Uwe Himmelreich is a Full Professor at the Faculty of Medicine, KU Leuven , leading the Biomedical MRI unit. He is actively involved in the Medical Imaging Division , KU Leuven Brain Institute , KU Leuven Institute for Integration of Micro- and Nano-scale Technologies , and KU Leuven Cancer Institute . Role: Full Professor and Head of Biomedical MRI Affiliations: Faculty of Medicine, Medical Imaging Division, LBI, LIMNI, LKI His research spans neuroscience , cardiovascular imaging , and nano/micro-scale technologies . Key projects include: MindMAP: Radiotherapy-induced neurotoxicity in juvenile brains Preclinical cancer models for oral tumors Quantitative T2 mapping of lung disease in murine models Neuroinflammation and cognitive decline in cryptococcosis Resistance training effects on cortical thickness in aging cohorts His work integrates MRI , multi-photon microscopy , and novel contrast agents for longitudinal in vivo studies. Methodologies include vascular density mapping , proton therapy verification , and preclinical radiotherapy evaluation . Notable contributions include: 2025: JAK/STAT inhibition in malaria-induced inflammation 2025: Manganese-enhanced MRI for cardiac injury 2025: Quantitative lung imaging at 9.4T 2024: IVIM as vascular density marker in rat brain 2024: Phase-change ultrasound agents for proton therapy
Andrew Warfield is an Adjunct Professor in the Department of Computer Science at the University of British Columbia (UBC) and a Senior Principal Engineer at Amazon. His research focuses on computer systems software, including virtualization, distributed storage, security, and high-availability systems. He previously held roles as Associate Professor at UBC, CTO at Coho Data, and Technical Director at Citrix Systems. His work has led to projects like Remus (high-availability replication), Tralfamadore (execution analysis), and secure hypervisor development with Xen. Warfield's education includes a PhD from the University of Cambridge's Computer Laboratory, where he researched I/O device virtualization under Steven Hand. He has held visiting roles at Intel Research Cambridge and internships at AT&T Research and Nortel Networks. Research Grants: Supported by Intel Research, NSERC, Network Appliance, and the Communications Security Establishment. Professional Activities: Technical Advisory Board Member at Teradici, and involvement in program committees for conferences like HotOS, EuroSys, and FAST. His research emphasizes practical systems, aiming to bridge the gap between theoretical computer science and real-world applications. Notable contributions include innovations in storage for virtualized environments, secure hypervisor architectures, and disaster-tolerant systems like SecondSite. Warfield is affiliated with UBC's Department of Computer Science and maintains active collaboration with industry partners. Though currently not actively recruiting students, his prior mentorship has influenced many in systems research.
Dr. Samuel Cheng is an Associate Professor at the Gallogly College of Engineering , University of Oklahoma , specializing in Electrical and Computer Engineering . He holds a Ph.D. in Electrical Engineering from Texas A&M University (2004), preceded by M.S. and M.Phil. degrees from the University of Hawaii and Hong Kong University of Science and Technology. Education: B.S. (University of Hong Kong, 1995), M.Phil. (HKUST, 1997), M.S. (University of Hawaii, 2000), Ph.D. (Texas A&M, 2004) Professional Experience: Senior Research Engineer at Advanced Digital Imaging Research (2004-2005), prior internships at Microsoft Asia and Panasonic Technologies His research focuses on Information Theory , Signal and Image Processing , and Pattern Recognition , with applications in remote sensing, urbanization analysis, and disaster monitoring. His publications span topics including urban impervious surface mapping , nighttime light analysis , and machine learning for environmental data . His work often integrates multi-source datasets (e.g., Landsat, LiDAR, social media) for spatiotemporal modeling. Technical Expertise: Spectral unmixing, machine learning, thermal remote sensing, GIS integration Key Applications: Power outage detection, vegetation-crime correlation, PM2.5 estimation, smart meter data fusion Dr. Cheng holds three US patents in digital watermarking and is affiliated with IEEE, Sigma Xi, and AAAS. His recent articles demonstrate a trend toward leveraging AI for remote sensing challenges and analyzing urbanization impacts on ecosystems.
Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .
Yize Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health and an Associate Professor in the Department of Biomedical Informatics & Data Science at Yale University. She holds affiliations with multiple Yale research centers including the Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute, Yale Center for Brain and Mind Health, and Yale Computational Biology and Bioinformatics. Dr. Zhao's research focuses on developing statistical and AI methods to analyze large-scale complex biomedical data including medical imaging, genomics, and electronic health records. Her methodological expertise spans Bayesian statistics, feature selection, predictive modeling, data integration, missing data analysis, and network analysis. Her research interests span multiple biomedical domains with a strong focus on mental health, psychiatry, neurodegenerative diseases, and aging. Her recent work includes brain-to-behavior modeling, multi-layer biomedical networks, imaging genetics and genomics, and the integration of multi-modal biomedical data with real-world data. Dr. Zhao's work has resulted in numerous high-impact publications, with recent research focusing on Alzheimer's disease, brain network analysis, and advanced statistical methods for neuroimaging. Her publications show a strong trend toward integrating multi-modal data sources and developing sophisticated statistical approaches to address complex biomedical questions. Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS) COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS) YSPH Investigator Research Award Yale Alzheimer's Disease Research Center Research Scholar Award Elected member of the International Statistical Institute Dr. Zhao serves as an Associate Editor for Biometrics and is a standing member of the NIH Biodata Management and Analysis (BDMA) study section. Her research is supported by multiple NIH grants, highlighting the significance and impact of her work in biostatistics and biomedical data science.
Giuliano Di Baldassarre is a Professor of Hydrology and Environmental Analysis at the Department of Earth Sciences, Uppsala University , Sweden. He serves as Head of Division for LUVAL (Air, Water and Landscape Sciences) and directs the Centre of Natural Hazards and Disaster Science (CNDS) (2016–2025). His work bridges water, environment, and society through interdisciplinary methods , focusing on disaster risk reduction, climate adaptation, and sustainable development. Education : Details not explicitly provided in the text. His research examines feedbacks between human activities and hydrological processes , including floods, droughts, and reservoir management . Key themes include social-ecological systems , inequalities in water crises , and policy implications of hydrological extremes . He has pioneered sociohydrology and human-water system modeling . Recent articles highlight global drought-flood interactions , urban water inequality , climate service maladaptation , and sociohydrological modeling . His work spans Nature Sustainability , Science Advances , and Hydrological Sciences Journal . Scientific Awards : International Hydrology Prize (Volker Medal) Plinius Medal (EGU) Witherspoon Lecture Award (AGU) European Research Council Consolidator Grant He led Panta Rhei - Everything Flows (2013–2022), IAHS’s global initiative on water-society interactions. Current efforts include transdisciplinary praxis and climate risk reduction frameworks .
Dr. Robert J. Teather is an Associate Professor and the Director of the School of Information Technology at Carleton University in Ottawa, Canada. He previously served as an interim Director of the School of Information Technology during the 2022-23 academic year. His academic journey includes a PhD in Computer Science from York University (2013) and a postdoctoral fellowship at McMaster University (2015). Dr. Teather's educational background includes: PhD in Computer Science from York University (2013) Master's Thesis: "Comparing 2D and 3D Direct Manipulation Interfaces" from York University (2008), which was awarded the Joseph Liu Thesis Award Dr. Teather's research broadly falls under the field of human-computer interaction, with specialization in 3D user interfaces, virtual reality, and user interfaces for computer games. His work establishes methods for direct comparison of 2D and 3D interfaces for conceptually equivalent tasks, such as selection and manipulation interfaces. He investigates factors influencing human performance in VR, including stereo 3D graphics, haptic feedback, and head-tracking. His research also evaluates novel user interfaces like tilt control or touchscreens, and examines human performance with game input devices in complex tasks involving navigation, selection, and manipulation of objects in game environments. His research has been published extensively in top venues including IEEE VR, ACM SUI, and Graphics Interface. Among his notable scientific achievements are: NSERC Postgraduate Scholarship during his PhD studies Ontario Graduate Scholarship during his PhD studies Best Paper Honourable Mention at the ACM Symposium on Applied Perception 2020 Best Demo Award for SUI 2017 Joseph Liu Thesis Award (2008) Dr. Teather actively supervises graduate students at Carleton University, currently overseeing multiple PhD and Master's students in the areas of human-computer interaction and interactive digital media. His research is supported by NSERC and the Canada Foundation for Innovation, providing funding for his students and laboratory equipment. His students have produced research spanning VR as a persuasive tool to improve vaccine confidence, selection performance using smartphones in VR, and text entry methods in virtual reality environments. Dr. Teather leads a well-equipped CFI-supported lab focused on virtual and augmented reality research. His team works collaboratively on projects related to interactive virtual reality systems, computer game user interfaces, and input devices for 3D interaction. The lab environment fosters interdisciplinary research with opportunities for students to work on cutting-edge VR/AR technologies and contribute to the growing field of spatial computing.
Søren Munch Kristiansen is an Associate Professor in the Department of Geoscience at Aarhus University, Faculty of Natural Sciences. His interdisciplinary research bridges geoscience and archaeology, focusing on the complex interactions between soil, water, and human societies across time. He is actively engaged in transdisciplinary projects involving geoarchaeology, groundwater, and public health. Research Interests: His work centers on how soil and groundwater have shaped human prehistory and continue to influence modern life. Key areas include safe drinking water from a lifelong perspective, geoarchaeological prospection, Viking Age settlements, and the application of geophysical and geochemical methods in archaeological contexts. He is particularly interested in novel, interdisciplinary methodologies. Recent Research Trends: His recent publications reveal a strong focus on integrating geophysical data (e.g., GPR, borehole databases) with archaeological interpretation, especially in 3D urban modeling and landscape change. Themes include Viking Age sites, interglacial deposits, and anthropogenic soil modifications. His work increasingly employs machine learning and large-scale data synthesis. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While specific students are not listed, he leads and participates in multiple funded research projects, indicating an active supervisory role. His grants span from 2016 to 2024, including projects like TITAN, SAGA, and 'Fingerprinting displaced molecular substances,' highlighting sustained funding and leadership in interdisciplinary geoscience-archaeology research. Labs and Teams: He is involved in collaborative networks such as the Soil Science & Archaeo-geophysics Alliance (SAGA), suggesting leadership in interdisciplinary research teams. His work often involves multi-proxy analyses and international collaborations, particularly in Scandinavian archaeological geophysics.
Mariam Zachariah serves as a Research Fellow at the Centre for Environmental Policy within the Faculty of Natural Sciences at Imperial College London. She is a core contributor to World Weather Attribution (WWA), an international scientific collaboration conducting rapid climate change attribution analyses for extreme weather events globally. Her work bridges climate science, vulnerability assessment, and policy-relevant research. Her educational foundation includes a PhD from the Indian Institute of Technology Bombay (IITB), where she investigated climate impacts on Indian agriculture. This research focused on drought and extreme temperature effects on crop yields in major agrarian regions, recognizing agriculture's critical role in India's climate-vulnerable economy. Zachariah's research centers on near-real-time attribution of extreme events to quantify human-induced climate change influences. Her expertise spans climate modeling, statistical analysis of extreme weather, and integrating vulnerability frameworks to assess compound impacts on communities. She examines how climate change interacts with socioeconomic factors to exacerbate disasters, particularly in agricultural systems and flood-prone regions worldwide. Analysis of her recent publications reveals a dominant focus on rapid attribution of droughts, floods, and heatwaves across diverse global contexts - from the Horn of Africa to Central Europe and South America. These studies consistently demonstrate climate change as a significant amplifier of event severity, while emphasizing how pre-existing vulnerabilities determine actual impacts. Her work increasingly addresses compound hazards and the intersection of climate change with infrastructure failures and land management. As a key member of the World Weather Attribution initiative, Zachariah collaborates with climate scientists, social scientists, and vulnerability experts in a unique operational framework that delivers scientific assessments within days of extreme events. This work directly informs policymakers, media, and affected communities about climate change's role in contemporary disasters.
Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.
Catherine Polling is an NIHR Clinical Lecturer in General Psychiatry at King’s College London (KCL), affiliated with the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) and the Health Inequalities Research Group . Her work focuses on mental health inequities, self-harm epidemiology, and mixed-methods research, particularly in urban and marginalized communities. Education: MBBS from University College London, MSc in Epidemiology from the London School of Hygiene and Tropical Medicine, PhD from KCL's Department of Psychological Medicine Research Interests: Catherine investigates health disparities in mental health services using advanced statistical methods (multi-level modeling, Bayesian disease mapping) and GIS-based data visualization. Her clinical work with the South London and Maudsley NHS Foundation Trust complements her academic focus on systemic racism and mental health outcomes. Teaching & Engagement: She lectures on urban mental health for KCL’s Urban Informatics MSc and co-leads training on racism in mental health services. She also facilitates reflective practice groups accredited by the Balint Society and contributes to curriculum reform via the Maudsley Cultural Psychiatry Group. Scientific Awards: NIHR Clinical Lecturer Fellowship Wellcome Training Fellowship Research Trends: Her publications emphasize self-harm risk factors, pandemic impacts on healthcare workers, ethnic disparities in mental health services, and the intersection of urban environments with mental health outcomes. She integrates large-scale clinical datasets, qualitative interviews, and spatial analysis to address systemic inequities.
Dr. Philipp Rode is Executive Director of LSE Cities and Associate Professor (Education) at the London School of Economics' School of Public Policy. He leads interdisciplinary urban development research, focusing on transport, sustainability, and governance. His work spans global urban challenges, including climate policy, emergency governance, and urban transitions. Rode co-founded the Urban Age Programme and advises international organizations like UCLG and Metropolis. He holds degrees in transport systems (TU Berlin), city design (LSE), and urban governance (PhD, LSE), and has authored/co-edited influential books such as Governing Compact Cities and Shaping Cities in an Urban Age . Affiliations: LSE Cities, University of St. Gallen (Visiting Professor) Key Roles: Co-Director of LSE's MSc in Cities, Lead of Emergency Governance Initiative Global Engagement: Partnered with OECD, UNDP, World Resources Institute, and over 50 city governments Research interests center on multi-dimensional urbanization, socio-technological transitions, and governance systems. His recent work emphasizes emergency governance frameworks for cities, climate-resilient urban policies, and accessibility strategies. Rode has contributed to shaping the UN's New Urban Agenda and advised the Global Commission on the Economy and Climate. Publications span peer-reviewed journals ( Transport Policy , Environment and Planning B ) and edited volumes addressing urban sustainability, transport governance, and strategic planning. His work bridges academic insights with policy impact, emphasizing actionable frameworks for equitable and resilient cities.
Dr. Xin Zhou is an Oxford-Bristol Myers Squibb Fellow at the Department of Computer Science, University of Oxford. Her research integrates computational modeling, clinical data, and experimental findings to investigate cardiac disease mechanisms and develop human-based simulations for drug evaluation. BSc and MSc in Life Sciences, Beijing Normal University DPhil in Computational Biology, University of Oxford Her work focuses on multi-scale cardiac modeling , particularly in ischemic heart disease and heart failure, exploring ionic currents, tissue conduction, and organ-level dynamics. She develops electromechanical simulations to study cardiac alternans and arrhythmic risks, translating these into clinical applications for patient stratification and pharmaceutical testing. Recent publications emphasize in silico clinical trials , sex-specific cardiometabolic analysis, and Purkinje network modeling. Collaborative efforts with clinicians and pharmaceutical partners highlight her translational approach to regulatory science. Model of the Year 2024, BioModels EPSRC Impact Acceleration Account Microsoft Research Project Award Recognition Award, University of Oxford She supervises PhD and MSc students in computational cardiology, while serving on the editorial board of Frontiers in Physiology . Her current projects involve digital twinning and predictive cardiac safety models to reduce animal testing reliance.
Professor Byung S. Lee is a distinguished faculty member in the Department of Computer Science at the University of Vermont's College of Engineering and Mathematical Sciences. He joined UVM in 1999 and continues to be actively engaged in teaching, research, and service. His office is located in Innovation Hall at the Burlington campus, where he maintains regular office hours and oversees his research lab. Professor Lee holds a Ph.D. from Stanford University, an MS from Korea Advanced Institute of Science and Technology, and a BS from Seoul National University. His educational background provided the foundation for his extensive career in computer science research and education. Professor Lee's research spans multiple domains within computer science, with a particular focus on database systems, data mining, and data science. His work increasingly integrates machine learning techniques with traditional database approaches, especially in the analysis of time series data. He has made significant contributions to graph theory applications, anomaly detection methods, and environmental data analysis. His research often bridges computer science with practical applications in healthcare, environmental science, transportation, and astrophysics through interdisciplinary collaborations. An analysis of his recent publications reveals a strong trend toward time series analysis and anomaly detection, particularly applied to environmental monitoring and healthcare data. His work demonstrates a consistent evolution from foundational database research to more applied machine learning approaches, with increasing emphasis on real-world problem solving across multiple scientific domains. Professor Lee has served as primary advisor for numerous graduate students across multiple cohorts, including PhD candidates, Master's students, and postdoctoral researchers. His advising portfolio reflects the breadth of his research interests, with students working on topics ranging from graph neural networks to medical informatics applications. He has also been actively involved in professional service, serving on program committees for major conferences including SAC, PAKDD, DASFAA, and CIKM. Professor Lee leads a vibrant research laboratory that focuses on cutting-edge data science methodologies and their applications. His team collaborates extensively with researchers in environmental science, hydrology, and healthcare, demonstrating the interdisciplinary nature of modern data science research. The lab maintains active projects in time series analysis, graph analytics, and environmental monitoring systems, often working with large-scale datasets from real-world applications.
René van de Molengraft is a Full Professor of Robotics at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e). He holds dual professorships in EAISI High Tech Systems and EAISI Foundational. His research focuses on autonomous robotic systems operating in human environments, emphasizing adaptability and task execution in varying conditions. Academic Background: MSc in Mechanical Engineering (TU/e, 1986) PhD in Identification of Mechanical Systems for Control (TU/e, 1990) Career progression: Assistant Professor (1990–2008) → Associate Professor (2008–2024) → Full Professor (2024) Research Interests: Autonomous robotics, human-robot interaction, agricultural automation, and control systems. His work emphasizes practical applications, such as the Tech United RoboCup team (world champion in multiple years) and large-scale robotics competitions. Projects: Key initiatives include the Tech United RoboCup team, the AI-matters manufacturing network, and the Frontiers in Autonomous Systems Technology (FAST) project. He has organized major robotics events like the 2013 and 2024 RoboCup World Championships in Eindhoven. Labs/Teams: Founder and leader of Tech United, a robotics team renowned for its achievements in robotic soccer and service robotics. Active in TU/e's Robotics research group and collaborations with industry partners.
