جست‌وجوی استاد و پژوهشگر

Yixin Zouمشاهده پروفایل

استادیار

• Human-Centered Security
• Privacy Studies
• Cross-Cultural Security Research
• +۳ مورد دیگر

Dr. Yixin Zou is a tenure-track Assistant Professor and Group Leader of the Human-Centered Security and Privacy group at the Max Planck Institute for Security and Privacy (MPI-SP) in Bochum, Germany. They are also a Principal Investigator at Ruhr University Bochum's CASA Cluster of Excellence. Their research focuses on making technologies safer and equitable for underserved communities, including accessibility challenges for deaf individuals and older adults, cross-cultural security practices, and responsible AI development. They lead interdisciplinary collaborations with legal scholars and social scientists to translate research into real-world impacts. Zou holds a Ph.D. in Information from the University of Michigan (advised by Florian Schaub), recognized with an ACM SIGCHI Outstanding Dissertation Award. Their work is funded by MPI-SP, DFG, Google, and Meta. Notable grants include a Google Academic Research Award on safeguarding emerging adults from short-form video scams and a Meta grant studying digital privacy expectations. Research interests include differential access to security tools, cross-cultural digital privacy norms, and designing interventions to address algorithmic discrimination. They prioritize global perspectives, contrasting WEIRD (Western, Educated, Industrialized, Rich, Democratic) and non-WEIRD populations. Recent projects examine online fraud prevention among Chinese seniors and trauma-informed computing approaches. Zou has received multiple awards, including Best Paper Honorable Mentions (ACM CHI 2025/2020/2019) and a Distinguished Paper Award (SOUPS 2018). Their group's work bridges academia and practice through partnerships with companies, NGOs, and policymakers. Current initiatives focus on explainable hardware (XHW) and mitigating image-based sexual abuse on online platforms. Students and collaborators include researchers from computer science, law, and social sciences. Former members have moved to industry and academia roles. Zou advises via the MPI-SP doctoral programs and offers internships through the CS@Max Planck program.

Eleni Straitouriمشاهده پروفایل

استاد

• Machine Learning
• Causal Inference
• Large Language Models
• +۴ مورد دیگر

Eleni Straitouri is a Professor at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany, where she leads research at the intersection of artificial intelligence safety and human-centered decision systems. Her work bridges theoretical machine learning with practical applications in high-stakes environments requiring rigorous uncertainty quantification and causal reasoning. Her primary research focuses on causal inference in large language models , counterfactual prediction sets , and human-AI complementarity . She develops methods to control algorithmic harm through counterfactual reasoning, enhances model evaluation via conformal prediction, and designs decision support tools that leverage human expertise. Current projects address critical challenges in LLM safety, including bias detection through coupled token generation and harm mitigation in medical/operational decision systems. Analysis of her 13 publications (2021-2025) reveals an evolving trajectory from reinforcement learning foundations toward cutting-edge LLM safety frameworks. Her work consistently integrates causal methods with human factors, producing practical tools for reliable AI deployment across healthcare and operational domains. Recent NeurIPS/ICML publications demonstrate increasing influence in trustworthy AI research. Best Paper Award, Workshop on AI and HCI (ICML), 2023 Spotlight Paper (top 3.5%), ICML 2024 Dr. Straitouri maintains active collaborations with Manuel Gomez-Rodriguez's research group, evidenced by co-authorship on 100% of her recent publications. While specific grant funding isn't detailed in available materials, her work aligns with MPI-SWS's focus on software systems for societal benefit. No information about academic advising or laboratory infrastructure was found in the provided text.

• Computer-Supported Cooperative Work (CSCW)
• Human-Computer Interaction (HCI)
• Ethnography
• +۷ مورد دیگر

Peter Tolmie is a Researcher at the University of Siegen's Faculty III Business Informatics and New Media. He holds a PhD in Sociology from Lancaster University (2003) and has extensive experience in ethnography and CSCW research. His career includes roles at Xerox Research Center Europe (2000-2002) and the University of Nottingham (2010-2017). Education: Bachelor's Degree in Independent Studies (First Class Honors), Lancaster University (1997) PhD in Sociology, Lancaster University (2003) Research Interests: Tolmie focuses on Computer-Supported Cooperative Work , Human-Computer Interaction , and ethnography . His work explores digital transformation in healthcare, activism, manufacturing, and rural communities. Key themes include accountability in AI, content moderation in conflict zones, and the design of inclusive technologies. Articles Trends: Recent work addresses challenges in social robotics, digital inclusion in marginalized regions, and ethical design in voice assistants. His studies often combine ethnographic methods with participatory approaches to address systemic inequalities and technological barriers. Awards: Best Paper Award at CHI 2017 (with Rob Proctor et al.) Grants & Advising: Tolmie has contributed to projects funded by the EU and German research initiatives, including the European Digital Innovation Hub South Westphalia (EDIH) . He advises on interdisciplinary research at the intersection of technology and socio-cultural contexts, particularly in healthcare and rural development. Labs & Teams: Involved in the Fab Lab Siegen and PRAXLABS , promoting hands-on innovation and community-driven tech solutions. Collaborates with global teams on projects like Shielding or Silencing? and Robots in Care .

Tim Polzehlمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Speech Technology
• Machine Learning
• +۵ مورد دیگر

Tim Polzehl is a Senior Researcher at the German Research Center for Artificial Intelligence (DFKI) in Berlin's Speech and Language Technology (SLT) Department. He holds a PhD in technical communication sciences from TU Berlin (2014), focusing on automatic personality prediction from speech/user data. Previously, he led the Next-Generation Crowdsourcing group as a postdoc at TU Berlin's Quality and Usability Lab, overseeing projects like the Crowdee crowdsourcing platform. His current research spans speech anonymization, disinformation detection, deepfake analysis, and AI ethics. He actively supervises doctoral students and collaborates on EU-funded projects. Education: PhD in Technical Communication Sciences, TU Berlin (2014) Studies in Technical Communication Sciences, TU Berlin Research Interests: Focuses on applying AI to speech technology, privacy-preserving systems, and combating disinformation through machine learning. Specializes in multimodal systems, ethical AI deployment, and human-AI collaboration frameworks. Publications: Recent work emphasizes regulatory challenges of AI (e.g., EU AI Act compliance), privacy in clinical speech data, and personality-aware chatbots. Key areas include disinformation detection via LLMs and technical cybersecurity for speech systems. Grants & Awards: Participated in BMBF-funded leadership programs and EIT-Digital EU projects. Current projects involve developing frameworks for ethical AI integration in critical applications like elections. Labs/Teams: Leads SLT Department initiatives on autonomous AI agents and voice cloning at DFKI. Collaborates with TU Berlin's Quality and Usability Lab on ongoing research.

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

Cécile Paris is a researcher at CSIRO , focusing on interdisciplinary applications at the intersection of Artificial Intelligence , Cybersecurity , and Human-AI Collaboration . Her work spans domains such as biomedical informatics, social media analysis, and robotics. Research Interests: Developing collaborative frameworks for human-AI teams Explainable AI in cybersecurity Trust modeling in social networks Fake news detection via temporal and graph-based networks Image captioning with multimodal learning Stance classification across domains Article Trends: Recent publications emphasize adaptive alert prioritization (2025), systematic reviews on cybersecurity challenges (2024), and foundational work in NLP for epidemic intelligence (2018-2020). Key methodologies include graph neural networks, transformer models, and adversarial training.

• Statistical Relational Artificial Intelligence
• Human-aware AI
• Explainable AI
• +۱۲ مورد دیگر

Tanya Braun is a Junior Professor in the Institute of Computer Science at the University of Münster, Department of Mathematics and Computer Science. She leads the Data Science research group, focusing on statistical-relational AI, human-aware AI, and text understanding. Her work bridges formal AI methods with real-world applications in healthcare, digital humanities, and public sector systems. Education: Bachelor's and Master's in Computational Informatics, Hamburg University of Technology Doctorate in Computer Science, University of Lübeck (2020), thesis: 'Rescued from a Sea of Queries - Exact Inference in Probabilistic Relational Models' Her research centers on probabilistic inference in relational domains , with a focus on lifted inference techniques that exploit symmetries to scale reasoning. She investigates human-aware AI , particularly how AI systems can reconcile learned models with human expectations to improve explainability and trust. Her work on text understanding addresses challenges in data-scarce settings such as digital humanities, where traditional large language models fail. She has developed methods for identifying and enriching subjective content descriptions, topic modeling in specialized domains, and feedback-driven model improvement. The 15 most recent publications highlight a strong trajectory in lifted inference, model compression, privacy-preserving AI, and explainability . Her work integrates formal AI foundations with practical concerns in high-stakes domains like healthcare. She frequently publishes in top venues such as AAAI, IJCAI, ECAI, and Artificial Intelligence, often in collaboration with Ralf Möller, Marcel Gehrke, and Jan Speller. Scientific Awards: No specific awards listed in the provided text. Tanya Braun actively advises students and leads the HAPPI project, which focuses on human-AI model reconciliation using lifted probabilistic inference. She has supervised multiple theses and mentored researchers including Jan Speller (PostDoc), Nazlı Nur Karabulut, and Sagad Hamid. She has secured funding from the Ministry of Culture and Science of North Rhine-Westphalia for her research. She is deeply involved in academic service: serving as program co-chair for KI 2025, guest-editing special issues in journals like Künstliche Intelligenz and Annals of Mathematics and Artificial Intelligence , and organizing major conferences including ICCS and KR. Labs and Teams: She leads the Data Science Group at the University of Münster, which conducts research in AI, probabilistic modeling, and data science. The group is actively involved in teaching and mentoring students in advanced AI topics.

Olga Levinaمشاهده پروفایل

استاد

• Ethical Issues of Digitalization
• Business Process Management
• Low-Code Development
• +۲ مورد دیگر

Prof. Dr. Olga Levina serves as Professor of Business Informatics at Brandenburg University of Technology (BTU), Department of Economics, where she bridges technical systems design with ethical governance in digital transformation. Her institutional leadership includes contributions to DIN working groups on Responsible AI and UNESCO's "Artificial Intelligence for more gender equality and against discrimination" guideline. Her educational background includes: Industrial Engineering with technical specialization in Information and Communication Systems (Technical University of Berlin and LUISS Rome) Doctorate in Network Analysis (TU Berlin) Levina's research critically examines ethical digitalization , business process management , and low-code development through participatory frameworks. She investigates how socially-aware information systems can mitigate digital inequality while advancing sustainability. Current projects analyze dark patterns in consent interfaces and AI's impact on journalistic values, emphasizing transparency and stakeholder inclusion as foundational principles. Her 15 most recent publications (2021-2025) reveal three dominant trajectories: (1) operationalizing ethics in software design through assessment tools and pipelines, (2) analyzing low-code platforms' organizational impact, and (3) exposing biases in algorithmic systems via empirical studies of dark patterns and recommender systems. This work consistently connects technical implementation with societal consequences. Levina actively supervises Master's theses through structured processes requiring English proficiency and research proposals. Her Ethical and Legal Aspects of Digitalization course generates publishable student research on topics like cookie consent dark patterns and AI sentiment analysis. She leads the InnoWest project on sustainable IT development while maintaining roles as journal/conference reviewer and DIN working group contributor. Her research group produces empirical studies through student projects examining digital ethics in real-world contexts, including cross-national analyses of cookie banners and values in messenger apps. Current work explores "naming as framing" in sustainability discourse and machine learning system auditing.

Christian Meskeمشاهده پروفایل

استاد

• Socio-technical Systems
• Artificial Intelligence
• Digital Transformation
• +۷ مورد دیگر

Prof. Dr. Christian Meske is a faculty member at Ruhr University Bochum , holding the Chair of Socio-technical System Design and Artificial Intelligence since September 2021. He previously served as an Assistant Professor at Freie Universität Berlin (2017–2021) and conducted postdoctoral research at the University of Duisburg-Essen (2015–2017) and University of Münster (2012–2015). Education: Diploma in Business Administration (Diplom-Kaufmann), University of Potsdam His research focuses on the intersection of Artificial Intelligence , socio-technical systems , and digital transformation . Key areas include Explainable AI , Digital Twins , AI Governance , and Human-AI Interaction . His recent publications analyze algorithmic transparency, digital nudging, and affordance theory in AI systems. Notable trends in his work include: Foundational AI models and their ethical implications Relational quality in social networks Feedback mechanisms in mobile health applications Philosophical perspectives on digital twin perception Design principles for AI-based decision support Scientific accolades include: Best Paper Award at ICAART (2022) ICIS Best Short Paper in Health IS (2020) AIS Best Information Systems Publication of the Year (2016) Elite Award for Excellence (European University Information Systems, 2015) He has contributed to projects like sciebo – the Campuscloud for NRW and supervised student initiatives such as 'Mobile Learning.' Meske is an active member of the Association for Information Systems , German Informatics Society , and other academic bodies, focusing on computer-supported cooperative work and digital ethics.

• Agent Technology
• Artificial Intelligence
• Autonomous Driving
• +۹ مورد دیگر

Prof. Dr.-Ing. habil. Dr. hc Sahin Albayrak is a distinguished academic and entrepreneur at the Technical University of Berlin , where he founded and directs the Distributed Artificial Intelligence Laboratory (DAI Laboratory) . He leads the Agent Technologies in Business Applications and Telecommunications research group and serves as founding member of Deutsche Telekom Laboratories (2004) and European Center for ICT (EICT) (2005). As initiator of Connected Living e.V. (2009) and managing director of German-Turkish Advanced Research Center for ICT (2012), he bridges international collaborations. He also founded IOLITE GmbH (2014) and other startups. Research Focus: Agent technology, autonomous driving, smart cities, cyber security, machine learning, and AI applications in energy systems Awards: Federal Cross of Merit (2014), multiple Best Paper Awards Leadership: Director of DAI Laboratory, head of research group at TU Berlin His 20+ recent publications (2022-2025) demonstrate expertise in agent-based architectures , smart mobility solutions , context-aware computing , and AI-driven security systems . Notable trends include integrating large language models into database interfaces, optimizing multi-agent coordination for logistics, and advancing explainable AI through feature attribution frameworks. Scientific Contributions: Recipient of Germany's Bundesverdienstkreuz for German-Turkish cooperation Best Paper Award at Smart Grid Architectures conference

Debayan Banerjeeمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Explainability
• Machine Learning
• +۵ مورد دیگر

Dr. Debayan Banerjee is a Researcher at the Institute for Business Information Systems (IIS) and part of the Professorship for Business Informatics, especially Artificial Intelligence and Explainability at Leuphana University Lüneburg. His work bridges academic research with practical applications in knowledge management, network science, and AI systems. Institute: Institute for Business Information Systems (IIS) Professorship: Business Informatics, Artificial Intelligence and Explainability Location: Universitätsallee 1, C4.308b, Lüneburg (21335) Email: debayan.banerjee@leuphana.de Research interests focus on knowledge graph integration, hybrid intelligence systems, and explainable AI. His projects include USIN5G, ARDIAS, and INSTANT, emphasizing human-AI collaboration and scholarly data accessibility. Recent publications highlight SPARQL translation automation, hybrid question answering frameworks, and environmental impact analysis of language models. Collaborative work spans DBpedia-Wikidata interoperability, DBLP knowledge graph applications, and graph embeddings for QA systems. Education and advising : Mentored students include Mathias Gross, Fatemeh Ghoochani, and Soham Majumder, focusing on final theses related to AI-driven data extraction and knowledge graph development.

• Trustworthy Machine Learning
• Program Synthesis
• Formal Verification
• +۳ مورد دیگر

Osbert Bastani serves as an Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania. He leads the trustml@Penn research group and holds affiliations with the ASSET, PRECISE, and PRiML research centers, as well as PLClub. His academic work centers on developing reliable and interpretable artificial intelligence systems through interdisciplinary approaches combining programming languages, formal methods, and machine learning. He earned his Ph.D. in Computer Science from Stanford University under the guidance of Alex Aiken, followed by a postdoctoral position at MIT working with Armando Solar-Lezama. This foundation in both theoretical computer science and practical systems has shaped his research trajectory. Bastani's primary research areas include Trustworthy Machine Learning (focusing on robustness against adversarial attacks, fairness in algorithmic decision-making, and explainable AI), program synthesis, and formal verification. His recent publications address critical challenges in large language models, such as defending against jailbreaking attacks and ensuring trustworthy retrieval-augmented generation. He also develops methods for conformal prediction under distribution shifts and neurosymbolic program synthesis for complex tasks like web question answering. His teaching portfolio features advanced courses including CIS 7000: Trustworthy Machine Learning and CIS 4190/5190: Applied Machine Learning, where he integrates cutting-edge research into the curriculum. Through his research group, he mentors graduate students on projects spanning neurosymbolic programming, uncertainty quantification, and fairness in sequential decision-making. As an active member of Penn's research ecosystem, Bastani contributes to the ASSET center's mission of building secure systems, PRECISE's work on cyber-physical systems, and PRiML's machine learning initiatives, while collaborating with PLClub on programming language innovations.

Muhammad Bilal Zafarمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Fairness in AI
• +۳ مورد دیگر

Professor Muhammad Bilal Zafar holds the Chair of AI and Society within the Department of Computer Science at Ruhr University Bochum. He maintains key affiliations with the Research Center for Trustworthy Data Science and Security, Cluster of Excellence CASA (as Principal Investigator), and the Horst Görtz Institute for IT Security. His research program centers on human-centric artificial intelligence with core expertise in: Fairness algorithms for bias mitigation Explainable AI systems Robustness testing in human-AI interaction Trustworthy machine learning deployment Professor Zafar develops technical solutions addressing challenges that emerge when AI models interact with human users across various application domains. Prior to his academic appointment, he gained significant industry experience as Senior Applied Scientist at Amazon Web Services (AWS) in Berlin and Research Scientist at Bosch Center for Artificial Intelligence in Renningen. His educational foundation includes a PhD from the Max Planck Institute for Software Systems (MPI-SWS) and Saarland University under the supervision of Krishna P. Gummadi and Manuel Gomez Rodriguez. He leads the AI and Society research team at Ruhr University Bochum, which investigates the societal implications of artificial intelligence while developing concrete technical approaches for responsible AI development. Prospective researchers can find current opportunities through the team's dedicated information page.