جستجوی استاد راهنمای دانشگاهی

Toby Jia-Jun Liمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, where he leads the SaNDwich Lab. He also serves as the Director of the Human-Centered Responsible AI Lab in the Lucy Family Institute for Data & Society and is a Faculty Fellow at the Institute for Educational Initiatives (IEI). Previously, he was affiliated with Carnegie Mellon University's Human-Computer Interaction Institute (HCII) and GroupLens Research. Dr. Li's research spans the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP), with recent work focusing on addressing societal challenges in the future of work through human-AI collaborative approaches. His work has resulted in over 40 publications at premier venues including CHI, UIST, CSCW, ACL, and ICSE, with 8 papers winning Best Paper or Honorable Mention awards. His recent publications demonstrate a strong focus on human-AI collaboration across various domains, including code understanding, privacy, accessibility, and creative tools. The work shows a trajectory toward increasingly sophisticated integration of human-centered design with AI capabilities, particularly using large language models to enhance human productivity and address societal challenges. Google Research Scholar Award recipient Recipient of Yahoo! Fellowship ($100,000/year) Best Paper Award at UIST 2020 Best Paper Honorable Mention Award at CHI 2021 Best Paper Award at CSCW 2024 Best Paper Award at CHI 2025 Dr. Li actively mentors Ph.D. students and has established collaborations with Google, Microsoft Research, IBM Research, Adobe, Verizon, and J.P. Morgan. His research has been supported by NSF, Google Research Scholar Program, AnalytiXIN Initiative, Yahoo! InMind project, and J.P. Morgan. He is currently recruiting Ph.D. students and undergraduate researchers for his SaNDwich Lab, which focuses on developing interactive systems to empower individuals to create, configure, and extend AI-powered computing systems.

Nicole Ondruschمشاهده پروفایل

استاد

• Digital Transformation
• Innovation Management
• Design Thinking
• +۳ مورد دیگر

Prof. Dr. Nicole Ondrusch is a Professor at Heilbronn University (HHN) within the Faculty of Computer Science. She specializes in teaching methodological fundamentals of software engineering, including ERP systems, Design Thinking, Change Management, and digital transformation. Her research focuses on educational concepts for computer science technologies and future-relevant skills. Key Roles and Projects: Member of BW-CAR doctoral center Organizer of Barcamp Heilbronn, an unconference teaching project fostering student teamwork Principal investigator in funded projects like DigiTrans (digital transformation education) and DEV:GAMES (educational game development) SAP Academic Board DACH spokesperson since 2021 Research Interests: Her work emphasizes innovative teaching methods such as Design Thinking, agile project implementation, and digital experimentation. She explores ethical AI education, interdisciplinary collaboration, and the societal impact of digital transformation. Nicole also develops practical teaching tools like virtual escape rooms and game-based learning frameworks. Grants & Partnerships: Funded by DAAD (DigiTrans), Stiftung Innovation, and others Collaborates with industry partners like SAP and local IT organizations (ConnectIT) Labs & Teams: She leads the Lab:D initiative, developing digital teaching platforms, and co-organizes the Barcamp, a student-led event integrating real-world project management and community building.

Elena Simperlمشاهده پروفایل

استاد

• Human-centric AI
• Knowledge Graphs
• Knowledge Engineering
• +۷ مورد دیگر

Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.

Alexander Pretschnerمشاهده پروفایل

استاد

• Software Engineering
• Testing
• Information Security
• +۵ مورد دیگر

Prof. Alexander Pretschner is a Professor of Software & Systems Engineering at the Technical University of Munich (TUM) and Founding Director of the Bavarian Research Institute for Digital Transformation (bidt). He also serves as Scientific Director of fortiss, a Bavarian research institute for software-intensive systems. His research focuses on software engineering, testing, information security, and ethical software development. Pretschner holds a PhD from TUM and has held academic positions at Karlsruhe Institute of Technology (KIT) and TU Kaiserslautern. He is a co-editor of several prestigious journals, including IEEE Transactions on Reliability and the Journal of Software Testing, Verification and Reliability. Education: PhD in Computer Science, Technical University of Munich MSc in Computer Science, University of Kansas (on Fulbright Scholarship) Diplom in Computer Science, RWTH Aachen University Research Interests: His work spans testing methodologies, secure software design, and ethical considerations in agile development. Notable contributions include frameworks for metamorphic testing, distributed data usage control, and accountability mechanisms for cyber-physical systems. Awards: IBM Faculty Award (2012, 2013) Google Focused Research Award (2011, 2012) EARTO Innovation Prize (2014) 2nd Platz Supervisory Award (2020) Advising & Grants: Pretschner has supervised numerous PhD and Master’s students, contributing to over 200 publications. He leads projects like EDAP (Ethical Deliberation in Agile Processes) and collaborates with industry partners on cybersecurity and AI ethics initiatives. Labs & Teams: His work is anchored in bidt, fortiss, and TUM’s Chair of Software & Systems Engineering, focusing on societal impacts of digitalization and trustworthy AI systems.

• Networked Systems
• Distributed Systems
• Social Computing
• +۵ مورد دیگر

Krishna Gummadi is a Scientific Director and Professor at the Max Planck Institute for Software Systems (MPI-SWS) in Germany, where he leads the Networked Systems Research Group. He also holds a professorship at the University of Saarland, demonstrating his dual commitment to research and academic instruction in computer science. His educational background includes: Ph.D. in Computer Science and Engineering from the University of Washington (2005) B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Madras (2000) Gummadi's research spans networked and distributed computer systems with a current focus on social computing systems. His work addresses critical challenges in algorithmic fairness, privacy in social media, trustworthiness of online identities, and information dissemination in social networks. He approaches these problems through interdisciplinary methods combining user-centric studies, data-centric analysis, and systems-centric design to create practical solutions that enhance fairness, transparency, and user control in online platforms. His methodology integrates large-scale observational studies, computational modeling, and system implementation to tackle complex human-computer interaction challenges at societal scale. His recent publications reveal a strong emphasis on fairness in algorithmic decision making, with significant contributions to quantifying and addressing discrimination in machine learning systems. His work bridges computer science, social science, and ethics, creating frameworks for fair classification, understanding media bias, and developing privacy-preserving techniques that maintain functionality while protecting user data. The research demonstrates a progression from technical system design to addressing societal implications of computing systems. Among his notable scientific achievements: ERC Advanced Grant in 2017 for 'Foundations for Fair Social Computing' Test of Time Awards at ACM SIGCOMM and AAAI ICWSM Casper Bowden Privacy Enhancing Technologies (PET) and CNIL-INRIA Privacy Runners-Up Awards IW3C2 WWW Best Paper Honorable Mention Multiple Best Paper awards across prestigious conferences Gummadi has advised numerous PhD students and postdoctoral researchers who have gone on to prominent positions in academia and industry. His ERC Advanced Grant has supported extensive research into fair social computing, while his leadership in major conferences (including serving as General Chair for ICWSM 2016 and Program Chair for WWW 2015) has shaped research directions in the field. His teaching portfolio includes courses on Distributed Systems, Human-Centered Machine Learning, and Social Media Analysis. He leads the Networked Systems Research Group at MPI-SWS, which has developed several publicly available systems including tools for fair classification, privacy risk assessment, trust evaluation in social media, and information diet management. The group's work bridges theoretical advances with practical implementations that address real-world challenges in social computing, with numerous software releases and datasets made available to the research community.

Daniel J. Langمشاهده پروفایل

استاد

• Real-World Laboratory Research
• Transdisciplinarity
• Sustainability Research
• +۶ مورد دیگر

Prof. Dr. Daniel J. Lang is a leading academic at Karlsruhe Institute of Technology (KIT), where he serves as Professor for Designing Real-World Laboratory Research and Head of the Research Group "Designing Real-World Laboratory Research" at ITAS. He also holds the UNESCO Chair in Higher Education for Sustainable Development at Leuphana University of Lüneburg. His career spans key roles including Dean of the Faculty of Sustainability at Leuphana University (2012-2016) and leadership positions in multiple research projects. Current affiliations: KIT (2022-present), Leuphana University (2010-2022) Research focus: Real-world laboratories, transdisciplinary research, sustainability transformations, knowledge integration, and urban mobility systems His work connects academic research with practical sustainability challenges, particularly in mobility (TRAMIGO, ADMoS-Future), digitalization (LinkLab), and societal transformation. He has developed frameworks for evaluating socio-technical experiments and co-designed tools for policy implementation. Scientific contributions include establishing transdisciplinary methodologies and contextual analysis frameworks. Recent projects examine equity in automated mobility (CulturalRoad), knowledge transfer in real-world labs, and sustainability transitions in SMEs (TRANSFORM). His 15 most recent publications address topics like socio-technical experiments, equity metrics, and cross-case learning. Key awards: UNESCO Chair in Higher Education for Sustainable Development Advising: Supervised Beecroft, R.'s 2020 dissertation on real-world labs

Oliver Crönertzمشاهده پروفایل

استاد

• Digital Transformation
• Business Analytics
• Industry 4.0 Technology Potentials
• +۴ مورد دیگر

Prof. Dr. Oliver Crönertz serves as Dean and Professor of Business Administration and IT-Supported Business Processes at the Faculty of Digital Transformation , HTWK Leipzig. His work bridges digital transformation with business management, focusing on interdisciplinary project management, digital business models, and sustainability. Current roles: Dean, supervising professor for HTWK Robots/nao Team Research areas: Digital Transformation, Business Analytics, Industry 4.0, Stoffstrommanagement Research Trends : Recent publications emphasize digital solutions for environmental management, business process optimization, and smart urban logistics. His work connects Industry 4.0 with financial sustainability and societal impacts of digitalization. Projects : Leads Mittelstand-Digital Zentrum Leipzig-Halle, involved in EXIST-Potentiale, Future Parking, and FAssMII (Feedback-based E-Assessment in STEM).

Janick Edingerمشاهده پروفایل

استاد

• Distributed Operating Systems
• Edge Computing
• Computation Offloading
• +۷ مورد دیگر

Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.

Mariya Tonevaمشاهده پروفایل

پژوهشگر

• Machine Learning
• Natural Language Processing
• Neuroscience
• +۵ مورد دیگر

Mariya Toneva is a tenure-track faculty member at the Max Planck Institute for Software Systems , conducting groundbreaking research at the intersection of Machine Learning , Natural Language Processing , and Neuroscience . She leads the Bridging AI and Neuroscience (BrAIN) group , focusing on computational models that align AI systems with human brain processes. Her work aims to enhance both AI capabilities and neuroscience understanding through this cross-disciplinary approach. Actively recruiting postdocs, PhDs, and research interns in areas like code/text representation, brain-AI alignment, and neuroimaging data analysis Collaborator on NIH-funded projects using fMRI and neuropixel data Research Themes : Her group explores neural mechanisms of language processing, event segmentation in narratives, memory reactivation via music, and effective human-AI collaboration frameworks. Key methods include LLM analysis, cross-modal similarity metrics, and naturalistic task-based fMRI studies. Key Publications (2024-2025): Brain-tuned speech models (INTERSPEECH 2025) Cognitive event boundaries in LLMs (Behavioral Research Methods 2025) Music-induced memory reactivation (biorxiv 2024) LLM-brain alignment reasons (EMNLP 2024) Advising : Mentors PhD candidates Omer Moussa (speech processing), Camila Kolling (representational similarity), and Gabriele Merlin (LLM alignment). Collaborates with institutions like MIT, NYU, and ETH Zurich.

Kevin Baumمشاهده پروفایل

پژوهشگر

• Explainable AI
• AI Ethics
• AI Fairness
• +۴ مورد دیگر

Kevin Baum is a computer scientist currently serving as the deputy head of the Neuro-Mechanistic Modelling (NMM) department at the German Research Center for Artificial Intelligence (DFKI) since January 2023, and head of the Centre for European Research in Trusted AI (CERTAIN) at DFKI since December 2023. Based at the Saarland Informatics Campus in Saarbrücken, Germany, he completed his doctorate in philosophy in March 2024, combining technical expertise with philosophical depth. His work bridges computer science with ethics, focusing on making AI systems transparent and accountable to human users. Dr. Baum's research program centers on interdisciplinary questions concerning the explainability and transparency of AI systems. His work spans multiple significant projects including the Explainable Intelligent System (EIS) initiative and project E7 of the Transregional Collaborative Research Centre 248 "Foundations of Perspicuous Software Systems" (CPEC). He has developed frameworks for understanding stakeholder perspectives on explainable AI and investigated how different information types about automated systems affect user perceptions of fairness and justice. His approach consistently combines theoretical foundations with practical implementations across diverse contexts. Analysis of his publication trends reveals a clear trajectory from theoretical foundations in machine ethics toward practical implementations of explainability requirements in real-world contexts. His work demonstrates increasing focus on human oversight effectiveness, fairness monitoring, and ethical considerations across various AI applications. He has made significant contributions to both academic discourse and practical AI development guidelines, with publications spanning computer science, philosophy, psychology, and human-computer interaction venues. Award for Ethics for Nerds lecture series As a research leader, Dr. Baum contributes to shaping AI development practices through his departmental leadership and interdisciplinary collaborations. His current work with CERTAIN focuses on establishing European research standards for trusted AI development and deployment, emphasizing the practical implementation of ethical requirements in AI systems. He maintains active collaborations across multiple institutions and disciplines, reflecting his commitment to bridging technical and philosophical considerations in AI development. At DFKI, he leads research that combines neuroscientific insights with AI development to create more interpretable systems. The NMM department focuses on both theoretical research on explainable AI foundations and practical applications in various domains, with particular attention to how different stakeholders understand and require explanations from AI systems.

Niina Zuberمشاهده پروفایل

پژوهشگر

• Ethical Software Design
• Digital Ethics
• Agile Software Development
• +۶ مورد دیگر

Niina Zuber is a Research Coordinator at the Bavarian Institute for Digital Transformation (bidt), focusing on ethical software design, agile development processes, and the intersection of digital technologies with democratic systems. Her work emphasizes integrating ethical principles into technical systems through frameworks like EDAP (Ethical Deliberation for Agile Processes). PhD in Ethics and Software Development (LMU Munich) Former roles: Research Consultant (Cognostics AG), LMU Munich, Center for Digitalization Bavaria (ZD.B) Key projects: EDAP, ReCREATIV, AI Gender Bias Dialogue Her research spans: ethical requirements management, value-sensitive design, AI's impact on creativity, facial recognition regulation, and digital responsibility frameworks. She regularly contributes to academic publications and public discourse on digital ethics. Scientific Contributions: Co-developed EDAP framework for ethical agile software processes Investigated ethical challenges in large language models (Vox ChatGPT) Explored gender bias in AI systems Studied generative AI's impact on creative industries Contributed to regulatory discussions on facial recognition Zuber collaborates across disciplines, connecting philosophy with technical implementation through projects like EDAP and publications in journals such as Philosophy & Technology and Informatics Spectrum.

• Financial Mathematics
• Actuarial Mathematics
• Stochastic Processes
• +۷ مورد دیگر

Thorsten Schmidt is Professor of Mathematical Stochastics at the University of Freiburg, succeeding Prof. Ernst Eberlein in the summer semester of 2015. He also serves as Senior Financial Engineer at MathFinance. Previously, he held professorships at Chemnitz University of Technology (2008-2015), Technical University Munich (2008), and University of Leipzig (2004 onwards). From 2017-2019, he was a Research Fellow at the Freiburg Institute for Advanced Studies (FRIAS) in a joint research group with the University of Strasbourg and USIAS on the topic of Linking Finance and Insurance. His research focuses primarily on financial and actuarial mathematics, stochastic processes, and statistics, with recent work on machine learning methods and their applications in financial mathematics and AI regulation. In Freiburg, his goal with his young team is to tackle complex challenges with improved mathematical models and apply these methodologies to various fields. Key Research Areas: Financial mathematics and credit risks Pricing and hedging of derivative financial products Statistics of stochastic processes Energy markets and nonlinear filter theory Machine learning applications in finance and insurance His recent publications show a strong trend toward integrating machine learning with traditional mathematical finance, particularly in risk management, insurance-finance arbitrage, and robust financial modeling. His work increasingly addresses ethical considerations in AI applications within finance, reflecting his broader interest in responsible AI development. Notable Awards: IDA Award Finance (2015) FRIAS-USIAS Research Fellow (2017/2018) IDA Award Machine Learning and AI (2020) MAPFRE Research Grant (2020) Luis Bachelier Fellow (2021) As Editor-in-Chief of Statistics and Risk Modeling and Associate Editor for Mathematical Finance and International Journal of Theoretical and Applied Finance, Schmidt plays a significant role in academic publishing. He leads the CRC 'Small Data' research center with Harald Binder, focusing on medical problems where disease progression must be estimated with few data points per patient. His LeanAI project, funded by the Vector Foundation, explores the connection between machine learning and theorem-proving software LEAN, aiming to develop AI that can translate between mathematics and formal proof systems. His laboratory work centers around the application of stochastic methods combined with machine learning to solve problems in finance and insurance where data is limited ('Small Data' initiative), with significant funding from DFG (€12 million for CRC Small Data) and the Carl Zeiss Foundation.

• Human-Computer Interaction
• Geographic Information Science
• Virtual Reality
• +۷ مورد دیگر

Johannes Schöning is a Professor of Human-Computer Interaction at the University of St. Gallen, where he leads a research group focused on developing novel user interfaces that empower individuals and communities with data-driven decision capabilities. His work bridges rapidly advancing technologies with human needs across diverse contexts including geographic information science, public health, medical applications, and extreme environments such as space missions. He publishes extensively at premier HCI venues including ACM CHI, MobileHCI, and DIS, as well as in interdisciplinary journals like NATURE and PLOS ONE. Professor Schöning's research interests center on understanding the interplay between technology and human activities through rigorous methods from AI, computer graphics, and cognitive psychology. His work emphasizes user-centered design methodologies and mixed methods approaches to create interfaces that fit both technological possibilities and human requirements. Key focus areas include virtual and augmented reality applications, accessibility solutions, navigation technologies, and the social implications of digital interfaces in everyday life. His research mission prioritizes theoretical and practice-based inquiry to develop disruptive solutions for real-world problems. Analysis of his recent publications reveals strong trends in virtual reality applications for emotional regulation and accessibility, with increasing emphasis on generative AI integration, environmental awareness, and space-related HCI challenges. His work consistently demonstrates interdisciplinary collaboration across computer science, psychology, geography, and medical fields, with publications showing growing interest in social implications of technology, particularly regarding navigation systems and their externalities. His scientific contributions have been recognized with numerous awards including: Best Presentation Award at IEEE VR 2023 Best Paper Award & Accessibility Award at Interact 2019 10 Year Impact Award 2021 Multiple Honorable Mention Awards at top conferences Professor Schöning actively mentors students across bachelor, master, and PhD levels, with his lab seeking candidates interested in the intersection of HCI, geoinformatics, and ubiquitous computing technologies. He emphasizes creating a 'detox-free academic environment' that focuses on meaningful teaching and research outcomes rather than academic pressures. His group frequently collaborates with international researchers and institutions on projects spanning medical applications, space exploration interfaces, and public health technologies. The research laboratory led by Professor Schöning maintains strong interdisciplinary connections across multiple domains. Current projects include developing AI-powered wearables for blind and low vision users, exploring VR applications for emotional regulation, investigating navigation technologies' social impacts, and creating interfaces for space mission contexts. The lab's work on CubeSat control software and plant visualization for space greenhouses demonstrates their unique focus on extreme environment applications, while their research on citizen participation through generative AI shows engagement with contemporary societal challenges.

Claire Le Gouesمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Defect Repair
• +۵ مورد دیگر

Claire Le Goues is a Professor of Computer Science at Carnegie Mellon University, primarily affiliated with the Software and Societal Systems Department (S3D) within the School of Computer Science (SCS). She serves as the Associate Department Head for Faculty within S3D and leads the squaresLab research group. Le Goues also co-directs the REUSE@CMU summer program and teaches software engineering and program analysis at undergraduate, master's, and PhD levels. Her research spans software engineering and programming languages, with a particular focus on how to construct, maintain, evolve, improve/debug, and assure high-quality software systems. Le Goues has made significant contributions to automated program repair, program analysis, and defect detection. Her work often bridges theoretical foundations with practical applications, addressing real-world challenges in software development and maintenance. Le Goues' recent publications demonstrate a clear trend toward integrating large language models and generative AI with traditional software engineering techniques. Her research examines how these technologies can enhance program repair (BatFix, AdverIntent-Agent), vulnerability detection (Interpretable Vulnerability Detection Reports), and testing (LWDIFF for WebAssembly). This represents an evolution from her earlier foundational work in program repair (GenProg) toward leveraging contemporary AI advancements. She has mentored numerous students through her squaresLab research group and has been instrumental in developing educational programs that prepare the next generation of software engineers. Le Goues is also known for her advocacy for double-blind review processes in academic conferences, having implemented this approach when co-chairing the Symposium for Search-Based Software Engineering in 2014.

Ruben Taelmanمشاهده پروفایل

پژوهشگر

• Decentralization
• Linked Data Publishing
• Web Querying
• +۳ مورد دیگر

Ruben Taelman is a postdoctoral researcher at IDLab , Ghent University – imec, specializing in decentralization, Linked Data publishing, and querying. He develops open-source JavaScript libraries like the Comunica engine for decentralized data access and focuses on intelligent infrastructure for data publication and retrieval. His research bridges academic and industrial perspectives, addressing challenges in decentralized knowledge graphs, policy negotiation, and data governance. Key projects include Triple Storage for versioned RDF querying and contributions to the Solid ecosystem for user-centric data control.