جست‌وجوی استاد و پژوهشگر

• Cancer Nursing
• Genomics
• Personalized Health Care
• +۵ مورد دیگر

Professor Kim Alexander is a distinguished academic and clinician in Cancer Nursing at Queensland University of Technology (QUT), leading the School of Nursing's research initiatives. Her work spans personalized cancer care, genomics, and symptom management, with a focus on improving patient outcomes and quality of life. She holds joint appointments at St Vincent's Private Hospital and chairs key committees such as the Cancer Nurses Society of Australia Research Committee. Education: Doctor of Philosophy (Public Health), QUT Master of Education (Higher Education), QUT Graduate Certificates in Business (Philanthropy), Academic Practice, and Health Science, QUT Bachelor of Nursing and Public Health, QUT Research Interests: Professor Alexander's research integrates clinical practice with innovative methodologies, including systematic reviews, RCTs, and mixed-methods approaches. Key areas include genomic applications in cancer care, patient-reported outcomes (PROs), and tailoring interventions to improve survivorship. Her work emphasizes translational research and industry collaboration, such as enhancing St Vincent's Hospital's research capacity through strategic partnerships. Awards: 2015 Vice-Chancellor's Award for Excellence in Learning & Teaching National/international recognition in cancer genomics and survivorship Grants & Industry: She collaborates with organizations like QLD Health and the Department of Veterans Affairs. Recent projects include the iPROMOS implementation study and EVEREST energy conservation trial, demonstrating her commitment to real-world healthcare impact. Labs & Teams: Active member of QUT's Centre for Healthcare Transformation and Cancer and Palliative Care Outcomes Centre , fostering interdisciplinary research networks.

Julien Delarueمشاهده پروفایل

دانشیار

• Sensory Science
• Consumer Behavior
• Food Technology
• +۳ مورد دیگر

Julien Delarue is an Associate Professor in Sensory & Consumer Science at the University of California, Davis. Formerly a Professor at AgroParisTech (Université Paris-Saclay), he specializes in sensory perception, consumer preferences, and contextual influences on food evaluation. His work integrates immersive environments and digital tools to study how context shapes hedonic measures and drives healthy/sustainable food choices. Research Focus: Delarue's studies address sensory determinants of food preferences, leveraging methods like rapid profiling and contextual testing. He explores category labels' impact on consumer expectations, sensory complexity in desserts, and the role of non-verbal evaluation (e.g., facial expressions) in assessing novel products. Leadership: He served as Chair of the French Society for Sensory Analysis (SFAS) and the European Sensory Science Society (E3S), advocating for rigorous methodologies in sensory evaluation. His interdisciplinary approach bridges food science, consumer behavior, and data science. Key Themes: Publications emphasize ecological validity in testing, sensory-led reformulation (e.g., cookies, pizzas), and the interplay between product context and perception. Recent work investigates non-dairy milk labeling, sports nutrition products, and child food preferences.

Kay C. Wieseمشاهده پروفایل

استاد

• Bioinformatics
• Computational Biology
• Evolutionary Computation
• +۴ مورد دیگر

Kay C. Wiese is a Professor and Software Systems Chair at the School of Computing Science, Simon Fraser University. His research focuses on computational intelligence and bioinformatics, particularly RNA secondary structure prediction and visualization. He leads the Bioinformatics Research Lab and has contributed to RNA design and gene finding. Wiese holds a PhD in Computer Science from the University of Regina (1999) and degrees in Computer Science and Mathematics from the Universität des Saarlandes (Germany). He has extensive editorial roles, including Associate Editor for the IEEE/ACM Transactions on Computational Biology and Bioinformatics, and has organized major conferences like the IEEE Symposium on Computational Intelligence in Bioinformatics. His teaching interests include Bioinformatics, Computational Biology, and Discrete Mathematics. Wiese has supervised numerous graduate students, including Boris Shabash, Wenbo Jiang, and Andrew Hendriks. His research group developed tools like jViz.RNA for RNA visualization and SARNA-Predict for structure prediction. His work bridges computational methods with biological applications, emphasizing algorithmic innovation and practical software solutions.

Elizabeth Clareمشاهده پروفایل

دانشیار

• Environmental DNA
• Biodiversity Monitoring
• Response of Species to Habitat Change
• +۴ مورد دیگر

Elizabeth Clare is an Associate Professor in the Department of Biology at York University, affiliated with the Faculty of Science. Her research focuses on developing novel technologies to monitor biodiversity and assess ecosystem responses to environmental change, particularly using environmental DNA (eDNA). She pioneered airborne DNA sampling to study terrestrial biodiversity at continental scales and has contributed to BIOSCAN, a global biodiversity program. Research Themes: Biodiversity monitoring, species interactions, environmental change resilience, bat biology, tropical ecosystems. Technological Innovations: Airborne eDNA, iDNA from leeches, and mobile lab sequencing in remote locations. Her work has been featured in Science , Nature , and media outlets like Wired and NPR . She teaches courses in evolution, ecology, and conservation biology, emphasizing critical thinking and applied research. Recent grants include NSERC and Genome Canada funding for airborne DNA projects. Clare collaborates globally, with fieldwork in Belize, South America, and Southeast Asia. Her lab's 'airDNA' technology has revolutionized biodiversity surveys, leveraging existing air-quality networks for ecological insights. She advises students on projects like urban bat ecology and BIOSCAN applications. Awards include election to the Royal Society of Canada (2023) and recognition for teaching innovations like the BioAudio podcast. Her lab also develops open-access tools, such as 3D-printable eDNA filters.

• Ecological Epidemiology
• Wildlife Disease Dynamics
• Veterinary Epidemiology
• +۴ مورد دیگر

Dr. Martin Lange is part of the Project Group Ecological Epidemiology within the Department of Ecological Modelling at the Helmholtz Centre for Environmental Research (UFZ). His research focuses on computational epidemiology, particularly in wildlife and livestock systems. Key areas include disease transmission dynamics, surveillance strategies, and the development of predictive models for infectious diseases like African Swine Fever (ASF) and Bovine Viral Diarrhea Virus (BVDV). Affiliations: UFZ, Department of Ecological Modelling; EcoEpi research group. Education: PhD in Veterinary Epidemiology (2013, TU Bergakademie Freiberg). Research interests span ecological epidemiology, wildlife disease control, and the application of agent-based and individual-based models to understand pathogen spread. Notable contributions include modeling ASF in wild boar populations and BVDV eradication strategies in Ireland. Awards: Received the 2018 UFZ-Wissenstransferpreis (shared with H.H. Thulke) and the Konrad-Bögel-Nachwuchsförderpreis for his doctoral work on eco-epidemiology of wild boar diseases. Also recognized at the DACh Epidemiologietagung 2011. Publications: Over 50 peer-reviewed articles since 2006, emphasizing interdisciplinary approaches to disease modeling and environmental systems. Recent work includes digital twin frameworks for biodiversity monitoring and Python-based model coupling tools like FINAM. Labs/Teams: Active in the EcoEpi group and contributes to projects like BioDT (Biodiversity Digital Twin) and CauSES (Causation in Social-Ecological Systems).

Sicong Sunمشاهده پروفایل

استادیار

• Equity
• Financial Capability and Asset Building
• Health Disparities
• +۵ مورد دیگر

Sicong (Summer) Sun is an Assistant Professor of Social Welfare at the UCLA Luskin School of Public Affairs. Born in China as a first-generation immigrant and identifying as nonbinary queer, they hold a Ph.D. and MSW from Washington University in St. Louis. Previously, they served as faculty at the University of Kansas School of Social Welfare. Their research focuses on intersections of race, poverty, and health equity, with a particular emphasis on how structural racism influences wealth disparities and health outcomes. Sun’s work bridges quantitative analysis, policy advocacy, and interdisciplinary collaboration to address systemic inequities. Education: Ph.D. in Social Work, Washington University in St. Louis Master of Social Work, Washington University in St. Louis Research Interests: Racial/ethnic inequities in wealth and health Social determinants of health Financial capability and asset building Immigration and mental health Sun’s publications span journals like Annual Review of Public Health , SSM – Population Health , and Journal of Racial and Ethnic Health Disparities , emphasizing empirical and theoretical contributions to health equity. Their research highlights how wealth disparities rooted in structural racism exacerbate health inequalities across lifespans. Recent work examines racial differences in wealth-health relationships and evaluates interventions like cash transfers in global health contexts. Awards: Outstanding Doctoral Dissertation Award (Society for Social Work Research) Jane Aron Fellowship (National Association of Social Workers Foundation) Teaching: Courses include Foundations of Social Welfare Policy and Human Behavior and the Social Environment (HBSE). Dr. Sun advocates for data-driven policies to combat socioeconomic and racial inequities, with ongoing projects in Uganda and Hong Kong. Their interdisciplinary approach integrates public health, social work, and economics to foster actionable solutions.

• Artificial Intelligence
• Machine Learning
• Fairness in AI
• +۵ مورد دیگر

Sanmi Koyejo is an Assistant Professor of Computer Science at Stanford University and holds an adjunct position as Associate Professor at the University of Illinois at Urbana-Champaign. He leads the Stanford Trustworthy AI Research (STAIR) group, focusing on fairness, robustness, and healthcare applications in machine learning. His work bridges theoretical foundations with practical systems, emphasizing ethical AI and clinical informatics. Affiliations: SAIL, HAI, CRFM, AIMI, AI Safety, and the Machine Learning Group. Research Interests: His expertise spans trustworthy AI, federated learning, and neuroimaging. He actively addresses challenges in algorithmic fairness, particularly in healthcare, where he collaborates with institutions like OSF Healthcare on projects like federated learning for clinical data. Key Contributions: Co-developed frameworks for unlearning in large language models, evaluated AI systems' societal impacts, and advanced benchmarks for medical applications. His work has been featured in venues like NeurIPS, ICML, and AAAI. Awards: NSF CAREER Award, Alfred P. Sloan Fellowship, and Terman Faculty Fellowship. Grants & Teams: Leads NSF-funded projects on domain adaptation and fairness in breast cancer risk scoring. Collaborates with interdisciplinary teams on NIH's MIDRC and NSF's AIFARMS initiative for agricultural sustainability. Labs/Teams: STAIR lab drives interdisciplinary research in ethical AI, with emphasis on real-world deployment and policy implications.

Andreawan Honoraمشاهده پروفایل

مدرس

• Digital Technology
• Service Management
• Consumer-Brand Relationships
• +۳ مورد دیگر

Andreawan Honora is a Lecturer in Marketing at the UWA Business School, University of Western Australia, since February 2024, previously serving as a Postdoctoral Research Associate at Ivey Business School, Western University, Canada. His academic qualifications include: Ph.D. in Business Administration (Marketing) from National Dong Hwa University (awarded January 31, 2022) Master of Management (Marketing) (awarded July 31, 2017) Bachelor of Science in Management (Marketing) (awarded February 1, 2016) Honora's research examines how digital technologies shape consumer and employee behavior, focusing on service management, consumer-brand relationships, and psychological impacts. His work explores business applications of technology and contributions to social goals like health and well-being through experimental methodologies. His 2024-2025 publications reveal interdisciplinary trends spanning healthcare informatics (telemedicine, electronic health records), AI-driven workplace dynamics, and social media psychology. Key themes include technology-induced behavioral changes, service recovery mechanisms, and health-focused digital interventions, bridging marketing, information systems, and public health. Honora serves as co-applicant on a 2025 SSHRC Insight Development Grant (CAD 58,165) from Canada's Social Sciences and Humanities Research Council. No student advising information is available.

Fred Espen Benthمشاهده پروفایل

استاد

• Mathematical Finance
• Energy Markets
• Insurance
• +۴ مورد دیگر

Roles and Affiliations: Fred Espen Benth is a Professor in the Department of Mathematics at the University of Oslo, affiliated with the Risk and Stochastics research group. He holds a Dr. scient (PhD equivalent) in mathematics from the University of Oslo (1995). His academic journey includes roles as a researcher at the Norwegian Computing Center, a postdoc at the Universities of Aarhus and Oslo, and an Associate Professor at the University of Trondheim before becoming a full professor in 2002. Research Interests: Benth’s research focuses on mathematical finance, particularly energy and weather markets, commodity derivatives, and stochastic analysis. He explores modeling, estimation, and simulation of spot and forward prices, as well as pricing options and portfolio optimization. Recent work extends to climate systems, energy transition dynamics, and machine learning applications in financial and environmental modeling. Publications and Projects: His extensive publication record includes over 150 journal articles and book chapters, with a focus on energy markets, stochastic processes, and climate-related financial instruments. Notable projects include ‘Spatial-Temporal Uncertainty in Energy Systems (SPATUS)’ and contributions to interdisciplinary energy informatics. His work bridges theoretical stochastic analysis with practical applications in energy systems and risk management. Labs and Collaborations: Benth collaborates with the Stochastics of Renewable Energy Markets (STORE) group and contributes to initiatives like the ‘Computational Modelling and Machine Learning for Applications in Hydropower’ project. His research emphasizes the integration of stochastic methods with real-world energy and climate challenges.

Colin Garrowayمشاهده پروفایل

دانشیار

• Biodiversity
• Evolutionary Biology
• Genetics
• +۵ مورد دیگر

Dr. Colin Garroway is an Associate Professor in the Department of Biological Sciences at the University of Manitoba, Faculty of Science. His research focuses on understanding how population-level processes influence biodiversity at genetic, population, and species levels. He employs interdisciplinary approaches, including genomics, ecological modeling, and data synthesis, to address challenges in conservation and climate change impacts. His work often targets systems undergoing significant environmental changes, such as urbanized areas and Arctic ecosystems. Dr. Garroway teaches advanced courses in Evolutionary Genetics and Evolutionary Biology. His research emphasizes the interplay between human-driven environmental changes—such as urbanization and climate warming—and their effects on genetic diversity, species distribution, and adaptation. He leads the Garroway Lab, which collaborates on global projects like biodiversity assessments in protected areas and epigenetic studies in wildlife. Key research themes include: biodiversity conservation, climate adaptation genetics, urban evolution, and the genetic consequences of human activities. His work integrates field studies, genomic analyses, and computational models to provide actionable insights for conservation strategies.

Frederick R Haseltonمشاهده پروفایل

استاد

• Global Health Technologies
• Molecular Diagnostics
• Nano Science and Technology
• +۳ مورد دیگر

Frederick R. Haselton is a Professor of Biomedical Engineering, Chemistry, and Ophthalmology and Visual Sciences at Vanderbilt University’s School of Engineering. His research focuses on developing low-cost, accessible diagnostic technologies for global health challenges, particularly in resource-constrained settings. He leads the Haselton Lab, a multidisciplinary team advancing innovations like Adaptive PCR, coffee ring-based diagnostics, and quantum dot imaging systems. Education : Ph.D. in Bioengineering from the University of Pennsylvania; B.A. in Mathematics from Haverford College. Research Interests : Dr. Haselton’s work spans molecular diagnostics, nanotechnology, and global health. Key projects include: Adaptive PCR: A revolutionary PCR method using synthetic L-DNA for temperature-independent cycling, enabling point-of-care diagnostics. Coffee Ring Diagnostics: Leveraging evaporation phenomena to create simple malaria and tuberculosis tests requiring no electricity. Quantum Dot Imaging: Developing multispectral tools for retinal and cardiovascular disease monitoring. Global Health Collaborations: Leading LIGHT (Laboratories for Innovation in Global Health Technologies), a cross-disciplinary initiative addressing diagnostic needs in low-resource environments. Grants & Funding : Haselton has secured major grants from NIH, Bill & Melinda Gates Foundation, and others for projects like tuberculosis detection via magnetic bead systems and mobile-connected diagnostic tests. Labs & Teams : The Haselton Lab collaborates with faculty across engineering, medicine, and chemistry. Current personnel include postdocs, graduate students, and undergraduates working on projects ranging from HIV viral load monitoring to SARS-CoV-2 diagnostics.

Jisun Anمشاهده پروفایل

استادیار

• Computational Social Science
• Data Science
• Social Media Analysis
• +۳ مورد دیگر

Jisun An is an Assistant Professor at the Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington (IUB), leading the Social Data and AI (SODA) Lab. Previously, she held positions at Singapore Management University (SMU) and the Qatar Computing Research Institute (QCRI). She earned a Ph.D. in Computer Science from the University of Cambridge (2015), supported by EPSRC, and received the Google European Scholarship. Her research focuses on computational social science, leveraging NLP and machine learning to analyze social media, political communication, health informatics, and journalism. Education: Ph.D. in Computer Science (University of Cambridge, 2015). Notable roles include Associate Editor of EPJ Data Science and PC member for conferences like ICWSM, ACL, and AAAI. She co-organized the News and Public Opinion (NECO) workshop (2016-2020). Teaching includes courses on Performance Analytics and Computational Social Science. Research highlights include studies on media attention patterns, user engagement, hate speech detection, and public health campaigns. Her work bridges interdisciplinary gaps, combining theoretical foundations with practical computational methods. Recent projects explore discursive power in media systems and predictive modeling of collective behavior. Awards: Google European Scholarship Key Projects: Discursive Power in Media, Precision Public Health Campaigns, and Algorithmic Bias Analysis Labs/Teams: SODA Lab at IU, previously contributed to QCRI's research initiatives

Jiangwen Sunمشاهده پروفایل

استادیار

• Machine Learning
• Data Mining
• Medicine
• +۶ مورد دیگر

Jiangwen Sun is an Assistant Professor in the Department of Computer Science at Old Dominion University (ODU), within the College of Science. He directs the ODU Computational Systems Medicine Lab and focuses on machine learning approaches for analyzing multi-dimensional biological data (phenome, genome, transcriptome, etc.) to advance precision medicine and its automation. His research is supported by ODU and federal agencies like NIH and NSF. Education: Ph.D., University of Connecticut M.E., Nanjing University, China B.M., Secondary Military Medical University, China Research Interests: Machine learning/data mining for medicine, health, drug discovery, and bioinformatics Multi-view bi-clustering and integrative analysis of genomic/phenotypic data Phenotype refinement and genetic association studies for complex diseases Applications in addiction medicine, cardiovascular biology, and bovine development Publications: Over 40 peer-reviewed articles in top venues like NIPS, ICML, Bioinformatics, and BMC Genomics. Recent work focuses on cryo-EM protein structure analysis, single-cell multiomics, and epigenetic modeling. Awards/Grants: NIH/NSF funding pending; previously supported by UConn's Health Informatics Lab and collaborations with University of Pennsylvania. Teaching: Courses include Machine Learning (CS722/822), Data Structures (CS361), and Deep Learning in Medicine (CS795/895). Labs/Teams: Leads the ODU Computational Systems Medicine Lab and collaborates with UConn Health Informatics Lab, Penn Medicine, and others.

Ajita Rattaniمشاهده پروفایل

استادیار

• Biometrics
• Deepfake Detection
• Facial Recognition
• +۶ مورد دیگر

Ajita Rattani is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas, affiliated with Discovery Park. Her research focuses on biometrics, AI fairness, deepfake detection, and machine learning applications in health and security. She holds a Ph.D. in Computer Science and Engineering, with expertise in facial recognition, ocular biometrics, and multimodal authentication systems. Research Interests: Her work addresses algorithmic fairness in facial attribute classification, robustness of biometric systems against adversarial attacks, and developing lightweight models for on-device authentication. She also explores applications of machine learning in health informatics, such as BMI prediction from facial images and analyzing social determinants of health. Publications Trends: Recent work emphasizes bias mitigation in AI systems (e.g., gender/racial fairness), deepfake detection through fusion of audio-visual cues, and advancing ocular biometric recognition under challenging conditions. Notable contributions include frameworks like CodeIT for data-efficient deepfake detection and PatchBMI-Net for lightweight BMI prediction. Advising & Grants: Leads research projects funded by NSF SaTC grants (e.g., probing fairness in ocular biometrics). Active in organizing competitions like VISOB 2.0 for mobile ocular biometrics evaluation. Her lab develops practical solutions for real-world challenges in biometrics and AI ethics. Labs/Teams: Involved in interdisciplinary teams addressing transdisciplinary collaboration challenges and applying AI to disaster detection (wildfires, droughts) using satellite and sensor data fusion.

Cody Buntainمشاهده پروفایل

استادیار

• Crisis Informatics
• Online Political Engagement
• Information Quality
• +۳ مورد دیگر

Cody Buntain is an Assistant Professor at the College of Information Studies (iSchool) at the University of Maryland (UMD), serving as Co-Director of the Center for AI, Data, and Conflict. He is also an Affiliate Fellow at UMD's Honors College – Artificial Intelligence Cluster and a research affiliate at NYU’s Center for Social Media and Politics (CSMaP). His research focuses on crisis informatics, online political engagement, and information quality, particularly examining how AI shapes information ecosystems during crises, conflicts, and social unrest. Dr. Buntain’s work addresses disinformation, health misinformation, and AI-driven methods for emergency response. Key affiliations include the Global Elections and Information Security (GEIS) initiative and the Tech Policy Research & Education Hub. His research has been featured in major media outlets like the New York Times, Washington Post, and WIRED. Education: PhD in Information Studies from University of Maryland (2016), postdoctoral research at NYU’s SMaPP Lab (2018-2019) and UMD’s Human-Computer Interaction Lab (HCIL, 2016-2018). Previously served as Assistant Professor at NJIT’s Informatics department and Adjunct Faculty at American University. Professional experience includes Director of Research at Pikewerks Corporation (2008–2013). Current projects include E-VERIFY (HMT-ISR analysis), M3I (maps/models for influence efforts), and the Incident Streams TRECIS initiative. His GitHub repositories reflect technical contributions to crisis informatics, including tools for social media analysis during disasters.