Model-based software testing Professors and Supervisors in Germany | ApplySharif

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نمایش ۶۹۱-۷۰۵ از ۷۳۱ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Markus Pösselمشاهده پروفایل

پژوهشگر

Max Planck Institute for AstronomyGermany

Markus Pössel serves as Managing Scientist at Haus der Astronomie (House of Astronomy), Senior Outreach Scientist at the Max Planck Institute for Astronomy, and Director of the International Astronomical Union's Office of Astronomy for Education. Based at the MPIA Campus in Heidelberg, he has dedicated his career to astronomy education and outreach since completing his PhD in quantum gravity in 2003. His research interests focus on effective methods for teaching complex astrophysical concepts to non-specialists, with particular expertise in relativity physics, cosmology education, and science communication. Pössel has developed numerous educational resources and regularly contributes to teacher training programs through Heidelberg University partnerships. His recent publications reveal a consistent focus on making advanced astronomical concepts accessible, with work spanning gravitational waves, black holes, cosmic expansion models, and astronomy education methodology. The publications demonstrate his dual commitment to theoretical understanding and practical educational application. Hanno and Ruth Roelin Prize for Science Communication (2007) As an educator, Pössel mentors pupils during research internships and actively participates in teacher training events. His YouTube series 'Faszination Astronomie Online' (330 episodes), 'Fragen ans Universum' (34 episodes), and 'Astro & Co.' have reached wide audiences. He also contributes to the Einstein Online portal and maintains the 'Relativ einfach' blog. At Haus der Astronomie, Pössel oversees a variety of outreach activities including guided tours, educational resources for media and planetaria, and collaborations with Heidelberg University on teacher training programs for physics educators.

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Marit Kastaunمشاهده پروفایل

مدرس

University of KasselGermany

Dr. Marit Kastaun serves as Lecturer for special tasks in the Didactics of Biology at the University of Kassel since November 2023, with continuous affiliation to the department since 2013. She is a core researcher at the FLOX Teaching and Learning Laboratory and contributes to the outdoor education site Freilandlabor Dönche. Her educational background includes: First State Examination for Gymnasium Teaching (Biology/History), University of Kassel (2017) Cumulative PhD in Biology Didactics, University of Kassel (2024) Dr. Kastaun's research pioneers the integration of AI tools in biology teacher education, focusing on adaptive feedback systems for scientific hypothesis formation and diagnostic competence development. Her work bridges digital learning environments with hands-on experimentation, particularly through video-based resources and eye-tracking studies of cognitive processes during scientific inquiry. Current projects emphasize context-aware AI applications in both classroom and outdoor laboratory settings. Her funded research includes: Shift project (2023-present): AI-driven hypothesis feedback systems ProfiLL (2020-2023): Intelligent systems for teacher professionalization Digital Media Handling (2020-2022): Baseline digital competencies for biology students At the FLOX Teaching Laboratory, she develops and tests digital learning scenarios that merge theoretical knowledge with practical experimentation, with recent focus on Mimosa pudica movement studies and photosynthesis measurement techniques. Her approach emphasizes inclusive design principles for diverse learner needs in science education.

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Andreas Schmietendorfمشاهده پروفایل

استاد

Berlin School of Economics and LawGermany

Prof. Dr. Andreas Schmietendorf is a Professor of Business Informatics – System Development at the Berlin School of Economics and Law (HWR Berlin) and holds a private lectureship in Software Engineering at the Otto von Guericke University Magdeburg. He leads the Business Informatics – System Development research group and is actively involved in the HWR doctoral college and Competence Center Digitization. His research focuses on the intersection of software engineering, business informatics, and artificial intelligence, with particular emphasis on: AI-driven changes in software engineering practices Trustworthy AI implementations in domain-specific contexts Web API security and management Digital transformation through low-code development approaches Requirements engineering for trustworthy digital services Prof. Schmietendorf's recent work has centered on the TAHAI (TrustAdHocAI) research project, which investigates trustworthy ad-hoc AI solutions across multiple domains including railway infrastructure, mediation research, and forestry. His research group regularly publishes on software engineering, AI applications, and digital transformation, with a strong focus on practical industry collaborations. The group has produced numerous workshops (ESAPI, KI4SE), conference proceedings, and practical implementations that bridge academic research and industry needs. He has successfully supervised multiple PhD students to completion and maintains an active doctoral supervision portfolio. His research group collaborates extensively with industry partners, particularly Deutsche Bahn, and regularly organizes events that foster academic-industry dialogue. Prof. Schmietendorf is also active in teaching, offering courses on Service Engineering at the University of Magdeburg and various business informatics topics at HWR Berlin. His teaching emphasizes practical applications of software engineering principles and the integration of emerging AI technologies through hands-on exercises and industry-relevant case studies.

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Achim Schweikardمشاهده پروفایل

استاد

University of LübeckGermany

Prof. Achim Schweikard is a Full Professor at the University of Lübeck's Institute for Robotics and Cognitive Systems, where he has led pioneering research since 2002. His academic journey spans Stanford University's neurosurgery and computer science departments and Technical University of Munich, establishing him as a leading figure in medical technology translation. His research focuses on Medical Robotics and Artificial Intelligence with transformative clinical applications. Key achievements include inventing correlation-based tracking for cancer radiosurgery (now global standard of care) and developing stereotactic arrhythmia radioablation (STAR) protocols. Current projects address critical challenges in cardiac radioablation through the RAVENTA multicenter trial, MATRIX-VT imaging fusion study, and SonoBox robotic ultrasound system for pediatric diagnostics. His publication record shows sustained high impact with 15+ articles in 2023-2025 in top journals including Radiotherapy and Oncology and Heart Rhythm. These works demonstrate progression from foundational robotics to clinical implementation, with recent focus on cardiac motion estimation, target transfer automation, and S-ICD patient treatment solutions. As Academic Director of UNI Luebeck's Grad School (2025), he oversees doctoral training while leading the Robotics Laboratory (RobLab). The lab maintains active grants supporting: RAVENTA trial: German multicenter feasibility study for ventricular tachycardia radioablation DYNAMIC phantom development for end-to-end treatment validation ECG-gated 4D CT motion modeling for precision targeting Landmark-based ultrasound-CT fusion techniques Students gain comprehensive experience across the medical technology pipeline - from hardware prototyping to clinical trial participation - within an internationally collaborative environment spanning the STOPSTORM.eu consortium and multiple EU research networks.

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Michael Pradelمشاهده پروفایل

استاد

Max Planck Institute for Biology TübingenGermany

Michael Pradel is a full professor in the Computer Science Department at the University of Stuttgart and faculty member at CISPA Helmholtz Center for Information Security (effective September 2025), where he leads the Software Lab. He is also affiliated with the International Max Planck Research School for Intelligent Systems and the Stuttgart ELLIS Unit, reflecting his interdisciplinary research approach. His research interests focus on software engineering, particularly program analysis, bug detection, and the application of machine learning to developer tools. Pradel's recent work increasingly explores LLM-based approaches for program repair, code analysis, and automated software development, as evidenced by projects like RepairAgent and ExecutionAgent. Pradel's publication record shows a clear trend toward integrating AI techniques with traditional software engineering methods, with recent papers focusing on LLM applications for program repair, change validation, and quantum software analysis. His work bridges theoretical foundations with practical tool development, as seen in frameworks like DyLin for Python analysis and LintQ for quantum programs. Ernst-Denert Software Engineering Award Emmy Noether grant (1.3 million Euro) by the DFG ERC Starting Grant (1.5 million Euro) Multiple ACM SIGSOFT Distinguished Paper Awards ACM Distinguished Member recognition Pradel actively mentors PhD students, with recent graduates including Matteo (specializing in quantum software) and Luca (focusing on software evolution). His group has received significant funding and maintains strong industry connections, including past sabbaticals at Facebook. He serves in leadership roles for major conferences, including PC co-chair for FSE 2027, demonstrating his standing in the software engineering community. The Software Lab maintains active collaborations with institutions worldwide, including CMU, Google, KAIST, and several European universities.

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Silvia Helmreichمشاهده پروفایل

استاد

RheinMain University of Applied SciencesGermany

Dr. Silvia Helmreich serves as Professor and Head of the English Master's program "Quantitative Asset and Risk Management" at the University of Applied Sciences BFI Vienna. Her academic role centers on advanced financial education and research in banking risk frameworks. Her research expertise spans banking risk management with specific focus on credit risk, Basel III/IV regulatory requirements, and supervisory reporting mechanisms. She examines systemic risk in liquidity management and contributes to European banking supervision discourse through publications and international collaborations. Helmreich's publication history (2008-2022) reveals an evolutionary trajectory from Basel II implementation to contemporary Basel IV challenges, emphasizing regulatory reporting, stress testing, and payment system liquidity. Her work consistently bridges theoretical frameworks with practical banking applications across EU and global contexts. No scientific awards were documented in the source materials. As program head, Helmreich oversees academic development in quantitative finance while leading a research collaboration with the University of Economics in Katowice on systemic risk in liquidity management. Her current project analyzes Large Volume Payment Systems liquidity dynamics, demonstrating active engagement in cutting-edge financial stability research.

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Ulrich Eiseneckerمشاهده پروفایل

استاد

Leipzig UniversityGermany

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.

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Jens Bechtholdمشاهده پروفایل

استاد

South Westphalia University of Applied SciencesGermany

Prof. Dr.-Ing. Jens Bechthold is a Professor in the Department of Mechanical Engineering and Automation Technology at South Westphalia University of Applied Sciences (Soest campus), a position he has held since 2010. He chairs the Mechanical Engineering Examination Committee and maintains industrial collaborations through past roles at Winergy AG and Ipsen International GmbH. His affiliations include: Full-time Professor at South Westphalia University (2010-present) Former Development Engineer at Ipsen International GmbH (2007-2010) Former Calculation Engineer at Winergy AG (2006-2007) His research spans mechanical engineering , automation , and sustainable technology , with specialized focus areas: Electric mobility and automotive system design Experimental validation of simulation models Wind turbine gearbox dynamics and vibration analysis Additive manufacturing/3D printing applications He directs the Laboratory for Design Engineering and 3D Printing Lab , facilitating hands-on student projects. He actively supports the R4 Team Westfalen, a student group competing in humanitarian rally events. His 13 publications demonstrate consistent output in mechanical systems validation, CAD education, and renewable energy technology, with recent work exploring electric vehicle innovation. Professor Bechthold teaches courses including Machine Elements, Automotive Technology, Fatigue Strength, and Design for 3D Printing. He holds a European patent for industrial furnace gas processing systems.

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Andreas Wübbekeمشاهده پروفایل

استاد

South Westphalia University of Applied SciencesGermany

Prof. Dr. Andreas Wübbeke is a Professor of Software Engineering at the Faculty of Electrical Engineering, University of Applied Science Southern Westphalia (since 2022). With extensive industry experience in tech leadership roles at CLAAS E-Systems and Wincor Nixdorf, his research bridges academic rigor and practical applications. Research Focus: His work spans Agile methodologies, VR application testing, digital agriculture, and cloud systems. Recent projects include AI-driven classification of agricultural operations and sustainable energy solutions. He leads the South Westphalia Software Engineering Lab, mentoring thesis students through structured programs. Professional Engagement: Active in academic communities, he serves on committees for conferences (PROFES, GIL) and journals. His invited keynotes address topics like smart farming connectivity and agile transformations. Education & Background: PhD in Computer Science (Databases/Information Systems), University of Paderborn (2010) Business Computer Science degree, University of Paderborn (2007)

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Michael Beckمشاهده پروفایل

استاد

Hochschule Weihenstephan-TriesdorfGermany

Sustainable Horticultural Management
Water Resource Management in Agriculture
Digital Knowledge Bases for Agricultural Decision Support
+۵ مورد دیگر

Professor Michael Beck holds a HTA Professorship in Sustainable Horticultural Management at the University of Applied Sciences Weihenstephan-Triesdorf (HSWT), where he also serves as Director of the Institute of Horticulture. He is affiliated with the Department of Horticulture and Food Technology, contributing to HSWT's research focus on sustainable land use and horticultural production. His research interests span Sustainable Horticultural Management , Water Resource Management in Agriculture , Digital Knowledge Bases for Agricultural Decision Support , and LED Lighting Control in Horticulture . Professor Beck has pioneered work in developing decision support systems for nutrient management using semantic web technologies and fuzzy logic, as well as exploring energy-saving strategies through dynamic LED lighting in plant production. His recent publications demonstrate a strong trend toward digital transformation in agriculture, focusing on data integration, knowledge management, and precision farming techniques. These works consistently address practical challenges faced by farmers while incorporating cutting-edge technologies to improve sustainability and efficiency. Lead researcher on water-saving potential assessment in horticultural irrigation systems Principal investigator for projects bundling research capacities in sustainable horticulture Key contributor to Bavaria's agricultural data space initiatives Professor Beck's advisory approach centers on practical, field-tested solutions that bridge the gap between academic research and real-world agricultural challenges. His projects typically involve close collaboration with industry partners, ensuring research outcomes directly benefit farming practices. As Director of the Institute of Horticulture, he oversees research activities focused on optimizing horticultural production while maintaining environmental sustainability.

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Ali Mesbahمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Ali Mesbah is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), where he leads the SALT lab. His research focuses on software engineering with emphasis on AI-driven software analysis, software testing, and software evolution. Previously, he was a Visiting Research Scientist at Google during 2017-2018. Dr. Mesbah received his BSc/MSc (2003) and PhD (2009) degree cum laude in Computer Science from the Delft University of Technology (TUDelft). After completing a postdoctoral fellowship with the Software Engineering Research Group at TUDelft and a Visiting Researcher position at Fujitsu Laboratories of America, he joined UBC in 2011. His research interests span software engineering with particular focus on AI-driven software analysis, software testing, software evolution, program comprehension, fault localization and repair. His work has significant applications in web application testing, JavaScript analysis, and automated program repair. He has pioneered techniques for testing modern web applications, analyzing JavaScript code, and leveraging AI for software maintenance tasks. His recent publications demonstrate a clear evolution toward integrating large language models with traditional program analysis techniques, focusing on test generation, bug repair, and understanding multi-hunk patches. His work bridges theoretical software engineering concepts with practical applications, particularly in web technologies and AI-assisted development. Amazon Research Award (2023) Killam Accelerator Research Fellowship (KARF) (2020) Killam Faculty Research Prize (2019) NSERC Discovery Accelerator (DAS) award (2016) ACM Distinguished Paper Awards at ICSE (2009, 2014) IEEE Distinguished Paper Award at ICST (2018) Best Paper Award at ESEM (2015) Best Paper Award at ICWE (2013) Dr. Mesbah has advised numerous PhD and MASc students, many of whom have gone on to positions at leading technology companies including Google, Amazon, Apple, Microsoft, and SAP. His research has been supported by various grants including the Amazon Research Award and NSERC funding. He leads the SALT lab at UBC, which focuses on software analysis, testing, and learning, with current research directions including AI-driven software engineering, web application testing, and program repair. The lab maintains active collaborations with industry partners and academic institutions worldwide.

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Chang-ai Sunمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Chang-ai Sun is a full professor at the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB). He currently serves as Vice Dean of the Institute for Multidisciplinary Innovation (IMI), Head of the Department of Computer Science, and Director of the Software Engineering Institute at USTB. He received his bachelor's degree in computer science from the University of Science and Technology Beijing and his PhD in computer science from Beihang University, China. Prof. Sun's primary research focuses on software engineering with particular emphasis on software testing, program analysis, and service-oriented computing. Recently, he has been devoted to developing novel theories, techniques, and supporting tools for intelligent software development and maintenance. His work spans theoretical foundations to practical applications in software quality assurance, with increasing focus on AI-driven approaches to traditional software engineering challenges. His publication record shows consistent contributions to metamorphic testing, program repair, and the application of AI techniques to software engineering problems. Recent work explores the intersection of large language models and software testing methodologies, demonstrating both theoretical innovation and practical implementation. Prof. Sun has received significant recognition for his contributions: 11 national Software Prototype/Service Innovation Awards Senior Member of IEEE Distinguished Member of China Computer Federation (CCF) As principal investigator and major investigator, he has completed over 40 research projects funded by the European Union, Australia, China, and Hong Kong. His extensive grant portfolio demonstrates strong international collaboration and significant impact in the software engineering community. He actively mentors students and junior researchers through his leadership roles. Prof. Sun leads the Software Engineering Institute at USTB, where his team focuses on advancing research in software testing, program analysis, and intelligent software development tools. His leadership extends to departmental administration as Head of the Department of Computer Science, shaping curriculum and research directions for one of China's leading technical universities.

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Xin Xiaمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Xin Xia is a Qiushi Distinguished Professor at the College of Computer Science and Technology, Zhejiang University. Previously, he served as the Chief Expert and Director of the Software Engineering Application Technology Lab at Huawei Technologies, China from 2021 to 2025. His academic career spans software engineering research with a focus on AI applications in the field. Ph.D. from Zhejiang University (2014) Supervised by Prof. Xiaohu Yang and Prof. Jianling Sun Visiting student at Singapore Management University (2012-2014) under Prof. David Lo Xin Xia's research primarily focuses on applying data science techniques to software engineering problems. His work spans AI for Software Engineering, Mining Software Repositories, Empirical Software Engineering, and Large Language Models for code understanding and generation. He employs data mining, information retrieval, natural language processing, search-based algorithms, and program analysis to transform software engineering data into automated tools and insights. His recent publications show a strong trend toward leveraging Large Language Models for various software engineering tasks, including code generation, vulnerability detection, and test generation. He has been exploring how to make these models more effective, reliable, and practical for real-world software development scenarios, with a particular focus on Java and Python ecosystems. ACM SIGSOFT Early Career Researcher Award (2022) ACM Distinguished Member 16 best or distinguished paper awards, including nine ACM SIGSOFT Distinguished Paper Awards Recipient of the IEEE Transactions on Software Engineering 2021 Best Paper Award Runner-Up Xin Xia has advised numerous students who have gone on to publish in top software engineering venues. His research has been supported by grants from both academic institutions and industry partners, particularly during his time at Huawei. He actively collaborates with researchers worldwide, especially with David Lo at Singapore Management University. At Zhejiang University, Professor Xia leads research in the intersection of AI and Software Engineering. His work has practical applications in improving developer productivity through automated tools that analyze software repositories and provide actionable insights.

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Hui Liuمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

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.

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Shangwen Wangمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Shangwen Wang is an Assistant Professor in the School of Computer Science at National University of Defense Technology (NUDT) in Changsha, China. He earned his Bachelor's degree in June 2017, Master's degree in December 2019, and Ph.D. in December 2023, all from NUDT. During his graduate studies, he was supervised by Professor Xiaoguang Mao. From May 2022 to July 2023, he was a visiting student at Southern University of Science and Technology under Professor Yepang Liu. His educational background includes: Ph.D. in Software Engineering, NUDT (2020.3-2023.12), supervised by Prof. Xiaoguang Mao Visiting Scholar, SUSTech (2022.5-2023.7), supervised by Prof. Yepang Liu M.A. in Software Engineering, NUDT (2017.9-2019.12), supervised by Prof. Xiaoguang Mao B.A. in Software Engineering, NUDT (2013.9-2017.6) Wang's research focuses on program repair, program comprehension, mining software repositories, software maintenance and evolution, software testing, and AI for Software Engineering. His work bridges traditional software engineering techniques with modern AI approaches, particularly leveraging large language models for various software engineering tasks. He has made significant contributions to automated program repair, fault localization, vulnerability detection, and code generation. His research demonstrates a strong emphasis on empirical validation and practical applicability to real-world software development challenges. His recent publications show a clear trend toward integrating large language models with traditional software engineering tasks. The 15 most recent articles reveal a focus on applying LLMs to program repair, fault localization, vulnerability detection, and code generation, while maintaining strong empirical foundations. His work spans both theoretical advancements and practical tool development, with applications in software security, testing, and maintenance. His notable achievements include: CCF Outstanding Doctoral Dissertation (CCF优博) 2024 Outstanding Doctoral Graduates, NUDT, 2023 Multiple distinguished paper awards including ACM SIGSOFT Distinguished Paper Award (ISSTA'24) and IEEE TCSE Distinguished Paper Awards (ICSME'22, SANER'22) Prestigious scholarships from NUDT throughout his academic career As an active member of the software engineering community, Wang serves on numerous program committees for top conferences including ICSE, ASE, ESEC/FSE, and ISSTA. He has also contributed to teaching as a teaching assistant for courses such as Compiler, Python Programming, Discrete Mathematics, and C++ Programming. His research group appears to be actively mentoring students, as evidenced by his role as corresponding author on multiple student-led publications. Wang maintains an active research presence with collaborations across multiple institutions in China. His work demonstrates a clear trajectory from traditional program analysis techniques toward integrating cutting-edge AI approaches, particularly large language models, into software engineering practices.

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