoctoral Research Fellow at Oxford, Visiting Researcher at Microsoft Research Redmond, and Research Engineer at Codeplay Software Ltd. His research spans automated reasoning, compiler verification, and GPU programming with significant contributions to software reliability. He pioneered metamorphic testing for graphics drivers through GraphicsFuzz (acquired by Google in 2018) and developed innovative compiler fuzzing techniques. His work addresses critical challenges in memory models, concurrency, and verification of complex systems. Recent publications show increasing focus on applying these techniques to modern challenges including AI-generated code and verification-aware programming languages like Dafny. Donaldson's scientific contributions have been recognized with the 2017 BCS Roger Needham Award, an EPSRC Early Career Fellowship, and multiple best paper awards including EuroSys 2024 (Best Paper), ICST 2024 (Best Industry Paper), and ISSTA 2023 (Distinguished Paper). His 2012 GPUVerify paper received the ACM SIGPLAN Most Influential OOPSLA Paper Award in 2022. As an advisor, Donaldson has mentored numerous PhD students and postdocs, many now in prominent academic and industry positions. His research is supported by Amazon Research Awards (2022-2023) for Dafny ecosystem testing and compiler validation. He previously served as Senior Software Engineer and Visiting Researcher at Google following the GraphicsFuzz acquisition. The FastPL group maintains strong industry connections with Google, Microsoft, and Amazon, ensuring practical relevance of their theoretical work. Donaldson currently serves as Editor-in-Chief of ACM TOPLAS (2025-present) and on program committees for major conferences including PLDI, ICSE, and ASPLOS.

Minlan Yuمشاهده پروفایل

استاد

• Computer Networking
• Distributed Systems
• Data Center Networks
• +۵ مورد دیگر

Minlan Yu serves as the Gordon McKay Professor of Computer Science at Harvard University's School of Engineering and Applied Sciences (SEAS). She holds leadership positions as assistant director of the SRC/DARPA JUMP 2.0 ACE Center for Evolvable Computing and co-leads both the Harvard Power and AI initiative with Prof. Le Xie and the Harvard Systems + Theory group with Prof. Michael Mitzenmacher. Her research spans data networking, distributed systems, enterprise and data center networks, network virtualization, and software-defined networking, with recent expansion into AI infrastructure systems. She has made significant contributions at the intersection of traditional networking and machine learning systems, particularly in optimizing network performance for large-scale AI training and inference workloads. Her publication record shows a clear trajectory toward integrating large language models with networking systems, with multiple papers accepted to premier conferences like SIGCOMM, SOSP, NeurIPS, and HotNets in 2025. These works address critical challenges in LLM scheduling, network management for ML workloads, and acceleration techniques for multi-modal systems. Amazon Research Award (2023) for Troubleshooting Distributed Training Systems As an educator, Professor Yu teaches advanced networking courses including CS 145 Networking at Scale and CS 243 Advanced Computer Networks. She maintains active research collaborations with industry partners and supervises graduate students working on cutting-edge network systems research. Her lab develops practical systems that address real-world challenges in cloud networking and AI infrastructure.