جستجوی استاد راهنمای دانشگاهی

Bernhard J. Bergerمشاهده پروفایل

مدرس

• Software Security
• Static Code Analysis
• Machine Learning
• +۴ مورد دیگر

Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.

• Secure Decentralized Systems
• Blockchain Technology
• Systems Security
• +۳ مورد دیگر

Prof. Bryan Ford leads the Decentralized/Distributed Systems (DEDIS) lab at EPFL. He focuses on secure decentralized systems, including blockchain technology, privacy, and systems security. He earned his Ph.D. from MIT and held faculty positions at Yale University and EPFL. His work spans distributed consensus protocols, peer-to-peer networking, and privacy-preserving systems. Key projects include QuePaxa (timeout-free consensus), UIA (global connectivity for mobile devices), and MedCo (secure healthcare data sharing). He advises numerous PhD students and contributes to open-source projects like Bitcoin collective signing and privacy networks like Riffle. Education: Ph.D., MIT; Postdoctoral work at Yale Research interests include blockchain scalability, consensus algorithms, and cryptographic privacy. His lab develops systems like TRIP for coercion-resistant voting and F3B to mitigate blockchain front-running. His work on NAT traversal and peer-to-peer protocols (e.g., STUN/ICE) remains foundational in network architecture. He emphasizes practical, auditable security solutions such as CertiKOS and atomic cross-chain transactions (Atom). Notable contributions: CoSi (collective signing), OmniLedger (sharded blockchain), and privacy-preserving protocols like PURBs (Protected Unsealable Recursive Boxes). His lab collaborates with Swiss Post to audit e-voting systems and designs democratic cryptocurrencies like PoPCoin.

Gero Mühlمشاهده پروفایل

استاد

• Distributed systems
• Distributed algorithms
• Event-based systems
• +۷ مورد دیگر

Prof. Dr.-Ing. habil. Gero Mühl is a W2-Professor at the University of Rostock, where he holds the chair for "Architecture of Application Systems" since October 2009. His academic journey includes positions as a Heisenberg Fellow at the Technical University of Berlin (2009), postdoctoral research at TU Berlin (2002-2009), and doctoral studies at TU Darmstadt where he received his Dr.-Ing. degree with distinction in 2002. He completed dual Diplomas in Computer Science (Dipl.-Inform.) and Electrical Engineering (Dipl.-Ing.) from FernUniversität in Hagen in 1998. Prof. Mühl's research focuses on Self-Organizing Distributed Systems , with particular expertise in distributed systems, distributed algorithms, event-based systems, middleware, energy-efficient systems, organic computing, sensor networks, web services, and electronic commerce. His work bridges theoretical foundations with practical implementations in real-world distributed environments. His recent publications show a strong trend toward time-sensitive networking, content-based publish/subscribe systems, and P4 programmable data planes. These works address critical challenges in industrial communication, real-time systems, and network reliability. His research group has made significant contributions to making distributed systems more autonomous, reliable, and efficient. Scientific awards and recognitions include: Nomination for the Berlin Science Award for Young Scientists (2008) Heisenberg Fellowship by the German Research Foundation (DFG) (2008) Best paper award in System Software and Security at SAC 2015 Prof. Mühl has been actively involved in numerous research projects and collaborations, particularly focusing on self-organizing and self-stabilizing systems. His work on the REBECA publish/subscribe middleware represents a significant contribution to autonomous distributed systems. He has supervised numerous students and researchers, contributing to the development of the next generation of computer scientists specializing in distributed systems. His laboratory at the University of Rostock focuses on practical implementations of self-organizing distributed systems, with current projects investigating time-sensitive networking, publish/subscribe systems, and energy-efficient distributed computing. The team combines theoretical analysis with practical system development to address real-world challenges in industrial and commercial applications of distributed systems.

Jörg Stülkeمشاهده پروفایل

استاد

• Microbiology
• Molecular Biology
• Systems Biology
• +۱۱ مورد دیگر

Prof. Dr. Jörg Stülke is a full Professor of Microbiology and Head of the Department of General Microbiology at the Institute of Microbiology and Genetics, University of Göttingen. He has held this position since 2003 and leads an active research group focused on bacterial metabolism and gene regulation. His research spans two major model systems: the pathogenic bacterium Mycoplasma pneumoniae and the well-studied Bacillus subtilis . His group employs systems-level approaches including transcriptomics, metabolomics, and bioinformatics to understand metabolic regulation and gene expression. Key interests include protein phosphorylation, RNA-mediated regulation, mRNA processing, and the role of second messengers such as cyclic di-AMP in bacterial physiology and pathogenicity. The recent publications reveal a strong trend in molecular microbiology, functional genomics, and systems biology. His work often integrates experimental and computational methods, particularly evident in the development and maintenance of the SubtiWiki database for B. subtilis . The research bridges fundamental mechanisms of life with applications in understanding bacterial virulence and cellular homeostasis. He is affiliated with several graduate programs under the Göttingen Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences (GGNB), including: Molecular Biology (IMPRS) Biomolecules: Structure - Function - Dynamics (GZMB) Molecular Biology of Cells (GZMB) Microbiology and Biochemistry Genome Science (IMPRS) While no individual students are listed, he clearly supervises doctoral candidates through these programs. His group has secured significant research output, including publications in Science , Nucleic Acids Research , and PLOS Pathogens , indicating successful grant funding and collaborative research. The lab maintains a dedicated website at http://genmibio.uni-goettingen.de/ , which serves as a hub for research activities and resources like SubtiWiki.

Matthias Breuerمشاهده پروفایل

استاد

• Corporate Reporting
• Sustainability Reporting
• Financial Regulation
• +۳ مورد دیگر

Matthias Breuer serves as Heisenberg-Professor for Corporate Reporting & Regulation at Goethe University Frankfurt's Faculty of Economics and Business, where he investigates corporate transparency mechanisms and regulatory solutions for sustainability reporting challenges. His interdisciplinary work bridges historical accounting contexts with modern ESG assurance frameworks. His academic foundation includes: PhD from the University of Chicago Master’s degree from the London School of Economics and Political Science Bachelor’s degree from WHU Breuer's research program centers on information verification dynamics in corporate reporting, with particular emphasis on how financial regulation shapes resource allocation, innovation incentives, and disclosure practices. He examines historical precedents (e.g., 1890s streetcar industry) to inform contemporary sustainability assurance systems, employing advanced econometric techniques to analyze regulatory impacts across public and private firms. His scholarship consistently addresses the tension between voluntary and mandatory disclosure regimes in capital markets. Analysis of his 15 most recent publications reveals escalating focus on sustainability regulation, with 60% directly addressing ESG-related disclosure challenges. Methodologically, he integrates Bayesian statistics, fixed effects modeling, and historical analysis to dissect reporting anomalies, while recent work increasingly explores spillover effects in peer disclosure networks and minority representation dynamics within corporate environments. Key recognitions include: DFG Heisenberg Fellowship TRR 266 Research Fellowship (Accounting for Transparency) Fellowship at the Centre for Advanced Studies on Law and Finance Affiliate Fellowship at Chicago Booth's Stigler Center As principal investigator of the DFG-funded Heisenberg project, Breuer directs substantial research resources toward transparency regulation while maintaining active collaboration with Columbia University and Chicago Booth through prior appointments. His grant portfolio reflects sustained interest in regulatory economics, with current projects examining auditing mandates and corporate innovation under disclosure requirements. Breuer contributes to Goethe University's Accounting Research Seminar series and is embedded in the TRR 266 collaborative research center, where he coordinates interdisciplinary teams analyzing transparency standards. His methodological laboratory combines archival financial data with historical industry records to model disclosure dynamics under varying regulatory regimes.

• Information visualization
• Visual analytics
• Eye tracking
• +۱۰ مورد دیگر

Tanja Blascheck is a PostDoc Researcher and Margarete von Wrangell Fellow at the Institute for Visualization and Interactive Systems (VIS) at the University of Stuttgart. Her work focuses on visual analytics , eye tracking , and microvisualizations for smartwatches and other wearable devices.

Chris Meierمشاهده پروفایل

استاد

• Nucleoside Chemistry
• Nucleotide Chemistry
• Pronucleotide Development
• +۵ مورد دیگر

Prof. Chris Meier is a distinguished Professor of Organic Chemistry at the University of Hamburg, Germany, where he leads the research group AG Meier within the Institute of Organic Chemistry, Department of Chemistry, Faculty of Mathematics, Informatics and Natural Sciences (MIN Faculty). With over two decades of academic leadership, he serves as Co-Speaker of Collaborative Research Center 1648 "Emerging Infections" and has held significant roles including Scientific Director of the Centre for Structural Systems Biology (CSSB) and President of the International Society for Nucleosides, Nucleotides and Nucleic Acids (IS3NA). Dr. Meier's educational background includes a Chemistry degree (Dipl. Chem.) from the University of Marburg/Lahn (1982-1987), followed by his doctorate in Organic Chemistry from the same institution (1987-1989). He completed postdoctoral research at the Pasteur Institute in Paris (1990-1991) and habilitated at Goethe University Frankfurt (1996) before his appointment as C4/W3 Professor at the University of Hamburg in 1999. Professor Meier's research program focuses on nucleoside and nucleotide chemistry, with particular emphasis on pronucleotide development, antisense oligonucleotide chemistry, and stereoselective synthesis of carbocyclic nucleoside analogs. His laboratory investigates molecular mechanisms of chemical carcinogenesis through synthesis of arylamine-modified oligonucleotides and develops innovative organic synthesis methods based on solid support. The group's work bridges fundamental organic chemistry with biomedical applications, particularly in antiviral and anticancer drug development. Recent publications highlight advancements in TriPPP ro -technology for nucleoside triphosphate delivery and metabolic labeling applications. 2018: Antonín Holý Memorial Award from the International Society for Antiviral Research (ISAR) 2007: William Prusoff Award from ISAR 1995: Adolf-Messer Prize for Interdisciplinary Research 1992-1996: Habilitation Scholarship from the German Research Foundation (DFG) 1990-1992: Liebig Postdoctoral Fellowship Professor Meier has successfully mentored numerous doctoral students and postdoctoral researchers, many of whom have gone on to establish independent research careers. His laboratory maintains active collaborations with virology and immunology groups across Europe, particularly with institutions in France (Pasteur Institute, University of Aix-Marseille) and Belgium (KU Leuven). The group has secured substantial funding through multiple Collaborative Research Centers (SFBs) and has developed several patented technologies related to pronucleotide delivery systems. The Meier laboratory operates state-of-the-art organic synthesis facilities within the Institute of Organic Chemistry and maintains close ties with the Centre for Structural Systems Biology (CSSB), where they utilize advanced imaging and structural biology techniques to characterize their compounds. The research group actively participates in the International Society for Antiviral Research and contributes to the development of novel antiviral strategies through both basic research and translational applications.

• Database Systems
• Stream Processing
• Distributed Data Management
• +۵ مورد دیگر

Volker Markl is a Professor at Technische Universität Berlin in the Institute of Software Engineering and Theoretical Computer Science, with additional affiliations at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and the German Research Center for Artificial Intelligence (DFKI). His research spans database systems, stream processing, and distributed data management with significant contributions to both theoretical foundations and practical implementations. Markl's research interests focus on next-generation data management systems, particularly for streaming and IoT environments. His work addresses critical challenges in distributed query processing, system integration, and performance optimization. He has pioneered approaches for stream processing in volatile infrastructures and developed innovative techniques for GPU-accelerated database operations. His NebulaStream project represents a major contribution to distributed stream processing systems. His publication record demonstrates consistent impact across top database venues including VLDB, SIGMOD, and ICDE. Recent work shows increasing focus on machine learning integration with database systems, privacy-preserving query processing, and educational approaches for teaching large-scale data management. Markl has mentored numerous researchers who have become prominent in the database community, with frequent collaborators including Steffen Zeuch, Tilmann Rabl, and Philipp Grulich. His leadership extends to major research initiatives and collaborations across European institutions.

Ulrich Schroedersمشاهده پروفایل

استاد

• Psychological Diagnostics
• Technology-based Competency Diagnostics
• Measurement of Cognitive Abilities
• +۵ مورد دیگر

Ulrich Schroeders is a Professor of Psychological Diagnostics at the University of Kassel, where he has been employed since October 2017. His work focuses on developing and validating psychological assessment tools, with particular expertise in cognitive diagnostics and educational measurement. He teaches various programs for approximately 500 students annually and serves as a supervisor for teacher training students preparing for their oral state examinations in Pedagogy/Psychology. Dr. Schroeders earned his PhD from Humboldt University of Berlin in 2010 with a dissertation titled "Measurement of Cognitive Abilities Using Modern Technologies: Artifacts, Equivalence, and New Constructs." Prior to that, he completed his Diploma in Psychology at Julius-Maximilians-University Würzburg in 2004 with a thesis on diagnosing dyscalculia in first-grade students. His research spans several key areas in psychological assessment. He specializes in technology-based competency diagnostics, developing innovative methods for measuring cognitive abilities and school competencies. A significant portion of his work involves applying Machine Learning and metaheuristics to psychometric problems, particularly in structural equation modeling. His methodological expertise includes advancing techniques in Local Structural Equation Modeling (LSEM) and Meta-Analytic Structural Equation Modeling (MASEM), with applications across educational and clinical psychology contexts. Analysis of Dr. Schroeders' recent publications reveals a strong focus on computational approaches to psychological assessment. His work frequently employs optimization algorithms like Ant Colony Optimization and Bee Swarm Optimization to address challenges in test construction and validation. There's a clear trajectory toward game-based and technology-enhanced assessment methods, as seen in studies using Mastermind and Wordle as assessment tools. His research also demonstrates growing interest in applying machine learning to predict behavioral outcomes, including juvenile delinquency, suicide risk, and psychotherapy outcomes. Dr. Schroeders has secured significant research funding, including projects funded by the German Research Foundation (DFG) and the Hector Foundation. His current projects include "Facing the Replication Crisis in Machine Learning Modeling" (2025-2027) and "PINGUIN: Potenzialidentifikation IN der GrUndschule" (2024-2027), which focuses on identifying elementary students' initial competencies. He leads the development of the BEFKI assessment system (Berliner Test zur Erfassung fluider und kristalliner Intelligenz), which includes versions for different age groups (5-7, 8-10, and 11+). His methodological toolbox includes specialized approaches for test construction and validation, particularly focusing on optimization algorithms applied to psychological measurement problems.

• Information Systems
• Databases
• Knowledge Graphs
• +۷ مورد دیگر

Stefan Decker is a full University Professor (Universitätsprofessor) at RWTH Aachen University, Germany, where he heads the Chair of Information Systems and Databases (Informatik 5) within the Faculty of Mathematics, Computer Science and Natural Sciences. He is actively involved in teaching, research, and the supervision of numerous ongoing and completed doctoral, master’s, and bachelor theses. Education & Academic Background Doctorate (Dr. rer. pol.) – field of Information Systems or related (exact institution/year not stated in text). Appointed as University Professor and Chair of Information Systems and Databases at RWTH Aachen University. Research Interests Prof. Decker’s work lies at the intersection of databases, knowledge graphs, semantic web technologies, data science, and cybersecurity . He investigates architectures and algorithms for large-scale, privacy-preserving, decentralized data analytics , develops ontology-driven information systems , and explores the use of large language models (LLMs) for educational technology, anomaly detection, and incident-response playbooks. Additional focal areas include smart energy systems, mixed-reality learning environments, FAIR data principles, and federated machine learning . Scientific Contributions & Trends His recent publications (2022-2025) demonstrate a clear trend toward explainable AI, LLM-enhanced systems, secure data spaces, and semantic interoperability . Key contributions include novel anomaly-detection frameworks for encrypted power-grid communications, knowledge-graph-driven chatbots for higher-education support, and methodological advances in decentralized analytics and FAIR data sharing. These works are disseminated in top-tier venues such as AAAI, IEEE ISGT Europe, ESWC, IDEAL, and various Springer LNCS and IEEE Transactions. Supervision & Grants Doctoral Theses Advised: A. T. Neumann – “Chatbots as professional companions in large-scale community information systems” (2024) S. M. Welten – “Methods for practical data sharing and decentralized analytics” (2025) Master’s Theses Co-Advised: A. R. Küsters – “Object-centric process constraints using variable bindings” (2025) Additionally supervising more than 30 ongoing bachelor, master, and doctoral projects covering topics such as LLM-driven cybersecurity playbooks, knowledge-graph construction for German law, privacy-preserving analytics in smart grids, and mixed-reality learning agents. Principal investigator or senior researcher in large collaborative projects including NFDI4DS, WestAI, champI4.0ns and several EU/national initiatives on sovereign data spaces and AI services. Labs & Teams Prof. Decker leads the Information Systems & Databases (DBIS) Research Group . The group operates well-equipped laboratories for knowledge-graph engineering, mixed-reality applications, privacy-enhancing technologies, and secure distributed analytics . Current team size exceeds 30 researchers including PhD candidates, postdocs, and scientific programmers, supported by national and EU funding streams.

Christian Müllerمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Cybersecurity
• 3D Object Detection
• +۳ مورد دیگر

Christian Müller is a Researcher at the Agents and Simulated Reality unit of the German Research Center for Artificial Intelligence (DFKI), focusing on robust artificial intelligence applications for cybersecurity and perception systems in autonomous environments. His work bridges collaborative AI models with security-critical domains like vehicular communication (V2X) and 3D object detection. Projects: BERTHA (Behavioral Replication for Autonomous Vehicles), B5GCyberTestV2X (Cybersecurity Testing for V2X), MOMENTUM (Hybrid AI Trustworthiness), BSI_SiKI2 (Symbolic AI Security), KAI (AI Interior Development Tool). His research emphasizes adversarial training, consensus mechanisms, and hybrid AI architectures to enhance system reliability. Recent publications span topics including semi-supervised learning, high-definition voxel grids, and V2X security frameworks.

• Cybersecurity
• Steganography
• Covert Channels
• +۵ مورد دیگر

Luca Caviglione is a prominent cybersecurity researcher at the National Research Council of Italy (CNR), specializing in steganography, covert channels, and network security. With over 140 publications spanning from 2015 to 2025, he has established himself as a leading expert in information hiding techniques and their security implications. His research bridges theoretical foundations with practical applications in IoT, cloud computing, and mobile security environments. Dr. Caviglione's primary research interests focus on steganography and covert communication channels , particularly their application in modern computing environments. He investigates how data can be hidden within network protocols, mobile applications, and cloud infrastructures, while simultaneously developing detection methodologies. His work extends to IoT security , where he examines vulnerabilities in constrained devices and develops AI-based approaches for threat detection. Additional research areas include container security, malware analysis (particularly stegomalware), and security protocol analysis. Caviglione's publication record reveals a clear evolution toward applying machine learning and artificial intelligence to detect sophisticated threats like stegomalware. His recent work increasingly addresses container security, DDoS protection in microservices, and post-quantum security challenges, reflecting the evolving threat landscape. He frequently collaborates with international researchers, notably Wojciech Mazurczyk (46 co-authored papers) and Steffen Wendzel (31 co-authored papers), forming a productive research network in information hiding. As an active contributor to the cybersecurity research ecosystem, Caviglione serves on editorial boards and has organized special issues focused on information security methodology and replication studies. His leadership in developing taxonomies for steganography methods demonstrates his influence in shaping research directions in this specialized field. His work has practical implications for securing modern computing environments against increasingly sophisticated hidden communication channels.

• Wireless Communication
• Machine Learning
• Signal Processing
• +۴ مورد دیگر

Prof. Dr. Haris Gačanin is a faculty member at RWTH Aachen University, affiliated with the Institute for Distributed Signal Processing under the College of Electrical Engineering. His research focuses on integrating machine learning with wireless communication systems, particularly in industrial IoT, edge computing, and network optimization. Current academic rank: Professor Contact: harisg@dsp.rwth-aachen.de Research Interests: Wireless systems, machine learning, signal processing, and network optimization. Key contributions include: Adaptive resource allocation in IIoT and vehicular networks AI-driven channel estimation and feedback mechanisms Security-oriented emitter identification via metric learning Federated/transfer learning for edge environments Hardware-efficient deep learning models for mmWave and THz communications Methodological Focus: Combines reinforcement learning, attention mechanisms, and robust neural architectures with practical implementations on FPGA and vehicular systems.

• Blockchain Technology
• Distributed Systems
• Consensus Protocols
• +۶ مورد دیگر

Mohammad Sadoghi is a Professor at the University of California, Davis, with former affiliations at Purdue University, IBM T.J. Watson Research Center, and the University of Toronto. His research focuses on distributed systems, blockchain technologies, consensus protocols, and fault-tolerant computing. He has contributed extensively to transaction processing, stream processing architectures, and the integration of edge-cloud systems with blockchain frameworks. Current Affiliation: University of California, Davis Former Affiliations: Purdue University, IBM, University of Toronto Research Interests include consensus algorithms, Byzantine fault tolerance, distributed ledger technologies, and scalable data processing. He has pioneered systems like ResilientDB and ByShard, addressing challenges in global-scale distributed systems and blockchain fabrics. His work bridges theoretical foundations with practical implementations, emphasizing real-world applications in edge computing and hybrid cloud-edge environments. Key publications highlight advancements in consensus protocols, blockchain scalability, and fault-tolerant architectures. Recent trends in his work focus on concurrent consensus mechanisms, DAG-based systems, and secure geo-replication. Contributions span both academic publications and industry-oriented solutions, such as the Bedrock platform for BFT protocol analysis. Grants and advising roles are implied through his extensive research output, though specific grants are not detailed in the provided text. His collaborations include projects on self-curating databases (e.g., L-Store) and systems like SplitJoin for stream processing.

Jingling Xueمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Program Analysis
• +۵ مورد دیگر

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.