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Alexandra Winifred ChadwickView profile

Research Fellow

• Computer Architecture
• Programming Languages
• Semantics and Verification
• +4 more

Alexandra Winifred Chadwick is a Research Fellow in the Department of Computer Science and Technology at the University of Cambridge, affiliated with the School of Technology. She is actively engaged in research within the Computer Architecture Group with specific expertise in programming languages, semantics, and verification. Her academic work bridges theoretical computer science with practical applications in system performance and optimization. Her research interests include: Computer Architecture, particularly Instruction-Level Parallelism and processor design Programming Languages and Semantics, with focus on programming idioms and verification Embedded Systems optimization for machine learning applications Performance analysis techniques for computer systems Compiler construction and optimization Dr. Chadwick's publication record shows consistent research output from 2016 through 2025, with multiple publications in 2025 indicating active current research. Her work demonstrates a progression from embedded systems and memory optimization toward cutting-edge research in instruction-level parallelism and programming idiom prediction. She contributes significantly to the academic community through teaching responsibilities including Foundations of Computer Science (Part IA), Compiler Constructions (Part IB), and supervision of Part II projects, reflecting her expertise across theoretical and applied computer science domains.

• High-performance Computing
• Parallel Algorithms
• Scientific Computing
• +3 more

Professor Tobias Weinzierl holds the position of Professor in the Department of Computer Science at Durham University. He is the Co-director of the Institute for Data Science (IDAS) and leads the Scientific Computing research group. His expertise includes high-performance computing, parallel algorithms, and scientific computing, with a focus on numerical methods and adaptive mesh refinement techniques. Research interests encompass high-performance computing architectures, parallel algorithm design, and the development of scalable numerical solvers for hyperbolic partial differential equations (PDEs). He has contributed to projects like ExaHyPE, an engine for exascale simulations of wave phenomena, and has authored influential books such as *Principles of Parallel Scientific Computing* and *A Framework for Parallel PDE Solvers on Multiscale Adaptive Cartesian Grids*. He has held roles including inaugural director of the Master in Scientific Computing and Data Analysis (MISCADA) and has reviewed for the European High Performance Computing Joint Undertaking (EuroHPC JU). His work emphasizes resilience in numerical software, compiler optimizations, and energy-efficient computing. Key contributions include the Peano software framework for adaptive grid traversals, and research on task-based parallelism, GPU offloading, and fault tolerance in HPC systems. Current research focuses on exascale computing, multiscale optimisation, and the application of parallel computing to astrophysics and fluid dynamics. Labs/Teams: Scientific Computing research group, ExaHyPE project team Grants/Projects: PI/Co-I on ExCALIBUR projects, H&ES installations

• Bioinformatics
• Machine Learning
• Health Informatics
• +3 more

Dr. Matloob Khushi is an academic staff member at the University of Sydney's School of Computer Science, where he has held roles since joining in 2017. He earned his Ph.D. from the University of Sydney and has published over 50 research papers. His research focuses on big data analysis, machine learning applications in health, finance, and genomics, with notable contributions to adverse drug event prediction, bioinformatics tools, and predictive modeling in healthcare. Dr. Khushi's work has been recognized in media for innovations like the MatCol tool aiding cancer research. Education: Ph.D. in Computer Science, University of Sydney (2008). Research Interests: Machine learning for big data, biomedical informatics, financial analytics, and health informatics. Recent articles highlight advancements in graph neural networks, predictive models for chronic diseases, and tools for genomic analysis. He advises two Ph.D. students and collaborates on interdisciplinary projects.

Hoda MehrpouyanView profile

Associate Professor

• Cybersecurity
• Cyber-Physical Systems
• Formal Verification
• +3 more

Dr. Hoda Mehrpouyan is an Associate Professor in the Computer Science department at Boise State University. Her research focuses on privacy, security, and robustness of mission-critical cyber-physical systems, including water treatment plants, smart manufacturing, and smart cities. She has received significant funding, including a 2019 NSF CAREER Award for developing a security framework for industrial control systems (FORENSICS) and an NSF CRII grant in 2016. Additional support includes Idaho Secretary of State funding for election cybersecurity and NSA GenCyber Teacher Program grants for outreach. Her work integrates formal verification, model-based design, and resilience analysis to address cyber threats and system failures. Recent efforts include open-source simulation tools for hydraulic networks and Bayesian belief networks for cyber-informed engineering. She currently oversees a lab with open positions for master’s and PhD students, emphasizing interdisciplinary collaboration across system design, software engineering, and complex network theory. Research Interests Key areas include requirement analysis for safety-critical systems, compositional modeling, resilience frameworks for industrial control systems, and privacy engineering for ubiquitous systems. Her tools and methodologies aim to bridge gaps between theoretical models and practical implementations in safety-critical domains. Awards NSF CAREER Award (2019) NSF CRII Grant (2016) Idaho Secretary of State Funding (Election Cybersecurity) NSA GenCyber Teacher Program Support (2017, 2019) Lab & Collaborations Dr. Mehrpouyan’s lab focuses on developing open-source tools and frameworks for securing critical infrastructure. Current projects include FALCON (anomaly detection in ICS) and CoVeriTeam (cooperative verification of PLC programs). She collaborates with industry partners and government agencies to align research with real-world challenges in cybersecurity and resilience.

• Formal Languages
• Programming Language Semantics
• Cybersecurity
• +5 more

William Steingartner is an Associate Professor at the Faculty of Electrical Engineering and Informatics, Technical University of Košice (TUKE). He specializes in formal languages, programming language semantics, cybersecurity, and computer science education. His research focuses on advancing pedagogical tools for teaching formal semantics, compiler design, and secure software development. He actively contributes to academic governance, serving as Principal Investigator on projects like 'Application of new principles in the education of IT specialists' and participating in 'Evolving Architectural Knowledge in the Edge-to-Cloud Continuum.' Dr. Steingartner holds editorial roles, including guest editor for the Central European Journal of Computer Science (since 2011) and editor of proceedings for conferences like INFORMATICS 2019. He has organized major events such as the International Scientific Conference Informatics in 2013, 2015, 2017, and 2019, demonstrating leadership in academic event management. His teaching spans formal languages, logic for computer scientists, and domain-specific language design. Research highlights include developing tools like OnlineProver for formal logic education and RISCAL for semantics visualization. He explores cybersecurity challenges in hybrid threats, API security, and cyber resilience strategies, alongside innovations in VR applications for therapy and education. Key contributions include over 50 publications since 2015, with recent work addressing disinformation campaigns, smart orthosis design, and pedagogical software for programming semantics. He emphasizes interdisciplinary collaboration, bridging theoretical computer science with practical applications in medicine, robotics, and user experience design.

• Software Engineering
• Program Comprehension
• Build Systems
• +4 more

Matúš Sulír is an Assistant Professor at the Department of Computer Science and Engineering, Faculty of Electrical Engineering and Informatics, Technical University of Košice. He specializes in software engineering, program comprehension, and educational methodologies in programming. He teaches courses like Základy softvérového inžinierstva (Foundations of Software Engineering) and actively contributes to research in software build systems, domain-specific languages, and usability evaluation. His research interests include Java build processes, educational tools for programming, and empirical studies on software quality and testing. He has published extensively on topics such as automated test case identification, voice command APIs, and large-scale software build analysis. His work often integrates empirical methods with practical software development challenges. No awards or advisory roles are listed, and there are no explicitly mentioned research grants or projects. His academic contributions focus on advancing software engineering practices through empirical research and tool development.

• Speech Recognition
• Artificial Intelligence
• Pattern Recognition
• +3 more

Michael Russell is a Lecturer in the Faculty of Engineering and Informatics, Department of Computer and Software Engineering. His academic career spans over three decades, with active research contributions from 1988 to the present. He specializes in interdisciplinary fields blending technical innovation with pedagogical exploration. Research interests include Speech Recognition, Artificial Intelligence, and Pattern Recognition. Notable work involves intelligent agents, data mining, and applying artificial life principles to speech processing systems. His educational research focuses on software engineering curriculum design, tacit knowledge integration, and team-based learning strategies. Publications reflect a dual focus on advancing technical domains like speech enhancement algorithms and educational methodologies. Recent works emphasize curriculum design and team-based learning, while earlier contributions include foundational research in distributed operating systems and early AI models. No scientific awards were listed in the provided information. Advising and grants details are currently unavailable. No specific lab affiliations or teams are mentioned.

• Child Psychopathology
• Biological Markers of Risk
• Gender/Sex Differences in Mental Health
• +3 more

Andrew Daoust is an Assistant Professor in the Department of Psychology at Acadia University, using they/them pronouns and maintaining an office in Horton Hall 426. They teach advanced seminars in psychopathology and the honours seminar, with clinical expertise in Cognitive Behavioural Therapy (CBT) and Acceptance and Commitment Therapy (ACT). Their educational background includes: H.B.Sc. in Life Sciences from the University of Toronto M.Sc. in Clinical Science & Psychopathology from Western University Ph.D. in Clinical Science & Psychopathology from Western University Pre-doctoral Clinical Residency (CPA Accredited) at the Northern Ontario Psychology Internship Consortium (NORPIC) Dr. Daoust's research program investigates biological markers of risk (particularly cortisol and telomeres) for child psychopathology, with emphasis on gender/sex differences driven by social, psychological, and biological factors. Their work employs multi-method approaches including physiological measurements, neuroimaging, and behavioral observation to understand developmental trajectories of mental health disorders. Analysis of their 15 most recent publications (2018-2024) reveals a dominant focus on stress physiology and internalizing symptoms in youth, with significant attention to pandemic-related mental health impacts. Key themes include cortisol reactivity during acute stressors, neural correlates of parental interactions, biological aging markers through telomere length, and development of pandemic-specific assessment tools like the Pandemic Avoidance and Concern Scales (PACS). The work consistently examines sex differences across biological, social, and psychological domains. Dr. Daoust currently welcomes honours students to their research laboratory but will not accept graduate students for the 2026/2027 academic year. They are actively working toward registration as a clinical psychologist in Nova Scotia, bridging research and clinical practice through evidence-based therapeutic approaches. Their laboratory employs longitudinal and multi-method designs to investigate risk markers for psychopathology, with particular focus on physiological stress responses, neural reactivity patterns, and developmental trajectories of mental health disorders in children and adolescents. Current projects examine pandemic-related mental health impacts and biological embedding of stress.

Nan NiuView profile

Associate Professor

• Requirements Engineering
• Machine Learning
• Software Engineering
• +5 more

Dr. Nan Niu is an Associate Professor in the Department of Electrical Engineering and Computer Science (EECS) at the University of Cincinnati. He specializes in requirements engineering, software traceability, and model-driven approaches. His work focuses on machine learning applications, continuous deployment, and testing scientific software. Dr. Niu holds a Ph.D. in Computer Science from the University of Toronto (2010, supervised by Steve Easterbrook), an M.Sc. from University of Alberta (2006), and a B.Eng. from Beijing Institute of Technology (2004). Research interests include software engineering challenges in AI/ML systems, automated refactoring, and environment-driven requirements engineering. His research is funded by agencies like NSF, NSA, and industry partners like P&G. Recent publications address topics like POS tagging in code, GUI reuse via vision-language models, and privacy concerns in mobile apps. Teaching: Software Engineering (EECE3093C), Requirements Engineering (CS5127/6027), and Large-Scale Software Engineering (CS5128/6028) Labs/Teams: Active in requirements traceability and scientific software testing Awarded over 15 honors including NSF CAREER Award (2014-2019), Best Paper Awards at RE (2016,2018,2021), and teaching excellence recognition.

• Types
• Programming Languages
• Domain-Specific Languages (DSLs)
• +6 more

Edwin Charles Brady is an Associate Professor (Reader) at the School of Computer Science, University of St Andrews. His research focuses on programming languages, dependent types, and formal verification. He leads projects such as Type-Driven Verification of Communicating Systems and contributed to EU-funded FP7 ADVANCE. He actively participates in academic events like Lambda World and organizes annual 'Doors Open @ Computer Science' outreach events. His expertise includes type systems, DSL design, compilers, and theorem proving. Notable contributions include the Idris programming language and frameworks for resource-aware EDSLs. Brady supervises research in areas like type-level testing and program refactoring. Projects: Type-Driven Verification of Communicating Systems (EPSRC-funded) FP7 ADVANCE (EU-funded) Activities: Speaker at Lambda World (2016) Organizer of Doors Open events (2023–2025)

• Translation Technologies
• Machine Translation
• Post-editing Evaluation
• +4 more

Mihaela Vela is a Senior Lecturer at the Department of Language Science and Technology at Saarland University. Her research focuses on machine translation evaluation, post-editing strategies, and translation technologies. Prior to her academic role, she worked as a researcher at the Language Technology Lab of DFKI (2007–2011), contributing to projects like ontology schema extraction from financial news. She holds a PhD in Computational Linguistics (2011) from Saarland University, supervised by Hans Uszkoreit and Thierry Declerck, and a Licentiate degree in Linguistics from West University of Timisoara. Her teaching portfolio includes courses such as Translation and Content Management , Applied Language Technologies , and Machine Translation , reflecting her expertise in integrating computational methods with translation practice. She has developed tools like TeLeMaCo (a collaborative teaching repository) and Catalog (a post-editing interface). Her work emphasizes improving translation workflows through better CAT tool design, metadata preservation, and cognitive load analysis in post-editing tasks. Key contributions include the SubCo corpus of learner translations and studies on post-editing effort in low-resource languages. Her research bridges theoretical linguistics with practical applications, addressing challenges in legal text classification, parliamentary discourse analysis, and neural post-editing systems.

João Pascoal FariaView profile

Associate Professor

• Software Engineering
• Model-Based Testing
• Software Process Improvement
• +5 more

João Pascoal Faria is an Associate Professor at the Department of Informatics Engineering, Faculty of Engineering of the University of Porto. He holds a PhD in Electrical and Computer Engineering and serves as Director of the Integrated Master in Informatics and Computing Engineering (MIEIC). He is a researcher at INESC TEC, coordinating the Software Engineering area, and represents FEUP and INESC TEC in national and international technical commissions for health informatics and software quality. Education: PhD in Electrical and Computer Engineering (1999), University of Porto His research focuses on model-based testing , software process improvement , and model-driven development . He explores the use of Large Language Models (LLMs) for automated test generation in REST APIs and formal verification tools like Dafny. His work emphasizes practical applications, including IDE integration and market-driven tools like SAGA, a rapid application development platform based on domain-specific languages. João has supervised multiple theses in areas such as IoT systems, sign language recognition, and low-code development. He has over 25 years of experience in education and industry collaboration, co-founding companies like Qualisoft and Strongstep. His contributions span formal verification, test automation, and software quality assurance.

• Augmented Reality
• Conceptual Modeling
• Enterprise Modeling
• +3 more

Dr. Fabian Muff is a Senior Researcher at the Department of Informatics, University of Fribourg, within the Interfaculty Informatics unit. He holds a position as Oberassistent (Senior Research Assistant) specializing in Digitalization and Information Systems. His research focuses on the intersection of conceptual modeling with augmented reality (AR) and virtual reality (VR), emphasizing workflow modeling languages, AR application frameworks, and AI integration in modeling tools. He teaches courses on Requirements Engineering, Information Systems Modeling, and Project Development. Dr. Muff's work addresses challenges in hybrid modeling environments, contextual AR applications, and the limitations of large language models in conceptual modeling. His recent projects include developing the M2AR web-based modeling tool and exploring the use of ChatGPT in schema generation. He actively collaborates with academic and industry partners, publishing widely in venues like ER Conference and AAAI workshops. His contributions span technical innovations in AR modeling languages (e.g., ARWFML) and methodological advancements in combining conceptual modeling with emerging technologies. Current research explores AI-augmented visualization, context-aware AR systems, and the ethical implications of digital-physical integration in enterprise systems.

• Natural Language Processing
• Artificial Intelligence
• Information Retrieval
• +7 more

Dr. Rohini K. Srihari is a full Professor and Associate Chair in the Department of Computer Science and Engineering at the University at Buffalo, The State University of New York , and also serves as an Adjunct Professor in the Department of Linguistics within the School of Engineering and Applied Sciences . Her expertise lies at the intersection of natural language processing , artificial intelligence , information retrieval , and AI for social good . Education: PhD in Computer Science, University at Buffalo, 1992 B.Math, University of Waterloo, Canada Research Interests: Dr. Srihari’s research spans a wide range of topics including conversational AI systems (especially empathetic and socially-aware chatbots), disinformation detection and attribution , multilingual text mining for low-resource languages, and predictive analytics for social unrest using heterogeneous data sources. She also explores multimedia information retrieval and AI-driven early warning systems for social and economic disruption. Recent Research Trends: Her recent publications reflect a strong focus on conversational AI and AI for social good , with applications in mental health support, misinformation mitigation, and empathetic dialogue systems. She has led interdisciplinary teams in competitions like the Alexa Prize Socialbot Grand Challenge , where her team won the bronze medal in 2021. Scientific Awards & Recognition: Bronze Prize, Alexa Prize Socialbot Grand Challenge 4 (2021) NSF Grant: Purposeful Conversational Agents based on Hierarchical Knowledge Graphs Holds two US patents in multilingual text mining and face recognition Advising & Funding: Dr. Srihari has supervised numerous PhD and Master's students across departments and has led research funded by NSF , DARPA , IARPA , and the US Government . She has also served as Chief Data Scientist at PeaceTech Lab, leading AI initiatives for conflict prevention. Research Labs & Teams: She directs the Conversational AI for Social Good research group, which focuses on building trustworthy, empathetic, and socially responsible AI systems. The group integrates deep learning, knowledge graphs, and symbolic AI to address real-world societal challenges.

Nikos SpanoudakisView profile

Assistant Professor

• Multi-Agent Systems
• Artificial Intelligence
• Agent-Oriented Software Engineering
• +11 more

Nikos Spanoudakis is an Assistant Professor at the Department of Electronic Engineering of Hellenic Mediterranean University , with concurrent research collaboration at Technical University of Crete . He holds a PhD in Computer Science (Artificial Intelligence) from Paris Descartes University (2009, "Très Honorable"), an MSc in Organization and Administration from Technical University of Crete, and a Diploma in Computer Engineering and Informatics from University of Patras. Research Focus: Multi-Agent Systems (AOSE, Computational Argumentation), Model-Driven Engineering , Smart Buildings , IoT , and Artificial Intelligence Applications in Ambient Intelligence, Finance, and Education Key Contributions: Created ASEME Methodology and AMOLA Language for agent modeling, developed Gorgias-B argumentation framework, and designed Kouretes Statechart Editor for robotic behavior specification His recent publications reveal a strong trend in Explainable AI (2023: Explainable Argumentation as a Service ), Smart Energy Systems (2025: Engineering IoT-Based Open MAS for Large-Scale V2G/G2V ), and EdTech Innovations (2024: Role Assignment in Programming Courses ). He has received prestigious ACM Senior Member (2023) and IEEE Senior Member (2012) distinctions, along with teaching recognition (2021) from Technical University of Crete. Academic Leadership: Serves as Editor for Springer Nature's Computer Science journal and has reviewed for 15+ top-tier publications including IEEE Intelligent Systems and Journal of Web Semantics Conference Involvement: Program Committee Member for 20+ international conferences (IJCAI, ECAI, AAMAS, AAAI) and organizer of multiple European Agent Systems Summer Schools