Prof. Margret Keuper is a Professor in the Department of Computer Vision and Machine Learning at the Max Planck Institute for Informatics. Her research focuses on advancing machine learning and computer vision techniques, with an emphasis on model fairness, adversarial robustness, and multimodal interactions. She leads interdisciplinary projects exploring topics such as dataset analysis, generative models, and climate action through visual narrative analysis. Research Interests: Her work bridges theoretical foundations and practical applications in domains like adversarial training, image classification robustness, and robotics perception. She explores how vision-language models can be steered to align with human biases and develops methods for data-efficient learning and interpretability. Recent Contributions: Recent work includes FAIR-TAT (model fairness via adversarial training), VSTAR (video synthesis), and TikZero (zero-shot graphics program generation). Her publications in top venues like CVPR, ICCV, and ICLR highlight contributions to both methodological innovation and real-world impact. Collaborations: Works closely with researchers across Max Planck and academic partners, focusing on projects such as sensor layout optimization, climate discourse analysis via social media imagery, and domain-aware foundation model fine-tuning.
Professor Karen Soldatic is a leading academic in the School of Social Sciences at Western Sydney University, specializing in disability studies, social justice, and intersectional analysis. Her work critically examines the intersections of disability, migration, Indigenous rights, and digital technology within Global South contexts. Her research interests focus on Disability Studies , Social Justice , Artificial Intelligence and Disability , Indigenous Rights , and Migration Studies . Through participatory methodologies, she investigates how digital systems, welfare policies, and social structures create barriers for marginalized communities, particularly women with disabilities in low-income countries and Indigenous populations in Australia. Analysis of her recent publications reveals a strong emphasis on technology-facilitated violence against women with disabilities , digital inclusion frameworks , and intersectional resistance strategies . Her work consistently bridges academic theory with community action, focusing on practical interventions for systemic change. Professor Soldatic has secured significant research funding through projects including Walking my path: NSW Indigenous LGBTIQ+ peoples' experiences & aspirations (2023-2027) and Environmental Stewardship Resurgence in Walbanga Land . Her community engagement includes membership in the Australian Sociological Association and Diversty Arts Australia. Her academic contributions include 181 research outputs, 14 major projects, and active supervision of HDR candidates. She holds a PhD from the University of Western Australia and maintains strong connections with disability advocacy organizations including the Australian Federation of Disability Organisations.
Yong Zhang is affiliated with Tsinghua University's Research Institute of Information Technology in Beijing, China. His research focuses on machine learning, optimization algorithms, edge computing, and their applications in areas like time series analysis, federated learning, and sensor networks. He has collaborated on projects involving neural networks, scheduling problems, and privacy-preserving techniques. Education: Yong Zhang earned a PhD in Computer Science and Engineering from Fudan University in 2007. His academic career includes roles at institutions like the Chinese Academy of Sciences and the University of Hong Kong, reflecting a strong interdisciplinary background. Research Contributions: His work spans theoretical computer science, algorithm design, and applied machine learning. Notable areas include developing efficient scheduling algorithms for energy systems, creating robust federated learning frameworks for industrial demand forecasting, and advancing methods for sentiment analysis using multimodal data. He has also contributed to biomedical engineering through smartphone-based health monitoring systems. Collaborations: He frequently collaborates with researchers at institutions like the University of Electronic Science and Technology of China, Nanyang Technological University, and The Hong Kong Polytechnic University. Key projects involve data caching optimization in edge computing, distributed algorithms for dynamic networks, and combinatorial optimization problems. Labs & Future Work: His team explores cutting-edge topics in AI-driven systems, including trust-aware machine learning, distributed resource allocation, and real-time data processing for IoT applications. Current research emphasizes scalable solutions for complex optimization challenges in both academic and industrial settings.
Dr. Shivanjali Khare is an Assistant Professor in the Computer Science department at the University of New Haven, affiliated with the Tagliatela College of Engineering. She leads the SARI (Security and ARtificial Intelligence) Research Lab and teaches courses in Artificial Intelligence and Data Mining. Her research focuses on enhancing cybersecurity through hybrid cryptography, IoT data security, machine learning, and wireless sensor technologies to empower user protection in the digital age. Education: Ph.D. and M.S. in Computer Science from the University of Louisiana at Lafayette (2021 and 2016, respectively). Research Interests: IoT Data Security Hybrid Cryptography Systems Wireless Sensor Networks Big Data Sharing Mechanisms AI-Driven Cybersecurity Solutions Publications highlight contributions in IoT security protocols, cryptographic algorithm optimization, and machine learning applications. Notable work includes energy-efficient secure IoT drone systems (ESIoD) and ensemble learning for anomaly detection in smart homes. Recent outreach includes conducting cybersecurity seminars for senior citizens through the New Haven Free Public Library, demonstrating her commitment to societal impact and public education.
Associate Professor Rachel Burke is an Applied Linguist and TESOL educator in the School of Education at the University of Newcastle, affiliated with the College of Human and Social Futures. Her research focuses on linguistically and culturally diverse educational contexts, critical examination of policy impacts, and praxis-driven approaches to language education. She holds a PhD and has extensive experience in refugee education, forced migration studies, and equity in higher education. Research Interests: Dr. Burke’s work spans sociolinguistics, TESOL curriculum development, and educational equity for marginalized groups. Her recent projects explore the linguistic experiences of refugee/asylum seeker students, ethics in fragile research contexts, and digital empowerment for displaced learners. She employs critical discourse analysis to examine structural inclusion/exclusion mechanisms in education systems. Key Contributions: Her 2023 co-authored book Questioning Care in Higher Education challenges conventional definitions of academic service. Over 26 peer-reviewed articles and 12 book chapters address topics like EMI in Vietnam, mental health in teacher education, and policy barriers for asylum seekers. She has secured $418k in grants including the Scanlon Foundation’s Unity Works initiative supporting refugee employment. Grants & Impact: Leads projects like Refugee Mothers & Children Toolkit (Perpetual Limited, 2021) and co-leads the Co-designing Legal Literacy Resources grant (2024). Her work informs institutional policies on linguistic equity and asylum seeker access to education. Supervision: Supervises 12 current PhD students researching topics from EFL pedagogy in Vietnam to wellbeing in primary education. Her mentorship focuses on ethical research practices in sensitive contexts.
Dr. Lizhen Qu is a Lecturer at Monash University’s Faculty of Information Technology, part of the AIM Lab. His research focuses on robust and privacy-preserving neuro-symbolic methods for NLP and multimodal applications, including causal reasoning in dialogue systems, legal AI, digital health, and social NLP. Previously, he worked at Data61/CSIRO and completed his PhD at Saarland University and the Max-Planck-Institute for Informatics. Education: PhD in Computer Science from Saarland University and Max-Planck-Institute for Informatics. Research interests include integrating deep learning with logical reasoning, causal discovery, and ethical AI applications. He leads projects like TMLGenAI (Trusted Generative AI) and HARNESS (Neuro-Symbolic Systems), addressing model robustness and societal impact. Projects: TMLGenAI (2024–2026), HARNESS (2023–2027), and Accessible Data Exploration for Blind People (2023–2027) Contributions: Developed benchmarks like LazyReview and ACCESS, and co-organized ACL and IJCNLP workshops Research trends span causal discovery in NLP, federated learning for legal systems (e.g., FedLegal), and multimodal security. His work aligns with UN SDGs for innovation and health.
Dr. Kaie Maennel is a Lecturer at the School of Computer and Mathematical Sciences, part of the Faculty of Sciences, Engineering and Technology at the University of Adelaide. Her research focuses on Human Aspects of Cyber Security, including Cyber Awareness and Hygiene, Serious Games (Cyber Defence Exercises), and Learning Analytics in Cyber Training. She also investigates Usable Security, Information Security Culture, and Cybersecurity Risk Management. With over 20 years of corporate experience in Audit and Assurance at Deloitte, she holds professional certifications: ACCA, CIA, and Estonian CPA. Her research interests emphasize bridging cybersecurity education with practical applications, leveraging experiential learning and advanced analytics. She actively participates in high-profile cybersecurity initiatives like the NATO CCDCOE’s Locked Shields workshop, contributing to exercise design and assessment frameworks. Dr. Maennel is eligible to supervise Masters and PhD students as a Co-Supervisor, focusing on cybersecurity education, exercise methodologies, and human-centric security strategies. She prioritizes interdisciplinary approaches and real-world impact through collaborations with industry and academic partners. Her work spans cyber defense exercise ontology development, cultural adaptation of cybersecurity programs, and leveraging behavioral genetics insights. Recent trends in her publications highlight the integration of AI into cybersecurity training and the critical role of human factors in mitigating cyber risks.
Prof. Dr. Zeki Bayram is a full Professor and current Chairman of the Computer Engineering Department at Eastern Mediterranean University (EMU). He has served as the founding chairman of the Internet Technologies Research Center (2006) and chaired the departmental ABET committee from 2010 to 2023. His academic contributions span semantic web services, mobile payment systems, and XML-based technologies. Founded Cybersoft Bilişim Teknolojileri Limited, a dormant software company in North Cyprus Active in academic service, including thesis supervision and editorial roles Teaches courses on programming languages, automata theory, and software tools Research focuses on semantic web service composition, secure payment schemes, and declarative programming paradigms. His work integrates logic programming, constraint solving, and ontology engineering. Prof. Bayram has published extensively in journals and conferences since the 1990s, with notable contributions to formal methods in service-oriented architectures.
May Britt Drugli is a Professor at the Regional Centre for Child and Youth Mental Health and Child Welfare, affiliated with NTNU's Faculty of Medicine and Health Sciences and Department of Mental Health. Her research focuses on early childhood care, student-teacher relationships, child mental health, and intervention research. She has contributed to numerous publications addressing childcare quality, child well-being, and developmental outcomes. Her work includes studies on cortisol levels in toddlers in childcare, the impact of professional development programs like 'Thrive by Three,' and the importance of play-based learning in educational policies. She frequently collaborates with educators and policymakers to translate research into practical pedagogical strategies. Key areas of exploration include transition processes for young children entering childcare, the role of teacher-child interactions, and addressing socioeconomic disparities in early education. Her research emphasizes evidence-based practices to enhance child development and mental health.
Maria Cristina Morales is a Professor in the Department of Sociology & Anthropology at the University of Texas at El Paso, College of Liberal Arts . Her research critically examines how Latinx ethnicity intersects with social statuses and institutions, particularly along the U.S.-Mexico border , using quantitative and qualitative methodologies while prioritizing reflexive and theory-driven approaches . Education: PhD in Sociology, Texas A&M University (2004) Research Focus includes structural violence at the U.S.-Mexico border, environmental hazard perceptions near border ports, and gender/sexuality dynamics . Her publications and presentations bridge border studies, immigration, labor rights, and environmental justice . Recent projects include decolonizing survey research and Latinxs on the Margins (forthcoming). Scientific Awards include the Norma Williams Distinguished Service Award (2024), UT Regents Outstanding Teaching Award (2016), and multiple recognitions from the Southwestern Sociological Association and Building Scholars programs. Grants highlight her leadership in National Science Foundation and North American Development Bank funded projects addressing sociological issues, air quality assessment , and data accessibility for vulnerable communities.
Jen'nan Ghazal Read is a Professor of Sociology at Duke University with multiple cross-appointments as a Research Professor of Global Health at the Duke Global Health Institute and Professor in the Sanford School of Public Policy. She is also a Faculty Research Scholar at Duke's Population Research Center. Her interdisciplinary work bridges sociology, public health, and policy studies with a focus on ethnic diversity within racial categories. Professor of Sociology, Trinity College of Arts & Sciences (2018-Present) Research Professor of Global Health, Duke Global Health Institute (2018-Present) Professor in the Sanford School of Public Policy (2025-Present) Faculty Research Scholar, Duke Population Research Center (2010-Present) Dr. Read is an internationally renowned scholar who challenges conventional approaches to racial and ethnic categorization in health research. Her work demonstrates substantial health disparities among ethnic groups within broad racial categories like 'White,' particularly focusing on Middle Eastern Americans. She has conducted groundbreaking research showing that using non-Hispanic Whites as a reference category masks important health inequalities among White subgroups, including immigrants from different regions. Her expertise on U.S. Census categories contributed to recent revisions of federal standards for collecting race and ethnicity data. Her publication record reveals a consistent focus on health disparities, with recent work examining immigrant health advantages among White populations, discrimination effects on mental health, and the unique health experiences of Arab Americans. Dr. Read's research spans multiple methodologies including quantitative analysis of national datasets and qualitative interviews with Muslim American women. Bass Chair and Bass Society of Fellows (2019) Howard D. Johnson Teaching Award (2020) Outstanding Teaching Assistant of the Year, University of Texas (1999) Dr. Read has secured significant research funding including the 2022 Census Study Research grant, the ACCESS Arab American Research Initiative, and the Thriving after Surviving project focused on Muslim refugee students. She has been featured in major media outlets including The New York Times, NPR, and Al Jazeera English, and has presented at prestigious institutions worldwide including the National Academy of Medicine, the U.S. Census Bureau, and universities across Europe and the Middle East.
Shahin Jabbari is an Assistant Professor in the Computer Science Department at the College of Computing & Informatics, Drexel University, where he is a member of the EconCS research group. His research lies at the intersection of machine learning, game theory, and algorithmic fairness, with a focus on ethical AI and its societal implications. Prior to Drexel, he was a CRCS postdoctoral fellow at Harvard University's School of Engineering and Applied Sciences, hosted by Milind Tambe, and affiliated with the EconCS group. Education: PhD in Computer and Information Science, University of Pennsylvania (2013–2019), advised by Michael Kearns Master's in Computing Science, University of Alberta, advised by Robert Holte and Sandra Zilles Bachelor's in Computer Engineering, Sharif University of Technology His research interests center on machine learning, algorithmic fairness, and game theory, particularly focusing on how AI systems can be designed to be more equitable, interpretable, and robust. He investigates ethical aspects of algorithmic decision-making, aiming to ensure AI technologies contribute positively to society. His work often integrates human behavior modeling and experimental validation, especially in cybersecurity and public health domains. His recent publications span top venues including ICML, NeurIPS, AAAI, AAMAS, PNAS, and TMLR. The research trends show a consistent focus on fairness in AI, explainability, robustness, and strategic interactions in complex systems. Topics include fair influence maximization, adaptive phishing training, cyber deception games, and ethical machine learning frameworks. These works reflect a multidisciplinary approach combining theoretical rigor with real-world applicability. Scientific Awards and Recognitions: Best Paper Finalist, AAMAS 2021 Best Paper, GameSec 2020 Spotlight Presentation, ICML 2021 Best Paper, KI 2012 Shahin Jabbari actively contributes to the academic community through advising, teaching, and service. He teaches graduate courses such as CS 589: Responsible Machine Learning and CS 590: Privacy. He has served on the senior program committees of ICML and NeurIPS, is an Action Editor for TMLR, and has reviewed for numerous top-tier conferences and journals. He mentors students through research projects and invites prospective PhD candidates to apply through Drexel’s formal channels. He is involved in the Drexel Computer Science Theory Reading Group and contributes to advancing responsible AI practices. He is affiliated with the EconCS group at Drexel, which focuses on economic and computational aspects of AI, including game theory, mechanism design, and multi-agent systems. His lab integrates tools from machine learning, behavioral modeling, and optimization to develop AI systems that are not only intelligent but also fair and trustworthy. Future work is expected to further explore human-AI collaboration, ethical AI deployment, and policy-aware algorithm design.
Daniel Frumin is an Assistant Professor in the Department of Fundamental Computing Science at the University of Groningen, affiliated with the Bernoulli Institute. His research focuses on Logic, Type Theory, and Program Verification, with a particular emphasis on formal methods for concurrency, type systems, and homotopy type theory. He has contributed to foundational work in denotational semantics, modular programming language design, and mechanized verification of concurrent systems. His expertise includes the application of logical frameworks to concurrency models, such as ReLoC (Relational Logic for Concurrent Programming) and the integration of type theories with operational semantics. Recent work explores guarded interaction trees, interval domains in homotopy type theory, and compositional security properties for fine-grained systems. Frumin has published extensively in top-tier venues like ESOP, CONCUR, and ACM POPL, with peer-reviewed contributions on topics ranging from bunched implications in session-based concurrency to formal verification of data structures like concurrent queues. His research often bridges theoretical computer science and practical formal verification, leveraging tools like Coq for mechanized proofs. Collaborations include projects with institutions such as Aarhus University (Denmark) and the University of Bologna, focusing on univalent foundations, categorical semantics, and security verification. His work is supported by grants from the Dutch Research Council (NWO) and industry partnerships like Meta's Folly Library verification efforts. Labs/Teams: Active contributor to the Bernoulli Institute's Formal Methods Group and the Univalent Foundations initiative. His research group specializes in applying type-theoretic and categorical methods to concurrency and verification challenges.
Mohamed Sarwat is an Associate Professor at Arizona State University specializing in databases , spatial data management , and recommender systems . His research focuses on GeoSpark —a cluster computing framework for spatial data—and its extensions like GeoSparkViz for visualization and GeoSparkSim for traffic simulation. Key Contributions: LARS* (Location-Aware Recommender System), Horton* (Graph Reachability), Sindbad (GeoSocial Platform), and Riso-Tree (Graph Database Indexing) Research Themes: Integration of spatial/temporal data with machine learning, efficient indexing for big geospatial datasets, and scalable frameworks for mobility data science His work spans collaborations with 23+ co-authors across institutions like University of Minnesota, University of Melbourne, and University of Salzburg. Current projects emphasize GeoTorchAI —a spatiotemporal deep learning system—and mobility data science infrastructure.
Prof. Martin Teufel is a Professor at the University of Teacher Education Styria, Austria, affiliated with the Institute for Digital Media Education. He specializes in educational technology with a focus on mobile learning, digital competency, and innovative teaching methodologies. His work includes developing MOOC-based learning systems and analyzing student digital preparedness. Key projects include the Styrian University Conference digital competency analysis and the Digital Learning Lab initiative. He holds a BEd from the University of Graz and actively contributes to teacher training programs integrating emerging technologies. Research interests span digital pedagogy, seamless learning environments, and computational thinking tools like BBC micro:bit. His publications highlight patterns in online learning behaviors and institutional digital transformation strategies. He advises on educational technology policy and has led cross-institutional studies on student readiness for digital education. His work often bridges theory and practice through collaborative formats like the Hochschuldidaktik-Café for educators' professional development. Teaching responsibilities include courses on digital media in education and technology-enhanced learning design. He manages educational technology projects and serves as a consultant for digital learning infrastructure. His GPG public key (F361ADE9) indicates active engagement in secure academic communication.
