استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۲۷۱-۲۸۵ از ۳۵۱ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Patrik Jansson is a Professor of Computer Science at Chalmers University of Technology since 2011, with joint affiliation to Gothenburg University. His work bridges Functional Programming, Domain-Specific Languages (DSLs), and applications to Climate Impact Research, Fusion, and Physics.
Lecorney Stéphane is an Associate Professor at the Media Engineering Institute (MEI) within the School of Engineering and Management of the Canton of Vaud . His research focuses on Sustainable IT , Green IT , Software Engineering , and Eco-friendly Web Design . Key Projects : CarbonViz (2020–2026), an open-source tool for measuring digital energy footprints; Open Data CO2 (2022), a module for Odoo ERP to track CO2 emissions; Rouge Kaki (2022), a sustainability dashboard for SMEs. Research Trends : His work bridges Environmental Science and Software Engineering , emphasizing tools to visualize digital carbon footprints, assess web analytics for sustainability, and integrate Corporate Social Responsibility (CSR) into business practices. Collaborations : He collaborates with teams across HES-SO (e.g., ReDS, MEI) and partners like Romande Énergie and Ville de Lausanne . Publications : Recent articles explore Open Science citation impacts (2024), digital sustainability myths (2024), and methodologies for eco-conscious web analytics (2024 conference). Earlier work includes APIs for 3D georeferenced historical data (2022) and hybrid event sustainability (2021).
Prof. Mihai Alexandru Botezatu serves as Dean of the Faculty of European Economic Studies and Full Professor in the Department of Informatics, Statistics, Mathematics at the Faculty of Managerial Informatics, Romanian-American University (URA). With 17 years of prior experience in public administration (Labor Inspectorate, Ministry of Labor, AMPOSDRU) and private sector project management (S&T Romania, Romanian Employers' Association), he brings practitioner expertise to academia since joining URA in 2015. His educational background includes a PhD in Cybernetics and Economic Statistics from Bucharest Academy of Economic Studies (2011) and undergraduate studies at URA's Faculty of European Integration Studies (2004). Professional development encompasses advanced training in project management, IT systems, and European funding mechanisms. Research focuses on interdisciplinary connections between IT systems and socio-economic policy, particularly AI/NLP applications in software development , sustainable development modeling , and European project management . Recent work analyzes Java code generation with AI tools, regional sustainable development metrics, and renewable energy drivers in Central/Eastern Europe, emphasizing practical implementation for labor market transitions. His 15 most recent publications (2019-2025) reveal an accelerating convergence of artificial intelligence with socio-economic analysis , shifting from traditional project management toward NLP-driven coding solutions and big data analytics for sustainable development indicators. This evolution reflects growing emphasis on generative AI tools while maintaining core focus on EU funding mechanisms and regional policy impacts. Prof. Botezatu has managed or monitored approximately 14 European-funded projects (2010-2019) and participated in three competitively funded research contracts (one international). His consulting firm specializes in European project management, complementing academic work through practical implementation of social responsibility measures and organizational management solutions. Professional engagement includes membership in Danube Adria Association for Automation & Manufacturing (DAAAM), Computer Science Teachers Association, and World Academy of Science, Engineering and Technology (WASET), supporting knowledge exchange in AI applications and sustainable development metrics.
Stéphane Bedwani is an Associate Professor in the Department of Physics and an Assistant Professor-Researcher in the Department of Radiology, Radiation Oncology and Nuclear Medicine at the University of Montreal. He also serves as a Medical Physicist in the Department of Radiation Oncology at CHUM (Centre Hospitalier de l'Université de Montréal). His interdisciplinary work bridges physics, engineering, and clinical medicine with a focus on advancing radiation therapy techniques. Dr. Bedwani's educational background includes a Master of Science (M.Sc.) and Doctor of Philosophy (Ph.D.), though specific institutions and years are not mentioned in the provided text. His academic career demonstrates strong integration between theoretical physics, biomedical engineering, and clinical applications in radiation oncology. Dr. Bedwani's research interests focus on several key areas in medical physics and radiation oncology. His primary research focuses on dual-energy computed tomography (DECT) applications for quantitative imaging and radiation therapy planning, particularly in assessing pulmonary function. He has developed innovative approaches using 3D printing technology to create patient-specific radiation therapy devices, including the "Montreal split ring applicator" for gynecological brachytherapy. His work also explores real-time monitoring techniques for mobile tumors and methods to improve cardiac sparing in left breast cancer radiation therapy . Dr. Bedwani's research bridges the gap between advanced imaging techniques and practical clinical applications to improve patient outcomes in radiation oncology. Analysis of Dr. Bedwani's publication record reveals a strong emphasis on translating engineering solutions to clinical radiation oncology problems. His research demonstrates a clear progression from fundamental imaging physics to practical clinical applications, with particular focus on dual-energy CT techniques, 3D printing applications in radiation therapy, and functional lung imaging. His work often involves interdisciplinary collaboration between physicists, engineers, radiation oncologists, and other medical specialists. Dr. Bedwani leads research initiatives focused on the Imaging and Engineering axis at CRCHUM (Centre de recherche du Centre hospitalier de l'Université de Montréal). His laboratory work emphasizes the development and validation of novel imaging techniques and medical devices for radiation therapy. He collaborates with a multidisciplinary team including medical physicists, radiation oncologists, engineers, and computer scientists to advance precision radiation therapy techniques. His current projects include optimizing 3D-printed patient-specific devices for brachytherapy, developing quantitative imaging biomarkers for radiation-induced lung injury, and improving functional imaging techniques for treatment planning.
استاد مدعو
Dr. Damiano Perri serves as an Adjunct Professor in the Department of Mathematics and Computer Science at the University of Perugia. With a strong background in computer science research and teaching, his work spans multiple cutting-edge domains with practical applications. His academic profile demonstrates a consistent commitment to both theoretical research and real-world implementation. His research interests encompass a broad spectrum of computer science disciplines including Virtual Reality, Augmented Reality, Artificial Intelligence, Cloud Computing, Machine Learning, High Performance Computing, Quantum Computing, and Health Informatics. His work often bridges multiple domains, such as applying VR/AR technologies to healthcare problems like Visual Snow Syndrome treatment, or combining quantum computing principles with machine learning approaches. Professor Perri's publication record shows consistent output with 37 publications spanning from 2018 to projected 2026, demonstrating his active research trajectory. His work appears in high-impact venues including IEEE Access and Lecture Notes in Computer Science, often in collaboration with colleagues like Osvaldo Gervasi and Marco Simonetti. His research has evolved from foundational work in parallel computing and VR to increasingly interdisciplinary applications including health informatics and quantum computing. As an educator, Professor Perri has supervised numerous students, contributing as co-author to 7 master's theses and 52 bachelor's theses since 2019. He teaches several courses including Elements of Computer and Operating System Architecture, Virtual and Augmented Reality Laboratory, Computer Networks: Protocols, and Informatics across different degree programs. He serves as the technical manager of the LibreEOL project since 2015, which appears to be an important electronic assessment platform used at the university. Additionally, he is currently participating in a PRIN research project focused on analyzing Italian language corpora using artificial intelligence techniques. Professor Perri has developed several practical tools to support teaching and research, including a Confusion Matrix generator, Timezones tool, Countdown Timer, Banker's Algorithm solver, Money Calculator, and Break Timer. These tools reflect his commitment to practical applications of computer science concepts and enhancing the educational experience.
استادیار
Qijun Hong is an Assistant Professor of Materials Science and Engineering at Arizona State University's School for Engineering of Matter, Transport and Energy. He holds a PhD in Physical Chemistry from Caltech (2014) and BS in Chemistry from Fudan University, China (2009). Prior to joining ASU, he completed postdoctoral research at Brown University (2014-2020) and worked as a Machine Learning Scientist at Amazon.com (2020-2021). Education: PhD, Physical Chemistry, California Institute of Technology, 2014 BS, Chemistry, Fudan University, China, 2009 His research integrates materials science, machine learning, and density functional theory to predict material properties. Key focus areas include melting temperature prediction, heat capacity calculations, thermal expansion, and enthalpy via first-principles molecular dynamics. His group developed SLUSCHI software for melting point calculations and the MAPP framework used globally for materials property prediction. Notably, his prediction of the world's highest melting temperature material (confirmed experimentally) received widespread media coverage including Washington Post and Science. Analysis of his recent publications reveals a strong trend toward machine learning applications in materials discovery, particularly graph neural networks for predicting thermodynamic properties. His work bridges computational modeling with experimental validation, focusing on refractory materials and high-entropy alloys. Scientific Recognition: NSF, DoD, and DOE-funded research projects SLUSCHI software with 3,000+ downloads MAPP framework with 7,000+ web uses and 300,000+ API calls CDC-featured COVID-19 forecasting model Extensive media coverage for materials breakthroughs As a dedicated educator, Hong teaches graduate courses including MSE 457 (Quantum Mechanics), MSE 511 (Math and Computational Methods), and specialized topics in materials science. His research group actively recruits graduate students for projects at the intersection of AI and materials science. He leads multiple federally funded projects including Rare Earth Materials Under Extreme Conditions (NSF) and Emergent Refractory Behaviors (DoD).
Jide Edu is a Lecturer in the Department of Computer and Information Sciences at the University of Strathclyde. His research focuses on the intersection of Artificial Intelligence and Cyber Security, with expertise in AI security, IoT security, risk management, identity management, and digital forensics. He brings practical experience from his prior role as an IT security specialist to his teaching and research. Education: PhD from King's College London on 'Assessing and measuring the privacy practices of voice assistant applications' MSc from Lancaster University on 'Anomaly detection in cloud computing using network traffic data analysis' His research develops intelligent and automated approaches to address cyber security challenges, emphasizing Privacy, Trust, and Human Factors. Key projects include analyzing AI assistants' ecosystems for vulnerabilities and designing frameworks for national electronic identity (eID) systems. Jide supervises undergraduate and postgraduate research projects and teaches courses in the MSc Cybersecurity program, including CS810, CS807, and CS885. He actively contributes to academic service as a peer reviewer for journals like IEEE Transactions on Dependable and Secure Computing and ACM Transactions on Privacy and Security.
Prof. Dr. Katrin Weller is a leading scholar in computational social science and research data management. She holds the Professorship for Research Data Management in the Social Sciences at Heinrich Heine University Düsseldorf (since 2024) and serves as Scientific Director of the Data Services for the Social Sciences department at GESIS - Leibniz Institute for the Social Sciences . Her career includes co-leading the Research Data and Methods team at the Center for Advanced Internet Studies (CAIS) (2021-2023) and heading GESIS's Digital Society Observatory team (2015-2024). Academic Appointments Professor for Research Data Management in Social Sciences, HHU Düsseldorf (2024-present) Scientific Director, Data Services for Social Sciences, GESIS (2024-present) Research Themes Digital behavioral data quality and reusability Ethical challenges in social media research Altmetrics and scholarly communication Platform data preservation and archiving Key Collaborations Center for Advanced Internet Studies (CAIS) Library of Congress (Digital Studies Fellow) International conferences (AoIR, WebSci, ICWSM) Scientific Contributions span 15+ years of publications addressing social media's methodological, ethical, and archival dimensions. Notable works include: Frameworks for assessing data quality in digital social research Ethical implications of decentralized platform data collection (e.g., Mastodon) Preservation strategies for Twitter and Wikipedia references Analysis of affective drivers in political information seeking Her teaching includes seminars on social media research fundamentals at Heinrich Heine University. As an organizer , she has led European symposia on computational social science challenges and co-founded the #FAIL workshop series to study social media research failures.
Dr. Eng. Sorin Ilie is a Lecturer at the Faculty of Automatic Control, Computers and Electronics, University of Craiova (Romania). His research focuses on agent-based systems , distributed computing , and software engineering , with notable work in ant colony optimization and human-computer interaction . He has contributed to automated software development frameworks like ReLEL and Praxeme, as well as renewable energy applications in urban environments. Role: Lecturer Email: sorin.ilie@edu.ucv.ro Research Interests: Agent-based simulation for emergency scenarios Mathematical modeling of emissions in power systems Automated code generation from requirements models Application of game theory to electric vehicle rentals Swarm intelligence algorithms in distributed systems Publication Trends: His recent work spans artificial intelligence , renewable energy , and software engineering , emphasizing agent-based resource allocation , ant colony optimization , and model-driven development . He explores interdisciplinary applications in environmental management , urban mobility , and collaborative learning tools . Projects: Includes research on distributed constraint topologies, federated agent systems for environmental monitoring, and semantic logging in multi-agent architectures. His work bridges theoretical frameworks (e.g., ACODA optimization, JADE middleware) with practical implementations in disaster management and auction systems.
استادیار
Ignacio Domínguez is an Assistant Professor at North Carolina State University's Department of Computer Science within the College of Engineering. He serves as Assistant Director of the Senior Design Center and specializes in human behavior modeling in virtual environments, with applications in cybersecurity, game design, and educational technology. Ph.D. in Computer Science (2018, NC State) M.S. in Computer Science (2015, NC State) B.S. in Informatics Engineering (2010, Universidad Católica Andrés Bello) His research focuses on computational modeling of human decision-making in interactive systems, with interdisciplinary applications spanning: Human-Computer Interaction (HCI) and User Experience Animal-Computer Interaction (Canine physiology monitoring) Software Engineering Education and Capstone Project Management Cognitive Modeling through typing and game behavior The 15 most recent publications demonstrate expertise in flipped classroom analytics, game-based security modeling, posture classification, and educational software automation. Key trends include: Integration of behavioral data with security protocols Real-time physiological monitoring for accessibility Machine learning in educational contexts Visual and cognitive factors in virtual environments Scientific recognition includes: Best Paper Honorable Mention (CHI 2016) Outstanding Teaching Assistant awards (2011-2014) Grow with Google Scholarship (2018) He has mentored 8 undergraduate and graduate students through research projects and serves as a teaching advisor for: DELTA Grant-funded initiatives Senior Design Center operations NC Collaborative training portal migration
استادیار
Bowen Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University, where he leads the SoftMax Lab within the College of Engineering. Previously, he was a postdoctoral researcher at Singapore Management University (SMU), where he also earned his PhD from the School of Computing and Information Systems. His research spans the intersection of machine learning and software engineering, with particular focus on securing AI models for software engineering tasks from both model and data perspectives. Key research interests include AI for Code, Backdoor Attack and Defense on Large Code Models, Code Data Interpretation and Quality, Code Representation Learning, Model Compression, Vulnerability Detection and Repair, and Safety of AI-enabled Software Systems. Xu's publication record shows a strong focus on the security aspects of AI code models, with several recent papers examining backdoor attacks and defenses. His work also explores the application of large language models to software engineering tasks like vulnerability repair, API documentation, and technical question answering. His publications appear in top venues including IEEE Transactions on Software Engineering (TSE), ACM Transactions on Software Engineering and Methodology (TOSEM), and International Conference on Software Engineering (ICSE). Highly Commended Full Paper Award at ESEM 2018 Honorable Mention Award at ACSAC 2022 Nominated for ACM SIGSOFT Distinguished Paper Award at ASE 2022 Xu actively serves the software engineering community through editorial and program committee roles, including serving as Paper Review Co-chair for ICSE 2025 and FSE 2025, and as a member of the Editorial Board for Empirical Software Engineering Journal. He has advised numerous graduate and undergraduate students who have gone on to positions at companies like Microsoft, Marvell Semiconductor, and Barclays.
استاد آموزشی
Margaret M. Fleck is a Teaching Professor at the University of Illinois, Urbana-Champaign , associated with the Discrete Structures and Artificial Intelligence course sequences. She earned her Ph.D. and M.S. in Electrical Engineering and Computer Science from MIT, and a B.A. in Linguistics from Yale. Education: MIT Ph.D. (EE&CS), Yale B.A. (Linguistics) Her research spans computational linguistics, speech processing, and computer vision, with a focus on unsupervised word boundary detection , prosodic feature analysis , and hybrid programming environments for AI and vision tasks. Notable works include the Berkeley-Iowa Naked People Finder and Schwa 1.0 language system. Key article trends include speech prosody analysis , language acquisition , computer vision systems , and educational technology . She received the Rose Teaching Award in 2019 and has advised students who now hold faculty positions at institutions like MIT and SUNY Buffalo. Her teaching emphasizes frequent assessments , readable materials , and interleaved technique-application pedagogy . Selected Awards: Rose Teaching Award (2019) Advising Legacy: Mentored students in computational linguistics and computer vision, including Ph.D. theses on jigsaw algorithms and road sign detection .
پژوهشگر
Marcus Nyström is a Researcher at Lund University Humanities Lab and part of the eSSENCE: The e-Science Collaboration . He holds a PhD in Information Theory (2008) and was appointed Associate Professor of Ergonomics in 2015. His work focuses on eye tracking methodology , including instrument development and data analysis techniques. Research Areas : Eye Movement Physiology, Human-Computer Interaction, Cognitive Science, Deep Learning for Eye Tracking Projects : ADAPT2 (adaptive developer tools), GANDER (code review eye tracking), eSSENCE@LU (astronomy VR visualization) Recent publications analyze eye tracking fundamentals , deep learning frameworks , and multi-tracker systems . He contributes to journals like Behavior Research Methods and conferences on eye tracking research. His work intersects with UN Sustainable Development Goals related to Quality Education and Industry Innovation .
پژوهشگر
K.O. Salako is a researcher at City, University of London, specializing in software reliability, Bayesian inference, and safety-critical systems. His work spans autonomous vehicles, cybersecurity, and critical infrastructure resilience, with a focus on conservative statistical approaches and probabilistic modeling. Key research interests include: Software Reliability Assessment Bayesian Statistical Methods Autonomous Vehicle Safety Cybersecurity and Malware Detection Critical Infrastructure Risk Analysis His recent publications demonstrate trends in malware behavior analysis using machine learning, reinforcement learning generalization , and conservative Bayesian approaches for reliability claims. He has contributed to stochastic modeling of database protocols and interdependency analysis in infrastructure systems. Salako’s work appears in journals like Quality and Reliability Engineering International and IEEE Transactions on Software Engineering , with conference presentations at venues including European Dependable Computing Conference and IEEE/IFIP DSN . His collaborations with Zhao, Strigini, Popov, and others highlight interdisciplinary research in safety and security domains.
دانشیار
Dávid Szabó is a habilitated Associate Professor at the Institute of Romance Studies , Department of French Language and Literature , Eötvös Loránd University. His academic profile bridges sociolinguistics , focusing on argot and slang studies in French-Hungarian contexts, with computer graphics and C# software development . He has contributed to diverse fields, including AI in education , sustainable finance , and real-time graphics APIs . Research Highlights: His work explores the intersection of language evolution and technology, with recent publications on Green Finance , AI-driven educational tools , and parallel processing in graphics programming . He investigates linguistic taboos in Hungarian politics and translation challenges of urban French slang into Hungarian, while developing educational software like StudyHelper. Technical Contributions: Szabó has pioneered the integration of modern C# with graphics APIs (Vulkan, OpenGL) for real-time rendering , creating frameworks for multi-platform applications and shader program development . His technical papers emphasize code efficiency, API abstraction, and GPU optimization.
