جست‌وجوی استاد و پژوهشگر

Alicja Olejniczakمشاهده پروفایل

مدرس

• Deep Learning
• Wireless Communications
• LTE Technology
• +۶ مورد دیگر

mgr inż. Alicja Olejniczak serves as a Lecturer at the Department of Radiocommunication Systems and Networks within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. Her work focuses on the intersection of wireless communications and artificial intelligence, particularly applying deep learning techniques to solve challenging problems in modern radio systems. Her primary research interests include: Deep learning applications in wireless communication systems Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) identification in indoor environments Signal processing for GMSK modulation schemes Software-defined radio implementations for NB-IoT technologies Train detection using LTE reference signals Radiolocation systems and multilateration techniques Analysis of her recent publications reveals a strong trend toward applying deep learning methods to solve practical problems in wireless communications. Her work spans both theoretical development and practical implementation of algorithms for signal processing, channel estimation, and radio interface design. A significant portion of her research focuses on NB-IoT and LTE technologies, with applications ranging from Internet of Things to transportation systems like train detection. Dr. Olejniczak actively participates in multiple research projects at Gdańsk University of Technology, including: SDIDS - Software-Defined Device for Detecting and Mitigating Interferences in 4G-LTE and 5G-NR radio interfaces DUCH IoT - A software-defined, universal radio interface for intelligent IoT devices VCS-MLAT - Innovative method of aircraft locating in distributed VCS systems AEGIS - Mobile Device for Generating Electromagnetic Curtain Her laboratory work involves hands-on implementation of software-defined radio systems and conducting measurements in real-world environments to validate theoretical models. She collaborates extensively with colleagues including O. Błaszkiewicz, K. Cwalina, P. Rajchowski, and J. Sadowski on various research initiatives.

Ulrich Eiseneckerمشاهده پروفایل

استاد

• Software Engineering
• Generative Software Development
• Software Product Lines
• +۵ مورد دیگر

Professor Ulrich Eisenecker serves as the Director of the Institute for Business Informatics at Leipzig University's Faculty of Economics and Business Administration. He holds the Chair of Business Informatics with specialization in software development for business and administration, a position he has maintained since October 2004. Prior to this, he served as Dean of the Faculty (2012-2016) and Pro-Dean (2008-2012). His academic journey includes professorships at Kaiserslautern University of Applied Sciences (1999-2004) and Heidelberg University of Applied Sciences (1995-1999), following research positions at Daimler-Benz Research Institute and Mannesmann Kienzle GmbH. Professor Eisenecker's research focuses on Generative Software Development , Software Product Lines , Software Visualization (including 2D, 3D, AR and VR applications), and E-Assessment systems . His work bridges theoretical computer science with practical business applications, particularly evident in his application of set theory to software features and product lines. He leads the ongoing 'Visual Software Analytics' project and has previously directed projects funded by the European Social Fund and German Federal Ministry of Education and Research. His publication record spans over two decades, highlighted by the influential 2000 book 'Generative Programming' co-authored with K. Czarnecki and the 2017 Most Influential Paper Award from the Software Product Line Conference. Recent work (2023-2025) continues to advance software engineering and educational technology, particularly in automated assessment systems using AI techniques. Notable recognition: Most Influential Paper Award from Software Product Line Conference 2017 (SPLC 2017) Professor Eisenecker supervises doctoral and master's students, with numerous successful completions including Dr. Richard Müller, Dr. Max Lillack, and Dr. Johannes Kristan. His research group includes several scientific staff members and regularly publishes with student co-authors. He teaches 'Introduction to Computer Science' for economics students, 'Programming,' and 'Software Engineering' courses, integrating his research in automated feedback systems into his pedagogy. His research group maintains strong connections between academic research and practical applications, particularly through open source initiatives and industry collaborations focused on software analytics and educational technology.

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.

Austin Mordahlمشاهده پروفایل

استادیار

• Static Analysis
• Taint Analysis
• Automated Testing
• +۴ مورد دیگر

Austin Mordahl is an Assistant Professor in the Department of Computer Science at the University of Illinois Chicago. His research focuses on improving the usability and reliability of software quality assurance tools, particularly static analyses and fuzz testing. Dr. Mordahl actively seeks students interested in cutting-edge research in software engineering at UIC. Dr. Mordahl's research interests span multiple areas of software engineering with a particular emphasis on: Static Analysis and Taint Analysis for software security Automated Testing techniques including fuzz testing Improving the usability and reliability of software quality assurance tools Configurable static analysis tools and their behavior Applying machine learning to triage and configure static analysis tools Lifting static analysis to work on software product lines Improving evaluations of fuzz testing tools His recent publications demonstrate a strong focus on addressing challenges in configurable static analysis tools, with particular attention to nondeterministic behavior, configuration spaces, and automatic testing and debugging approaches. Mordahl's work bridges theoretical foundations with practical applications, aiming to make software quality assurance tools more accessible and effective for developers. Dr. Mordahl has received several prestigious awards for his work: NSF Graduate Research Fellowship Awardee (2020) Eugene McDermott Graduate Research Fellowship Awardee (2020) ICSE 2019 Student Research Competition Winner Dr. Mordahl is actively involved in mentoring and seeks students interested in software engineering research. He has served on numerous program committees for top software engineering conferences including ICSE, ASE, ISSTA, and PLDI. His service to the academic community extends to artifact evaluation committees, demonstrating his commitment to research reproducibility and rigor.

Yutian Tangمشاهده پروفایل

استادیار

• AI+SE
• Large-language Model+SE
• Program Analysis
• +۵ مورد دیگر

Dr. Yutian Tang serves as an Assistant Professor (UK Lecturer) and Principal Investigator at the School of Computing Science, University of Glasgow, where he supervises PhD students and leads research in AI-driven software engineering. His academic journey includes a PhD from The Hong Kong Polytechnic University's Department of Computing. His research spans AI+SE integration , particularly focusing on Large Language Models for program analysis, software testing, and Android security. Key areas include: LLM-assisted vulnerability detection and repair Empirical studies of real-world software systems Privacy protection mechanisms Configuration compatibility in mobile applications Smart contract security optimization His publication portfolio shows a clear trajectory toward AI-augmented software engineering , with recent work demonstrating how LLMs can enhance taint analysis, binary code similarity detection, and test generation. This evolution reflects the field's broader shift toward AI integration while maintaining rigorous empirical validation. Award highlights include: Best Industry Paper Award at ISSRE'18 Elevation to IEEE Senior Member (2024) Three Android OS defects confirmed by Google Security Team As an active researcher and community contributor, Tang serves on 40+ program committees including PLDI, ICSE, and FSE. His work receives funding from National Natural Science Foundation of China, Shanghai Science Commission, OpenAI, and Google. Current projects focus on automated bug localization and LLM-based testing frameworks, with recent grants from OpenAI Cybersecurity and Google Cloud programs. He leads research groups investigating Android security and AI-assisted program analysis, collaborating with institutions like Lund University.

Djamel Eddine Khelladiمشاهده پروفایل

پژوهشگر

• Software engineering
• Model-Driven Engineering
• Software Evolution
• +۳ مورد دیگر

Djamel Eddine Khelladi is a CNRS Researcher at the IRISA laboratory within the DIVERSE team at University of Rennes, specializing in software engineering with emphasis on model-driven techniques and empirical validation. His work bridges theoretical frameworks and industrial-scale applications, particularly in evolving software ecosystems. His academic foundation includes a Ph.D. from Sorbonne University (formerly University Pierre et Marie Curie) at the Laboratory of Computer Science of Paris 6 (LIP6), followed by postdoctoral research at Johannes Kepler University Linz's Institute for Software Systems Engineering. This trajectory established his expertise in software evolution and model-driven approaches. Khelladi's research centers on software evolution challenges, particularly model-code co-evolution in highly-configurable systems like the Linux kernel. He develops scalable analysis tools (e.g., HyperAST, HyperDiff) and investigates empirical phenomena in build systems, configuration management, and polyglot programming environments. Recent work increasingly integrates large language models for automated co-evolution tasks while maintaining rigorous empirical validation. His publication trends reveal a consistent focus on practical tooling for software evolution, with growing exploration of AI-assisted engineering. Key themes include scalability in software history analysis, reproducibility in configurable systems, and debugging multi-language environments, often using Linux kernel ecosystems as testbeds. As an active community contributor, Khelladi serves on program committees for ASE, ICSE, and ESEC/FSE while advancing research through the DIVERSE team at IRISA. This group specializes in variability-intensive software systems, providing the collaborative environment for his empirical and tool-building research.

Leopoldo Teixeiraمشاهده پروفایل

استادیار

• Software Engineering
• Software Product Lines
• Configurable Systems
• +۷ مورد دیگر

Leopoldo Teixeira is an Assistant Professor at the Informatics Center (CIn) of the Federal University of Pernambuco, where he leads the Software Testing and Analysis Research group. He is also affiliated with the Software Productivity Group and CIn-Trust. Since May 2023, he has served as head of graduate studies at his department. His educational background includes: PhD in Computer Science from the Federal University of Pernambuco (CIn-UFPE) in 2014, supervised by Paulo Borba and Rohit Gheyi MSc in Computer Science from CIn-UFPE in 2010 Bachelor's degree in Computer Engineering from the Polytechnic School of Pernambuco in 2007 During his PhD, he spent a winter term at the University of Waterloo working with Krzysztof Czarnecki. In 2022, he was a CAPES-Alexander von Humboldt Experienced Research Fellow at the Chair of Software Engineering of Universität des Saarlandes, working with Sven Apel on variability analysis over time and space. His research focuses on Software Engineering with emphasis on improving software quality and productivity. His work spans software product lines, configurable systems, refactoring, formal methods, software testing, and mobile development. His publication record shows a consistent focus on software analysis, testing, and maintenance, with recent work exploring Dockerfile repair and flaky test detection. His scientific recognition includes the CAPES-Alexander von Humboldt Experienced Research Fellowship in 2022. As an active member of the software engineering research community, he has served on program committees for numerous conferences including ASE, ICSE, ESEC/FSE, and others across multiple years. Leopoldo leads the Software Testing and Analysis Research group at CIn-UFPE and is affiliated with the Software Productivity Group and CIn-Trust, indicating a strong institutional presence and collaborative research environment.