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Xiaoxing Ma is a Professor at the State Key Laboratory for Novel Software Technology , Nanjing University , focusing on Software Engineering , Self-adaptive Software Systems , and Software Engineering for Machine Learning . His recent work bridges neuro-symbolic reasoning and formal verification. Key research areas: Software Engineering, Self-adaptive Systems, Neuro-symbolic AI Awards: China National Awards (2006, 2011), MOE Award (2010), CVIC SE Award (2009) His 2023-2024 publications emphasize: Formal semantics for hardware description languages (Verilog) Neuro-symbolic frameworks for mathematical reasoning Dynamic update verification and CRDT model checking LLM-driven API migration and traceability recovery He serves as Program Co-Chair for SEAMS 2024 and contributes to major software engineering conferences (ICSE, ASE, FSE, PLDI).

• Software Engineering
• Self-adaptive Software Systems
• Software Engineering for Machine Learning
• +3 more

Rubén Vera-Rodríguez is a researcher at the Biometrics and Data Pattern Analytics (BiDA) Lab, part of the Escuela Politécnica Superior at Universidad Autónoma de Madrid, Spain. His work focuses on biometrics, human-computer interaction, and privacy-enhancing technologies, with strong emphasis on mobile and wearable systems. Research Interests: His primary research areas include behavioral biometrics (keystroke dynamics, gait recognition), face recognition, synthetic data generation, and privacy-preserving methods in biometric systems. He explores the use of deep learning and transformer models for mobile authentication and digital phenotyping. The trends in his recent publications show increasing use of synthetic data, explainable AI, and transformer architectures in biometric systems. His work spans both technical innovation and privacy-aware design, contributing to benchmark datasets and open challenges. Scientific Contributions: Co-organizer of the SVC-onGoing and WAMWB workshops. Contributor to major biometric databases including BehavePassDB and ChildCIdb. Active in privacy-focused biometric research, as seen in surveys on sensor vulnerabilities. Advising and Collaborations: He collaborates extensively with researchers such as Ruben Tolosana, Aythami Morales, and Julian Fierrez. While no formal students are listed, he leads and contributes to team-based research projects and competitions. Labs and Teams: He is a core member of the Biometrics and Data Pattern Analytics (BiDA) Lab at UAM, a research group focused on advancing biometric technologies with attention to real-world usability and ethical considerations.

• Biometrics
• Behavioral Biometrics
• Human-Computer Interaction (HCI)
• +8 more

John Sartori is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Minnesota , holding the Robert and Sydney Anderson Professorship. His research focuses on extending Moore's law through energy-efficient computing by addressing hardware bottlene | [truncated for display]

• Ultra-low-power embedded systems
• Internet of Things (IoT)
• Wearable electronics
• +5 more

Nadine Cullot is a Professor in Data Science at the Université de Bourgogne, affiliated with the College of Science and Technology and the Department of Computer Science, Electronics, and Mechanics. Her work spans Semantic Web technologies, data analysis, and ontology-driven applications. Research Themes: Knowledge modeling using ontologies, logical reasoning, semantic contextualization of data analysis results, and AI techniques for fraud detection. Projects: Co-leads the i-site Cocktail project (2019-2023) focused on Twitter discourse analysis in the food domain, developing ontologies for semantic enrichment. Publications focus on data lakes, fraud detection in interbank systems, and social network polarization. She co-supervises theses on AI-driven anomaly detection and data lake automation. Teaching: Courses in Java programming, advanced algorithms, NoSQL databases, and Semantic Web technologies (OWL, SPARQL, SWRL) at undergraduate and Master's levels. Administrative Roles: Deputy Director of the Department of Computer Science, Electronics, and Mechanics; responsible for the Master in Computer Science program.

• Semantic Web
• Data Analysis
• Ontologies
• +9 more

Dr. Meng Wang is a Professor at the School of Computer Science, University of Bristol, where he leads the Programming Languages Research Group. His career includes prior roles as a Lecturer at University of Kent and Assistant Professor at Chalmers University of Technology. Current Affiliation: University of Bristol Past Affiliation: University of Kent Past Affiliation: Chalmers University of Technology Research interests center on applying theoretical rigor to practical programming, with a focus on designing languages and tools for software development and testing. Key areas include: Bidirectional Programming Functional Programming Software Testing Type Systems Embedded Languages Publication trends show a strong emphasis on bidirectional programming, functional language design, and compiler techniques. His recent work explores large language model applications in code translation and formal verification of refinement types in object-oriented systems. Supervision and team leadership include mentoring 12 current PhD students and 1 Research Associate, while past mentees include notable researchers who have transitioned to industry and academic roles. He has organized workshops like VeTSS summer school and co-chaired PEPM 2024, demonstrating active community engagement.

• Programming Languages
• Functional Programming
• Bidirectional Programming
• +2 more

Taro Sekiyama is an Associate Professor at the National Institute of Informatics in Japan. His research focuses on programming language theory and applications, particularly in type systems, gradual typing, and program verification with effects. Academic Rank: Associate Professor University: National Institute of Informatics His research interests span type theory , polymorphic algebraic effects , gradual typing , and temporal verification . His work combines theoretical foundations with practical applications, including Rust programming language verification and effect handling. The analysis of Taro Sekiyama's publications reveals a consistent focus on: Algebraic effect systems Refinement type theory Gradual typing semantics Temporal verification techniques Neural-guided program analysis Effect handler design

• programming languages
• type theory
• gradual typing
• +6 more

Nikolay "Nick" Ivanov, Ph.D., is an Assistant Professor at Rowan University's College of Science & Mathematics, Department of Computer Science. His research focuses on advanced cyber systems, self-sovereign digital identities, and blockchain applications for security and equity. Ph.D., Computer Science, Michigan State University B.S., Computer Science, Southwest Minnesota State University As director of the ACSUS Lab, Ivanov explores intersections of: Distributed Systems Applied Cryptography Digital Equity Usable Security Cyber Systems His recent publications span topics like adversarial attacks on language models, smart contract vulnerabilities, and blockchain scalability. Ivanov has received NSF funding for self-sovereign identity frameworks and holds professional memberships in ACM and IEEE.

• Distributed Systems
• Applied Cryptography
• Digital Equity
• +4 more

Winfried Lamersdorf is a full professor in the Department of Computer Science at the University of Hamburg , leading the Distributed Systems (VSIS) research unit. His career spans from IBM's European Networking Centre to leading numerous DFG, EU, and industry-funded projects. Major research interests include: Service-oriented computing (SOA, Web Services) Mobile and ubiquitous systems Agent-oriented software construction Self-organizing systems Context-aware middleware Cloud/edge computing Applications in E-Health, Smart Cities, and Industrial Informatics Recent projects like SANE (Smart Networks for Citizen Participation), CloudAware (context-adaptive mobile cloud systems), and FYPA²C (future production automation) highlight his focus on urban data spaces, energy-efficient mobile systems, and evolutionary software management. His scientific contributions span 200+ publications, with 15 recent articles covering topics such as: Complex event processing Decentralized blockchain coordination Context-aware computation offloading Model-driven production system evolution BDI agent architectures Service composition patterns Advising over 20 PhD students including Heiko Bornholdt (Smart Cities), Philipp Kisters (Distributed Platforms), and Gabriel Orsini (Mobile Clouds, 2016), Lamersdorf has shaped research in distributed applications through long-term collaborations with institutions like TU Munich, HSU Hamburg, and international IFIP committees.

• Distributed Systems
• Service-Oriented Computing
• Cloud Computing
• +4 more

Mojtaba Elahi is a Doctoral Researcher and Visitor at the Department of Computer Science , Aalto University , affiliated with the research group led by Jussi Rintanen . His work focuses on artificial intelligence and automated planning , with a particular emphasis on optimization techniques and formal verification of planning systems. Email: mojtaba.elahi@aalto.fi

• Artificial Intelligence
• Automated Planning
• Computer Science
• +1 more

Hong-Linh Truong is an Associate Professor (tenured) at the School of Science , Aalto University in Finland. She leads the AaltoSEA Group focused on Systems and Services Engineering Analytics. Additionally, she holds an Adjunct Associate Professor position at the Faculty of Informatics, TU Wien, Austria. Her research spans Cloud Computing Internet of Things (IoT) Big Data Analytics Distributed Systems Elastic Computing Context-aware Systems with particular emphasis on engineering analytics for hybrid cloud-IoT systems and service elasticity management. Analysis of her 15 most recent publications reveals focus areas including Edge Computing (5 papers) Blockchain Applications (3 papers) Machine Learning Systems (2 papers) Cyber-Physical Systems (2 papers) Collaborative Computing (2 papers) Resource Orchestration (1 paper) Scientific achievements include Best Poster Award at European Grid Conference 2005 Best Paper Award at CAiSE'12 She actively collaborates with institutions across Europe and Asia, with research applications in both industrial contexts (air traffic management, manufacturing) and public sectors (disaster response, sustainability governance). Her work integrates theoretical foundations with practical implementations, as evidenced by numerous toolset developments like SCALEA-G and IoTCloudSamples.

• Cloud Computing
• Internet of Things (IoT)
• Big Data Analytics
• +9 more

María Encarnación Beato Gutiérrez is a Professor of Computer Science and Artificial Intelligence at the School of Computer Science , Pontifical University of Salamanca . She leads the MARATON research group, focusing on disruptive technologies like the Internet of Things (IoT), semantic technologies, open data, and data processing. Her work addresses societal needs in the technological revolution through research, innovation, and development in these domains. Her research spans IoT frameworks, event-driven architectures, semantic data integration, and AI ethics. Notable projects include frameworks for smart tracking (SCIFI series), capacity control systems using BLE technology, and semantic tools for university transparency. Her publications highlight trends in IoT, AI ethics, and open data applications. The MARATON group collaborates on projects like UPSA-INNOVA , integrating mobile technologies and semantic solutions for e-learning and university innovation. Her work also explores human-computer interaction, software engineering, and the societal impact of AI. She earned her PhD from the University of Valladolid in 2004, with a thesis on Formal Verification of UML under the supervision of Dr. Manuel Barrio Solórzano and Dr. Carlos Enrique Cuesta Quintero.

• Computer Science
• Artificial Intelligence
• Internet of Things (IoT)
• +7 more

Mahsa Varshosaz is an Associate Professor in Software Engineering at the IT University of Copenhagen, specializing in AI safety, formal verification, and program repair. Her work bridges theoretical research with practical applications in autonomous systems, particularly marine robotics. Current research focuses on model-based testing and formal specification for reinforcement learning systems Active in program repair techniques for concurrency bugs Collaborates with European Commission-funded initiatives in AI safety Recent publications highlight her expertise in autonomous underwater vehicle safety analysis and static program analysis for locking bugs. Her work intersects software engineering, artificial intelligence, and systems validation. Key projects include REMARO (Reliable AI for Marine Robotics) and DIREC (Verifiable and Safe AI), funded by major research foundations. She contributes to open-access datasets and peer-reviewed research through collaborations.

• Software Testing and Verification
• Reinforcement Learning
• Program Repair
• +5 more

Luis Lago is an Associate Professor at the Polytechnic School of the Autonomous University of Madrid . His office is located in EPS, B-307, and he can be contacted via email at luis.lago@uam.es . His research primarily spans Computer Science and Artificial Intelligence , with a focus on neural networks, natural language processing, and computational neuroscience. His work integrates theoretical and applied machine learning, addressing challenges in sequence modeling, formal automata, and anomaly detection. Recent publications highlight innovations in recurrent neural networks for brain-computer interfaces (e.g., P300-ERP detection) and text analysis (e.g., authorship attribution, fake news detection). No awards, grants, or student advising details are documented in the available information.

• Computer Science
• Artificial Intelligence

Matthew D. Green is an Associate Professor of Computer Science at Johns Hopkins University and a member of the Johns Hopkins University Information Security Institute. He is a nationally recognized expert in applied cryptography and cryptographic engineering with significant contributions to privacy-enhanced technologies and secure communication systems. Oberlin College: BMus in Technology of Music and Related Arts and BA in Computer Science (1998) Johns Hopkins University: MS in Computer Science (2005), PhD in Computer Science (2008) Green's research focuses on practical applications of cryptography, including privacy-enhanced information storage, anonymous payment systems, and bilinear map-based cryptography. His work bridges theoretical cryptography with real-world security challenges, particularly in blockchain technologies, end-to-end encrypted communications, and privacy-preserving systems. He has made significant contributions to understanding cryptographic vulnerabilities in widely deployed systems and developing more secure alternatives. His recent publications demonstrate a strong focus on emerging cryptographic challenges including machine unlearning, privacy in encrypted messaging, compliance-enabled digital assets, and detecting synthetic content from large language models. These works show his ability to address both theoretical foundations and practical implementations of security systems. NSF CAREER Award (2017) $100,000 Google Security and Privacy Research Award Green is actively engaged in both academic research and public discourse on security issues. He is the author of the popular blog 'A Few Thoughts on Cryptographic Engineering' and has over 140,000 followers on X (formerly Twitter). His work has been instrumental in analyzing security flaws in commercial products and contributing to the development of more secure cryptographic protocols. He was one of the creators of the Zerocash protocol used by Zcash cryptocurrency and founded the encryption startup Zeutro. His research group at Johns Hopkins focuses on practical cryptographic engineering challenges, with particular emphasis on how theoretical cryptographic constructions can be implemented securely in real-world systems. The group maintains strong connections with industry partners and regularly contributes to security standards discussions.

• Cryptography
• Computer Security
• Applied Cryptography
• +3 more

Jonathan Aldrich is a Professor of Computer Science at Carnegie Mellon University in the School of Computer Science , jointly appointed in the Software and Societal Systems Department and the Computer Science Department . He is an internationally recognized expert in programming languages, software engineering, and verification, with a strong emphasis on human factors and usability in language design. Education: Ph.D. in Computer Science and Engineering, University of Washington (2003) B.S. in Computer Science, Caltech Research Interests: Prof. Aldrich's research lies at the intersection of programming languages and software engineering , focusing on how language design affects software quality and developer productivity. His work spans: Gradual verification and type systems Ownership and typestate checking Security and information flow control Usability of advanced type systems Domain-specific languages for blockchain and IoT Recent Work Trends: His recent publications emphasize gradual verification techniques, which allow developers to incrementally verify software correctness. He has also explored liquid types , information flow control , and usability barriers in advanced type systems. His work often combines formal methods with empirical studies to ensure practical impact. Awards & Recognition: NSF CAREER Award (2006) Dahl-Nygaard Junior Prize (2007) ICSE Most Influential Paper Award (2012) DARPA Computer Science Study Group Leadership & Service: Prof. Aldrich has held numerous leadership roles in the academic community, including: Director, CMU Software Engineering Ph.D. Program (2013–2019) General Chair, SPLASH 2015 Program Chair, OOPSLA 2017 Steering Committee Chair, SPLASH (2017–2019) Member, ACM Publications Board Industry Engagement: He is the Chief Technology Officer of Noteful , a startup he co-founded during his 2022 sabbatical, focused on music education through interactive apps.

• Programming Languages
• Software Engineering
• Verification
• +7 more