Find Academic Supervisors

Thomas DemmelhuberView profile

Professor

• Middle Eastern Politics
• Authoritarianism
• Gulf Politics
• +5 more

Thomas Demmelhuber is Professor of Middle Eastern Politics and Society at Friedrich-Alexander University Erlangen-Nuremberg (FAU), holding the Chair of Middle Eastern Politics and Society at the Institute of Political Science since October 2015. He also serves as Visiting Professor at the College of Europe (Natolin) since 2015 and has held previous academic positions including Junior Professor of Political Science at the University of Hildesheim (2012-2015). Demmelhuber's research focuses on authoritarian dynamics in the Middle East, particularly examining how authoritarian regimes influence and attract neighboring states. His work spans Middle Eastern politics, Gulf monarchies, European Neighbourhood Policy, and comparative authoritarianism. He has developed the influential concept of 'Authoritarian Gravity Centers' to explain how certain regimes act as forces of attraction and contagion for countries in geopolitical proximity, examining this phenomenon across multiple regions including the Middle East, Latin America, Eastern Europe, Central Asia, and Asia. His publications reveal a consistent focus on authoritarian diffusion, Gulf politics, and the interplay between domestic political structures and international relations. Recent work increasingly examines China-Gulf relations and the strategic partnerships forming between authoritarian states. His research demonstrates how authoritarian regimes adapt and innovate through decentralization, historical narratives, and regional organizations to maintain power while influencing neighboring states. Fellow of the Bavarian Science Alliance for Peace, Conflict, and Security Research (FOKS) since 2024 Member of the academic advisory board of the Orient Institute in Beirut since 2020 Member of the research advisory board of the German Institute for International and Security Affairs (SWP) in Berlin since 2021 Board member of the German Association for the Middle East (DAVO, 2018-2025) At FAU, Demmelhuber has held numerous leadership positions including Managing Director of the Institute of Political Science (2017-2021), Chair of the Doctoral Committee of the Faculty of Philosophy (2018-2024), and currently serves as Member of the Senate and University Council since 2023. He manages the MA Middle Eastern Studies program since 2017 and the MA Political Science program since 2018, demonstrating significant commitment to academic administration and student mentoring.

Jan SeedorfView profile

Professor

• Computer Science
• IT Security
• Computer Networks

Jan Seedorf serves as a Professor at Stuttgart University of Applied Sciences, where he is integral to the Computer Science discipline through teaching and academic leadership. His responsibilities span three bachelor's programs: Computer Science, Business Information Systems, and Augmented Reality / Virtual Reality Engineering, reflecting a commitment to multidisciplinary technical education. His research and teaching focus centers on critical infrastructure domains: IT Security encompasses cryptographic systems, threat mitigation, and secure protocol design, while Computer Networks addresses modern architectures, wireless transmission, and network optimization. These areas directly respond to evolving digital security challenges and communication demands in enterprise environments. Professor Seedorf maintains dedicated student engagement through Wednesday office hours (10:00-11:00 AM) and appointment-based consultations, supporting academic development across all enrolled bachelor's cohorts. His structured availability underscores an advisor role focused on practical application of theoretical concepts in rapidly advancing technological fields.

Jiachi ChenView profile

Associate Professor

• Software Security
• Program Analysis
• Smart Contracts
• +4 more

Jiachi Chen is an Associate Professor at the School of Software Engineering, Sun Yat-sen University, China. He received his Ph.D. from Monash University, Australia, and has established himself as a leading researcher in blockchain security and Web3 technologies. His educational background includes: Ph.D. in Information Technology from Monash University (2019-2022) Research Assistant at Hong Kong Polytechnic University (2016-2018) Dr. Chen's research spans software security, program analysis, smart contracts, and Web3 technologies. His work bridges traditional software engineering with blockchain, focusing on security vulnerabilities, large language models for code generation, and empirical studies of smart contract development. Recent publications show increasing integration of AI techniques to address blockchain security challenges. His publication trends reveal deep expertise in smart contract security, with numerous papers on vulnerability detection and code analysis. Recent work has expanded into LLM applications for software engineering, particularly examining code generation quality and security implications in Web3 contexts. Dr. Chen has received significant recognition: Multiple ACM SIGSOFT Distinguished Paper Awards (ICSE 2025, ISSTA 2024, Internetware 2024) Best Paper Award at IEEE CSCloud/EdgeCom 2023 Best Paper Award at IEEE INFOCOM 2018 Best Paper Award at ISPEC 2017 He serves on program committees for top software engineering conferences (ICSE, FSE, ASE, ISSTA) and is actively recruiting students in Web3/Blockchain/Smart Contract research areas. His work appears consistently in premier venues including IEEE Transactions on Software Engineering and ACM conferences, demonstrating sustained research impact.

Ajay JhaView profile

Assistant Professor

• Software Engineering
• Software Testing
• Software Maintenance
• +4 more

Ajay Jha is an Assistant Professor in the Department of Computer Science at North Dakota State University (NDSU), where he leads the Software Testing and Maintenance (STAM) Lab. His academic journey began with industry experience, followed by graduate studies and postdoctoral research that shaped his current focus on software engineering research. His educational background includes: Ph.D. in Computer Science from Kyungpook National University (2017) Master's degree from Kyungpook National University (2013) Over five years of industry experience before graduate studies, including co-founding two startups Postdoctoral research at University of Alberta (over two years) and Kyungpook National University (three years) Dr. Jha's research focuses on software engineering, particularly in the areas of software testing, maintenance, and evolution. His work centers on mining large-scale software repositories to uncover real-world issues in software quality, reliability, and maintainability. He develops innovative tools and techniques to address challenges in regression testing, library migration, and mobile application development. His research has significant practical implications for improving software development processes and enhancing the reliability of modern software systems, particularly in mobile and Python environments. His publication record shows a clear progression from Android-focused research to broader software engineering challenges, with recent work emphasizing Python library migration and large language models for software engineering tasks. His research methodology typically involves empirical studies of real-world software repositories combined with tool development to address identified challenges. Dr. Jha is actively involved in academic service, serving on program committees for major software engineering conferences including MSR, ICSME, SANER, ASE, and ICSE. He also reviews for prestigious journals such as IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology. At NDSU, he teaches a range of courses from undergraduate to graduate level, including Mobile Software Engineering, Software Development Processes, and Software Project Planning and Estimation. He also leads graduate seminars on specialized topics like 'LLMs for Software Testing and Maintenance' and 'Code Smell and Refactoring.' He leads the Software Testing and Maintenance (STAM) Lab at NDSU, which focuses on mining software repositories to identify quality issues and developing practical tools to address software maintenance challenges. The lab's research has produced several benchmarks (PyMigBench, JTestMigBench) and tools (TRec) that have been shared with the research community.

Xiang ChenView profile

Associate Professor

• Empirical Software Engineering
• Mining Software Repositories
• Software Testing and Maintenance
• +5 more

Xiang Chen is an Associate Professor at the Department of Software Engineering, School of Artificial Intelligence and Computer Science, Nantong University, China. He received his B.Sc. degree from Xi'an Jiaotong University in 2002 and his M.Sc. and Ph.D. degrees in computer software and theory from Nanjing University in 2008 and 2011 respectively. He is an editorial board member of Information and Software Technology and serves as a program committee member for prestigious conferences including FSE 2026 and ASE 2025. Chen is also a senior member of the China Computer Federation (CCF) and active in various academic committees. Chen's research focuses on empirical software engineering, mining software repositories, and software testing and maintenance, with particular emphasis on applying AI techniques to software engineering problems. His work spans large language models for software engineering, security vulnerability analysis, code change representation, and regression testing. He has published over 110 papers in top-tier journals and conferences including IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology. His recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models, with traditional software engineering practices. The research spans code generation evaluation, deep learning framework testing, vulnerability detection, and automated program repair, showing a consistent focus on improving software quality through innovative testing and analysis techniques. ACM SIGSOFT Distinguished Paper Award (ICSE 2021) ACM SIGSOFT Distinguished Paper Award (ICPC 2023) Top 1% CNKI Highly Cited Scholar (2024) Top 2% Scientist by Stanford University (2023-2025) NASAC 2019 Prototype Competition First Prize Chen has successfully advised numerous graduate and undergraduate students who have gone on to prestigious institutions including Nanjing University, Tsinghua University, and Zhejiang University. Many of his students have won national programming competitions and received scholarships. His research group, smartSE, actively works on projects funded by the Natural Science Foundation of China and various provincial research programs. Chen also serves as a reviewer for top journals including IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology.

Fang LiuView profile

Assistant Professor

• Software Engineering
• Artificial Intelligence for Software Engineering
• Program Understanding
• +3 more

Fang Liu is an Assistant Professor at the School of Computer Science & Engineering, Beihang University, China. She has made significant contributions to the field of software engineering, particularly in the intersection of artificial intelligence and software development practices. Dr. Liu received her Ph.D. in Computer Science from Peking University (Sep. 2017 - Jul. 2022), supervised by Prof. Zhi Jin and Prof. Ge Li. Prior to that, she earned her B.S. in Computer Science from Chongqing University (Sep. 2013 - Jul. 2017). Her research interests focus on AI for Software Engineering, including program understanding and generation, program repair, and applications of Large Language Models to software development tasks. Dr. Liu teaches Compiler Technology as a compulsory course at Beihang University (Fall 2024) and Programming in Cangjie Language as an elective course (Spring 2025). Her recent publications demonstrate a clear trend toward leveraging large language models for various software engineering tasks, with a particular emphasis on code editing, program repair, and code translation. Her research spans both theoretical advancements in model architectures and practical applications to real-world software development challenges, with numerous publications in top-tier venues like ASE, ICSE, and FSE. Distinguished Paper Award at ICPC'20 for "A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning" Dr. Liu actively participates in the software engineering research community as a program committee member for major conferences including ASE, FSE, and ICSE. Her work has significant implications for improving developer productivity, software quality, and the integration of AI technologies into the software development lifecycle.

Michael PradelView profile

Professor

• Software Engineering
• Programming Languages
• Program Analysis
• +6 more

Michael Pradel is a full professor at the University of Stuttgart and a faculty member at the CISPA Helmholtz Center for Information Security. He leads the Software Lab at the University of Stuttgart and holds additional affiliations with the International Max Planck Research School (IMPRS) for Intelligent Systems and the Stuttgart ELLIS Unit. Previously, he served as an assistant professor at TU Darmstadt, a postdoctoral researcher at UC Berkeley, and a lecturer and postdoctoral researcher at ETH Zurich, where he completed his PhD. His educational background includes computer science studies at TU Dresden and engineering studies at Ecole Centrale Paris, with a master's thesis conducted at EPFL. He has taken sabbaticals at Facebook, UC Berkeley, and UCLA. Pradel's research spans software engineering, programming languages, security, and machine learning, with a focus on tools and techniques for building reliable, efficient, and secure software. He is particularly interested in neural-symbolic software analysis, analyzing web applications, dynamic analysis, and test generation. His recent work increasingly incorporates large language models for software engineering tasks including bug detection, test generation, and program repair. His research group has produced significant work in WebAssembly analysis, Python dynamic analysis, quantum program analysis, and automated program repair, with notable tools including Wasm-R3, DynaPyt, LintQ, and RepairAgent. Ernst-Denert Software Engineering Award Emmy Noether grant by the German Research Foundation (DFG) (1.3 million Euro) ERC Starting Grant (1.5 million Euro) Best/Distinguished Paper Awards at FSE (3x), ISSTA, ASE, ASPLOS, and MSR ACM Distinguished Member Multiple ACM SIGSOFT Distinguished Paper and Artifact Awards Pradel has advised numerous PhD students including Matteo (thesis on "Testing and Analysis of Quantum Software"), Luca (thesis on "Supporting Software Evolution via Search and Prediction"), and Daniel (thesis on program analysis for WebAssembly). His research has been supported by significant grants including the Emmy Noether grant and ERC Starting Grant. He serves in leadership roles for major conferences including PC co-chair for FSE 2027 and area chair for ICSE 2026. Pradel leads the Software Lab at the University of Stuttgart, which includes visiting professors Cristian Cadar and Prem Devanbu (both supported by Humboldt Research Awards). The lab maintains active collaborations with institutions including CMU, Google, KAIST, and USI Lugano, and regularly contributes to major software engineering conferences.

Jongmoon BaikView profile

Professor

• software process modeling
• software economics
• software reliability engineering
• +1 more

Jongmoon Baik serves as a Professor at the Korea Advanced Institute of Science and Technology (KAIST), School of Computing, South Korea, and maintains active membership in IEEE and ACM professional organizations. His academic foundation includes a PhD in Computer Science from the University of Southern California, establishing expertise in rigorous software engineering methodologies. Professor Baik's research program centers on software process modeling, software economics, software reliability engineering, and software Six Sigma, with emphasis on quantifying development efficiency and product quality through statistical process control. His work bridges theoretical modeling with industrial application in software lifecycle optimization. Current research trajectories demonstrate growing integration of security analysis into process modeling, exemplified by his upcoming ASE 2025 publication on vulnerability detection using modifiability signals at the line-level code analysis. Professional recognition includes sustained engagement with premier software engineering venues through conference participation and publications. He advises graduate researchers within KAIST's School of Computing and leads the Software Process Research Laboratory (SPIRAL), identifiable through his institutional web presence at spiral.kaist.ac.kr, focusing on empirical studies of software development economics and reliability metrics.

Petra BendelView profile

Professor

• Migration Policy
• Refugee Studies
• EU Asylum Policy
• +5 more

Petra Bendel is Professor of Political Science at Friedrich-Alexander-Universität Erlangen-Nuremberg (FAU), where she serves as Academic Director of the Central Institute for Regional Research and Deputy Director of FAU's Center for Human Rights Erlangen-Nuremberg (CHREH). She holds influential policy positions including Chair of the Expert Council of German Foundations on Integration and Migration (SVR), Chair of the Scientific Advisory Board of the Federal Office for Migration and Refugees (BAMF), and Member of the German Federal Government's expert commission on "Framework Conditions and Capacity for Integration." Her research focuses on EU asylum and refugee policy, German refugee policy at national and local levels, integration policy, and human rights of refugees and migrants. Bendel examines migration governance through multiple political levels, analyzing tensions between EU policy frameworks and their human rights implications. Her work often addresses the practical implementation challenges of migration policies in diverse political contexts. Analysis of Bendel's publication record reveals consistent scholarly contribution since the 1990s, with recent work increasingly focused on pandemic impacts on migration systems, municipal-level integration approaches, and sustainable solutions for displacement. Her research bridges academic analysis with practical policy recommendations, particularly regarding EU burden-sharing mechanisms and local implementation of integration policies. Bendel leads multiple research projects examining displacement, migration, and integration across political levels. Her institutional leadership positions demonstrate significant influence in shaping German and European migration policy discourse. The empirical focus on 92 municipalities across 12 German states in her 2020 work "Zwei Welten? Integrationspolitik in Stadt und Land" exemplifies her commitment to evidence-based policy analysis.

Soha HusseinView profile

Assistant Professor

• program analysis
• fuzzing
• symbolic execution
• +4 more

Soha Hussein is an Assistant Professor at Ain Shams University in Egypt. She is actively involved in the software engineering research community, serving in various roles including Publication Co-chair for ASE 2025 and Posters/Tools/SRC Co-Chair for SPLASH/ISSTA 2026. Dr. Hussein received her Ph.D. and M.S. in Computer Science from the University of Minnesota. She also completed the Early Career Teaching and Learning program and the Prepare Future Faculty program at the University of Minnesota, demonstrating her commitment to both research and education. Her research focuses on enhancing software reliability and security through advanced program analysis techniques. Specifically, she specializes in symbolic execution, fuzzing, formal verification, and software testing. Her work addresses the critical challenge of path explosion in symbolic execution through innovative path-merging approaches. Dr. Hussein's research has practical applications in verifying Java programs and improving automated program verification techniques, with recent work extending to AWS Lambda applications. Her publications demonstrate a consistent trajectory of advancing verification techniques while maintaining strong theoretical foundations. Dr. Hussein has received multiple prestigious awards for her work on Java Ranger, including Gold Medals at SV-COMP 2020, 2021, and 2025, as well as a Bronze Medal at SV-COMP 2020. These awards recognize the effectiveness of her path-merging approach in reducing path explosion and improving verification efficiency. She is actively involved in mentoring students, particularly through the Google Summer of Code program where she serves as an organization admin and mentor for the Java Pathfinder (JPF) Organization. Dr. Hussein encourages excellent students to reach out for research opportunities in her lab, having successfully mentored students like Kunha Kim who accepted a Master scholarship at University of Colorado Boulder. Dr. Hussein leads research related to Java Ranger, an extension to Symbolic Pathfinder that implements path-merging techniques for Java verification. Her team continues to advance this work, with recent developments supporting string and array operations and applying the technology to AWS Lambda applications. She maintains active contributions to the SymbolicPathFinder/jpf-symbc repository on GitHub, demonstrating her commitment to open-source verification tools.

Diego GarbervetskyView profile

Associate Professor

• Static analysis
• Program verification
• Smart Contract analysis
• +5 more

Diego Garbervetsky is an Associate Professor at the Computer Science Department, School of Sciences, University of Buenos Aires, and a Researcher at ICC/CONICET. He also serves as Director of the Institute of Research in Computer Sciences (ICC). His academic career spans multiple roles in software engineering research and education. His educational background is not explicitly stated in the provided texts, but his current position reflects extensive academic achievement. Garbervetsky's research focuses on static analysis techniques for Java-like programs and Smart Contracts, automated program verification , program understanding , and validation . His specific interests include program understanding, testing and verification of programs featuring rich protocols, static analysis for program verification, and automatic symbolic resource analysis (gas consumption, dynamic memory, energy, etc.). His research has significant implications for blockchain technology, particularly in smart contract verification. Analysis of his recent publications reveals a strong trend toward smart contract security and verification , with multiple papers on modal abstractions, predicate abstractions, and tools like VeriSol for Solidity smart contracts. His work bridges formal methods with practical software engineering challenges, particularly in the blockchain domain. His scientific contributions include the development of multiple research tools: Contractor: Automated tool for behavior validation Contractor.NET: Visual Studio extension for .NET validation JConsume2: Compositional analysis for Java heap memory Consume.Net: Compositional analysis for .NET heap memory BudaPest: Automated software verifier VInTime: Verification suite for Real Time systems Garbervetsky has supervised numerous PhD students including Daniel Wappner, Javier Godoy, and Alexis Soifer, with former students now working at companies like Microsoft, Veritran, and Dialpad. He has served on program committees for major conferences including ICSE, FSE, ASE, and ISSTA, demonstrating his standing in the software engineering research community. His service includes chairing workshops and serving on artifact evaluation committees, showing his commitment to research quality and reproducibility. He currently teaches Software Engineering 2 at the University of Buenos Aires, having previously taught courses in algorithms, automatic software validation, program analysis, programming paradigms, and computer organization.

Lei BuView profile

Professor

• Software Verification
• Software Testing
• Software Analysis
• +8 more

Lei Bu is a Professor and Vice Dean of the Software Institute at Nanjing University, China. He has been with Nanjing University since 2010, progressing from Assistant Professor to his current position. His academic career includes a visiting position at Microsoft Research Asia through their StarTrack Program from 2014-2015. Professor Bu received his B.Sc. and Ph.D. degrees in Computer Science from Nanjing University, with additional research experience at Carnegie Mellon University and University of Texas at Dallas during his doctoral studies. His academic journey shows steady progression through the ranks at his alma mater. Lei Bu's research primarily focuses on software verification, testing, and analysis, with particular expertise in model checking, bounded model checking, formal methods, and cyber-physical systems. His work spans theoretical foundations to practical applications in safety-critical systems. Recent publications demonstrate growing interest in integrating machine learning techniques with traditional formal methods, as seen in works like SpecGen that leverage large language models for program specification generation. His research outputs show a consistent focus on verification techniques for complex systems, particularly addressing challenges in hybrid systems, cyber-physical systems, and IoT applications. Professor Bu has developed several verification tools including BACH (Bounded Reachability Checker for Linear Hybrid Automata) and BRICK (Bounded Reachability Checker of Numerically-Intensive C Code), which have been used in international verification competitions. 2023: Zhongchuang Software Talent Award 2022: CCF-IEEE CS Young Computer Scientist Award 2020: The Outstanding Teachers of Computing in Higher Education Award Program 2019: NASAC Young Software Innovation Award 2016: Young Talent Development Program 2014: StarTrack Program Visiting Young Faculty 2007: Full Scholarship under the State Scholarship Fund Professor Bu serves as a Principal Investigator on multiple significant research projects funded by the Natural Science Foundation of China, including a Key Program grant (2023-2027) on dynamic adjustment-control-fault tolerance theory. He has also advised numerous students and taught courses including Formal Languages and Automata, Theoretical Foundation of Software Engineering, and Preliminary Introduction to the Theory of Computation. His laboratory work focuses on developing practical verification tools for industrial applications in cyber-physical and IoT systems.

Mingwei LiuView profile

Associate Professor

• Software Engineering
• Artificial Intelligence
• AI4SE
• +4 more

Dr. Mingwei Liu is an Associate Professor at the School of Software Engineering, Sun Yat-Sen University, China. Previously, he completed postdoctoral research at Fudan University in 2024 and received both his Ph.D. (2022) and B.E. (2017) in Software Engineering from Fudan University under the mentorship of Xin Peng. Dr. Liu's research focuses on the intersection of Software Engineering (SE) and Artificial Intelligence (AI), specifically in the domains of AI4SE (AI for Software Engineering) and SE4AI (Software Engineering for AI). His primary interest lies in leveraging advanced AI technologies, particularly large language models (LLMs) and knowledge graphs (KGs), to address complex software engineering challenges and tackle system engineering problems in AI applications. His research portfolio demonstrates a strong focus on practical applications of AI in software development, with particular emphasis on code generation, vulnerability detection, test generation, and knowledge representation for software artifacts. Through his work, Dr. Liu has contributed significantly to understanding how LLMs perform in realistic software development scenarios beyond simple function-level code generation. Dr. Liu has published over twenty papers in top international journals and conferences including TSE, TOSEM, ICSE, FSE, and ASE. His research has been recognized with prestigious awards including the IEEE TCSE Distinguished Paper Award (ICSME 2018) and the ACM SIGSOFT Distinguished Paper Award (FSE 2023). IEEE TCSE Distinguished Paper Award (ICSME 2018) ACM SIGSOFT Distinguished Paper Award (FSE 2023) Dr. Liu actively contributes to the academic community as a program committee member for major conferences including ASE, ESEC/FSE, ICSME, and SANER. He leads the SYSUSELab research group, which has developed notable resources including the ClassEval benchmark for evaluating LLMs on class-level code generation tasks.

Dan HaoView profile

Professor

• software testing
• debugging
• program comprehension
• +7 more

Professor Dan Hao is a distinguished faculty member at the Institute of Software, School of Computer Science, Peking University, where he has established himself as a leading researcher in software engineering. His extensive service to the academic community includes membership on the Steering Committee for The International Conference on Automated Software Engineering (ASE) since 2021, The ACM SIGSOFT International Symposium on Software Testing and Analysis since 2025, and The International Systems and Software Product Line Conference (SPLC) from 2018-2022. He has served as Program Co-Chair for multiple major conferences including ISSTA 2027, ICSME 2025, ICST 2023, SANER 2022, and ASE 2021. Professor Hao received his Bachelor's degree from Harbin Institute of Technology in 2002 and completed his Ph.D. at Peking University in 2008, followed by post-doctoral research at the same institution until 2009. His academic journey reflects a deep commitment to advancing software engineering research and education in China. Professor Hao's research primarily focuses on software testing and debugging, program comprehension, and software maintenance. His work has significantly contributed to compiler testing, fault localization, regression testing, and automated program repair. He has pioneered approaches in compiler auto-tuning, test-case prioritization, and history-guided testing techniques. His research bridges theoretical foundations with practical applications, addressing real-world challenges in large-scale software systems, particularly in online service environments. His publication record demonstrates a consistent trajectory of high-impact research in top-tier software engineering venues. Professor Hao's work shows increasing integration of machine learning techniques with traditional software engineering problems, particularly evident in his recent publications on LLM applications for code generation, neural theorem proving, and contrastive learning for vulnerability detection. His research maintains strong connections between theoretical rigor and practical applicability in industrial settings. ACM SIGSOFT Distinguished Paper Award for PDCAT: Preference-Driven Compiler Auto-Tuning at FSE 2025 Distinguished Paper Award for Formalizing, Mechanizing, and Verifying Class-Based Refinement Types at ECOOP 2024 ACM SIGSOFT Distinguished Paper Award for History-Guided Configuration Diversification for Compiler Test-Program Generation at ASE 2019 ACM SIGSOFT Distinguished Paper Award for History-driven Build Failure Fixing: How Far Are We? at ISSTA 2019 As an advisor, Professor Hao has mentored numerous graduate students, currently supervising 9 Ph.D. students and 7 Master's students. His former students have gone on to prestigious positions at institutions including King's College London, Tianjin University, Fudan University, and major technology companies like Huawei and China Construction Bank. His academic leadership extends through editorial roles as Deputy Editor-in-Chief of Software Testing, Verification and Reliability (STVR) and membership on the editorial boards of several premier journals including ACM Transactions on Software Engineering and Methodology, ACM Computing Surveys, and Empirical Software Engineering. Professor Hao leads a vibrant research group at Peking University's Institute of Software, focusing on cutting-edge problems at the intersection of traditional software engineering and artificial intelligence. His team actively collaborates with both academic institutions and industry partners to address practical challenges in software development and maintenance processes.

Lili WeiView profile

Assistant Professor

• Software Analysis
• Software Testing
• Code Repository Mining
• +6 more

Lili Wei is an Assistant Professor in the Department of Electrical and Computer Engineering at McGill University's Faculty of Engineering. She specializes in software engineering research with a focus on Android applications, smart contracts, and IoT software. Prior to joining McGill, she completed her PhD at HKUST under Prof. S.C. Cheung and was a Postdoctoral Fellow in the CASTLE group at HKUST, receiving the Hong Kong Research Grant Council Postdoctoral Fellowship. Her research interests center on software analysis, testing, and mining code repositories, particularly addressing compatibility issues in Android applications, security vulnerabilities in smart contracts, and testing methodologies for mobile software. She has made significant contributions to understanding and solving fragmentation-induced compatibility issues in Android apps, which has been a persistent challenge for developers due to the diverse ecosystem of Android devices and OS versions. Dr. Wei's publication record shows a consistent trajectory of impactful research in top software engineering venues including ASE, ICSE, FSE, ISSTA, and IEEE Transactions on Software Engineering. Her recent work has expanded into blockchain security with a focus on front-running vulnerabilities in smart contracts. Her research combines empirical studies with practical tool development to address real-world software engineering challenges. Peter Silvester Faculty Research Award in Electrical & Computer Engineering (McGill University) Distinguished Reviewer (ASE 2022) Hong Kong RGC Postdoctoral Fellowship Scheme (2020) ACM SIGSOFT Distinguished Artifact Award (ICSE 2019) Google PhD Fellowship (in Mobile Computing, 2018) Microsoft Research Asia PhD Fellowship (2018) ACM SIGSOFT Distinguished Paper Award (ASE 2016) Dr. Wei has been actively involved in the academic community, serving on program committees for major software engineering conferences including ICSE, ASE, FSE, ISSTA, and MOBILESoft. She has held leadership roles such as Tutorials Track Chair for ASE 2023, PC Chair for MOBILESoft 2023, and is currently seeking PhD students interested in software engineering research, particularly in program analysis, test generation, and mobile computing. Her teaching at McGill includes ECSE 250: Fundamentals of Software Development, ECSE 321: Introduction to Software Engineering, and ECSE 688: Automated Software Testing and Analysis.