Dr. Joey van Angeren is an Associate Professor at the KIN Center for Digital Innovation within the School of Business and Economics at Vrije Universiteit Amsterdam. He holds a PhD in Innovation Management from Eindhoven University of Technology, an MSc (cum laude) in Business Informatics from Utrecht University, and a BSc in Information Science from Utrecht University. His research focuses on the intersection of strategy and technology, particularly digital platforms, with publications in journals like Strategic Management Journal and Organization Science. He has been recognized with multiple Best Reviewer Awards from the Academy of Management's TIM Division (2018, 2019, 2024) and his dissertation was a finalist for the Best Dissertation Award. Research interests include platform ecosystems, competitive strategy, and optimal distinctiveness in digital markets. He teaches courses on digital innovation, information systems, and research methods, including 'Introduction to Digital Innovation' and 'Analyzing Digital Data in Business Research'. Education: PhD in Innovation Management, Eindhoven University of Technology MSc (cum laude) in Business Informatics, Utrecht University BSc in Information Science, Utrecht University Projects: Active in the EDIH NWNL project focusing on SME digitalization, AI transformation, and High Performance Computing. Awards: 3 Best Reviewer Awards (TIM Division, Academy of Management), Dissertation Finalist (2020), and Student Paper Award (2016). Grants: Multiple grants including Best Reviewer recognitions and project funding. His research explores platform governance, venture capital impacts, and complementor dynamics. Recent articles analyze M&A activity in platform ecosystems, moral motives in governance, and optimal revenue model strategies. He actively participates in workshops and lectures on AI and digital innovation.
Annette ten Teije is a Full Professor at Vrije Universiteit Amsterdam (VU Amsterdam) with appointments in the Faculty of Science, Artificial Intelligence department, the Network Institute, and the Knowledge Representation and Reasoning research group. Her academic career spans several decades with a strong focus on the intersection of artificial intelligence and healthcare applications. Professor ten Teije's research interests center around Knowledge Representation, particularly in medical contexts. Her work bridges multiple domains including Semantic Web technologies, Ontology development, Neuro-Symbolic AI systems, and Clinical Decision Support. She has made significant contributions to the formalization of clinical guidelines, handling multimorbidity in healthcare systems, and developing design patterns for hybrid AI systems. Her research integrates machine learning with symbolic reasoning to create explainable and reliable AI systems for healthcare applications. Analysis of Professor ten Teije's recent publications reveals a strong trajectory toward neuro-symbolic AI approaches that combine the strengths of neural networks and symbolic reasoning. Her work increasingly focuses on explainability in medical AI systems, with numerous publications on feature selection, interaction detection, and narrative-based understanding. She has developed frameworks for shared understanding in multi-agent systems and created design patterns specifically for medical decision-making contexts. Her research consistently bridges theoretical AI advances with practical healthcare applications. Professor ten Teije has supervised 5 PhD theses as indicated in her academic profile and teaches courses including "AI in Health" and "Machine Learning and Reasoning for Health" for the 2024-2025 academic year. Her academic contributions extend to editorial work, including serving as editor for conference proceedings and special issues on Knowledge Representation for Healthcare Processes.
Deborah Lupton is a Professor at UNSW Sydney, holding positions in the Centre for Social Research in Health and the Social Policy Research Centre. She leads the Vitalities Lab and serves as UNSW Node Leader, Health Focus Area Leader, and People Co-Leader for the Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S). Her expertise spans medical sociology, digital health, public health, and qualitative methods. She has authored/co-authored 20 books and over 240 articles/chapters, including influential works like Self-Tracking, Health and Medicine and Digital Sociology . Education: BA, LittB, MPH, PhD, FASSA, FAHMS, FRSN. She has received prestigious awards such as the 2024 Fellowship from the Australian Academy of Health and Medical Sciences, a 2023 Honorary Doctorate from University of Skövde, and the 2021 Australasian Council of Deans Award. Her research projects include investigations into digitized school health, automated decision-making, and pandemic-related health practices. Grants and Collaborations: Lupton has led/co-investigated numerous grants, including ARC Discovery Projects (2015–2018, 2019–2020), Swedish Foundation grants (2016–2018, 2019–2021), and the Medical Research Future Fund project 'Cardiac AI'. She collaborates internationally with institutions like RMIT, Monash University, and Aarhus University. Research Supervision: Available to supervise postgraduate students in areas of health, digital culture, and sociocultural theory. She emphasizes creative methods in health education and has been involved in projects like 'Creative Approaches to Health Education' and 'Re-humanising automated decision making'.
Dr. Robert A Jenders is a Health Sciences Clinical Professor in the Department of Medicine at the University of California Los Angeles (UCLA) School of Medicine. He serves as a Senior Associate Director for the UCLA Clinical and Translational Science Institute (CTSI), where he coordinates CTSI activity on the Charles Drew University campus. Dr. Jenders also chairs the Healthcare Information Technology Research (HITR) study section of the US Agency for Healthcare Research and Quality (AHRQ) and holds leadership roles on the CTSI Council and Quality and Efficiency Council. His extensive experience bridges clinical medicine and health informatics, with active contributions to biomedical informatics standards development. Dr. Jenders' educational background includes: BS in Computer Science from Marquette University (1984) MD in Medicine from University of Wisconsin (1988) Residency in Internal Medicine from University of Wisconsin (1991) MS in Computer Science from Northeastern University (1993) Fellowship in Medical Informatics from Harvard University/Massachusetts General Hospital (1994) Dr. Jenders' research focuses on the development and application of health information technology standards, particularly in clinical decision support systems, electronic health records, and patient care registries. His work centers on the Arden Syntax standard, FHIR (Fast Healthcare Interoperability Resources), and other healthcare interoperability frameworks. He explores how standardized knowledge representation can improve clinical decision support, data interoperability, and computable knowledge sharing across healthcare systems. His research has significant implications for improving healthcare quality through better information systems and has influenced national standards for health information technology. Dr. Jenders' recent publications demonstrate a consistent focus on healthcare standards, particularly the Arden Syntax for clinical decision support and its integration with modern standards like FHIR. His work spans theoretical exploration of knowledge representation frameworks, practical implementation challenges, and evaluation of standards for clinical decision support. A notable trend is his increasing focus on interoperability between different healthcare information standards and how they can work together to create more effective clinical decision support systems. His research bridges computer science, medical informatics, and clinical practice, with applications across healthcare delivery, research, and quality improvement. Dr. Jenders has received numerous prestigious honors, including: Fellow of the American Medical Informatics Association (2019) Fellow (elected) of Health Level Seven International (2019) Distinguished Poster Award from American Medical Informatics Association (2016) Book of the Year Award from Healthcare Information and Management Systems Society (2012) Fellow (elected) of the American College of Medical Informatics (2005) Book of the Year Award from Healthcare Information and Management Systems Society (2005) Fellow (elected) of the American College of Physicians (2004) As an educator and mentor, Dr. Jenders serves on the KL2 and TL1 programs, advises on the KL2 program, and is a member of the CREST Committee for the Workforce Development program. He also mentors senior medical students at Charles Drew University, which primarily serves African American and Latino students. His research is supported by multiple NIH grants, including the UCLA Clinical Translational Science Institute (UL1TR001881), CDU-CRECD Mentored Postdoctoral Training program (R25MD007610), and the Accelerating Excellence in Translational Science (AXIS) initiative (U54MD007598), where he serves as Co-Investigator on all three projects. Dr. Jenders leverages his leadership role in Health Level Seven International, the premier standards development organization for health information technology, to ensure that his work with the CTSI is fully standards-based. This approach promotes interoperability and generalizability of information system solutions. He assists CTSI units in requirements analysis, data modeling, and system interfaces necessary to build and study the use of information technology infrastructure for collecting laboratory and survey data. His work connects clinical practice with informatics infrastructure to advance translational science.
Josiah Wang is a Senior Teaching Fellow in the Department of Computing at Imperial College London, where he also serves as the degree coordinator and admissions tutor for the MSc Computing program. He teaches Python Programming and Introductory Machine Learning courses. Previously, he held postdoctoral research positions at Imperial College London and the University of Sheffield, focusing on Artificial Intelligence with specializations in Computer Vision and Natural Language Processing. He earned his PhD in Computer Science from the University of Leeds (2013), advised by Katja Markert and Mark Everingham. His research explored cross-modal learning, including pioneering work on learning object recognition from textual descriptions and multimodal machine translation. Notable contributions include the MultiSubs dataset and methods for phrase localization without paired training examples. Education: PhD in Computer Science, University of Leeds (2013) MSc in Computing, University of Leeds (2007), supervised by David Hogg Research Interests: Josiah's work bridges AI and human cognition, emphasizing systems that learn from limited data and integrate multiple modalities. His contributions span visually descriptive language annotation, image captioning, and multimodal translation. Though no longer active in active research, his legacy includes foundational papers on object recognition from text (BMVC 2009) and unsupervised phrase localization (ICCV 2019). Grants & Projects: MultiMT and MMVC projects (Imperial College London) CHIST-ERA ViSen project (University of Sheffield) Labs & Teams: Collaborated extensively with interdisciplinary teams at Imperial, Sheffield, Lyon, and Barcelona, including work on multimodal machine translation and visual grounding systems.
Albert Qiaochu Jiang serves as a Visiting Research Fellow at the Department of Computer Science and Technology, University of Cambridge. His research integrates machine learning with formal theorem proving, focusing on neural theorem provers and mathematical reasoning systems. He leads the reasoning team at Mistral AI while maintaining academic supervision at Cambridge. His research interests center on machine learning for theorem proving , with specific expertise in neural-symbolic integration, autoformalization, and large language models for mathematical reasoning. His work bridges artificial intelligence with formal verification, developing systems that enhance automated reasoning capabilities through neural networks. Current projects involve improving premise selection for theorem provers, multilingual mathematical formalization, and creating efficient architectures for mathematical language models. Analysis of his recent publications reveals a strong focus on advancing neural theorem proving through innovative architectures like Target-Based Automated Conjecturing and Magistral. His research trajectory shows increasing sophistication in integrating language models with formal verification systems, with significant contributions to datasets like Numinamath and frameworks like Llemma. Key trends include optimizing compute efficiency in proof generation, enhancing multilingual mathematical reasoning, and developing interactive human-AI collaboration systems for formal mathematics. While no scientific awards are currently documented in available sources, his research output demonstrates significant impact in the intersection of AI and formal methods. As leader of Mistral AI's reasoning team, Jiang directs research on neural theorem proving systems while contributing to academic supervision at Cambridge. His work involves substantial industrial-academic collaboration, leveraging resources from both institutional contexts to advance mathematical AI. Current projects focus on creating practical systems for mathematical automation with real-world verification applications. His research operates at the intersection of academia and industry through Mistral AI's reasoning team, where he develops neural theorem proving systems with practical applications in formal verification. This dual affiliation enables rapid translation of theoretical advances into deployable tools for mathematical automation.
Prof. Dr.-Ing. Christina Simon-Philipp is a Professor of Urban Planning and Urban Development at the Hochschule für Technik Stuttgart (University of Applied Sciences Stuttgart), leading the Department of Urban Planning and Urban Development within the College of Architecture and Design. Her roles include serving as Dean of Studies for the Master of Urban Planning program since 2014 and director of the Competence Center for Sustainable Urban Development. She has held academic and professional roles since 1993, including urban planner, architect, and policy advisor in the Ministry of Economic Affairs (2003-2007). Education: Studied architecture and urban planning at the University of Stuttgart and ETH Zurich. Doctorate from the University of Stuttgart's Urban Planning Institute in 2001. Research focuses on sustainable urban development, transdisciplinary teaching-research projects, and urban renewal. Key projects include the 'Forschung iCity' series, 'MobiQ' mobility initiative, and 'Leben vor der Stadt' revitalization of post-war residential areas. She co-founded the Laboratory for Experimental Urban Space (LES) and leads the IBA StadtRegion Stuttgart 2027 research forum. Publications emphasize urban policy analysis, sustainable housing strategies, and participatory planning methods. She chairs the German Urban Prize jury and advises major urban projects like the Benjamin Franklin Kaserne conversion in Mannheim and the Heilbronn Neckarbogen model district. Professional memberships include the German Academy for Urban Development (DASL), the Deutscher Werkbund, and editorial roles at Forum Stadt . She oversees the Promotion Center BW-CAR and advises urban development initiatives across Baden-Württemberg.
Barbara Adams is an Assistant Professor of Art, Design and Social Justice at Parsons School of Design, The New School . Her interdisciplinary research explores how art and design projects generate knowledge and political action, with a focus on social justice, ethics, and collaborative practices. She holds a PhD in Sociology from The New School for Social Research (NSSR), supported by a GIDEST fellowship, alongside an MA in Social Sciences (Pedagogical Sciences) from the University of Amsterdam. Her academic trajectory includes coordinating the Anthropology + Design Graduate Minor at NSSR and serving as Andrew W. Mellon Postdoctoral Fellow in Design at Wesleyan University. Research Interests : Adams investigates poetic and creative methods in social research, the ethics of engagement in socially oriented art/design projects, and speculative solidarity frameworks. She co-edits the journal Design and Culture and leads research at the Design for Social Innovation and Sustainability Lab (DESIS Lab). Publications & Impact : Her work spans topics like pandemic design responses, museum visitor experiences, and public library roles in democracy. Recent outputs include essays on proximity ethics (2023), pandemic improvisation (2021), and UNHCR’s speculative solidarity projects (2021). Awards : Andrew W. Mellon Postdoctoral Fellowship Teaching : Courses include Collab: Writing in Practice and Speculative Storytelling (Fall 2025). Lab Affiliations : DESIS Lab (Researcher), Parsons Faculty Hotseat (Office).
Michaela Bačíková is an Assistant Professor at the Faculty of Electrical Engineering and Informatics (FEI) of the Technical University of Košice (TUKE). Her research focuses on Human-Computer Interaction (HCI), domain usability, and domain analysis, with an emphasis on graphical user interfaces (GUIs), domain-specific languages (DSLs), and gesture-driven interaction. She leads the development of the DEAL tool, a domain analysis framework for extracting domain models from software systems. Her teaching includes courses on component-based programming, web technologies, and user interface design. Research Projects: DEAL (Domain Extraction ALgorithm) : A tool for analyzing GUIs to generate DSLs, ontologies, and usability metrics. EU Project: 'Evolving Architectural Knowledge in the Edge-to-Cloud Continuum' (participant). Educational initiatives: Integrating gesture-driven IDEs and social networks for mentoring in programming courses. Research Interests : Automated domain usability evaluation using DEAL. DSL-driven GUI generation and feature modeling. Innovations in teaching software development and user experience design. Grants & Labs : Recipient of FEI TUKE Grant no. FEI-2015-16 for domain usability metrics research. Active in the FEI lab developing DEAL and related tools.
Nandini Sidnal serves as Senior Learning Facilitator and National Academic Course Coordinator for Torrens University's Master of Software Engineering program through the Centre for Artificial Intelligence Research and Optimisation (AIRO). With over 20 years of international teaching experience in Computer Science, Engineering, and Networking, she has established herself as a key academic figure in AI and blockchain applications. Her educational foundation includes: PhD in Computer Science and Engineering (Cognitive Computing using Intelligent Agents) from Visvesvaraya Technological University (2012) M.Tech in Computer Science and Engineering (Parallel and Distributed Computing using Intelligent Mobile Agents) (2003) Bachelor of Engineering (1993) Nandini's research spans Artificial Intelligence, Blockchain Security, and Cognitive Computing , with strong emphasis on practical implementations in agriculture and healthcare. Her work integrates intelligent agents with distributed systems to solve real-world problems like food supply chain security and medical diagnostics, demonstrating consistent innovation from her early best paper award-winning thesis to current cutting-edge applications. Recent publications reveal a pronounced trend toward AI-driven agricultural optimization (dairy quality, aeroponics, nut farming) and healthcare diagnostics (epilepsy detection), alongside critical work in edge security. These outputs consistently bridge theoretical frameworks with tangible industry solutions, particularly in blockchain-secured IoT systems and deep learning applications. Her scientific recognition includes: Best Paper Award at an international conference for distributed computing research Nandini actively mentors high-impact projects including 'Strengthening Mobile-Based Services for Agriculture' and 'Enhancing VANET Performance with Cloud and Edge Technology.' Her industry collaborations with Intel (Parallel Programming integration) and Nokia (Mobility Research Lab establishment in Finland) demonstrate exceptional academic-industry synergy. The AIRO Centre serves as her primary research hub where she guides PhD candidates in blockchain-secured agri-supply chains and semantic recommender systems. Her Mobility Research Lab in Finland remains a cornerstone of her practical innovation legacy, focusing on next-generation mobile application development that continues to influence current VANET and edge computing research directions.
Georgios Siolas is a Senior Researcher at the Artificial Intelligence and Learning Systems Laboratory (NTUA-ISLab), part of the School of Electrical & Computer Engineering at the National Technical University of Athens (NTUA). He holds a BSc in Electrical & Computer Engineering from NTUA (1998), an MSc in Cognitive Science from Sorbonne Université (1999), and a PhD in Computer Science (2003). His research focuses on machine learning, text mining, information retrieval, and semantic web technologies, with applications in computer vision, recommender systems, and social network analysis. He develops intelligent systems for cultural heritage management, smart tourism platforms, and sign language recognition. Key contributions include innovations in neural architecture search, deep learning for hyperspectral imagery, and plagiarism detection in imbalanced datasets. His work integrates semantic technologies with pervasive computing for smart home environments.
David Lo is an OUB Chair Professor and Director at the Information Systems and Technology Cluster , School of Computing and Information Systems , Singapore Management University . His research spans the intersection of Software Engineering , Cybersecurity , and Data Science , focusing on improving software quality, security, and developer productivity through socio-technical analysis and artifact evaluation. He has over 15 international Scientific Awards , including ACM Fellow (2023), IEEE Fellow (2022), and ASE Fellow (2021). His work has been funded by NRF , MOE , NCR , and AI Singapore . David leads the Software Analytics Research (SOAR) group and has mentored numerous PhD students , many of whom hold faculty positions or work in tech giants like Microsoft. He actively engages in service , chairing conferences like ICSE 2025 and ESEC/FSE 2024 , and serves on editorial boards of journals such as IEEE Transactions on Software Engineering . His recent keynotes address critical topics like AI for safer systems and LLM applications in software architecture , reflecting his vision for integrating AI into software engineering practices.
Katherine Fu is an Associate Professor of Mechanical Engineering at the University of Wisconsin-Madison and holds an adjunct role as Adjunct Associate Professor at the Georgia Institute of Technology's Woodruff School of Mechanical Engineering. Her research focuses on design cognition, computational design tools, and fostering innovation through analogy-based methods. She has a Ph.D. in Mechanical Engineering from Carnegie Mellon University (2012), joined Georgia Tech in 2014, and moved to UW-Madison in 2021. Education: Ph.D., Mechanical Engineering, Carnegie Mellon University, 2012 M.S., Mechanical Engineering, Carnegie Mellon University, 2009 B.S., Mechanical Engineering, Brown University, 2007 Research interests emphasize cognitive studies of design processes, computational tools for creativity, and design-by-analogy methodologies. Notable contributions include frameworks for design heuristics extraction, functional analogy search algorithms, and studies on analogical distance effects. Awards include the 2019 GT LGBTQIA Leadership Award, 2018 ASME Reviewer of the Year, and 2015 ASME Early Career Engineer of the Year. Her work bridges engineering education and design science, with a focus on fostering ethical and socially impactful innovation. Labs and Teams: Active leadership in the Design Research Lab (EDRL) and collaborations with institutions like Jet Propulsion Laboratory (JPL). Teaching contributions include curriculum development in GD&T and ethics integration in design education.
Yangming Li is a Research Fellow at the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, affiliated with the Cambridge Image Analysis research group. His work bridges applied mathematics, theoretical physics, and machine learning, with a focus on developing innovative models for image analysis, generative processes, and natural language understanding. Research interests include Fourier Neural Operators, diffusion models, generative adversarial networks (GANs), and their applications in solving complex problems across scientific computing and data-driven domains. His recent contributions explore operator learning for PDEs, robust diffusion models under noisy conditions, and adversarial attacks in text watermarking systems. Publications highlight advancements in operator-based neural networks, risk-sensitive generative modeling, and domain-aware NLP frameworks. His methodologies emphasize mathematical rigor while addressing practical challenges like missing data and model expressivity limitations. Active collaborations span interdisciplinary teams at DAMTP and the broader University of Cambridge research community.
Dr. Lei Yang is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University, focusing on Hardware/Software Co-Exploration for Neural Network Architectures, Embedded Systems, and High-Performance Computing. Previously, she served as an Assistant Professor at the University of New Mexico and held post-doctoral and research scholar positions at Notre Dame, UC Irvine, and the University of Pittsburgh. Research Interests: System-Level Optimization for Applied Machine Learning Automated Machine Learning (AutoML) Federated Learning for Medical AI and Drug Discovery Quantum Neural Networks and Dark Silicon Many-Core Systems Thermal-Aware and Energy-Efficient Computing Award Trends: 50+ publications in premier venues like DAC, ICCAD, and IEEE Transactions, with multiple Best Paper Awards and Nominations. Notable recognitions include the 2021 IEEE TCAD Donald O. Pederson Best Paper Award and the 2017 ICCD Best Paper Award. Honors & Service: General Chair, SIGDA Student Research Forum at ASP-DAC 2023 Organizer, E2ML Workshop at GLVLSI 2021 Registration Chair, ICCD 2021 TPC Member, DAC 2022, ICCAD 2021, and IEEE SOCC 2020
