جستجوی استاد راهنمای دانشگاهی

Muhammad Ali Gulzarمشاهده پروفایل

استادیار

• Fault Localization
• Big Data systems
• Data Intensive scalable computing
• +۵ مورد دیگر

Muhammad Ali Gulzar is an Assistant Professor in the Computer Science Department at Virginia Tech and an Amazon Scholar at Amazon Web Services. His research focuses on improving developer productivity through automated debugging and testing for applications in emerging domains, including data-intensive software such as dataflow programs, ML/AI applications, and computational notebooks. Education Ph.D. in Computer Science from University of California, Los Angeles (Google Ph.D. Fellow 2017-2020) Research Interests Gulzar's research spans three primary areas: (1) automated tracking-code localization techniques in web applications, (2) re-engineering testing and debugging for data-intensive applications, and (3) advancing current testing and debugging practices in Federated Learning Applications. His work addresses the challenges of debugging in complex systems where traditional approaches fail due to the scale and distributed nature of modern applications. His research has significant implications for improving software quality, developer productivity, and accessibility in web applications. Research Trends Recent publications demonstrate a strong focus on debugging and testing challenges in emerging application domains. His work bridges traditional software engineering with machine learning, data-intensive systems, and web technologies. Notably, he has made significant contributions to Federated Learning debugging (FedDebug), accessibility challenges in ad-driven web applications, and semantic caching for Large Language Models. His approach often combines novel algorithmic insights with practical implementations that address real-world challenges in software development and maintenance. Scientific Awards Google Ph.D. Fellow (2017-2020) $1.1 million NSF award for Federated Learning research ACM CCS 2024 Distinguished Artifact Award Advising and Grants Gulzar leads a productive research group with multiple students contributing to publications in top-tier venues. His NSF-funded research on Federated Learning demonstrates his ability to secure competitive funding for innovative projects. His advising style appears to emphasize practical impact alongside theoretical contributions, with students often taking lead roles in publications. Current research directions include debugging techniques for Large Language Models, accessibility challenges in modern web applications, and novel testing approaches for distributed data processing systems.

Wolfgang Nejdlمشاهده پروفایل

استاد

• Web Science
• Information Retrieval
• Artificial Intelligence
• +۴ مورد دیگر

Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .

Martin Stürzlingerمشاهده پروفایل

استاد

• Digital Archiving
• Electronic Records Management
• OAIS Model
• +۵ مورد دیگر

Dr. Martin Stürzlinger is a Part-Time Professor for Digital Archiving at the Department of Information Sciences, University of Applied Sciences Potsdam. He also operates his consulting firm Archiversum, advising organizations on long-term information storage (www.archiversum.com). His work bridges academic research with practical applications in digital preservation. Research Interests: Dr. Stürzlinger specializes in digital archiving, focusing on the OAIS model, life-cycle management, and archival description standards like Records in Contexts (RiC). His research addresses organizational challenges in digital preservation, legal compliance (e.g., GDPR), and metadata design for accessibility. Recent Publications: His selected works explore OAIS implementation, the impact of GDPR on private archives, and the evolution of archival description standards. These contributions highlight trends in digital preservation, emphasizing interoperability, sustainability, and cross-institutional collaboration. Collaboration & Standards: He actively contributes to international working groups, including ICA-EGAD (Archival Description) and nestor's certification standards for digital archives. His efforts in standardization include the Austrian implementation of ISAD(G) and ISDIAH, as well as Swiss guidelines for electronic records management. Teaching & Outreach: Dr. Stürzlinger has lectured extensively, including courses on archive management at BFI Vienna and IT applications in archives at the University of Vienna. He has delivered over 40 lectures globally, addressing topics like cost estimation for digital archiving and the role of corporate archives in business efficiency.

• Database Management Systems
• Transaction Processing
• In-Memory Databases
• +۶ مورد دیگر

Andrew Pavlo is a Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research focuses on database management systems, particularly in the areas of transaction processing, in-memory databases, and self-driving database systems. He leads a productive research group that has published extensively in top database venues including VLDB, SIGMOD, and CIDR. Pavlo's research interests span database management systems, transaction processing, in-memory databases, non-volatile memory databases, and self-driving database systems. His work often bridges theoretical database concepts with practical system implementation, focusing on performance optimization, query processing, and system architecture. Recent work has explored machine learning applications for database tuning, novel storage techniques, and innovative approaches to transaction processing. An analysis of his recent publications reveals a strong focus on self-driving database systems, with significant work on the Database Gym framework for training machine learning models to optimize database performance. His research also examines columnar storage formats, transaction scheduling, and novel approaches to user-defined function optimization. The work demonstrates a consistent trajectory toward making database systems more autonomous and efficient through a combination of systems techniques and machine learning. Pavlo has been instrumental in mentoring numerous PhD students who have become active contributors to the database research community. His research has been supported by significant grants that have enabled the development of innovative database technologies and frameworks. His research group operates within CMU's vibrant database ecosystem, collaborating with other researchers on projects related to database systems, storage engines, and query processing frameworks. The group maintains close connections with industry partners to ensure practical relevance of their research contributions.

Ioachim Pupezaمشاهده پروفایل

استاد

• Optical Spectroscopy
• Field-Resolved Spectroscopy
• Precision Optical Measurements
• +۶ مورد دیگر

Prof. Dr. Ioachim Pupeza serves as Group Leader in the Department of Spectroscopy/Imaging at the Leibniz Institute of Photonic Technology (Leibniz-IPHT) in Jena, Germany. His research focuses on advanced optical measurement techniques, particularly in the field of field-resolved spectroscopy and precision optical measurements. Dr. Pupeza's research interests center around optical spectroscopy with a particular emphasis on field-resolved techniques that capture the complete electric field waveform of light-matter interactions. His work spans infrared spectroscopy , molecular fingerprinting , ultrafast laser technology , and precision optical measurements . He has made significant contributions to electro-optic sampling techniques, which enable characterization of electric-field waveforms across the terahertz to visible spectral range. His research also extends to mid-infrared light generation , terahertz spintronic emitters , and cavity-enhanced spectroscopy , with applications ranging from fundamental physics to medical diagnostics. Analysis of Dr. Pupeza's recent publications reveals a strong trend toward increasingly sophisticated field-resolved spectroscopy techniques with applications in both fundamental science and practical diagnostics. His work has evolved from basic measurement techniques to applications in cancer detection through molecular fingerprinting of biofluids. A consistent theme across his publications is the pursuit of higher precision, broader bandwidth, and improved sensitivity in optical measurements, often achieving attosecond-level precision. His research bridges physics, engineering, and medical applications, demonstrating how fundamental optical advances can translate to real-world diagnostic tools. Dr. Pupeza leads the research group "Field-Resolved Optical Precision Measurement Methods" at Leibniz-IPHT, which appears to collaborate extensively with other research institutions and groups. His work involves sophisticated laser systems including high-power Yb:YAG thin-disk oscillators, femtosecond enhancement cavities, and dual-oscillator systems for precision measurements. The group's research has implications for molecular spectroscopy, medical diagnostics, and fundamental studies of light-matter interactions at the most fundamental time scales.

Viktor Leisمشاهده پروفایل

استاد

• Database Systems
• Cloud Computing
• Data Management
• +۳ مورد دیگر

Prof. Dr. Viktor Leis is a Professor in the Department of Computer Science at the Technical University of Munich (TUM), leading the Chair for Decentralized Information Systems and Data Management. His research focuses on cost-efficient data systems, particularly in cloud environments, with expertise in core database topics like query processing, transaction management, and storage optimization. He earned his PhD from TUM in 2016 and previously held professorships at Friedrich Schiller University Jena and Friedrich-Alexander-Universität Erlangen-Nürnberg before returning to TUM in 2022. His work has been recognized with prestigious awards, including the ACM SIGMOD Dissertation Award, VLDB Early Career Research Contribution Award, and an ERC Starting Grant. Research Interests: Cloud computing, database systems, query optimization, storage engines, transaction processing, and NVMe-optimized systems. Key Projects: Developed the LeanStore storage engine and contributed to the Hyper database system. His recent publications emphasize cloud-native architectures, high-performance storage solutions, and hybrid transactional/analytical processing. He actively teaches courses on distributed systems, cloud databases, and blockchain technologies.

Lucio Baccaroمشاهده پروفایل

استاد

• Comparative Political Economy
• Comparative Employment Relations
• Comparative Labor Movements
• +۷ مورد دیگر

Lucio Baccaro is Director at the Max Planck Institute for the Study of Societies (MPIfG) and was Full Professor of Macrosociology at the University of Geneva, where he also served as Deputy Dean for Research (2016–2020). He has held academic positions at MIT, Case Western Reserve University, and visiting roles at the University of Turin and the University of Vienna. His primary affiliations are with MPIfG and the University of Geneva, both central to his research in political economy and sociology. Education: PhD in Management and Political Science, Massachusetts Institute of Technology (MIT), 1999 Doctorate in Labor Law and Industrial Relations, University of Pavia, 1997 Master of Business Administration, Stoa' (IRI-MIT joint venture), 1991 Laurea in Philosophy, summa cum laude, University "La Sapienza", Rome, 1989 Lucio Baccaro’s research focuses on comparative political economy, labor relations, global worker rights, and deliberative governance . His work integrates economic sociology and political sociology to analyze institutional change, social dialogue, and the impact of globalization on labor and welfare systems. He has led major comparative studies on employment models, pension reforms, and international labor standards. His scholarship emphasizes the interplay between institutions, ideas, and power in shaping economic governance. His recent publications reveal a consistent focus on institutional change, deliberative processes, labor market reforms, and global justice . Themes include path dependence in international organizations, the transformation of collective bargaining, and the role of expertise in democratic governance. His interdisciplinary approach bridges sociology, political science, and economics, with strong methodological rigor in comparative and qualitative analysis. Scientific Awards and Honors: Honorary Professor, University of Duisburg-Essen (2023) Professeur honoraire, University of Geneva (2020) International Geneva Award (2011) Outstanding Young Scholar Award, IRRA (2003) Founder's Prize, SASE (2001) Maurice F. Strong Career Development Chair, MIT (2006–2009) Multiple fellowships from SSRC, Harvard, MIT, and CUNY Alfiere del Lavoro, awarded by the President of Italy (1984) Advising and Grants: While specific student advisees are not listed, Baccaro has supervised research and mentored scholars through his roles at MPIfG and the University of Geneva. He has secured substantial research funding, including grants from the Swiss National Science Foundation (SNF) and the Swiss Network for International Studies (SNIS), supporting projects on post-Fordist growth models, employment policy, and deliberative governance. His leadership in co-principal investigator roles highlights his collaborative research approach and institutional influence. Labs and Research Teams: As Director at MPIfG, Baccaro leads a major research institute focused on the study of societal and economic institutions. He has been instrumental in shaping research agendas on political economy and governance, fostering interdisciplinary collaboration and international scholarly exchange.

• Knowledge Representation
• Semantic Web
• Ontology Engineering
• +۷ مورد دیگر

Jiaoyan Chen is a Senior Lecturer (Associate Professor) in the Department of Computer Science at The University of Manchester. She previously held roles as a Lecturer at Manchester, a Senior Researcher at the University of Oxford, and a Postdoctoral Fellow at Heidelberg University. Education: PhD and Bachelor's in Computer Science and Technology from Zhejiang University (2016 and 2011), with a visiting PhD stint at Zurich University's Department of Informatics. Research Interests: Integrating knowledge graphs and ontologies with machine learning and large language models (LLMs), focusing on semantic embeddings, knowledge curation, and explainable AI systems. Publication Trends show emphasis on ontology embeddings (e.g., OWL2Vec*), LLM evaluation with knowledge graphs, and hybrid neural-symbolic reasoning. Her work bridges structured knowledge and modern AI through projects like OntoEm and ConCur . Current Research Team includes postdoctoral researchers, PhD students, and externally co-supervised associates. She actively recruits PhD candidates in areas like Retrieval-Augmented Generation and LLM Explainability , with projects funded by EPSRC and international consortia. Grants & Leadership: EPSRC New Investigator Award (2023-2026) Manchester-Melbourne-Toronto Research Fund (2024-2026) EPSRC ConCur Project (2021-2025) Professional Service: Associate Editor, Transactions on Graph Data and Knowledge EPSRC Peer Review College member OAEI Track Co-organizer at ISWC

• Art History
• Reformation and Visual Arts
• Mannerism
• +۵ مورد دیگر

Sergiusz Michalski is a Professor at the Institute of Art History within the Faculty of Philosophy at the University of Tübingen, where he has held his position since 2001. Previously, he served as Managing Director of the Art History Institute at TU Braunschweig from 1996-2001 and completed his Habilitation at Goethe University Frankfurt in 1995. His distinguished academic career spans multiple European institutions including universities in Munich, Leipzig, Frankfurt, Kiel, Fribourg, Zurich, and Torun. Michalski's research focuses encompass Reformation and Art, Mannerism, 16th and 17th century Dutch and Flemish painting, Art theory, 18th century French painting, 20th century art, Public monuments, and Methodological questions in art history. His scholarly output includes approximately 270 publications with notable books such as 'The Reformation and the Visual Arts' (1992), 'Public Monuments' (1998), 'L'art de l'Europe Centrale' (2008), and 'Einführung in die Kunstgeschichte' (2015). His recent publications demonstrate continued engagement with contemporary issues in art history, particularly in public monument discourse, digital methodologies, and Central European art traditions. Michalski has edited several prominent art history journals including Ars Artibus et Historiae, Folia Historiae Artium, and Ikonotheka. Member of Royal Swedish Academy for Literature and Humanities Member of Polish Academy for Sciences and Arts Member of Göttingen Academy of Sciences Member of Academia Europaea / The Academy of Europe London Member of Latvian Academy of Sciences Member of Council of Experts of European Science Foundation Michalski maintains an active research profile with recent publications addressing digital methodologies in art history, contemporary monument discourse, and Central European art traditions. His international scholarly network is reflected in his editorial roles and academy memberships across Europe.

• Computer Security
• Network Security
• Systems Security
• +۴ مورد دیگر

Nuno Santos is an Associate Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico (IST), University of Lisbon, and a senior researcher at INESC-ID Lisbon. He leads the SysSec team, focusing on systems security and privacy. His research spans secure enclaves, network security, and censorship-resistant systems. Education: Ph.D. in Computer Science (2013) from Max Planck Institute for Software Systems (MPI-SWS) in affiliation with Saarland University. Visiting research stints at Vrije Universiteit Amsterdam (2018) and Technical University of Munich (2024). Research Interests: Systems security, privacy, trusted execution environments (TEEs), network security, censorship resistance, AI security, and secure cloud computing. He has pioneered work on mitigating vulnerabilities in TrustZone-based TEEs and enhancing confidential computing. Publications: Over 30+ peer-reviewed articles in top-tier venues like S&P, USENIX Security, CCS, and NDSS. Recent trends focus on AI-driven security (e.g., automated exploit generation, prompt-to-SQL injections) and confidential computing (e.g., AMD SEV-SNP analysis). Awards: IST Outstanding Teaching Award (2019/2020), 2024 Prémio Científico Universidade de Lisboa/Caixa Geral de Depósitos. Advising & Grants: Supervised MSc theses in areas like AI-powered vishing attacks and confidential VMs. Active in conference organization (e.g., USENIX Security’25 Vice Chair, IEEE EuroSP’26 Co-Chair). Labs/Teams: Leads the SysSec team at INESC-ID Lisbon, collaborating on projects like AnyTEE (TEE framework) and FlowLens (network security tool).

• Database Systems
• Distributed Databases
• Transaction Processing
• +۵ مورد دیگر

Daniel J. Abadi is a prominent researcher in database systems at Yale University. With over two decades of impactful research, he has made significant contributions to the fields of distributed databases, transaction processing, and column-oriented database systems. His work bridges theoretical foundations with practical implementations that have influenced both academia and industry. Dr. Abadi's research primarily focuses on database system architecture, with particular emphasis on: Distributed and geo-replicated database systems High-performance transaction processing Column-oriented and analytical database systems Stream processing and real-time analytics Cloud and serverless database technologies Integration of machine learning with database systems His recent work shows a continued focus on addressing scalability challenges in modern database systems, with particular attention to multi-region transaction processing, automated data management, and the integration of machine learning techniques. The trend in his publications indicates a strong emphasis on practical, deployable systems that solve real-world problems faced by industry. Dr. Abadi has been instrumental in several major research initiatives and reports that have shaped the direction of database research, including the Seattle Report and the Cambridge Report on Database Research. Throughout his career, Dr. Abadi has mentored numerous students and collaborated extensively with leading researchers in the field. His work has received significant recognition through widespread citations and adoption of his ideas in both academic and industrial database systems.

• Lexicography
• Digital Humanities
• German Language
• +۳ مورد دیگر

Dr. Lothar Lemnitzer serves as a Researcher at the Berlin-Brandenburg Academy of Sciences and Humanities, affiliated with the Center for Digital Lexicography of the German Language in Berlin. His office is located at Jägerstrasse 22/23, Space 18, with contact details including phone +49 (0)30 20370 538 and email lemnitzer@bbaw.de. His research spans critical areas in linguistic technology: Lexicography Digital Humanities German Language Processing Computational Linguistics Natural Language Processing Language Technology Dr. Lemnitzer's work focuses on developing digital infrastructure for German language resources, contributing to modern lexicographic methodologies through computational approaches. His publications reflect ongoing advancements in creating structured lexical databases for academic and public use. No scientific awards are documented in the available profile information. While the text references publications and a curriculum vitae, specific details regarding student supervision, grant funding, or collaborative projects remain unlisted. The Center for Digital Lexicography operates as a dedicated unit within the academy, driving innovation in digital dictionary creation and language resource management for the German-speaking academic community.

Chang Xuمشاهده پروفایل

استاد

• Big data software engineering
• Intelligent software testing and analysis
• Adaptive and autonomous software systems
• +۳ مورد دیگر

Chang Xu is a Professor and Ph.D. supervisor at Nanjing University, affiliated with the State Key Laboratory for Novel Software Technology, School of Computer Science, and Institute of Computer Software (ICS). He has been a full-time faculty member since 2010, when he joined as an associate professor and was later promoted to full professor in 2015. Education: Ph.D. from The Hong Kong University of Science and Technology (HKUST) in 2008 (advisor: Prof. S.C. Cheung) M.Eng. from Institute of Software, Chinese Academy of Sciences (ISCAS) in 2003 B.Eng. from University of Science and Technology of China (USTC) in 2000 Research Interests: Professor Xu's research focuses on big data software engineering, intelligent software testing and analysis, and adaptive and autonomous software systems. His recent work centers on constructing and providing runtime support for intelligent software in open environments, with emphasis on inconsistency detection and resolution for environments, and quality assurance for adaptive, concurrent, learning-based, smartphone-based, and spreadsheet-based applications. His work bridges theoretical foundations with practical applications in software engineering, particularly in program analysis, software testing, and self-adaptive systems. Scientific Awards: ACM SIGSOFT Distinguished Paper Award from ICSE 2025 Best Student Paper Award from EUROSYS 2025 ACM Distinguished Member in 2024 Best Paper Award from SOSP 2023 Best Paper Candidate from ISSRE 2022 Yangtze River Scholar by the Ministry of Education in 2021 Multiple ACM SIGSOFT Distinguished Paper Awards from conferences including ASE, ICSE National Science and Technology Progress Award (Second Class) in 2011 Academic Service and Advising: Professor Xu has served on numerous program committees for top software engineering conferences including ICSE, ASE, ESEC/FSE, and ISSTA. He is an editorial board member for several journals including Journal of Computer Science and Technology and Frontiers of Computer Science. He has supervised numerous Ph.D. and MSc students, with research topics spanning program analysis, software testing, self-adaptive systems, and more. His students have gone on to successful careers in both academia and industry. Research Groups: Professor Xu is associated with the SPAR research group at Nanjing University and the CASTLE research group at HKUST, focusing on software analysis, reliability, and testing.

• Reconfigurable Computing
• FPGA Architectures
• Hardware Acceleration
• +۱ مورد دیگر

Prof. Dr. Andreas Koch leads research on reconfigurable computing at TU Darmstadt, focusing on FPGA-based acceleration, heterogeneous architectures, and hardware/software co-design for database systems and embedded applications.

Jörg Schultzمشاهده پروفایل

استاد

• Bioinformatics
• Computational Biology
• Evolutionary Genomics
• +۵ مورد دیگر

Prof. Dr. Jörg Schultz serves as a Professor for Bioinformatics at the Faculty of Biology, University of Würzburg, a position he has held since 2003. He is also a Group Leader at the Center for Computational and Theoretical Biology (CCTB) and was a member of the CCTB Managing Board from 2015-2019. His academic journey includes significant roles as Group Leader at the Max Planck Institute for Molecular Genetics in Berlin (2002-2003) and at cellzome in Heidelberg (2000-2002). He completed his PhD studies at EMBL Heidelberg (1996-2000) after conducting his diploma thesis there in 1995-1996, following biology studies at the University of Konstanz (1991-1996). Prof. Schultz's research spans bioinformatics, computational biology, and evolutionary genomics, with notable contributions to protein domain analysis, phylogenetics, and structural bioinformatics. His recent work has focused extensively on plant genomics, particularly studying carnivorous plants like the Venus flytrap to uncover the evolutionary roots of plant carnivory. His research integrates computational methods with biological questions to address fundamental evolutionary patterns and molecular mechanisms across diverse organisms. Prof. Schultz has maintained a prolific publication record since the late 1990s, with his most recent work demonstrating continued innovation in computational approaches to biological questions. His publications reveal a consistent trajectory from foundational work on protein domain evolution (including the development of the SMART database) to current research on plant genomics, molecular evolution, and bioinformatics tool development. His work shows particular strength in bridging computational methodology with biological insight across multiple domains. Among his significant contributions is the development of the ITS2 Database, a widely used resource for phylogenetic analyses, along with various computational tools including ALVIS for sequence alignment visualization, reper for repetitive element analysis, and BCdatabaser for DNA barcoding. These resources have advanced methodological capabilities in the bioinformatics community. As an academic mentor, Prof. Schultz has guided numerous students and researchers through his laboratory at the University of Würzburg, contributing significantly to the education and training of the next generation of bioinformaticians. His leadership roles demonstrate his commitment to advancing computational and theoretical biology as academic disciplines while maintaining strong connections between computational approaches and biological discovery.