Find Academic Supervisors

• Jewish History
• Early Modern History
• Economic History
• +4 more

Cornelia Aust is a historian and researcher at Bielefeld University, affiliated with the Faculty of History, Philosophy and Theology and the Department of History. She serves as a Postdoctoral Researcher in Collaborative Research Center (CRC) 1288 Project Area D03, focusing on practices of comparison in historical knowledge production. Her roles also include being a Research Associate at the Chair of Early Modern History since 2018 and prior affiliations with institutions like the Hebrew University of Jerusalem and the Leibniz Institute of European History. Education: Doctorate in History (University of Pennsylvania, 2010), Magister in History (Free University Berlin, 2003), and studies at Free University Berlin, Warsaw University, and Hebrew University Jerusalem. Research Interests: Cornelia Aust specializes in Jewish history from the Early Modern period to modernity in Central and Eastern Europe, with a focus on economic history, transnational networks, and cultural practices. Her work explores themes such as Jewish mercantile elites, clothing regulations, sumptuary laws, and the role of Jewish bankers in 19th-century economic crises. She integrates transcultural and transnational methodologies to analyze commercial networks and identity construction. Key Research Contributions: Her recent publications and conference papers examine the interplay between Jewish economic practices and broader European historical transformations. Topics include the cultural history of early modern clothing, legal norms governing Jewish merchants, and the socio-economic dynamics of Warsaw’s Jewish elite. Her engagement with CRC 1288 highlights comparative methodologies in analyzing knowledge production. Scientific Awards: Martin Buber Society of Fellows Postdoctoral Fellowship (2010-2013) Katz Center for Advanced Judaic Studies Fellowship (2008-2009) SSRC International Dissertation Field Research Fellowship (2006-2007)

Pola LehmannView profile

Research Fellow

• Democracy
• Political Representation
• Political Parties
• +3 more

Pola Lehmann is a Research Fellow at the Wissenschaftszentrum Berlin für Sozialforschung (WZB), affiliated with the Center for Civil Society Research. She co-leads the Manifesto Project, a cross-national initiative analyzing election manifestos in over 60 countries to study party preferences and political representation. Her work bridges political science, public administration, and computational text analysis, focusing on democratic accountability and electoral dynamics. Education: Studied Public Administration at the University of Potsdam and the University of Copenhagen Ph.D. from Humboldt-Universität zu Berlin (2021 Leibniz Dissertation Prize recipient) Research Themes: Lehmann’s research integrates automated text analysis with empirical studies on political representation, party systems, and electoral behavior. She examines discrepancies between electoral promises and parliamentary actions, particularly in the German Bundestag, and explores how populist parties like the AfD frame their agendas during crises such as the COVID-19 pandemic. Projects: Key initiatives include the Manifesto Project (tracking party positions globally), Observatory of Political Texts in European Democracies (OPTED), and The Best of Both Worlds (combining human and machine coding for precision). Her work also addresses the legitimacy of direct democracy and class-based inequalities in representation. Scientific Awards: Leibniz Dissertation Prize (2021) Collaborations: Lehmann frequently collaborates with researchers like Theres Matthieß, Sven Regel, and Henrike Schultze, contributing to interdisciplinary studies in political science. Her publications highlight methodological innovations in manifesto analysis and empirical evaluations of party-citizen congruence.

• Emergence of Europe in the Early Middle Ages
• Concepts of Work in the Middle Ages
• History and Theory of Historiography
• +3 more

Verena Epp is a Professor of Medieval History and Historical Regional Studies at Philipps University of Marburg since October 2000. She specializes in the emergence of Europe during the early Middle Ages, focusing on social structures, historiographical analysis, and political theories. Research Interests include: Concepts of work and free will in medieval societies Formation of political advisory systems Historiography and textual analysis Crusader states and cross-cultural interactions Legal integration during migrations Her publications span interdisciplinary studies on Crusades , elite networks , and cultural identity formation. While no explicit scientific awards are listed, her extensive work on medieval labor ideologies and political counsel demonstrates depth. She has contributed to edited volumes and journals, emphasizing ritualized social bonds and historical methodology.

• Computer Networks
• Distributed Systems
• Edge Computing
• +4 more

Osama Abboud is a researcher affiliated with Technische Universität Darmstadt. He holds a PhD in Computer Science from the same institution (2012), focusing on quality adaptation in peer-to-peer video streaming using scalable video coding. His work spans computer networks, distributed systems, edge computing, and federated learning. Key contributions include innovations in P2P video streaming resilience, serverless federated learning optimization, and mission-critical AI systems. He has collaborated extensively with researchers like Ralf Steinmetz and Michael Gerndt, publishing in venues such as IEEE Trans. Ind. Informatics, NetSoft, and ICC. His research emphasizes practical system design for heterogeneous environments, energy efficiency, and real-time performance. Education: PhD in Computer Science (Darmstadt University of Technology, 2012). Research Interests: Peer-to-Peer Systems, Edge Computing Architecture, Federated Learning Optimization, AI-driven Network Adaptation, and Low-Power Hardware Integration. His work bridges theoretical foundations with practical implementations in distributed environments. Notable Projects: Development of Apodotiko (serverless federated learning framework), MARQ (mission-critical AI system), and contributions to edge computing architectures like Trabant and Host Bypassing. These projects aim to enhance scalability, reduce latency, and improve sustainability in distributed systems.

Simon WorthingtonView profile

Researcher

• Open Science
• Open Source Software
• Publishing Technology
• +3 more

Simon Worthington is a leading researcher in future publishing systems, focusing on free and open source technologies, economic models, and the politics of Open Science. He serves as Editor-in-Chief at Generation Research, an editorial platform for open scholarship under the Leibniz Association Research Alliance Open Science, and works in R&D at the Open Science Lab, TIB - German National Library of Science and Technology. Board Member of FORCE11 (2019-2022) Co-founder of Mute magazine (1994) Executive Member of LIBER Citizen Science Working Group (2019-2021) Co-founder of Open Climate Knowledge (2019-ongoing) His research emphasizes creating platform-independent, interoperable publications to democratize research access. Key areas include open access publishing, semantic web applications for climate science, decentralized web technologies for academia, and innovative software citation practices. He has contributed to projects like AGATE (European academies digital integration) and Hybrid Publishing Lab. Recent publications highlight intersections between Free and Open Source Software (FOSS) and Open Scholarship, climate science open knowledge platforms, and infrastructure remixing for citizen science. His work often challenges traditional publishing norms while developing practical open systems. Simon studied media art at the Slade School (UCL, UK) and CalArts (USA), bringing interdisciplinary perspectives to his academic roles. He maintains active involvement in editorial and community-driven research initiatives across Europe.

• Parallel Computer architectures
• High Performance Computing
• Multi-/Manycore architectures
• +5 more

PD Dr. Josef Weidendorfer is a qualified private lecturer at Technische Universität München (TUM) and leads the Future Computing Group at the Leibniz Computing Centre (LRZ). He holds a dual affiliation with TUM's Department of Informatics, Chair of Computer Architecture and Parallel Systems (Prof. Schulz), and the Leibniz Rechenzentrum der Bayerischen Akademie der Wissenschaften. His work focuses on developing smooth migration strategies for future HPC systems and evaluating novel technologies to improve system-level and workload analysis tools. Weidendorfer's research interests encompass Parallel Computer Architectures, High Performance Computing, Multi-/Manycore architectures, GPGPU, Performance analysis and optimization, Cache Simulation, Virtual Machines, and dynamic code generation. He is particularly interested in strategies for improving computational efficiency across various hardware structures, including specialized accelerator hardware for HPC codes. He regularly organizes the UCHPC workshop (since 2010 with Euro-Par) about unconventional hardware for HPC computing and is co-organizer of the PSTI workshop series. His recent publications reveal a strong focus on HPC system optimization, with particular emphasis on load balancing techniques, cache partitioning, application malleability, and performance monitoring. The research trajectory shows increasing attention to practical implementation challenges in modern heterogeneous computing environments, especially regarding GPU utilization, resource partitioning under power constraints, and phase-aware system monitoring. Weidendorfer maintains the open-source tools Callgrind/KCachegrind for cache simulation and has supervised numerous student projects across bachelor's, master's, and guided research programs. He teaches courses including Virtualization Techniques, Parallel Programming Systems, and Advanced Computer Architecture, demonstrating strong commitment to both research and education in computer architecture and parallel systems. As principal investigator for multiple large-scale projects including EU Project SEANERGYS (2025-2028) and BMBF Project ScalNext (2022-2025), he leads significant research initiatives focused on future computing technologies and HPC system development.

Ajay JhaView profile

Assistant Professor

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

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

Mingwei LiuView profile

Associate Professor

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

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

Dan HaoView profile

Professor

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

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

Manel AbdellatifView profile

Professor

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +7 more

Manel Abdellatif is a Professor in the Department of Software Engineering and IT at École de Technologie Supérieure (ETS) in Montreal, Canada. Her research spans trustworthy AI, service computing, and software maintenance/evolution, with significant contributions to software engineering conferences including ASE (Tool Demo PC Member 2025), ICSE (Awards Chair 2025), and DeepTest (Committee Member 2026). She actively publishes in top venues like IEEE TSE and ACM TOSEM with recent work on deep learning safety and microservice modernization. Dr. Abdellatif holds an M.Sc. from ÉTS and a Ph.D. from Polytechnique Montréal. Her doctoral research focused on service identification approaches for legacy system migration to SOA, establishing her expertise in software modernization. She maintains strong industry connections through applied projects addressing real-world challenges in system migration and digital transformation. Her research program centers on AI system reliability and software modernization , with three interconnected thrusts: (1) Safety monitoring and testing of deep reinforcement learning systems (SMARLA framework), (2) Microservice migration including antipattern detection and service identification, and (3) Legacy system modernization using machine learning and semantic analysis. She combines empirical studies with practical tool development, often collaborating with industry partners on real systems. Analysis of her 15 most recent publications reveals a clear trajectory toward ensuring trustworthy behavior in AI systems while addressing architectural challenges in modern software. Her work bridges theoretical advances in deep learning testing with practical solutions for microservice adoption, showing increasing focus on formal methods for safety guarantees in autonomous agents. Dr. Abdellatif supervises a dynamic research group with 9 current graduate students working on cutting-edge topics including federated learning anti-patterns (Amirhossein Roudgar), AI-to-microservice migration (Hakim Ghlissi), and deep learning test optimization (Hatem Feki). Her supervision spans both theoretical research (master's theses) and industry-applied projects addressing concrete modernization challenges. Her work is conducted within ETS's Software Systems, Multimedia and Cybersecurity research axis, where she collaborates with colleagues on software quality, IoT systems, and empirical engineering methods. The department's strong industry connections enable her team to validate approaches on real-world systems while maintaining academic rigor.

• Software Engineering
• Source Code Analysis
• Software Clone Detection
• +12 more

James R. Cordy is a Professor in the School of Computing at Queen's University, Faculty of Engineering and Applied Science, Kingston, Canada. He is a leading researcher in software engineering, with a focus on source code analysis, software clone detection, model-driven engineering, and program transformation. He has been actively publishing since 1977, with a sustained record of contributions in top-tier venues such as ICSE, MoDELS, and WCRE. His research interests include software clone detection, model transformation, Simulink models, source transformation, software maintenance, and grammatical inference. He has developed and contributed to influential tools such as TXL and NiCad, and his work often involves empirical studies and tool evaluation in real-world software systems. The most recent articles highlight trends in model transformation, clone detection, verification of state machines, and migration of legacy systems. His work increasingly integrates formal methods and empirical validation, particularly in automotive and safety-critical domains. He has also explored applications in healthcare software, such as artificial pancreas systems. Most Influential Paper Award, SCAM 2001 (awarded in 2019) He has advised numerous students, including Manar H. Alalfi, Matthew Stephan, and Chanchal K. Roy, who have co-authored multiple publications with him. His research is often collaborative, involving teams from Queen's University and other institutions. He has also contributed to workshops and special issues, demonstrating leadership in the software engineering community.

Thomas LeichView profile

Professor

• Software Product Line Engineering
• Requirements Engineering
• IT Security
• +11 more

Prof. Dr.-Ing. Thomas Leich holds the Volkswagen Financial Services Endowed Professorship for Business Informatics, specifically Requirements Engineering, at Harz University of Applied Sciences. He is affiliated with the Faculty of Automation and Information, focusing on software variability and configurable systems. University: Harz University of Applied Sciences School: Faculty of Automation and Information Academic Rank: Professor Research Interests span software product line engineering, IT security, Industry 4.0, and feature-oriented programming. His work bridges academic innovation with industrial applications, particularly in secure and scalable systems for automotive and enterprise contexts. Recent Publications emphasize security in configurable systems, empirical software engineering studies, and automotive platform management. Articles often involve collaborations with teams at Otto von Guericke University and international institutions. Scientific Awards include the Hugo Junkers Research Award (2013), the Wissenschaftspreis der Wernigeröder Stadtwerkestiftung (2017), and the 2012 Faculty Research Award from the University of Magdeburg. Supervision of over 20 theses since 2008, spanning topics in ERP security, program comprehension, and embedded systems. He leads the EXPLANT project, funded by DFG, and contributes to FeatureIDE , an extensible framework for feature-oriented development.

• Sociolinguistics
• Migration Linguistics
• Conversation Analysis
• +3 more

Inken Keim is a former adjunct professor at the University of Mannheim and a retired senior researcher at the Institut für Deutsche Sprache (IDS) in Mannheim. Her academic career spanned over 37 years (1971–2008), focusing on sociolinguistics, migration linguistics, and conversation analysis. She held positions in the Departments of Pragmatics and Language and Society at IDS, contributing to projects such as 'Communicative Social Stylistics' and 'German-Turkish Linguistic Variation.' Her research emphasized ethnographic approaches to multilingualism and migrant communication, particularly among Turkish communities in Germany. Notable projects include analyzing communicative styles of German-Turkish youth and exploring language variation in urban settings. She collaborated with Werner Kallmeyer on a DFG-funded project investigating linguistic practices in migrant groups. Keim's publications (e.g., The 'Turkish Powergirls' , 2008) highlight her focus on sociocultural identity formation and language use in diasporic contexts. She also contributed to understanding language contact phenomena and multilingual lifeworlds of Turkish-origin youth. Her work bridges sociolinguistic theory with empirical fieldwork, emphasizing real-world language practices. Though no specific grants or awards are listed, her extensive project involvement underscores her role in shaping migration linguistics and German sociolinguistics. She was part of the IDS's research teams focusing on language variation and corpus-based studies, contributing to projects like 'Conversational Rhetoric' and 'Communication in the City.'

Alexander Schmidt-CatranView profile

Professor

• Social inequality
• Migration
• Welfare states
• +4 more

Prof. Dr. Alexander Schmidt-Catran is a Professor of Sociology with a focus on quantitative empirical social research at Goethe University Frankfurt, part of the Faculty of Social Sciences. He coordinates Project No. 5 of the RISS initiative, studying the impact of immigrant population composition on native attitudes. His research emphasizes statistical methods for multilevel and panel data, migration, welfare states, and secularization trends. He previously held roles at the University of Cologne and Mannheim. Educations: PhD in Social Sciences from University of Cologne (2013) Studies in Social Sciences at University of Cologne (2004–2009) Visiting scholar appointments at University of Bristol, Tilburg University, Umea University, and others Research Interests: Schmidt-Catran's work spans social inequality, migration patterns, welfare state dynamics, and methodological advancements in longitudinal data analysis. He explores how statistical models can better capture complex interactions in multilevel datasets and has contributed to debates on secularization and public opinion shifts in Europe. His projects often integrate international comparative perspectives to understand societal changes. Grants & Projects: Principal Investigator for RISS Project No.5 on 'Internalized Ethnic and Cultural Reconfiguration' Collaborations with Project No.1 for developing social identity measurement tools Labs/Teams: Leads a research team at Goethe University, including members like Dr. Christian Czymara and Zsofia S. Ignacz, focusing on immigration, welfare policies, and statistical methodology.

• Protoplanetary disks
• radiative transfer
• planet formation
• +3 more

Dr. David Melon Fuksman is a researcher at the Planet and Star Formation Department of the Max Planck Institute for Astronomy in Heidelberg, Germany. His work focuses on protoplanetary disks , radiative transfer , planet formation , and numerical fluid dynamics . Contact: +49 6221 528-403, Room 308/2 Research Interests include the study of protoplanetary disk dynamics, radiation hydrodynamics, and numerical simulations of planet formation processes. He also investigates high-energy astrophysical phenomena such as gamma-ray bursts and neutrino production in extreme environments. Publication Trends (15 most recent) span computational astrophysics, radiation hydrodynamics, and multiwavelength analysis of protoplanetary disks. His recent work (2025-2024) emphasizes three-temperature models , spiral structures , and implicit solvers for disk-planet interactions, while earlier studies (2023-2013) explore neutrino astrophysics , binary-driven hypernovae , and observational data analysis . Projects and Tools: Development of the PyPLUTO software package and the MATRICS solver, enabling advanced simulations of astrophysical systems.