جست‌وجوی استاد و پژوهشگر

Kyle Steinfeldمشاهده پروفایل

دانشیار

• Computational Design
• Design Computation
• Artificial Intelligence in Design
• +۳ مورد دیگر

Kyle Steinfeld is an Associate Professor of Architecture and Director of the Master of Design program at the University of California, Berkeley, College of Environmental Design. His work bridges computational design methods and architectural practice, emphasizing critical engagement with software and data. He teaches design studios, visualization courses, and seminars in digital design theories. Master of Architecture, MIT (2004) Bachelor of Design in Architecture, University of Florida (1999) Steinfeld's research explores the intersection of architecture and computational design, focusing on bioclimatic information design, software development, and the social implications of digital tools. His creative work has been exhibited at NeurIPS workshops and published in Towards Data Science . He has received notable awards including the IDEA Studio Fellowship (2013), Hellman Fellowship (2012), and multiple research grants like the Faculty Research Grant for "Decod.es" (2013) and the Research Enabling Grant for "Dhour" (2011). Steinfeld has taught core architectural design courses and contributed to software development for design computation.

Nicholas Clarkمشاهده پروفایل

مدرس

• Ecological Forecasting
• Disease Ecology
• Statistical Modeling
• +۲ مورد دیگر

Nicholas Clark is an ARC DECRA Fellow and Lecturer at the School of Veterinary Science, University of Queensland, with affiliations to the Centre for Marine Science. His research focuses on computational tools for predicting ecological responses to environmental change, including host-parasite interactions, wildlife populations, and veterinary diseases. Education includes: B.Sc. Marine Ecology, University of North Carolina Wilmington Ph.D. Ecological Modelling, Griffith University Research interests center on ecological forecasting, automatic time-series analysis, macroecology of infectious diseases, and epidemiology at the human-wildlife interface. He maintains several R packages including MRFcov for Markov Random Fields and mvgam for multivariate generalized additive modeling. His recent publications show strong focus on disease ecology, statistical methods, and One Health approaches. Research impacts include media coverage of ecological forecasting advances and applications in conservation and biosecurity. Honors include an ARC DECRA Fellowship. He actively mentors students in ecological forecasting and computational biology methods.

Guowei Yangمشاهده پروفایل

مدرس ارشد

• Software Engineering
• Machine Learning
• Programming Languages
• +۱ مورد دیگر

Dr. Guowei Yang is a Senior Lecturer at the School of Electrical Engineering and Computer Science , The University of Queensland, Australia. He transitioned to this role in 2021 after serving as a tenured Associate Professor at Texas State University's Department of Computer Science. His research focuses on the intersection of Software Engineering Machine Learning Programming Languages Cybersecurity with an emphasis on system reliability and security. His recent publications (2022-2025) analyze: Android API compatibility challenges Symbolic execution optimizations Fuzzing techniques for JVM security Moving target defense strategies Automated patch generation Constraint classification in code analysis He leads a research group seeking students with backgrounds in software engineering, formal methods, and AI. Current funding includes a 2023-2026 Oracle Corporation grant for DevSecOps analysis. Dr. Yang supervises multiple PhD and Master's projects, often as principal advisor, focusing on topics like deep learning testing, IoT analysis, and DevSecOps integration.

Daniel E. Kelleyمشاهده پروفایل

استاد

• Physical Oceanography
• Climate Science
• Marine Biology
• +۵ مورد دیگر

Prof. Daniel E. Kelley is a Professor in the Department of Oceanography at Dalhousie University, Halifax, Nova Scotia, Canada. He serves as Graduate Coordinator and teaches both undergraduate and graduate courses. His research focuses on physical oceanography, particularly ocean mixing caused by internal waves and double-diffusive convection. He holds academic affiliations including roles as university Senator and former executive member of the Canadian Meteorological and Oceanographic Society. Education: BSc from Mount Allison University PhD from Dalhousie University Research Interests: His work addresses small-scale mixing processes in ocean dynamics, parameterization of convection, internal waves, and frontal instabilities. He collaborates on topics ranging from under-ice algal blooms to whale-ship collision mechanics. His methodologies emphasize open-source tools like R and the 'oce' package, as highlighted in his book Oceanographic Analysis with R . Notable Contributions: Developed the 'oce' R package for oceanographic data analysis Recipient of Rosemary Gill Award and NSERC fellowships Author of over 50 peer-reviewed publications Awards & Honors: Rosemary Gill Award for outstanding service to students NSERC University Research Fellowship Outstanding PhD Thesis (CMOS) Labs/Teams: Collaborates with interdisciplinary teams on oceanographic software development and environmental data analysis initiatives.

Guofei Guمشاهده پروفایل

استاد

• Network and System Security
• AI Security
• Software-Defined Security (SDN/NFV)
• +۵ مورد دیگر

Guofei Gu is a Professor of Computer Science & Engineering and holder of the Eppright Professorship in Engineering at Texas A&M University's College of Engineering. He leads the SUCCESS Lab, focusing on cybersecurity research in areas such as software-defined security, AI security, and IoT/malware analysis. His work bridges networking, systems, and applied cryptography, addressing practical security challenges. Guofei received his Ph.D. from Georgia Tech (2008) and holds prestigious awards including IEEE Fellow (2020), NSF CAREER Award (2010), and AFOSR Young Investigator Award (2013). He has published extensively in top venues like S&P, CCS, and NDSS, with over 18,000 citations. Research Interests: Network/System Security, AI Security, SDN/NFV Security, Mobile/IoT Threats, Malware Analysis, and Zero Trust Frameworks. Selected Awards: Best Paper at ASIACCS 2022 Eppright Professorship in Engineering (2020) IEEE Fellow (2020) AFOSR Young Investigator Award (2013) Labs/Teams: Director of the SUCCESS Lab, collaborating on projects like S2OS (Security OS) and FRESCO. His work emphasizes programmable security solutions for emerging technologies.

Erwin Fieltمشاهده پروفایل

مدرس ارشد

• Business and IT Strategy
• Digital Innovation
• Business Model Innovation
• +۶ مورد دیگر

Dr. Erwin Fielt is a Senior Lecturer at the School of Information Systems within the Faculty of Science at Queensland University of Technology (QUT). He holds a PhD from Delft University of Technology and an MSc from the University of Twente, both in the Netherlands. His research focuses on the intersection of business strategy and information technology, emphasizing innovation, digital transformation, and data-driven business models. Current roles include Academic Lead Learning & Teaching in the School of Information Systems and Co-lead of the Algorithmic Enterprise theme at QUT's Centre for Future Enterprise, collaborating with the Technical University of Munich's KrcmarLab. Research Interests: Dr. Fielt's work explores digital business models, AI governance, platform ecosystems, and the strategic application of emerging technologies. His recent studies address topics such as metaverse entrepreneurship, value creation in digital platforms, and the governance challenges of data-driven enterprises. Awards: He has received the Best Paper Award at ICRIIS 2011 and the Best Poster Award at dg.o 2008. His teaching includes advanced units like IT Governance (IFN631) and the IT Capstone Project (IFB399), with a focus on preparing students for digital innovation challenges. Advising & Grants: Dr. Fielt has supervised doctoral and master's students on topics like shared services, software-as-a-service adoption, and enterprise architecture. His research collaborations span industry and academic institutions globally, addressing challenges in digital innovation, platform ecosystems, and public-sector AI applications. Labs/Teams: He contributes to QUT's Centre for Future Enterprise and Centre for Data Science, leading initiatives in algorithmic enterprise strategies and digital innovation frameworks.

Laine Nooneyمشاهده پروفایل

دانشیار

• Media Studies
• Digital History
• Gender Studies
• +۳ مورد دیگر

Laine Nooney is an Associate Professor in the Department of Media, Culture, and Communication at New York University's Steinhardt School of Culture, Education, and Human Development. Their work focuses on the intersections of gender, technology, and cultural history, particularly in the context of personal computing and video game development. Nooney teaches courses such as History of Computing: How the Computer Became Personal , exploring the social and cultural forces shaping digital technology. Research interests include the hidden histories of computing’s gendered labor, the material culture of early computing devices, and the socio-technical narratives surrounding personal computing’s emergence. They emphasize critical analysis of technological progress narratives and the role of marginalized contributors in tech history. Publications span topics like the Apple II’s cultural impact, the uncredited labor in video game history, and the archaeology of early software ecosystems. Their work challenges mainstream historiography to include underrepresented perspectives in tech’s evolution. Awards and grants are not explicitly listed in the provided materials. Nooney advises via their courses but no specific advisee names are provided. Their research extends to digital humanities methodologies and speculative design pedagogies, as seen in works like A ‘speculative pasts’ pedagogy . Professional presence includes a dedicated website (www.lainenooney.com) and active engagement in academic conferences like SHOT. No specific lab or team affiliations are mentioned in the text.

• Static Analysis
• Logic Programming
• Program Verification
• +۴ مورد دیگر

Manuel V. Hermenegildo is a Professor at the Universidad Politécnica de Madrid, Spain. He is a prominent researcher in the field of programming languages and static analysis, with significant contributions to logic programming, program verification, and formal methods. His work focuses on advancing static analysis techniques, compiler optimization, and energy-efficient computing. He has co-authored numerous papers and organized international conferences such as LOPSTR and SAS, demonstrating his leadership in academic and research communities. His research explores topics including abstract interpretation, runtime checking, and parallel logic programming systems. He is a key contributor to the Ciao Prolog system, emphasizing comprehensive tool integration and formal methods. His research interests span static analysis frameworks, program verification, resource usage analysis, and energy efficiency in computing. He has developed methodologies for optimizing program performance while ensuring correctness, with applications in both theoretical and applied domains. His work often bridges the gap between high-level program analysis and low-level hardware constraints, particularly in embedded systems. Recent trends in his publications include advancements in static cost analysis, dynamic inference of invariants, and tools for incremental assertion checking. His collaborations with institutions like the University of Copenhagen and the University of Kent reflect a global network in advancing computational logic and software engineering. He has been actively involved in academic service, including editorial roles for conference proceedings and journals. His contributions highlight a commitment to both foundational research and practical tools for the programming language community.

Antonio García Cabotمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Educational Technology
• Natural Language Processing
• +۵ مورد دیگر

Antonio García Cabot is an Associate Professor in the Department of Computer Science at the University of Alcalá. His research focuses on artificial intelligence, educational technology, natural language processing, and mobile computing. He leads the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to the PMI group (Intelligent Mobile Platforms). He earned his Doctorate in Computer Science from the University of Alcalá in 2013 with a thesis titled *Propuesta de un sistema multi-agente para la adaptación de contenidos docentes a las competencias, contexto y dispositivo del usuario*. His work emphasizes accessibility in digital education, gamification in MOOCs, and software engineering innovations like automated code repair using LLMs. Research trends in his 2024-2025 publications include: Advancing AI applications in educational assessment (e.g., automated question generation, distractor design) Improving mobile app usability through gesture-based interfaces and sensor integration Developing large language model-based tools for vulnerability repair and teacher simulation analysis Systematic reviews on digital competence ecosystems and multilingual AI systems His contributions to open educational resources (OER) and accessible virtual campuses have been widely adopted in Latin America. Current research extends into embedded systems education and olfactory stimuli impacts on mobile app performance.

• Artificial Intelligence
• Educational Technology
• Mobile Applications
• +۳ مورد دیگر

Eva García López is a Professor in the Department of Computer Science at the University of Alcalá. She holds a PhD from the same institution, completing her thesis on improving the usability of interfaces for teaching objects in m-learning in 2013. Her research focuses on usability engineering, artificial intelligence, and educational technology, with emphases on mobile applications, accessibility, and gamification. She is affiliated with the INTELIA research group (Interaction Technologies and Artificial Intelligence Lab) and previously contributed to TIFyC (Information Technologies for Training and Knowledge) and PMI (Intelligent Mobile Platforms). Eva’s work spans developing adaptive learning systems, enhancing digital content accessibility, and leveraging large language models for educational tools. Her projects include MOOC development, social gamification experiments, and usability evaluations of mobile instant messaging apps. She has also explored the impact of olfactory stimuli on user performance and the application of NLP in automated question generation. Her contributions include guidelines for accessible digital content creation and frameworks for personalized learning paths in web engineering curricula. Her research integrates interdisciplinary approaches, combining machine learning, human-computer interaction, and educational theory to address challenges in digital learning ecosystems. Notable contributions include frameworks for curriculum development, methodologies for usability evaluation, and tools for automated code vulnerability repair.

• Marketing Analytics
• Strategic Pricing
• Quantitative Analysis
• +۴ مورد دیگر

Preethika Sainam is an Assistant Professor at Thunderbird School of Global Management, Arizona State University, specializing in quantitative marketing and data analytics. She previously served as an Assistant Professor at Indiana University's Kelley School of Business. Her research focuses on strategic pricing, big data applications, and marketing analytics, published in top journals like Marketing Science and Journal of Marketing Research . She holds a PhD in Quantitative Marketing from the University of North Carolina-Chapel Hill, an MBA from the University of Texas at Dallas, and a BS from Purdue University as a Dean's Scholar. Education: PhD (UNC-Chapel Hill), MBA (UT-Dallas), BS (Purdue) Research Interests: Marketing Analytics, Pricing Models, Big Data, and International Marketing Dr. Sainam teaches courses such as Global Marketing Strategy, Data Analytics, and Big Data in the Global Economy. She actively contributes to professional associations like the American Marketing Association and serves as an ad hoc reviewer for multiple journals. As a founding member of Women in Marketing Strategy (WiMS), she advocates for gender inclusivity in academia. Her work bridges theoretical frameworks with practical applications, emphasizing data-driven decision-making in global business contexts.

Aleksandar Popovićمشاهده پروفایل

عضو هیئت علمی

• Forest Management Planning
• Ecological Characteristics of Tree Species
• GIS Applications in Forestry
• +۳ مورد دیگر

Aleksandar Popović is a Research Associate at the Faculty of Forestry, University of Belgrade, specializing in Forest Management Planning and Biotechnical Sciences. He holds a PhD from the Department of Forest Management Planning, awarded in 2023 for his work on habitat preservation of endangered tree species. His research focuses on adaptive forest management, GIS applications, and ecological assessment of forest ecosystems. Education: BSc (2016), MSc (2017), PhD (2023), all from University of Belgrade Faculty of Forestry. Affiliations: Employed at Faculty of Forestry since 2018; previously worked for Ministry of Agriculture and EU law harmonization projects. His teaching contributions include GIS-based forestry mapping exercises in the Forest Management Planning course. He is proficient in ArcGIS, QGIS, R, and statistical software. Awarded the Dositeja Young Talent Fund twice (2016/2017). Professional Activities: Consultancy on forest planning documents, EU regulatory alignment, and training in technical software.

Daniel Strüberمشاهده پروفایل

دانشیار

• Model-Driven Engineering
• AI Engineering
• Software Quality Assurance
• +۷ مورد دیگر

Daniel Strüber is an Associate Professor in Software Engineering at Chalmers University of Technology and the University of Gothenburg, Sweden, and an affiliate of the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and empirical software engineering, addressing challenges in software quality, variability management, and security. He holds a PhD (summa cum laude) from Philipps University Marburg and has held academic positions including Assistant Professor at Chalmers and postdoctoral roles at King's College London and Philipps University Marburg. Education: PhD in Computer Science, Philipps University Marburg (2011–2016) Diplom (M.Sc. equivalent) in Computer Science, Philipps University Marburg (2005–2011) Research Interests: Strüber's work spans model-driven engineering, AI integration in software systems, and empirical studies. Key areas include: Model-based languages and tools for software quality assurance Machine learning-enabled systems and their engineering principles Robotics software engineering and variability management Formal methods for consistency and security Search-based optimization in model-driven development Recent Contributions: Recent work includes studies on LLM-assisted reverse engineering, empirical analysis of manual abstraction in software systems, and model-driven approaches for edge deployment of ML models. His research bridges theory with practical implementations in domains like robotics and web-based systems. Awards: Best Reviewer Award (SoSyM 2025) Distinguished Reviewer Awards (GPCE 2024, SPLC 2023) Transformation Tool Contest Awards (2020, 2016) EASST Best Paper Awards (ICGT 2020, ICGT 2017) Grants & Leadership: Co-editor of a JSS special issue on Product Line Engineering (2024) and program co-chair of SPLC 2024. Active in conferences like ICSE, ICGT, and MODELS. Leads grants such as the VR SEMLA project (2022–2024) and the DFG EUphORia fellowship (2019). Teaching: Courses include 'Software Engineering for AI Systems' at Chalmers and 'Software Product Lines' at Radboud University. Involves students in real-world projects via GiPHouse, a student-run company.

Chantal Taconetمشاهده پروفایل

مدرس

• Internet of Things (IoT)
• Middleware Systems
• Context-Aware Computing
• +۳ مورد دیگر

Chantal Taconet is a Lecturer at Telecom SudParis, part of the SAMOVAR research institute. Her work focuses on middleware systems for the Internet of Things (IoT), context-aware computing, energy efficiency, and blockchain applications in supply chains. She has co-authored over 20 peer-reviewed articles and conference papers since 2008, addressing IoT middleware design, QoC management, and middleware for cloud-IoT integration. Her research spans IoT middleware architectures (e.g., IoTVar framework), energy-efficient IoT protocols, and blockchain-based supply chain traceability. She contributed to the ANR INCOME project on multi-scale context management, emphasizing model-driven engineering and distributed system frameworks. Taconet has organized workshops like M4IoT and co-edited special issues on IoT middleware in Annals of Telecommunications . Key technical areas include semantic-based discovery services, fog computing integration for sensor networks, and trust models for IoT systems. Her work bridges theoretical middleware design with practical implementations for IoT applications.

Håkan Örmanمشاهده پروفایل

دانشیار

• Health Informatics
• E-health
• Biomedical Engineering
• +۷ مورد دیگر

Håkan Örman is an Associate Professor at the Department of Biomedical Engineering, Linköping University, within the Faculty of Science and Engineering. He is actively engaged in teaching, research, and academic leadership, including serving as Chairman of the Board of Studies for Electrical Engineering, Physics, and Mathematics. His work bridges engineering and healthcare through digital innovation. His research focuses on health informatics and e-health , particularly in developing information models, ontologies, and knowledge representation systems to create interconnected, learning healthcare ecosystems. He advocates for rational use of digital tools to enhance accessibility, safety, and personalization in healthcare. The recent publications highlight a strong trend in digital health infrastructure , interoperability standards (e.g., openEHR, SNOMED CT), and educational development in engineering and health informatics. His work spans technical architecture, semantic modeling, and pedagogical innovation. Håkan is passionate about pedagogical development and views students as co-creators of knowledge. He teaches in the Master’s program in Biomedical Engineering, the Medical Program, and interdisciplinary eHealth courses. He collaborates with Didacticum for educational advancement and emphasizes dialogue, reflection, and sustainable skill development. He is involved in interdisciplinary initiatives at Linköping University, where students from medicine and engineering jointly develop digital health solutions. This reflects his commitment to collaborative, real-world problem solving and institutional investment in e-health education and research.