Dr. Mary E. Power is a Professor of the Graduate School at the University of California, Berkeley. She specializes in river ecology, focusing on algal-based food webs and their interactions with hydroclimatic regimes. Her research integrates field experiments and long-term monitoring in the South Fork Eel River, examining how flow variations and environmental conditions drive ecosystem state transitions. Primary Research Site: Angelo Coast Range Reserve (Mendocino Co., CA) Key Methodologies: In situ incubations, stable isotope probing, nanoSIMS analysis Current Focus: 2024- study of three alternative algal food web states during summer low flows Her work reveals critical thresholds where reduced summer flows and warming pools shift nutritious algal ecosystems toward toxic cyanobacterial dominance, impacting salmon and cross-ecosystem linkages. Selected Research Trends: Hydrological control of food web structure Cyanotoxin dynamics in river networks Climate change impacts on freshwater ecosystems Long-term ecological reconstructions via sediment cores Top-down and bottom-up regulation of river communities Her lab employs cutting-edge techniques to analyze microbiome elemental exchanges and successional patterns in Cladophora glomerata, a dominant green macroalga in the Eel River system.
Gregory Lawrence is a Professor in the Department of Civil Engineering at the University of British Columbia (UBC), Faculty of Applied Science. Since 1987, he has held a Tier I Canada Research Chair in Environmental Fluid Mechanics and focuses on the fluid dynamics of inland and coastal waters, particularly their impact on water quality, chemistry, and biology. His work addresses waste discharge minimization, lake restoration, and water system rehabilitation. He also instructs in UBC’s Master of Engineering Leadership in Integrated Water Management program. Research Interests : Environmental Fluid Mechanics, Hydraulics, Hydrodynamic Stability and Mixing, Physical Limnology, and Water Quality Management. His studies bridge fluid dynamics with environmental stewardship, emphasizing hydrodynamic processes in lakes, reservoirs, and mine pit lakes. Selected Publications highlight his expertise in stratified flows, Kelvin-Helmholtz instabilities, baroclinic responses, and artificial circulation techniques. These works span journals like Limnology and Oceanography , Physical Review Fluids , and Environmental Fluid Mechanics . Scientific Awards : 2018-2020: 2nd Year Student Appreciation Award (UBC Civil Engineering Club) 2016: Visiting Research Fellow (University of Western Australia) 2013: Elected Fellow (Canadian Society for Civil Engineering) 2012: Elected Fellow (Canadian Academy of Engineering) 2011: Camille Dagenais Award (Canadian Society for Civil Engineering) 2010: Premier’s Award – Partnership Category (British Columbia) 2001: Tier I Canada Research Chair in Environmental Fluid Mechanics 2001: Journal of Environmental Engineering Editor’s Award (ASCE) Teaching : Courses include CIVL 215 Fluid Mechanics I , CIVL 541 Environmental Fluid Mechanics , and CIVL 598L Contemporary Topics in Physical Limnology . He has been recognized for teaching excellence multiple times, including the 2018-2020 Student Appreciation Award.
Dr. George Chalhoub is a Lecturer (Assistant Professor) in Human-Computer Interaction at the UCL Interaction Centre (UCLIC), Department of Computer Science, University College London (UCL). He is also an Associate Member at the Department of Computer Science, University of Oxford, and a 2024–2025 Berkman Klein Fellow at the Berkman Klein Center for Internet & Society, Harvard Law School, Harvard University. His multidisciplinary research bridges cybersecurity, privacy, and human-centered computing, focusing on real-world technology use. DPhil in Cyber Security, University of Oxford (supported by Information Commissioner’s Office) MSc in Computer Science, University of Southampton (supported by Lloyd’s Register) BS in Computer Science, Lebanese American University His research centers on the security, privacy, and safety of digital technologies through a user-centered lens. Key areas include AI-powered systems (e.g., LLMs, smart assistants), emerging technologies in the wild (e.g., smart homes, IoT), embedded devices (e.g., routers), marginalized communities, data workers in AI, and online content creators. His work integrates UX principles to improve data protection in healthcare (e.g., NHS records) and children’s apps, with implications for GDPR compliance and responsible AI innovation. The analysis of his recent publications reveals a consistent focus on empirical studies of user experience in security and privacy, particularly in smart homes and data-intensive applications. His work spans design interventions, ethical frameworks, and policy-relevant findings, published in top venues like CHI, CSCW, SOUPS, and IJHCS. Themes include consent design, communal privacy, vulnerability patching, and developer support for privacy. UK Global Talent Visa recipient, UK Research and Innovation 2024–2025 Berkman Klein Fellow, Harvard University Dr. Chalhoub has advised on research projects related to secure networking by design and responsible AI (e.g., EWADA, RoboTIPS). He has received grant support from the Information Commissioner’s Office for his doctoral work. He is available for consultancy, collaborative research, grant assessment, and supervision of research degrees. His professional experience includes internships at Microsoft Research (Calc Intelligence) and Nokia Bell Labs (Social Dynamics), contributing to projects in AI and social computing. He is affiliated with research groups including the Human-Centered Computing group at Oxford, the UCL Interaction Centre (UCLIC), and the Berkman Klein Center at Harvard. His work is supported by tools and frameworks developed in collaboration with interdisciplinary teams focused on cybersecurity ethics, data governance, and platform accountability.
Stefano Noventa is a Research Fellow at the Methods Center, Department of Social Sciences, Faculty of Economics and Social Sciences, University of Tübingen. He has held multiple postdoctoral positions at the University of Tübingen and previously at the University of Verona and the University of Padova. Education: Ph.D. in Cognitive Psychology, University of Padova (2011) M.Sc. in Physics, University of Padova (2006) Studies in Physics, University of Padova (1999–2006) International Visiting Graduate Student, University of Toronto (2009, 2010) Dr. Noventa's research lies at the intersection of mathematical psychology, psychometrics, and psychophysics, with a focus on developing and unifying quantitative models of human cognition and assessment. His work integrates Item Response Theory (IRT) and Knowledge Space Theory (KST) to create more robust frameworks for educational and psychological measurement. He investigates latent variable models, probabilistic knowledge structures, and the identifiability of complex psychometric models, often applying these to domains such as education, organizational psychology, and entrepreneurship. His recent publications (2020–2024) demonstrate a strong trend toward theoretical integration, particularly in bridging cognitive diagnosis models with traditional psychometric frameworks. The articles emphasize mathematical rigor, model generalization, and empirical validation, with applications in both cognitive science and applied psychology. Topics include the unification of assessment models, parameter estimation under local dependence, and the modeling of intuitive physical reasoning. Scientific Awards: No awards or honors listed in the provided text. Dr. Noventa has not been explicitly mentioned as an advisor to students, but he has served as a corresponding author and collaborator on multiple research projects, indicating a leadership role in research teams. He has been involved in a DFG-funded project (GLI NON-NORM) since 2019, suggesting active grant participation. His work is highly collaborative, involving researchers from Germany, Italy, Austria, and Canada. Labs and Research Groups: Methods Center, University of Tübingen Hector Institute of Education Science and Psychology, University of Tübingen Center of Assessment, University of Verona Department of General Psychology, University of Padova
Professor Annette Byrne is a leading academic at RCSI University of Medicine and Health Sciences , where she serves as Professor of Physiology and Head of the Precision Cancer Medicine (PCM) Group. She has held this position since 2019 after progressing through roles as Lecturer (2008), Senior Lecturer (2013), and Associate Professor (2017). Her research focuses on precision medicine approaches for colorectal and brain cancers , integrating multi-modality molecular imaging , Next Generation Sequencing , and patient-derived xenograft models . PhD in Cell Biology (University of York, 1999) John Kerner Fellowship in Gynaecologic Oncology (UCSF, 1999-2001) Scientist at Pharmacyclics Inc. (2001-2003) Senior Scientist at Angion Biomedica Corp. (2003-2005) Principal Investigator at UCD Conway Institute (2005-2008) Her research interest lies in precision cancer medicine , particularly elucidating predictive biomarkers (genomic, transcriptomic, proteomic) and identifying novel therapeutic targets . Key methodologies include radiomics , fluorescence-guided surgery , and systems modeling of apoptosis pathways. She has pioneered Ireland's first Tumour Xenograft Facility and Translational In Vivo Imaging Centre . Recent publications highlight her work on cross-species radiomics , cell-free DNA analysis , and glioblastoma microenvironment subtyping . Her Marie Curie networks (Gliotrain, Glioresolve) and COLOSSUS project have trained 25+ PhD researchers in brain cancer therapeutics. Over €45M in national/international grants Member of Royal Irish Academy (2025) Highly cited in Cancer Discovery , Annals of Oncology , and Nature journals She supervises multiple PhD candidates and leads the RCSI Precision Cancer Medicine Group , which utilizes computational approaches and molecular imaging to improve cancer treatment outcomes. Her GLIORESOLVE and EDIReX projects focus on tumor microenvironment manipulation and distributed PDX infrastructure.
Jack Baker is the William Alden Campbell and Martha Campbell Professor of Engineering and Associate Dean for Faculty Affairs in the Stanford Doerr School of Sustainability at Stanford University. He is a Professor of Civil & Environmental Engineering with expertise in probabilistic and statistical tools for quantifying and managing disaster risk and resilience. His work has significantly influenced building codes, performance-based engineering guidelines, and catastrophe risk models. Dr. Baker's educational background includes: Ph.D. in Civil & Environmental Engineering from Stanford University (2005) M.A. in Statistics from Stanford University (2004) M.S. in Civil & Environmental Engineering from Stanford University (2002) B.A. in Mathematics/Physics from Whitman College (2000) His research focuses on disaster risk and resilience, particularly in earthquake engineering and seismic hazard analysis. Baker uses probabilistic and statistical approaches to analyze risk in spatially distributed systems, characterize earthquake ground motions, and simulate post-disaster recovery processes. His work bridges theoretical frameworks with practical applications in building codes and risk management strategies. He has made significant contributions to understanding the relationship between ground motion characteristics and structural response, while also expanding into climate-related hazards like atmospheric rivers and their compound effects. His recent publications demonstrate a growing focus on interdisciplinary research that connects engineering with socioeconomic factors in disaster contexts. There's a clear trend toward integrating machine learning techniques with traditional engineering approaches, particularly in modeling household displacement, economic recovery, and flood damage prediction. His work increasingly addresses the human dimension of disasters, examining how physical damage translates to social impacts and recovery timelines. Dr. Baker has received numerous prestigious awards recognizing his contributions to the field: William B. Joyner Lecture Award from the Seismological Society of America and Earthquake Engineering Research Institute (2023) PROSE Awards finalist for Seismic Hazard and Risk Analysis textbook (2022) Thorpe Medal from the European Council on Computing in Construction (2022) Walter L. Huber Civil Engineering Research Prize from the American Society of Civil Engineers (2018) CAREER Award from the National Science Foundation (2010) As an educator and mentor, Baker advises numerous doctoral and master's students while serving as Associate Dean for Faculty Affairs. His research group has secured significant funding for projects related to seismic risk, disaster recovery modeling, and infrastructure resilience. He has directed major initiatives like the Stanford Urban Resilience Initiative and co-founded the Haselton Baker Risk Group, demonstrating strong leadership in translating research into practical applications. Dr. Baker leads the Baker Research Group, which focuses on probabilistic approaches to disaster risk assessment and management. The group maintains active collaborations with government agencies, industry partners, and international research institutions to advance the state of knowledge in earthquake engineering and broader disaster resilience fields. Their work often involves developing innovative computational tools and frameworks that are made publicly available through GitHub repositories.
Tracy Becker is an Adjunct Assistant Professor in the Department of Civil Engineering at McMaster University, where she has been since 2014. Her expertise lies in the design, modeling, and experimental testing of high-performance structural systems with a focus on seismic isolation. Education: BS in Structural Engineering, University of California, San Diego MS and PhD in Structural Engineering, Mechanics and Materials, University of California, Berkeley Post-doctoral research at Kyoto University's Disaster Prevention Research Institute Research Interests: Becker specializes in seismic isolation systems, hybrid simulation methods, and structural performance under extreme events. Her work spans bridge engineering, nuclear infrastructure protection, and innovative materials for earthquake resilience. She integrates computational modeling with experimental validation to address challenges in: Nonlinear system behavior in isolated structures Multi-hazard optimization for seismic and wind loads Bridge management using data-driven and fuzzy logic frameworks Advanced gusset plate design for seismic retrofit Adaptive isolation systems for nuclear facilities Probabilistic lifetime demand predictions for infrastructure Teaching: She has instructed courses in Seismic Design (CIVENG 4ED4), Structural Mechanics (CIVENG 2C04), and Earthquake Engineering (CIVENG 730) at McMaster University.
Christine Tardif is an Assistant Professor in the Department of Biomedical Engineering and the Department of Neurology and Neurosurgery at McGill University. As head of the McConnell Brain Imaging Centre lab at the Montreal Neurological Institute, she develops advanced MRI techniques for in-vivo brain imaging, focusing on quantitative mapping of myelin and cortical microstructure. Her work spans methodological innovation (e.g., multi-modal biophysical modeling) and translational applications across preclinical (7 Tesla) and clinical (3 and 7 Tesla) systems. Undergraduate: B.Eng. in Computer Engineering, McGill University (2004) Master's: M.Sc. in Bioengineering, Imperial College London (2006) PhD: Biomedical Engineering, McGill University (2011) Her research explores myelin dynamics in health and disease, emphasizing its role in neural conduction, brain plasticity, and cognitive functions. The lab investigates dysmyelination in psychiatric disorders (e.g., bipolar disorder) and neurodegenerative conditions (e.g., multiple sclerosis) using relaxometry , magnetization transfer , and diffusion-weighted imaging . Recent methodological work includes 3D MERMAID sequences for motion-insensitive diffusion imaging and optimization of magnetization transfer saturation maps. Current projects integrate ultra-high field MRI with histological validation in preclinical models (e.g., marmoset brain sections), aiming to bridge microstructural metrics with macro-scale brain function. Applications span Alzheimer's disease risk assessment via white matter alterations, synaptic density mapping in psychosis, and cortical laminar differentiation studies.
Manav Raj is an Assistant Professor of Management at the Wharton School, University of Pennsylvania. His research examines how technological change affects competition, strategy, and institutional frameworks, with emphasis on digital innovation, platforms, and artificial intelligence (AI). Education: B.A. in Economics (Dartmouth College, 2015); Ph.D. in Management & Organizations (NYU Stern, 2023) Research interests span: Digital transformation of industries Institutional influences on innovation AI's economic and organizational impacts Startup dynamics and patent strategies Labor market implications of automation His publications focus on AI exposure metrics, legislative institutional effects, and automation's economic consequences. Collaborations with Edward Felten, Robert Seamans, and Deepak Hegde highlight interdisciplinary approaches combining economics, management, and technology policy. Scientific awards include: NYU Stern Harold W. MacDowell Prize (2022) Kauffman Foundation Knowledge Challenge Grant (2020) Strategic Management Society Best Conference PhD Paper Prize (2020) At Wharton, he teaches: MGMT2140 - Tech & Innov Strategy MGMT7310 - Technology Strategy
Thomas Riise Johansen is a Professor in the Department of Accounting at Copenhagen Business School (CBS), where he has been affiliated since completing his PhD in Accounting from CBS in 2005. Prior to joining CBS, he worked at Ernst & Young (1996-2005), bringing practical industry experience to his academic role. His primary academic home is within the Department of Accounting, focusing on critical intersections between auditing practices and corporate governance structures. His research centers on auditing, sustainability accounting, corporate governance, and annual report disclosure. Key investigations include: The relationship between board networks and auditor selection Value and barriers in annual report innovation Performance evaluation systems within audit firms Public oversight mechanisms in auditing Information systems for sustainability reporting Accountability dynamics between employees and organizations His work bridges academic rigor and practitioner relevance, addressing evolving regulatory landscapes and market demands. Analysis of his 15 most recent publications reveals consistent focus on audit quality determinants, sustainability reporting evolution, and governance-audit interdependencies. Recent work increasingly examines EU regulatory frameworks (Taxonomy Regulation, climate risk disclosure) and Big 4 governance structures, reflecting growing emphasis on public interest accountability in auditing. He actively supervises master's theses in accounting, auditing, and corporate governance. His current research portfolio includes projects on: Revisors' declaration (FSR) Enforcement impact on financial reporting Annual report disclosure value enhancement TIME MIRROR: Accounting for Green Transition Diversity in accounting careers Behavioral aspects of auditor professionalism
Darrell Ross is a Professor in Entomology at the School of Natural Resource Sciences , North Dakota State University . Previously, he held professorial roles at Oregon State University in the Department of Forest Ecosystems and Society and served as Director of the Richardson Hall Quarantine Facility from 2006–2019. His academic journey began with a PhD in Entomology from the University of Georgia (1990), an MS in Forest Ecology from Oregon State University (1985), and a BS in Forest Science from Pennsylvania State University (1981). PhD , Entomology, University of Georgia, 1990 MS , Forest Ecology, Oregon State University, 1985 BS , Forest Science, Pennsylvania State University, 1981 Dr. Ross specializes in forest entomology, focusing on bark beetle ecology, pheromone-based management strategies, and biological control of invasive species like the hemlock woolly adelgid. His work integrates chemical ecology with forest health assessment and ecological restoration. His research emphasizes pheromone applications (e.g., MCH) for bark beetle control, predator-prey dynamics in biological control of adelgids, and habitat manipulation for pest management. Recent studies address biodegradable pheromone formulations, predator phenology for invasive species control, and post-outbreak ecological impacts on pollinators. At Oregon State University, he directed the Richardson Hall Quarantine Facility, contributing to large-scale forest protection strategies. Current work at NDSU continues his legacy in integrating chemical signaling with forest ecosystem management.
Marika Mae Cusick is a tenure-track Assistant Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health . She holds a PhD in Health Policy from Stanford University , alongside a BA in Statistical Science and an MS in Information Science for Health Tech from Cornell University and Cornell Tech respectively. Education: PhD in Health Policy, Stanford University MS in Information Science for Health Tech, Cornell Tech BA in Statistical Science, Cornell University Her research focuses on computational health policy methods to address structural inequities in chronic disease management, particularly for Chronic Kidney Disease (CKD) . She investigates how algorithmic modifications (e.g., removing race adjustments from eGFR equations) interact with broader healthcare system limitations. Recent publications include work on CKD screening equity , race adjustment in clinical algorithms , and decision modeling frameworks that integrate social and disease processes. Her studies highlight the insufficiency of purely algorithmic interventions without addressing systemic inequities. Contact: marikacusick@jhu.edu | GitHub
John Rand is a Professor in Development Economics at the Department of Economics, University of Copenhagen, where he has been employed since 2021. He previously served as Professor (mso) at the Faculty of Social Sciences (2015-2020) and Faculty of Science (2011-2014), Associate Professor (2008-2011), and Assistant Research Professor (2005-2008) at the same institution. He is currently Vice-chair of The Consultative Research Committee for Development Research (FFU) and co-director of the Development Economics Research Group (DERG). Professor Rand's research focuses primarily on development economics, with specific expertise in applied econometrics, impact measurement, industrial economics, and interdisciplinary methods. His work spans topics including climate-smart agriculture, economic policy in developing countries, trade and productivity, and governance issues. He leads multiple externally funded research projects including 'Energy transition and climate-smart agriculture in Vietnam', 'Economic Research and Policy Making in Kenya', and 'Sedentarization and climate change resilience in Nigeria'. His extensive publication record shows a strong focus on empirical research in developing countries, particularly in Africa and Southeast Asia. His recent work demonstrates consistent attention to practical policy implications, with a growing emphasis on climate change adaptation, resource allocation efficiency, and the intersection of economic development with environmental sustainability. His research often employs rigorous quantitative methods to address real-world development challenges. Professor Rand is actively involved in several research networks including the Copenhagen Center for Disaster Research (COPE) as part of the steering group and the UCPH Migration Research Platform. He serves as Head of Studies for Global Development and teaches Development Economics (BA) and Theories, Facts and Current Issues (MSc Global Development). He has presented his research at numerous international conferences including UNU WIDER conferences, Nordic Conference in Development Economics, and various country-specific development forums. His work has been referenced in policy sources and picked up by news outlets, indicating its relevance to current development debates.
Larry D. Wigger serves as Teaching Professor of Supply Chain Management and Faculty Director of Assessment and Accreditation at the Henry W. Bloch School of Management, University of Missouri-Kansas City. With over twenty years of industry experience spanning strategic leadership, operations, and global project management, he integrates practical expertise into academic instruction. His educational background includes: MA in Economics from University of Missouri-Kansas City MS in Supply Chain Management and general MBA from Elmhurst University BA in Business Administration from William Jewell College He is currently completing his PhD dissertation in Economics at UMKC with a co-discipline in Public Affairs and Administration. Wigger's research bridges supply chain visibility through blockchain technology, public policy responses to automation-induced unemployment, and modern monetary theory constraints. His work examines systemic economic structures while addressing practical industry challenges in labor markets and capital allocation. Recent publications demonstrate consistent thematic focus on securing supply chains via traceability systems, analyzing labor-housing dynamics in critical materials networks, and developing holistic economic frameworks for supply chain analysis. His scholarship uniquely connects theoretical economics with tangible supply chain disruptions and policy interventions. Though no formal advisees are documented, Wigger's industry leadership included equity positions in construction startups serving petroleum, retail, and hospitality sectors, plus three years managing post-earthquake reconstruction in Port-au-Prince. His accreditation role indicates significant administrative responsibilities within the business school.
Dr. Dragan Doder is an Assistant Professor in the Intelligent Systems group within the Faculty of Science at Utrecht University. His office is located in the Buys Ballot Building at Princetonplein 5, Room 5.20, 3584 CC Utrecht, Netherlands. He is actively engaged in research and teaching within the domain of Artificial Intelligence, with a specific focus on logical frameworks for AI systems. Dr. Doder's research expertise spans several interconnected areas of theoretical and applied AI. His primary interests include: Artificial Intelligence with emphasis on logical foundations Argumentation theory and frameworks Probabilistic reasoning and temporal logic Deontic logic for normative reasoning Human-centered AI approaches His work bridges theoretical computer science with practical applications in multi-agent systems and decision-making frameworks. Analysis of Dr. Doder's recent publications (2020-2025) reveals a strong focus on the intersection of logic, probability, and AI. His research trajectory shows increasing sophistication in handling uncertainty through probabilistic temporal logics, while maintaining strong connections to practical applications in multi-agent systems and argumentation frameworks. A notable trend is his work on integrating causal reasoning with probabilistic models, particularly in multi-agent contexts where group responsibility and risk assessment become critical concerns. His publications demonstrate consistent contributions to top AI conferences including IJCAI, AAAI, and ECAI. Dr. Doder actively collaborates with researchers across multiple institutions. His collaborative network includes prominent researchers in AI and logic from institutions worldwide. His research has practical implications for developing AI systems that can reason under uncertainty, handle complex normative constraints, and make responsible decisions in multi-agent environments. Dr. Doder is affiliated with the Intelligent Systems research group at Utrecht University, which focuses on developing theoretically sound approaches to AI that can be applied to real-world problems. The group emphasizes human-centered AI approaches that consider ethical implications and practical usability alongside technical excellence.
