Sarah Wiegreffe is an Assistant Professor in the Department of Computer Science at the University of Maryland, affiliated with the CLIP laboratory. She holds a PhD from Georgia Institute of Technology (2022), advised by Prof. Mark Riedl. Previously, she was a postdoctoral researcher at the Allen Institute for AI (Ai2) and a member of H2Lab at the University of Washington, advised by Ashish Sabharwal and Hannaneh Hajishirzi. Her research focuses on mechanistic interpretability and transparency of language models, aiming to improve reliability, safety, and performance through natural language explanations. Notable contributions include the Mechanistic Interpretability Benchmark (MIB) and work on explaining model noncompliance. Awards include the Ai2 Outstanding Intern Award, Rising Star in Machine Learning/EECS/Generative AI, and recognition as an Outstanding Area Chair (ACL 2023, NeurIPS 2023). She has advised students like Alec Bunn and contributed to workshops like the Actionable Interpretability at ICML 2025. Education: PhD in Computer Science, Georgia Tech (2022); Master’s/Undergraduate degrees not explicitly stated. Active in organizing conferences (e.g., NAACL 2021 Publicity Co-Chair) and teaching (e.g., graduate seminar CMSC848R on LM interpretability).
Dr Yong Lin is an Associate Professor in Operations and Supply Chain Management at the Department of Management, Birmingham Business School, University of Birmingham. He joined the university in September 2021, having previously held academic positions at the University of Greenwich and Huazhong University of Science & Technology. He has also served as a visiting researcher at the Institute for Manufacturing (IfM), University of Cambridge, and as a research assistant at the Hong Kong University of Science & Technology. PhD in Management Science and Engineering, Huazhong University of Science & Technology, 2002 MSc in Industrial Engineering and Management, Huazhong University of Science & Technology, 1999 Dr Lin’s research focuses on digital transformation and sustainability strategies in operations and supply chains. His key interests include supply chain risk and resilience, digital logistics platforms, business ecosystems, and manufacturing strategies. He explores how digital technologies such as blockchain and RFID can enhance transparency, efficiency, and sustainability across supply networks. His recent publications reflect a strong trend toward digitalization, resilience, and sustainability in supply chains, with studies on modular resilience in multinational platforms, blockchain in remanufacturing, and digitalization in healthcare logistics. His work frequently appears in top-tier journals such as International Journal of Operations and Production Management , Journal of Cleaner Production , and Technological Forecasting and Social Change . Senior Fellow of the Advance HE (Higher Education Academy) Certified Management and Business Educator, Chartered Association of Business Schools (CABS) Chartered Fellow, Chartered Institute of Logistics and Transport (CILT) Dr Lin has led and coordinated several research projects funded by the National Natural Science Foundation of China (NSFC), the 863 Program, and the European Regional Development Fund. He actively engages in industry consulting to transfer research outcomes into practical business solutions. He welcomes PhD applicants interested in digital transformation, sustainability, logistics platforms, and business ecosystems. He is also involved in advising and mentoring graduate researchers in these domains. Dr Lin is affiliated with the Department of Management at Birmingham Business School, where he contributes to research, teaching, and knowledge exchange in operations and supply chain management. His work bridges academic rigor with real-world application, particularly in digital and sustainable supply chain innovation.
Jacob Østergaard is a Professor and Head of the Division for Power and Energy Systems at DTU Wind and Energy Systems, Technical University of Denmark. His research focuses on renewable energy systems, offshore wind power hubs, and quantum computing applications in energy systems. He leads initiatives like EnergyLab Nordhavn and PowerLabDK, emphasizing collaboration between academia and industry. Education: MSc in Electrical Engineering from DTU (1989–1995). External positions include roles at Research Institute of the Danish Electric Utilities and Ørsted (now SK Energy). Research Interests: Power system stability, flexibility markets, offshore wind energy, quantum computing in energy systems, Power-to-X, and energy storage. He advocates for integrated, market-based energy systems to achieve the green transition. Publications highlight quantum computing for grid optimization, offshore energy hubs, and Denmark’s energy island strategy. Recent work emphasizes scientific advice for energy policy and green hydrogen production. Awards: A. Angelo’s Prize (1996), AEG Electron Prize (2007), Danish Design Award (2019), and EU RESponsible Island Prize (2020). Advising and Grants: Supervises PhD students in grid integration and control. Active in projects like OEH (Offshore Energy Hubs) and BOSS (Battery Energy Storage System). His work drives Denmark’s energy policy through roles on Energinet’s board and the Danish Energy Commission. Labs/Teams: Leads PowerLabDK and EnergyLab Nordhavn, experimental facilities for smart grid and energy system research.
Jeppe Lund Nielsen is a Professor in the Department of Chemistry and Life Sciences at the Faculty of Engineering and Science, Aalborg University, Denmark. His research lies at the intersection of microbial ecology, genomics, and environmental biotechnology, with a strong focus on sustainable solutions for wastewater treatment, anaerobic digestion, and environmental monitoring. His primary research interests include Microbial Ecology, Functional Ecology, Genomics, Molecular and Technical Microbiology, Anaerobic Digestion, Metagenomics, and eDNA Metabarcoding . He applies molecular tools to understand microbial community dynamics in engineered and natural systems, particularly in wastewater and marine environments. His work contributes to the UN Sustainable Development Goals related to clean water, sustainable cities, and climate action. The recent publication trends reflect a strong emphasis on environmental applications of microbiome science, including nitrogen cycling in wastewater, bioaerosol exposure in workers, eDNA-based biodiversity monitoring, and valorization of waste streams through biotechnology. His articles frequently appear in high-impact environmental and microbiological journals and demonstrate interdisciplinary collaboration across engineering, ecology, and public health. Among his notable scientific contributions are leadership roles in significant research projects such as the AAU Bubble Project (Power2Proteins), JAMBO seabed impact study, and investigations into biotechnological pesticides. He has also contributed to public discourse through media engagement on topics like pesticide regulation and environmental innovation. Professor Nielsen has supervised PhD students, including M. Eskeldsen, and is actively involved in grants and collaborative research across Europe. He is a key member of research teams focused on environmental microbiology, wastewater biotechnology, and marine impact assessments. His lab integrates molecular biology, bioinformatics, and environmental engineering to address pressing sustainability challenges.
Elin Org is a Professor of Microbiomics at the University of Tartu's Institute of Genomics, where she also serves as Head of the Estonian Genome Centre and Vice Director of the Institute. Her academic career spans over two decades with significant contributions to microbiome and genomic research. Education: PhD in Genetics, University of Tartu (2006) Master's Degree in Molecular Biotechnology and Biomedicine, University of Tartu (2000) Bachelor's Degree, University of Tartu (1997) Classical Singing, Heino Eller Tartu Music School (1996) Professor Org's research primarily focuses on the intricate relationships between host and gut microbiota and their influence on metabolism and common complex diseases. Her work bridges microbiomics, genomics, and complex disease research, with particular emphasis on understanding how gut microbiome composition affects human health. She has pioneered research connecting long-term antibiotic usage with microbiota-dependent effects and has made significant contributions to understanding the role of gut microbiome in conditions such as gestational diabetes, endometriosis, and polycystic ovary syndrome. Her approach integrates advanced computational methods with comprehensive health data to uncover causal relationships in microbiome research. Her recent publications demonstrate a strong trend toward integrating microbiome data with extensive digital health metrics, using machine learning approaches to identify microbial predictors of health outcomes. This work is increasingly focused on translating microbiome research into clinical applications for disease prediction and personalized medicine approaches, particularly in the context of the Estonian Biobank initiative. Major Scientific Recognition: 2025 National Science Award in medical and health sciences 2023 and 2022: Recognized among the world's top 1% most cited researchers by Clarivate Analytics 2020: Member of AcademiaNet, a portal for top female researchers 2017: EMBO Installation grant 2013: Marie Curie International Outgoing Fellowship Professor Org has secured substantial research funding as principal investigator for multiple significant projects, including 'DISCERN - Discovering the causes of three poorly understood cancers in Europe' (€245,466, European Commission) and 'Improving colorectal cancer screening and prediction using microbiome-based biomarkers' (€760,450, Estonian Research Council). She has served as an opponent for numerous PhD theses across European institutions, contributing to the development of emerging researchers in her field. As Head of the Estonian Genome Centre, Professor Org leads a multidisciplinary research team that plays a crucial role in Estonia's transition from biobanking to personalized medicine applications. She is actively involved in international collaborations through COST networks including INFOGUT (focused on in vitro colon models) and ML4Microbiome (statistical and machine learning techniques in human microbiome studies), positioning her at the forefront of global microbiome research initiatives.
Peter H. Verburg is a Full Professor of Environmental Spatial Analysis at the Institute for Environmental Studies (IVM) , Vrije Universiteit Amsterdam, leading the Environmental Geography group. He has held this position since 2010 and previously served as an Assistant Professor at Wageningen University (2003–2010) and Senior Researcher at Alterra (2009–2010). His research focuses on land use analysis, spatial modeling, and interdisciplinary environmental studies. Education: PhD in Land Use Modelling, Wageningen University (2000) MSc in Physical Geography, Wageningen University (1996) Key Research Interests: Dr. Verburg is renowned for developing the globally used CLUE land-use modeling framework. His work integrates methods from social sciences, econometrics, and earth sciences to analyze land-use patterns and policies. He actively contributes to EU projects on sustainable urban planning, climate adaptation, and ecosystem services. Current roles include co-Editor-in-Chief of Landscape and Urban Planning , member of the Earth Commission, and Science-Policy Interface member of UNCCD. Professional Activities: Former Chair of Global Land Programme (Future Earth) Lead researcher in multiple EU initiatives (e.g., BrightspotsCSA, TURAS) Organized workshops on land-use modeling and ecosystem services Awards: Highly Cited Researcher (2018, Web of Science top 1%) Research and Collaboration: He has published over 415 peer-reviewed articles and supervised 38 PhD theses. His projects span land-use modeling in China, Central Asia, and the Mekong region. Collaborations include UN agencies, European research networks, and global sustainability initiatives.
Joakim Nivre is a Professor at Uppsala University's Department of Linguistics and Philology. He is a leading researcher in computational linguistics, with a focus on dependency parsing, Universal Dependencies (UD) framework development, and multilingual NLP applications. His recent work explores LLMs in climate change discourse analysis, pharmacovigilance explainability, and historical text processing. Key research areas: Dependency parsing theory, Universal Dependencies standardization, LLM evaluation Collaborations: SweSAT-1.0 benchmark development, ClimateEval project, PARSEME integration His 2025-2023 publications demonstrate expertise in explainable AI for healthcare, synthetic data generation for idioms, and multilingual benchmark design. Notably, he co-developed SweSAT-1.0 to evaluate Swedish LLMs and contributed to typology-informed UD revisions. Despite extensive work in NLP, no scientific awards are mentioned in available texts.
Kees Dorst is a Professor of Transdisciplinary Innovation at the TD School of the University of Technology Sydney. He bridges philosophical understandings of design with practical applications, focusing on tackling complex societal challenges through designerly thinking. His research develops methodologies for strategic transformation and networked problem-solving in public sectors. Professor of Transdisciplinary Innovation, UTS Director, Designing Out Crime Research Centre International keynote speaker and advisor on design thinking Research Interests Dorst specializes in: Transdisciplinary innovation for societal challenges Design thinking and co-evolutionary processes Reframing complex problems in public policy Design cognition and metacognition Urban environment design for safety Recent Research Trends show increasing focus on: Hypercomplex problem-solving frameworks Strategic transformation through design Cognitive models in design processes Public sector innovation methodologies Teaching & Leadership includes: Bachelor of Creative Intelligence and Innovation Master of Creative Intelligence and Strategic Innovation Founding the Designing Out Crime Research Centre International design research symposium leadership
Professor Ruerd Ruben is an external academic expert in Development Economics with over 300 research outputs spanning food systems, smallholder livelihoods, and rural poverty alleviation. His work focuses on value chain transformation, nutrition, and sustainable agricultural practices in Africa, Latin America, and Asia. Research Pillars: Food systems optimization Smallholder economic empowerment Value chain governance Sustainable diets and nutrition Rural development strategies Ruben's recent publications examine midstream actors in informal economies (2025), market-based poverty reduction (2024), and fair trade limitations (2023). His editorial work includes contributions to Food Security journal, and he has supervised 19 PhD projects on topics ranging from Ethiopian potato chains to climate-resilient East African agribusinesses. Scientific Leadership: Contributed to 300+ academic works Received 7 Scopus citations for key publications Active in global food systems discourse
Xilin Liu is an Assistant Professor at the Edward S. Rogers Sr. Department of Electrical & Computer Engineering (University of Toronto) and the Center for Advancing Neurotechnological Innovation to Application (CRANIA) . He obtained his PhD from the University of Pennsylvania and previously worked at Qualcomm Inc. in California. Expertise in integrated circuits and systems for brain-machine interfaces , neuromodulation , and edge AI Published in top venues including Nature Electronics , IEEE JSSC , and ISSCC Recipient of multiple best paper awards and IEEE Senior Member His research spans three main themes: High-speed data converters for wireless/wireline communication IC design for neural interfacing Accelerating machine learning via hardware Recent publications focus on closed-loop neuromodulation , ultra-wideband transceivers , and flexible biomedical sensors . These works integrate analog IC design , edge AI , and real-time neural interfacing across medical rehabilitation , parkinson's monitoring , and memory research . Awards include: IEEE Solid-State Circuits Society Predoctoral Achievement Award (2016) Best Paper Award at BioCAS (2015) ECE Department Teaching Award (2022) Multiple conference best paper finalists His lab collaborates with UHN , EMBS , and global institutions while maintaining strong commitments to equity, diversity, and inclusion (EDI) in research practices.
Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.
Zhaoli Song is an Associate Professor at the Department of Management and Organisation within NUS Business School, Singapore. His research bridges behavioral genetics with organizational behavior, focusing on leadership, AI in the workplace, cross-cultural management, and work-family dynamics. PhD in Human Resources and Industrial Relations (2004), University of Minnesota Master in Statistics (2004), University of Minnesota Master in Applied Psychology (1999), Chinese Academy of Sciences Bachelor in Optics (1995), Sichuan University Dr. Song pioneered molecular genetics applications in management research, achieving media recognition in Economist and Washington Post . His work spans AI strategy formulation, pandemic scenario modeling, and team innovation across Asia. He has taught organizational behavior, HRM, and research methods at undergraduate, Master's, EMBA, and executive levels. Recent publications analyze AI adoption frameworks, emotional dynamics in leader-member exchanges, and genetic determinants of creativity. He served as Academic Director for NUS Asian Pacific EMBA (Chinese) program (2013-2017), demonstrating educational leadership alongside scholarly contributions.
Prof. Dr. Nadja Kabisch is a leading academic at the Institute of Earth System Sciences within the Faculty of Natural Sciences at Leibniz University Hannover. Her work bridges landscape ecology , population geography , and health geography , focusing on nature-based solutions for urban challenges like climate change, demographic shifts, and environmental justice. She employs digital methods for ecosystem service analysis and urban climate resilience. Her research explores the health impacts of urban green spaces , environmental justice in global change contexts, and systematic approaches to human-environment interactions. Recent studies analyze allergenic pollen dynamics , microclimate regulation , and 15-minute city models for climate-resilient urbanism. As Deputy Management of her institute and a member of multiple committees (e.g., M.Sc. Landscape Sciences Selection Committee ), she shapes academic governance and curriculum. Her collaborations span institutions like Springer and Edward Elgar Publishing, with peer-reviewed articles in journals such as Nature Reviews Biodiversity and Landscape and Urban Planning .
Gerald Pruckner is a Professor at the Department of Economics, Johannes Kepler University Linz (JKU), where he serves as Head of the Institute of Health Economics and Dean of the Kurt Rothschild School of Economics and Statistics (RoSES). His academic career spans over three decades with significant leadership roles including heading the Christian Doppler Laboratory for Aging, Health, and the Labor Market (2014-2021), and serving on the board of the Austrian Health Economics Association (ATHEA). He teaches multiple courses including Introductory Microeconomics, Empirical Economics, and Health Economics for the 2025W semester. Pruckner earned his PhD in Economics from the University of Linz in 1993. His academic journey began as an Assistant Professor at JKU (1989-2002), followed by a Professorship at the University of Innsbruck (2002-2006), then returning to JKU as Associate Professor (2006-2010) before his current Professorship (since 2011). He has held visiting positions at the University of Adelaide and UC Berkeley. His research focuses at the intersection of health economics, behavioral economics, and aging, examining healthcare systems, physician behavior, and the relationship between labor markets and health outcomes. Recent work investigates hospital crowding effects, gender differences in medical practice, chronic disease screening effectiveness, and child health services. His research consistently applies economic principles to understand healthcare delivery with emphasis on the Austrian context, often utilizing register data for evidence-based policy insights. Analysis of Pruckner's publication trends shows a sustained focus on practical healthcare issues with policy relevance. His work spans hospital management challenges, gender differences in medical practice, chronic disease screening effectiveness, and child health services. The research consistently bridges academic inquiry with practical health policy applications, with increasing attention to pandemic impacts and digital transformation in healthcare. Board member of Austrian Health Economics Association (ATHEA) since 2015 Member of Health Economics Committee (Verein für Socialpolitik) since 2013 Deputy head of national research network 'The Austrian Center for Labor Economics and the Analysis of the Welfare State' (2008-2013) Head of Christian Doppler Laboratory for Aging, Health, and the Labor Market (2014-2021) Pruckner actively mentors graduate students through dissertation colloquia and master's thesis supervision. His research portfolio includes 23 projects with significant funding, including current work on health services research in Upper Austria and empirical analysis of Linz healthcare provision. As Dean of RoSES and Head of the Health Economics Institute, he provides institutional leadership while maintaining an active research agenda with over 100 publications. He leads multiple research teams focused on health services research, with current projects examining healthcare provision in Linz, health indicators for the region, and broader health system analysis. His work bridges academic research and practical health policy applications through collaborations with regional health authorities and participation in professional associations.
Dr. Craig S. Levin is a Professor of Radiology at Stanford University's Molecular Imaging Program at Stanford (Nuclear Medicine), with courtesy appointments in Physics, Electrical Engineering, and Bioengineering. He also holds memberships in Bio-X, the Cardiovascular Institute, the Wu Tsai Human Performance Alliance, and the Stanford Cancer Institute. Dr. Levin received his B.S. Summa Cum Laude in Physics and Mathematics from UCLA in 1985, followed by M.S., M.Phil., and Ph.D. degrees in Physics from Yale University in 1987 and 1993. His educational achievements were recognized with multiple honors including Phi Beta Kappa, Sigma Pi Sigma, and various departmental awards at UCLA. Dr. Levin's research focuses on the development of novel instrumentation and software algorithms for molecular imaging. His work spans medical physics, biomedical engineering, and instrumentation development with specific emphasis on positron emission tomography (PET), gamma camera technology, and multimodal imaging systems. His laboratory explores new concepts in radiation detection, image reconstruction algorithms, and the application of these technologies to cancer, heart disease, and neurological disorders. A notable aspect of his research involves pushing the physical limits of sensitivity and spatial, spectral, and/or temporal resolutions in imaging systems. His recent publications demonstrate a strong focus on enhancing PET technology, particularly time-of-flight capabilities, with significant work on improving coincidence timing resolution, developing MR-compatible PET systems, and applying deep learning techniques to image reconstruction and normalization. His research shows a clear trajectory toward higher resolution imaging with improved quantitative accuracy for both clinical and preclinical applications. Dr. Levin's scientific achievements have been recognized with numerous awards: American Institute for Medical and Biological Engineering's College of Fellows Academy of Radiology Research Distinguished Investigator Recognition Award National Research Service Award from NIH (1993-5) Pilot Research Award from the Society of Nuclear Medicine (1996) Multiple honors from UCLA including Phi Beta Kappa and Sigma Pi Sigma Full Tuition and Research Fellowship and Bates Graduate Fellowship from Yale University As an educator and mentor, Dr. Levin directs the NIH-NCI funded T32 Stanford Molecular Imaging Scholars postdoctoral training program and serves as a Doctoral Dissertation Advisor for students in Bioengineering and Biophysics. He currently advises five postdoctoral scholars and three doctoral candidates. His laboratory, the Molecular Imaging Instrumentation Laboratory, comprises approximately 20 members who work on developing new imaging technologies and translating them into clinical applications. Dr. Levin has secured substantial NIH funding as Principal Investigator along with grants from other government agencies, industry partners, and private institutions to support his research program. Dr. Levin's Molecular Imaging Instrumentation Laboratory is at the forefront of developing new imaging technologies that bridge physics, engineering, and medicine. The lab focuses on creating instrumentation for in vivo imaging of cellular and molecular signatures of disease, with particular emphasis on pushing the physical limits of imaging performance. Their work spans computer modeling, sensor development, electronics design, data acquisition systems, and advanced image processing algorithms. The lab maintains strong industry partnerships to translate their innovations into products used for patient care worldwide.
