Find Academic Supervisors

Sridhar ChimalakondaView profile

Associate Professor

• Software Engineering
• Educational Technologies
• Human Computer Interaction
• +11 more

Dr. Sridhar Chimalakonda serves as Associate Professor and Head of the Department of Computer Science & Engineering at the Indian Institute of Technology Tirupati, with an adjunct appointment as Associate Professor at the University of Waterloo. His academic leadership spans software engineering research and educational innovation. His educational qualifications include: Ph.D. from International Institute of Information Technology Hyderabad, India MS by Research from International Institute of Information Technology Hyderabad, India Research expertise encompasses: Software Engineering : Empirical studies, quality assurance, reuse methodologies, product lines, architecture, ontologies, and gamification Educational Technologies : Instructional design optimization, personalized learning systems, and VR/AR applications for educational storytelling and laboratories Human Computer Interaction : User-centered design in educational and software development contexts Publication analysis (2021-2024) reveals a strategic evolution from foundational software engineering research toward integrated educational applications, particularly in gamified machine learning education for K-12 audiences and sustainable software practices. His work demonstrates consistent methodological rigor in empirical studies while expanding into cross-disciplinary educational technology innovation.

Matteo CamilliView profile

Associate Professor

• Software Engineering
• Software verification
• Automated testing
• +4 more

Matteo Camilli is an Associate Professor in the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano, Italy, where he leads research in software engineering and verification. His academic journey includes positions as Assistant Professor at Free University of Bozen-Bolzano and postdoctoral research at the University of Milan and University of Bergamo. His educational background includes a PhD in Computer Science (2015), MSc in Computer Science (2012), and BSc in Computer Science (2009), all from the University of Milan. His doctoral research focused on combining advanced abstraction techniques and big data approaches to address state explosion problems in formal verification. Camilli's research primarily centers on software verification, testing, and methods to improve dependability of autonomous, cyber-physical, service-based, and ML-enabled critical systems. His work spans formal methods, model-based testing, uncertainty quantification, and design-time/runtime verification with applications to complex distributed systems. His recent publications reflect a growing focus on explainable self-adaptation, quality assurance for LLM-based systems, and managing uncertainty in adaptive systems. His publication record includes papers in top journals (TOSEM, TAAS, JSS, EMSE) and conferences (ICSE, ISSRE, ICST, ICSA). He serves on program committees for prestigious conferences including ICSE, ICSA, ICST, and ECSA, and is on the steering committee for the International Workshop on Formal Approaches for Advanced Computing Systems (FAACS). Camilli actively contributes to the academic community through conference organization, including serving as Program Committee Member for numerous conferences and as Program Co-Chair for the Software Architecture track at ACM SAC. He also serves as guest editor for special issues on automated testing and dependable AI systems. His teaching portfolio at Politecnico di Milano includes Software Engineering 2, Software Engineering for Automation, and Distributed Software Development. Previously at Free University of Bozen-Bolzano, he taught Systems Engineering and Verification and Reliability for Dependable Systems.

Istvan DavidView profile

Assistant Professor

• Digital Twins
• Model-Driven Engineering
• Sustainability
• +7 more

Istvan David is an Assistant Professor of Software Engineering at McMaster University's Faculty of Engineering, Department of Computing and Software, where he leads the Sustainable Systems and Methods Lab (SSM) and works as a researcher in the McMaster Centre for Software Certification (McSCert). His work bridges the gap between model-driven engineering, digital twins, and sustainability in systems engineering. Dr. David's research interests focus on digital twins , model-driven engineering , sustainability in computing, cyber-physical systems , and collaborative modeling . His lab develops novel reinforcement learning techniques , digital twin architectures , and modeling and simulation methods with a strong emphasis on sustainability as both a system characteristic and an engineering principle. His recent publications reveal a strong trend toward integrating digital twin technology with sustainability concerns, particularly in automotive systems, smart farming, and resource-efficient software engineering. The research spans from foundational modeling techniques to applied solutions addressing the four essential sustainability dimensions of technical systems: technical (long-term usage), economic (financial viability), environmental (reduced impact), and social (elevated utility). Scientific Awards: Best Practice Paper Award at MODELS Best Paper 2024 Runner-up in the Journal of Computer Languages Dr. David actively mentors students including PhD candidate Xiaoran (Sharon) Liu, and has supervised undergraduate researchers like Adwita Kashyap and Kyanna Dagenais. He has secured multiple research grants supporting work on sustainable systems and digital twin technologies, with applications in automotive engineering, smart farming, and resource-efficient computing. His lab collaborates with industry partners and academic institutions worldwide, including VU Amsterdam and University of Montréal. The Sustainable Systems and Methods Lab focuses on the vision of 'sustainable systems by sustainable methods,' addressing the growing problem of unsustainable systems engineering practices. The lab's work on bipartite sustainability aims to both build sustainable systems and develop systems using sustainable methods.

Antonio FilieriView profile

Visiting Associate Professor

• Static analysis
• Privacy
• Automated test generation
• +5 more

Antonio Filieri is a Senior Applied Scientist at Amazon Web Services (AWS) and holds a Visiting Associate Professor position at the Department of Computing, Imperial College London. Previously, he was a tenured Associate Professor at Imperial College London (2022-2024) and Assistant Professor (2016-2022), and served as Assistant Professor at the University of Stuttgart between 2013 and 2015. His academic career spans over a decade with significant contributions to software engineering research. Dr. Filieri's research focuses on formal mathematical methods for software design, verification, self-adaptation, and security. His primary research areas include static analysis, privacy, and automated test generation for security; exact and approximate methods for probabilistic program analysis; control theory for adaptive software; quantitative verification and model checking; and runtime-efficient and incremental verification. His work bridges theoretical foundations with practical applications in industry settings, particularly in cloud computing and security domains. His recent publications demonstrate a strong focus on probabilistic methods for software analysis, security testing, and performance modeling. The research trends show increasing integration of formal methods with machine learning techniques, particularly in test oracle generation and neural network analysis. There's also a clear emphasis on scalability and practical applicability of verification techniques to real-world systems like serverless computing and microservices architectures. Dr. Filieri has received numerous prestigious awards for his contributions: Best Student Paper Award (2025) for 'Robust Probabilistic Model Checking with Continuous Reward Domains' ACM Distinguished Paper Award (2023) for 'Sibyl: Improving Software Engineering Tools with SMT Selection' Best Paper Award (2022) for 'Enhancing Performance Modeling of Serverless Functions via Static Analysis' Best Artifact Award (2017) for 'Self-adaptive video encoder: comparison of multiple adaptation strategies made simple' Most Influential Paper Award (awarded at SEAMS 2025) for 'Software Engineering Meets Control Theory' ACM SigSoft Distinguished Paper Award (2011) for 'Run-time Efficient Probabilistic Model Checking' Dr. Filieri has advised several PhD students including Donato Clun (2024), Runan Wang (2024), and Xiaotong Ji (expected 2025). His advising focuses on probabilistic program analysis, automated testing, and security verification. His research has been supported by significant grants from both academic and industry sources, enabling collaborations across multiple institutions and contributing to advancements in software engineering practices. While specific lab information isn't prominently featured in the provided materials, Dr. Filieri's work suggests strong connections with research groups focused on formal methods, software verification, and adaptive systems at both Imperial College London and AWS. His research often involves interdisciplinary collaboration between theoretical computer science and practical software engineering challenges.

Xiang GaoView profile

Associate Professor

• Program Analysis
• Software Security
• Automated Program Repair
• +4 more

Xiang Gao is a Pre-tenure Associate Professor in the School of Software at Beihang University, China. His research focuses on applying program analysis, test generation, and formal methods to improve software quality through automated bug fixing and program synthesis. He has established significant collaborations with Fujitsu Laboratories of America, Microsoft Research, and other leading institutions in the software engineering field, demonstrating strong industry-academia connections. Dr. Gao received his Bachelor's degree in Computer Science (Elite Class) from Shandong University in 2016, followed by a Ph.D. from the School of Computing at the National University of Singapore, where he also served as a Postdoctoral Fellow until December 2021. His educational background spans both Chinese and Singaporean academic institutions, providing him with a global perspective on software engineering research. His primary research interests span multiple cutting-edge areas of software engineering: Program Analysis techniques for detecting and fixing software bugs with formal methods Software Security vulnerabilities with focus on automated repair methods Automated Program Repair systems that generate high-quality patches without overfitting Program Synthesis for creating transformation rules from examples Software Engineering for Artificial Intelligence (SE4AI) to improve AI model reliability and security Mobile Software Engineering with particular attention to UI testing and automation Deep Learning Security including model protection and obfuscation techniques Dr. Gao's recent publication trajectory shows a strategic evolution toward integrating large language models with traditional software engineering approaches, particularly in test generation and program repair. His work on DNN modularization (NeMo, CNNSpliter, SeaM) represents an innovative approach to enhancing model reusability and security in resource-constrained mobile environments, addressing critical challenges in deploying AI on edge devices. His scientific contributions have been recognized with multiple prestigious awards: ACM SIGSOFT Distinguished Paper Award for "ProveNFix: Temporal Property guided Program Repair" at FSE'24 IEEE TCSE Distinguished Paper Award for "Investigating and Detecting Silent Bugs in PyTorch Programs" at SANER'24 ACM SIGSOFT Distinguished Paper Award for "Modularizing while Training: A New Paradigm for Modularizing DNN Models" at ICSE'24 Distinguished Artifact Award for "Automated Patch Backporting in Linux (Experience Paper)" at ISSTA'21 Dr. Gao actively mentors students at various levels, seeking "self-motivated Ph.D, master, undergraduate students and interns with strong programming skills" for his research projects. He serves on numerous program committees for top software engineering conferences including ICSE, ASE, ISSTA, and FSE, demonstrating his growing influence in the academic community. His research has been supported through collaborations with industry partners including Microsoft Research and Fujitsu Laboratories of America, translating theoretical advances into practical applications. His laboratory focuses on several key research projects including Automated Software Vulnerability Repair (with techniques like Fix2Fit, VulnFix, and ExtractFix that address the overfitting problem in program repair), Program Synthesis for Program Transformation (including Semi-supervised synthesis and FixMorph for automated patch backporting in Linux), and Software Engineering for Artificial Intelligence (with projects like CNNSpliter, SeaM, and Sensei that apply software engineering principles to improve AI model usability and robustness). These projects represent cutting-edge work at the intersection of traditional software engineering and modern AI techniques, addressing critical challenges in software reliability and security.

Fuyuki IshikawaView profile

Associate Professor

• Software Engineering
• Testing
• Formal Methods
• +4 more

Fuyuki Ishikawa is an Associate Professor at the Information Systems Architecture Science Research Division of the National Institute of Informatics (NII) in Tokyo, Japan, where he also serves as Director of the GRACE Center. Additionally, he holds positions as Associate Professor at Sokendai (The Graduate University for Advanced Studies) and Visiting Associate Professor at The University of Electro-Communications. His research program, which he describes as 'Trustworthy & Smart Software Engineering,' focuses on dependability in Cyber-Physical Systems and Machine Learning Systems through techniques of formal methods and automated test generation. He investigates verification, reasoning, optimization, automated test generation, and self-adaptation by utilizing various models for requirements, specifications, and designs. His group promotes international and industry-academia collaborations with members from different organizations. Ishikawa's recent work has increasingly concentrated on quantum program testing, autonomous driving systems verification, and quality assurance frameworks for AI systems. His publications demonstrate significant contributions to software engineering, particularly in applying formal methods to emerging domains like quantum computing and machine learning. His research often bridges theoretical foundations with practical applications in safety-critical contexts, particularly for autonomous systems. Awards for Science and Technology (Research Category) from the Minister of Education, Culture, Sports, Science and Technology (April 2024) IPSJ/IEEE Computer Society Young Researcher Award for 'Research on Intelligence-driven Engineering of Dependable Smart Systems' (March 2020) Multiple Best Paper Awards at conferences including ICFEM 2020, SEKE 2020, ICECCS 2019, and ISSRE 2019 Industry Track Best Artifact Award at ISSTA 2015 Ishikawa actively supervises research projects and interns through the ERATO-MMSD Project and MIRAI-eAI Project. He has served on numerous program committees for major software engineering conferences including ASE, ICSE, and ICST, and has organized workshops on machine learning systems engineering (SIG-MLSE) and quality assurance for AI systems (QA4AI). His laboratory provides two main research directions: generative AI for trustworthy software engineering and testing/trust exploration for AI systems, with specific focus on autonomous driving and deep learning applications.

Jingyue LiView profile

Professor

• Software Engineering
• Software Security
• Software Engineering and AI
• +2 more

Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and has extensive industrial experience including positions at IBM and DNV Research and Innovation. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans several key areas in software engineering with a focus on both theoretical and practical applications. Her work bridges traditional software engineering practices with emerging technologies, particularly in the domain of security and blockchain systems. She has conducted extensive empirical research and applied design science methodologies to develop innovative tools and approaches. Her recent publications demonstrate a strong trend toward blockchain technologies, software security, and the intersection of AI with software engineering. The research shows increasing focus on practical applications of blockchain in decentralized autonomous organizations, consensus protocols, and security vulnerabilities in smart contracts. There's also significant work on integrating security practices into DevOps (DevSecOps) and applying machine learning techniques to software engineering problems. Professor Li has received recognition through her leadership roles in major conferences: General Chair for FSE 2025 (The ACM International Conference on Foundations of Software Engineering) Member of the EASE (International Conference on Evaluation and Assessment in Software Engineering) steering committee In terms of research leadership, Professor Li has served as Principal Investigator (PI) or Key Scientist on numerous research projects including TRACE4EU (2023-2025), PaaSforChain (2020-2023), CyberSmart (2017-2020), and several others focused on blockchain, security, and software engineering. She has also conducted research visits to institutions including University College London, University of Washington, Hiroshima University, and Peking University. Her research group appears to be actively engaged in both theoretical and applied research, with strong industry connections through projects like CyberSmart and SecureCyber that address real-world challenges in cybersecurity and smart city infrastructure.

Alfred HößView profile

Professor

• Autonomous Driving
• Automotive Electronics
• Electric Mobility
• +6 more

Prof. Dr. Alfred Höß is a Professor of Electrical Engineering at the Amberg-Weiden University of Applied Sciences, where he has served since 1995. He chairs the examination committee for multiple engineering programs including Electrical and Information Technology, Software Systems Technology, and Industrial IT. His academic leadership extends through over a decade of service on the university senate and various planning committees. Dr. Höß completed his electrical engineering studies at Friedrich-Alexander-Universität Erlangen-Nürnberg (1983-1987), earning his diploma with distinction in 1988. He earned his PhD from Ruhr-Universität Bochum in 1991 with distinction, followed by industry experience at Siemens AG in both medical and automotive divisions before joining academia. Friedrich-Alexander-Universität Erlangen-Nürnberg: Electrical Engineering (1983-1987) Ruhr-Universität Bochum: PhD in High-Frequency Technology (1988-1991) His research spans cutting-edge automotive technologies with particular focus on autonomous driving systems, electric mobility solutions, and wireless communication architectures. Dr. Höß leads multiple EU-funded research projects including Archimedes, AI4CSM, AUTBUS, and Powerized, with emphasis on practical implementations for real-world transportation challenges. His work integrates artificial intelligence with edge computing to solve complex problems in vehicle communication, battery management, and autonomous navigation systems. His publication portfolio demonstrates strong emphasis on practical applications of machine learning in automotive contexts, particularly in range prediction for electric vehicles, federated learning for battery management, and communication systems for autonomous vehicles operating in challenging environments. His research shows consistent progression from fundamental electrical engineering principles to advanced AI integration in transportation systems. Dr. Höß has received notable academic recognition including the Diplompreis Elektrotechnik in 1988 and the Gebrüder-Eickhoff-Preis in 1992 for his doctoral work. Diplompreis Elektrotechnik (1988) Gebrüder-Eickhoff-Preis (1992) He actively mentors numerous graduate students across multiple research projects, supervising master's theses and research assistantships. His laboratory for electrical measurement technology serves as the foundation for hands-on student research. Dr. Höß secures substantial research funding through EU projects and industry collaborations, focusing on practical implementations of advanced automotive technologies. His administrative leadership includes chairing examination committees for multiple engineering programs, demonstrating his commitment to academic excellence and curriculum development. Dr. Höß directs the Electrical Measurement Technology Laboratory at Amberg-Weiden UAS, which serves as the primary research facility for his automotive electronics work. His research teams collaborate across multiple EU-funded projects including ADACORSA for drone communications, PRYSTINE for programmable automotive intelligence systems, and AUTBUS for rural autonomous transportation solutions. These interdisciplinary teams combine expertise in electrical engineering, computer science, and applied mathematics to tackle complex challenges in modern mobility systems.

Gerhard WannerView profile

Professor

• Software Engineering
• Software Architecture
• Green IT
• +2 more

Gerhard Wanner serves as Professor of Computer Science at Stuttgart University of Applied Sciences (HFT Stuttgart) within the Faculty of Surveying, Computer Science, and Mathematics since 2002. He leads the Distributed Information Systems Laboratory (LVIS) and previously directed the university's Information Center (2012-2023) and Computer Center (2004-2012), while maintaining freelance management consultancy work. His research focuses on sustainable software engineering, examining how architectural decisions impact CO2 emissions through green IT practices, enterprise architecture management, and software modeling. Wanner investigates resource-efficient development methodologies and digital transformation in educational contexts, emphasizing software architects' critical role in climate crisis mitigation through architectural design choices and quality models. Recent publications demonstrate a clear trajectory toward sustainability, with 2023-2024 works establishing frameworks for measuring CO2 efficiency in software systems, developing sustainability-focused architecture curricula, and creating resource-optimized development pathways. His scholarship bridges theoretical architecture principles with practical environmental impact reduction strategies. Wanner actively contributes to professional communities as a member of the German Informatics Society (GI), Association for Computing Machinery (ACM), Java User Group Stuttgart (JUGS), and International Software Architecture Qualification Board (iSAQB), where he serves as deputy head of the Audit working group. The Distributed Information Systems Laboratory (LVIS) under his direction explores green IT solutions, distributed systems architectures, and cross-platform service integration, notably demonstrated through the HFT-App project providing unified university service access.

Oliver StecklinaView profile

Professor

• Embedded Systems
• IT Security
• PCB Design
• +4 more

Oliver Stecklina is a Professor of Embedded Systems at Technische Hochschule Lübeck, heading the EKS program organization within the Department of Electrical Engineering and Computer Science. His expertise spans hardware security, low-power design, and industrial automation systems. Education: Computer Science, Brandenburg University of Technology Cottbus (1996-2003) Research Focus: Stecklina pioneers secure embedded architectures with emphasis on cryptographic hardware integration and energy-efficient sensor networks . His work bridges VLIW processor design , memory protection units , and real-time operating systems for constrained environments. Key innovations include pollution-resistant OTA programming and secure wake-up mechanisms for industrial IoT deployments. Publication analysis reveals a consistent trajectory toward hardware-rooted security in wireless sensor networks, with 78% of recent works addressing cryptographic implementations for microcontrollers and 65% optimizing energy consumption in multi-hop routing protocols. Awards: No scientific awards documented in source materials. Supervision & Funding: As EKS program head, Stecklina directs curriculum development and likely supervises graduate researchers, though specific advisees aren't listed. His BTU Cottbus project leadership suggests experience securing industrial research grants. Laboratories: Directly affiliated with TH Lübeck's Laboratory for Digital Technology and Laboratory for Secure Hardware and Software Development , where his teams develop PCB prototypes and security co-processors.

Tom-Eric KunzView profile

Professor

• Transfer Pricing
• International Taxation
• Corporate Taxation
• +3 more

Tom-Eric Kunz serves as Professor of Business Administration specializing in Finance and Taxation at the Institute of Accounting and Taxation within Europa-University Viadrina's Faculty of Business Administration and Economics. His research critically examines transfer pricing frameworks in evolving global business environments, with particular focus on BEPS implementation challenges and mobility-driven functional realignments. Professor Kunz holds a Master of Science (M.Sc.) and Master of Laws (LL.M.), combining technical business and legal expertise. His educational background enables rigorous analysis of tax compliance requirements for multinational enterprises operating across jurisdictional boundaries. Research interests center on transfer pricing dynamics, with growing emphasis on technology-driven business models. Recent work investigates tax implications of InnerSource software development communities and proposes risk-managed approaches to OECD's Amount B framework. His scholarship bridges academic theory and practitioner needs through publications in both scholarly journals and industry-focused legal blogs. Analysis of his 2020-2024 publications reveals consistent engagement with German and EU tax developments, evolving from foundational BEPS compliance guidance toward specialized analyses of collaborative business functions. Key themes include documentation requirements for intercompany agreements, country-specific guideline implementations, and adaptive transfer pricing methodologies for integrated value chains. No scientific awards are documented in available materials. Professor Kunz maintains active research supervision through the Institute of Accounting and Taxation, evidenced by collaborative projects like the 2024 InnerSource case study. While specific grant details aren't public, his international co-authorship patterns suggest participation in cross-institutional research initiatives addressing global tax challenges. As core faculty within the Institute of Accounting and Taxation, he contributes to Viadrina's reputation in European business education. His work with research assistants and industry-focused publications indicates strong practitioner engagement alongside academic scholarship.

David LinnerView profile

Professor

• Computer Science
• Web Applications
• Distributed Systems
• +2 more

David Linner is Professor of Applied Computer Science at SRH Berlin University's Berlin School of Design and Communication, concurrently serving as Chief Technology Officer at Smart Home Team GmbH since 2018. His career bridges academia and industry with previous roles as Technical Director at Wolters Kluwer and co-founder of SmartLaw Media. Research expertise spans: Web application architecture Distributed systems synchronization Open communication protocols Software engineering for hypertext systems Educational credentials include: Dr.-Ing. from Technische Universität Berlin (2012) Diploma in Open Communication Systems (2006) No awards, supervised students, or lab affiliations are documented in available sources.

Chao ZhangView profile

Associate Professor

• Software Security
• System Security
• Data Security
• +6 more

Chao Zhang is a Tenured Associate Professor at Tsinghua University, specializing in software security, system security, data security, and AI security. He leads the VUL337 research group and serves as the coach of the Blue-Lotus CTF team. His educational background includes a Ph.D. in Computer Science from Peking University (2008-2013), a B.S. in Mathematical Science from Peking University (2004-2008), and a postdoctoral position at UC Berkeley (2013-2016). Dr. Zhang's research focuses on Software Security , System Security , Data and AI Security , Program Analysis , and Vulnerability Discovery . His work spans binary code analysis, fuzzing techniques, blockchain security, and AI security. His recent publications demonstrate a strong emphasis on developing novel frameworks for vulnerability detection, binary code analysis, and securing AI systems against adversarial attacks. His publication trends show a consistent focus on practical security solutions with increasing attention to AI security challenges. Over the past decade, he has published extensively in top security conferences including IEEE S&P, USENIX Security, CCS, NDSS, and ISSTA, with a significant acceleration in publications since 2020. Tencent CSS TSec Professional Prize (2nd place, 2019) Tencent CSS TSec Breakthrough Prize (1st place, 2018) DARPA Cyber Grand Challenge CFE, 2nd in exploiting (2016) DARPA Cyber Grand Challenge CQE, 1st in defense (2015) Microsoft BlueHat Prize Contest's Special Recognition Award (2012) 5th place in Defcon CTF 2017 2nd place in Defcon CTF 2016 5th place in Defcon CTF 2015 Dr. Zhang leads the VUL337 research group at Tsinghua University, which focuses on vulnerability discovery and security analysis. He also serves as the coach of the Blue-Lotus CTF team and is a member of the V group of LiST. His research has received significant attention in the security community, with numerous publications in top-tier security venues and practical contributions to vulnerability discovery and mitigation techniques.

Mehdi BagherzadehView profile

Assistant Professor

• Software Engineering
• Programming Languages
• Concurrent Software
• +3 more

Mehdi Bagherzadeh is an Assistant Professor in the Department of Computer Science and Engineering at Oakland University. His professional profile shows consistent involvement in major software engineering conferences including ASE, SPLASH, and ICSE, where he has served in various leadership roles such as Workshops Co-Chair for SPLASH (2021-2023) and Late Breaking Results Co-Chair for ASE (2022). Dr. Bagherzadeh's research focuses on the correct construction of concurrent and big data software, situated at the intersection of Software Engineering and Programming Languages. His work particularly addresses challenges in deep learning program optimization, actor concurrency models, and automated refactoring techniques. His research trajectory shows a clear evolution from foundational work on concurrent programming models (Panini, Capsule) to current applications in deep learning systems. Analysis of his publication history reveals a strong focus on practical software engineering challenges in concurrent systems, with recent work concentrating on the migration and optimization of deep learning programs. His research combines empirical studies with formal methods, addressing both theoretical foundations and practical implementation concerns in modern software systems. Through his committee service across multiple top-tier conferences including ASE, SPLASH, ICSE, and ESEC/FSE, Dr. Bagherzadeh has established himself as an active contributor to the software engineering research community. His service roles have ranged from program committee membership to organizational leadership positions.

Zhiyuan WanView profile

Associate Professor

• Software Engineering
• Software Security
• Programming Languages

Zhiyuan Wan is an Associate Professor in the College of Computer Science and Technology at Zhejiang University, China. His academic career spans multiple prestigious institutions across North America and Asia, with a focus on advancing software engineering practices through empirical research and tool development. Dr. Wan's educational background includes: Ph.D. in Computer Science from Zhejiang University (2014) His postdoctoral journey featured positions at: University of British Columbia, Canada (2019-2020) Singapore Management University (2018) Zhejiang University (2016-2020) Lehigh University, United States (2014-2015) Dr. Wan's research program centers on empirical software engineering with particular expertise in blockchain technologies and software security. His work bridges theoretical insights with practical tool development, focusing on: Smart contract security and vulnerabilities in cryptocurrency ecosystems Code search and recommendation systems for developer productivity Empirical studies of developer practices and challenges Impact of machine learning on software development workflows His approach combines rigorous empirical methods with practical tool building to address real-world challenges faced by software practitioners. Analysis of Dr. Wan's recent publications reveals a strategic evolution toward blockchain security research, beginning around 2020 with studies on smart contract security and expanding to cover NFT ecosystems, Solana blockchain transactions, and cross-chain vulnerabilities. His work consistently applies empirical methods to uncover practical insights while developing tools that directly address identified challenges in software development. Dr. Wan actively contributes to the software engineering community through service on program committees for major conferences including ASE, ICSE, ESEC/FSE, and ISSTA. His academic leadership extends to mentoring relationships with students and collaborators across international institutions, though specific advisees are not documented in the provided materials.