جستجوی استاد راهنمای دانشگاهی

• Fluid Dynamics
• Atmospheric Physics
• Turbulence
• +۵ مورد دیگر

Gholamhossein Bagheri is a Scientist and Group Leader at the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany, where he heads the Turbulence and Particles in Fluids research group within the Laboratory for Fluid Physics, Pattern Formation and Biocomplexity (LFPB). His research focuses on the complex physics of particle-laden turbulent flows across environmental, atmospheric, and biological systems. Dr. Bagheri's research spans multiple interconnected domains of fluid physics with significant real-world applications. His primary areas of investigation include: Cloud physics and aerosol-cloud interactions, particularly their role as major sources of uncertainty in weather models and climate projections Atmospheric transport of non-spherical particles such as volcanic ash, microplastics, pollen, and snowflakes Indoor air quality dynamics and the spatio-temporal evolution of respiratory aerosols relevant to infectious disease transmission Development of advanced measurement techniques for studying particle-laden flows in both laboratory and field conditions Analysis of Dr. Bagheri's publication record reveals a trajectory from fundamental fluid dynamics toward increasingly applied research addressing critical environmental and public health challenges. His work on respiratory particle transmission during the COVID-19 pandemic provided key evidence for mask efficacy that influenced policymakers and the public. His research consistently tackles significant uncertainties in atmospheric science while developing innovative instrumentation to bridge laboratory and field measurements. Dr. Bagheri leads an active research team that has developed several groundbreaking measurement platforms including the Max Planck CloudKite (MPCK), the HoloTrack instrument for cloud droplet measurements, and the WinDarts system for atmospheric turbulence measurements. His group has conducted major field campaigns such as the Pallas Cloud Experiment (PaCE) in September 2022 and IMPACT (In-situ Measurement of Particles, Atmosphere, Cloud, and Turbulence) from May to June 2024, where up to six second-generation WinDarts units were successfully deployed over Pallas, Finland.

Shing-Chi Cheungمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Software Testing
• +۷ مورد دیگر

Shing-Chi Cheung is a Professor of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), School of Engineering. He founded the CASTLE research group and co-founded the International Workshop on Automation of Software Testing (AST) in 2006. His leadership includes serving as General Chair of FSE 2014 and chairing multiple APSEC conferences. His research focuses on software quality enhancement through program analysis, testing, debugging, and AI techniques, targeting Android apps, open-source software, deep learning systems, smart contracts, and spreadsheets. Current projects include metamorphic testing frameworks, binary analysis tools, and vulnerability detection systems for emerging technologies. His publication portfolio demonstrates consistent contributions to software engineering since 2016, with recent work emphasizing AI-integrated testing methodologies, smart contract security, and deep learning system reliability. Key trends show increasing focus on cross-language analysis, data visualization quality, and compiler-level verification for modern software stacks. Distinguished Member of the ACM Fellow of the British Computer Society Editorial board member: Science of Computer Programming (SCP), Journal of Computer Science and Technology (JCST) Former editorial board member: IEEE Transactions on Software Engineering (2006-2009), Information and Software Technology (2012-2015) Four patents in China and the United States Cheung actively mentors through the CASTLE research group and serves on program committees for major conferences including ICSE, ESEC/FSE, and ISSTA. His work bridges academic research with practical applications through industry collaborations and tool development. He has contributed to numerous workshops and symposia as steering committee member and program chair.

Hui Liuمشاهده پروفایل

استاد

• Software Engineering
• AI-based Software Development
• LLM-based Program Generation
• +۵ مورد دیگر

Hui Liu is a Professor in the School of Computer Science and Technology at Beijing Institute of Technology, where he leads research in AI-based software development with a focus on LLM applications. His work spans software refactoring, quality improvement, and maintenance, funded by the National Natural Science Foundation of China and the National Key Research and Development Program of China. PhD from Peking University (2008) Former graduate student at Software Engineering Institute, Peking University Distinguished member of China Computer Federation Secretary-General of CCF Technical Committee on Software Engineering Professor Liu's research centers on LLM-based program generation, evaluation and testing of large language models, software refactoring techniques, and automatic construction of software engineering datasets. His work bridges artificial intelligence and software engineering, with particular emphasis on improving code quality through empirical studies and machine learning techniques. Current projects include code contamination detection, context-aware naming recommendations, and refactoring validation using LLMs. His research has evolved from traditional code smell detection to cutting-edge applications of large language models in software development. Liu's publication record shows a strong trend toward LLM applications in software engineering, with recent work focusing on code review generation, commit message generation, and refactoring validation using large language models. His research combines empirical methods with machine learning approaches, often analyzing large code corpora from open-source projects. The work spans both theoretical foundations and practical tool development, with several contributions merged into Eclipse as part of the open-source community. ACM Distinguished Paper Award (ESEC/FSE 2023) ACM Distinguished Paper Award (ICSE 2022) RE'2021 Best Research Paper Award IET Software Premium Award (2018) New Century Excellent Talents in University (2013) Beijing Higher Education Young Elite Teacher (2013) Professor Liu actively mentors PhD and Master's students, with recent graduates including Waseem Akram (awarded Outstanding Graduate) and several students publishing at top venues. His research is supported by major Chinese funding agencies, and he serves on program committees for leading software engineering conferences including ASE, ICSE, and FSE. He maintains strong industry connections through contributions to Eclipse and studies of open-source ecosystems like Rust. Liu leads a research group focused on AI for software engineering, with active projects on code generation, refactoring, and quality improvement. The group collaborates extensively with international researchers and contributes directly to open-source tools, particularly in the Eclipse ecosystem where multiple refactoring improvements have been merged.

Sven Apelمشاهده پروفایل

استاد

• Software product lines and configurable systems
• AI-based program generation and optimization
• Socio-technical software analysis
• +۳ مورد دیگر

Professor Sven Apel holds the Chair of Software Engineering at Saarland University's Saarland Informatics Campus in Germany. He is also the Director of the Saarbrücken Graduate School of Computer Science. His work focuses on software engineering with an emphasis on automation, human factors, and interdisciplinary approaches. Prof. Apel received his Ph.D. in Computer Science in 2007 from the University of Magdeburg. His academic journey includes: Ph.D. in Computer Science, University of Magdeburg (2007) Emmy-Noether Fellowship of the German Research Foundation Heisenberg Professorship of the German Research Foundation Prof. Apel's research centers on empowering software engineering practice to enter an era of intensive automation. His key research areas include software variability and configuration, AI-based program generation and optimization, socio-technical software analysis, and empirical and neurophysiological methods. He pays special attention to the human factor and interdisciplinary research questions, applying his findings to real-world software systems from both open-source projects and industry collaborations with partners like Siemens AG, Bosch Engineering, and Airbus Helicopters. Analysis of Prof. Apel's recent publications reveals a strong focus on configurable software systems, neurophysiological approaches to understanding programming, and the application of AI techniques to software engineering problems. His work often bridges the gap between theoretical foundations and practical applications, with many studies involving industrial collaborations. There's a noticeable trend toward interdisciplinary research combining software engineering with neuroscience, organizational studies, and machine learning. Prof. Apel has received numerous prestigious awards and honors: ERC Advanced Grant "Brains On Code" (2022) ACM Distinguished Member for "Outstanding Scientific Contributions to Computing" (2018) Multiple Most Influential Paper Awards (SPLC'18, ICPC'22, GPCE'23) Multiple Best Paper Awards (SPLC'11, Modularity'15, AOM'18) Heisenberg Professorship and Emmy-Noether Fellowship from the German Research Foundation Prof. Apel has advised numerous Ph.D., Master's, and Bachelor's students throughout his career. His research has been generously funded by multiple grants including an ERC Advanced Grant (2,500,000 Euro, 2022-2027), several DFG projects (CPEC, Congruence, Pervolution), and previous grants like SafeSPL, FeatureFoundation, and Pythia. His work has practical impact through collaborations with industry partners including Siemens AG, Bosch Engineering, and Airbus Helicopters. Prof. Apel leads research in the Chair of Software Engineering at Saarland University, where his team explores the intersection of software engineering, neuroscience, and artificial intelligence. His "Brains On Code" ERC project specifically investigates how programmers' brains process code using neuroimaging techniques. The research group maintains strong connections with both academic and industry partners, facilitating the transfer of research findings into practical applications.

• Atmospheric remote sensing
• Aerosol-cloud interactions
• Ice formation processes
• +۳ مورد دیگر

Dr. Patric Seifert is a Scientist at the Leibniz Institute for Tropospheric Research (TROPOS) in Leipzig, Germany, where he has been working since 2010. He is affiliated with the Remote Sensing of Atmospheric Processes department and leads the Ground-Based Remote Sensing group. His work focuses on atmospheric remote sensing, particularly using the LACROS instrument suite for aerosol and cloud observations. He also maintains a strong connection with the University of Leipzig, where he earned his PhD and currently teaches courses on cloud radar and remote sensing to master's students. PhD in Meteorology from University of Leipzig (2010) Diploma in Meteorology from University of Leipzig (2006) Student of Meteorology at University of Leipzig (2000-2006) Dr. Seifert's research centers on understanding aerosol-cloud interactions, particularly how aerosols influence ice formation processes in the atmosphere. His work involves extensive use of ground-based remote sensing instruments, including the LACROS suite, to observe cloud and aerosol properties. He investigates how aerosol particles affect numerical weather forecast models and develops methods to derive continuous datasets of aerosol and cloud microphysical properties through the Cloudnet data processing scheme. His current research spans multiple international projects across diverse geographical locations including the Arctic, Southern Ocean, Cyprus, and Antarctica. Analysis of Dr. Seifert's recent publications reveals a strong focus on cloud microphysics, particularly mixed-phase and ice clouds. His work frequently employs advanced remote sensing techniques including polarimetric radar and lidar to study ice nucleation processes, particle shape distribution, and aerosol-cloud interactions. A significant portion of his recent research relates to the MOSAiC expedition in the Arctic, examining cloud life cycles and the impact of wildfire smoke on cirrus formation. His publications also highlight innovative approaches to cloud seeding experiments using UAVs and the development of new methods for analyzing cloud radar data. Member of Deutsche Meteorologische Gesellschaft (DMG) since 2006 Ordinary Member of the DFG Transregio programme Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms (AC3) since 2021 Dr. Seifert actively collaborates on numerous international research projects including ACTRIS/Cloudnet, DACAPO-PESO (focusing on the Southern Ocean), PICNICC (examining hemispheric cloud contrasts), SPOMC (polarimetric observations of clouds), COALA (Antarctic observations), ATMO-ACCESS, ACTRIS-D, and EXCELSIOR. His work often involves mentoring students and conducting outreach activities to demonstrate TROPOS's contributions to understanding aerosol-cloud interactions and career opportunities in atmospheric sciences. He has been instrumental in operating and extending the LACROS instrument suite for various field campaigns around the world. Dr. Seifert leads the Ground-Based Remote Sensing group at TROPOS, which operates the LACROS (Leipzig Aerosol and Cloud Remote Observations System) infrastructure. This mobile observation platform has been deployed in diverse environments including Punta Arenas, Chile for the DACAPO-PESO campaign, Cyprus for multiple projects, and Antarctica for the COALA campaign. His team collaborates with international partners across Europe, New Zealand, and the Americas to study atmospheric processes in different climatic regions, with particular emphasis on aerosol-cloud interactions in pristine environments.

• Software Evolution
• Empirical Software Engineering
• Domain-Specific Languages
• +۲ مورد دیگر

Thomas Degueule is a researcher at CNRS (Centre National de la Recherche Scientifique) in France, actively contributing to software engineering research since 2015. He serves on program committees for major conferences including ASE, ICSE, and SLE, with primary research interests in Software Evolution, Empirical Software Engineering, and Domain-Specific Languages. His work focuses on breaking change analysis in APIs and libraries, client-library compatibility testing, and dependency management. He develops practical tools like Roseau for source-based breaking change detection and investigates semantic versioning impacts in ecosystems like Maven Central. His empirical approach leverages large-scale repository analysis to address real-world software maintenance challenges, particularly in Java ecosystems. Recent publications (2023-2025) show consistent contributions to breaking change analysis and compatibility testing, appearing in top venues like ASE, ICSE, and ISSTA. His research bridges theoretical insights with practical tooling for software evolution challenges, demonstrating strong empirical methodology and tool-oriented contributions. No scientific awards are documented in the available information. Degueule has advised no publicly listed students and holds no mentioned research grants. His organizational roles include Program Co-Chair for SLE 2023 and committee positions across multiple conferences, reflecting significant service to the software engineering community.

Ralf Brunsمشاهده پروفایل

استاد

• Data stream processing
• Evolutionary algorithms
• Machine learning
• +۶ مورد دیگر

Prof. Dr. Ralf Bruns is a full-time Professor in the Department of Computer Science at the Faculty of Business and Information Technology, Hannover University of Applied Sciences and Arts. His office is located at Ricklinger Stadtweg 120, 30459 Hanover, with direct contact available via phone (+49 511 9296 1817) and email. His research focuses on cutting-edge computational methodologies including: Real-time data stream processing systems Bio-inspired algorithms ( evolutionary and swarm intelligence ) Machine learning applications in enterprise systems Semantic Web technologies for knowledge representation Software architecture patterns for event-driven systems Complex Event Processing (CEP) frameworks His publications demonstrate a consistent focus on event-driven architectures applied to logistics, healthcare, IoT, and urban mobility systems. Recent work emphasizes agent-based modeling and real-time analytics for decision support in dynamic environments. Prof. Bruns leads two key research initiatives: the Software Architecture Working Group (AG SWA) and the Smart Data Analytics Research Cluster . He also serves as faculty representative in the Fachbereichstag Informatik (FBTI) and contributes to academic selection committees.

Elena Ambrosettiمشاهده پروفایل

دانشیار

• international migration
• migrants' integration
• migration policies
• +۴ مورد دیگر

Elena Ambrosetti serves as Associate Professor of Demography at Sapienza University of Rome's Department of Methods and Models for Economics, Territory and Finance. She holds editorial positions as Associated Editor for both Genus, Journal of Population Science and Sociology of Race and Ethnicity , and currently coordinates Sapienza's involvement in two major European Commission projects. Her research program centers on Italian migration dynamics with specialized focus on migrant integration processes and policy frameworks. She maintains significant expertise in Mediterranean demographic patterns, particularly Egypt's fertility transition, while also investigating sexual and reproductive health disparities among migrant populations and the socioeconomic implications of population ageing on welfare systems. Her methodological approach combines demographic analysis with social policy evaluation. Her documented publication output demonstrates consistent engagement with Egyptian demographic issues, particularly through her 2013 analysis of gender-based violence within shifting political and social contexts. This work exemplifies her regional specialization and interdisciplinary methodology. As principal coordinator for Horizon 2020 projects PERCEPTIONS (grant 833870) examining migration-security-technology interfaces and COVINFORM (grant 101016247) analyzing pandemic information dynamics, she leads substantial research initiatives with € multi-million budgets and international consortia. Her departmental affiliation within Sapienza's economics-focused unit reflects the quantitative and policy-oriented nature of her demographic research, bridging social science with economic modeling approaches to population studies.