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Janet FranklinView profile

Professor

• Landscape Ecology
• Global Change Biology
• Conservation Biogeography
• +3 more

Janet Franklin is the Endowed Campanile Foundation Professor of Geography at San Diego State University (SDSU), affiliated with the College of Arts and Letters and the Center for Open Geospatial Sciences. Her research focuses on Landscape Ecology, Global Change Biology, and Conservation Biogeography, addressing ecological resilience to human-induced environmental changes. She holds a Ph.D. in Geography from the University of California, Santa Barbara (1988). Franklin’s career includes roles as Distinguished Professor Emerita at UC Riverside, Distinguished Biogeographer, and Adjunct Professorships at Arizona State University and the University of Queensland. She has led interdisciplinary projects on species distribution modeling, climate change impacts, and geospatial technologies. Her research emphasizes understanding plant community dynamics in forests, shrublands, and other ecosystems under global change. Collaborations with international scholars and practitioners drive solutions to ecological challenges. Notable awards include the James J. Parsons Award (2020), election to the National Academy of Sciences (2014), and Distinguished Fellow of the International Biogeography Society (2024).

Michael SummersView profile

Professor

• Planetary Science
• Astrophysics
• Atmospheric Science
• +3 more

Dr. Michael Summers is a Professor in the Physics & Astronomy Department at George Mason University, with dual affiliations as Research Faculty and Faculty member. He holds a Ph.D. in Planetary Science from Caltech (1985), an M.S. in Space Physics from UT Dallas (1979), and a B.A. in Physics, Mathematics, and Russian from Murray State University (1976). His research focuses on planetary atmospheres, particularly through NASA missions like New Horizons (Pluto/Kuiper Belt) and AIM (Earth's mesosphere). He has contributed to groundbreaking discoveries about Pluto's atmospheric composition and dynamics, and led studies on interstellar travel limitations and exoplanet habitability. Summers has received the Alan J. Berman Research Award (NRL, 1992 and 1998) and a GMU Teaching Excellence Award (2013). Teaching emphasizes science education for societal challenges, including developing Mason's first Ph.D. programs in physics and atmospheric science. Courses span introductory astronomy to advanced atmospheric physics, with a focus on undergraduate research engagement. Key projects include: New Horizons mission to Pluto and Kuiper Belt Aeronomy of Ice in the Mesosphere satellite mission Studies on interstellar panspermia mechanisms Exoplanet civilization modeling Publications highlight Pluto's atmospheric structure, interstellar travel constraints, and planetary taxonomy debates. His work bridges astrophysics, planetary science, and educational innovation.

Chengkai LiView profile

Professor

• Artificial Intelligence
• Data Science
• Data Management
• +9 more

Chengkai Li is a Professor and Associate Chair in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA), directing the Innovative Data Intelligence Research (IDIR) Lab and co-directing the Center for Artificial Intelligence and Big Data (CARIDA). He holds adjunct roles in the Multi-Interprofessional Center for Health Informatics (MICHI). His academic journey includes a Ph.D. from UIUC (2007) and faculty positions at UTA since 2007, progressing from Assistant to Full Professor (2019). Education: Ph.D. in Computer Science (UIUC, 2007), M.E. and B.S. from Nanjing University (2000, 1997). Research focuses on AI-driven data systems for social good, including computational fact-checking, knowledge graphs, and graph data usability. Key projects include ClaimBuster (end-to-end fact-checking), FactWatcher (automated fact monitoring), and Maverick (exceptional fact discovery). His work spans 30+ news features and collaborations with organizations like Knight Foundation and Google. Publications (over 100) appear in top venues (SIGMOD, KDD, VLDB), with awards like the 2017 SIGMOD Most Reproducible Paper Award. He advises over 30 students and leads grants totaling millions from NSF, Knight Foundation, and industry partners. Labs/Teams: IDIR Lab (40+ researchers), CARIDA (AI/Big Data initiatives), and partnerships with Duke Tech & Check Cooperative.

Nguyen Hong NguyenView profile

Senior Lecturer

• Aquaculture Genetics
• Genetics and Genomics
• Genetic Epidemiology
• +9 more

Dr. Nguyen Hong Nguyen is a Senior Lecturer in Genetics at the School of Science, Technology and Engineering, University of the Sunshine Coast (UniSC). He serves as a Deputy Honours Coordinator and a member of the Centre for Bioinnovation. With a PhD from Queensland, he holds Higher Education Academy (HEA) Fellow status and has been recognized for his research in aquaculture genetics by SciVal’s Distinctive Competency classification. His teaching responsibilities include coordinating Genetics and Advanced Genetics courses, reflecting his commitment to education and pedagogical development. Nguyen’s research focuses on genetic improvement programs for aquaculture species, particularly disease resistance in striped catfish, shrimp, and yellowtail kingfish. He has contributed to breakthroughs in understanding genotype-environment interactions, epigenetic inheritance, and the application of omics technologies. As an Associate Editor for five international journals—including Frontiers in Genetics and BMC Genetics —he actively shapes scholarly discourse in his field. He reviews for over 30 journals, such as Nature Reviews Genetics . His grants include AU$5 million from the Australian Research Council for rock lobster culture systems (2014–2019) and AU$7 million from ACIAR for giant grouper aquaculture (2013–2019). Collaborative projects with industry partners like Seafood CRC and FRDC aim to enhance genetic planning for species like kingfish. Nguyen has supervised HDR students such as Khang V Pham, Vu Nguyen, and Trang Trinh Thi, advancing applied research in aquaculture challenges. Future work emphasizes integrating multi-omic data and precision farming systems to improve disease resistance and sustainability in marine finfish and crustaceans. His interdisciplinary approach bridges genetics, genomics, and environmental science, addressing global food production demands.

• Biostatistics
• Clinical Trials
• Public Health Epidemiology
• +2 more

Patrick Dicker is a Lecturer in the Departments of Epidemiology and Public Health Medicine and Obstetrics and Gynaecology at the RCSI University of Medicine and Health Sciences, affiliated with the School of Population Health and the Data Science Centre. His research spans biomarker discovery, clinical medicine, and public health epidemiology, including: Health and lifestyle surveys in Ireland Health systems research in developing countries Cohort studies and clinical trials in maternal-fetal medicine Developmental cohorts in neonates and early childhood Biomarker discovery in schizophrenia, bipolar disorder, and oncology His recent publications focus on obstetrics, perinatal care, and clinical trial methodology, with recurring themes including fetal development assessments, screening protocols for congenital conditions, and complex interventions for maternal health. Trends show particular emphasis on improving diagnostic accuracy in prenatal care and developing evidence-based protocols for gestational health management. Dr. Dicker serves on scientific advisory boards for the Irish Epilepsy Association and Perinatal Ireland Consortium. His teaching activities include coordinating modules in Renal & GU systems, Evidence-Based Health, and lecturing on research methodologies for medical students.

Leia B BagesteiroView profile

Associate Professor

• Biomechanics
• Motor Control
• Neurological Movement Analysis
• +6 more

Dr. Leia B Bagesteiro is an Associate Professor in the Department of Kinesiology at San Francisco State University. She specializes in biomechanics and motor control, with expertise in analyzing human movement through kinematics, kinetics, and electrophysiology. Her academic background includes a B.Eng. and M.Eng. in Mechanical Engineering and Biomechanics from the Universidade Federal do Rio Grande do Sul, Brazil, and a Ph.D. in Biomedical Engineering from the University of Surrey, England. She also completed postdoctoral research at Penn State University’s Movement Neuroscience Laboratory and Columbia University’s Motor Performance Laboratory. Her research focuses on interdisciplinary applications of biomechanics and biomedical engineering, including prosthetics control, ADHD diagnosis via EEG signals, and pediatric motor control analysis. She teaches advanced courses such as Biomechanics, Advanced Biomechanics, and independent study modules. Notable research trends include the use of machine learning (e.g., random forests, spiking neural networks) for signal classification and the development of adaptive systems for prosthetics. Her work bridges clinical diagnostics, rehabilitation engineering, and educational methodologies, emphasizing practical applications of biomechanical principles. Dr. Bagesteiro has collaborated on projects involving gait analysis on compliant surfaces, interlimb coordination in children, and the effects of aging on motor control. Her contributions span experimental biomechanics, computational modeling, and clinical validation of movement-related technologies.

Stefan RadevView profile

Assistant Professor

• Bayesian Inference
• Deep Learning
• Probabilistic Modeling
• +3 more

Stefan Radev is an Assistant Professor in the Cognitive Science department at Rensselaer Polytechnic Institute . His work focuses on developing Bayesian methods with generative neural networks and computational models for complex systems like cognition and disease outbreaks. He is the core developer of the BayesFlow framework, which enables amortized Bayesian inference using deep learning. Radev's research addresses computational challenges in Bayesian workflows, such as rapid parameter estimation and model validation through neural networks. His primary research interests include Deep Learning , Probabilistic Modeling , and their applications in computational neuroscience and biomedical engineering. He collaborates with the Center for Modeling, Simulation and Imaging in Medicine (CEMSIM) and contributes to open-source projects like BayesFlow, which supports multi-backend frameworks (PyTorch/TensorFlow/JAX). Recent publications highlight advancements in amortized inference, simulation-based calibration, and robust Bayesian workflows. His work spans domains from cognitive modeling to biomedical imaging, emphasizing interdisciplinary applications of Bayesian methods. No scientific awards are explicitly listed, though his contributions to open-source tools and impactful research indicate significant academic recognition.

George SlotaView profile

Associate Professor

• Graph Mining
• Network Analysis
• Big Data Analytics
• +5 more

George Slota serves as an Associate Professor in the Computer Science Department within the School of Science at Rensselaer Polytechnic Institute (RPI). Previously, he held positions as a Computer Scientist at Sandia National Labs New Mexico and as a Computer Engineer at the Naval Undersea Warfare Center. His research spans graph and network mining, big data analytics, machine learning, bioinformatics , and their intersections with parallel computing, scientific computing, and high performance computing . His work focuses on scalable algorithms for trillion-edge graphs, graph partitioning, community detection, and GPU-accelerated graph processing. His recent publications reveal strong emphasis on graph coarsening and spectral methods distributed graph algorithms for biconnectivity and coloring random graph generation and validation GPU acceleration for graph neural networks His research has been recognized with a prestigious NSF CAREER award supporting his project "Scalable Graph Processing to a Quadrillion Edges and Beyond." Award: National Science Foundation Faculty Early Career Development (CAREER) Award His work demonstrates consistent funding and collaboration with major national laboratories including Sandia National Labs and involvement in ExaGraph projects targeting exascale computing challenges. He maintains an active research group focused on extreme-scale graph analytics.

Kevin KeenView profile

Professor

• Biostatistics
• Multivariate Statistics
• Clinical Epidemiology
• +6 more

Dr. Kevin Keen is a Professor in the Department of Mathematics and Statistics at the University of Northern British Columbia (UNBC). He joined UNBC in July 2004 and was promoted to full Professor in July 2015. Dr. Keen holds dual accreditation as a Professional Statistician (P.Stat.) from both the Statistical Society of Canada and the American Statistical Association, and is a Fellow of the Royal Statistical Society. His academic career includes visiting appointments at the Netherlands Institute for Health Sciences (Erasmus University, Rotterdam) and the Faculty of Medicine at Leiden University. Dr. Keen's research focuses on the development of novel statistical techniques and cutting-edge computer software for the analysis of multivariate data in the study of complex diseases. His expertise spans clinical epidemiology, data science, genetic epidemiology, molecular epidemiology, and multivariate statistics. He has made significant contributions to statistical graphics methodology, particularly through his widely used textbook "Graphics for Statistics and Data Analysis with R." His work bridges statistical theory with practical applications in biomedical research, especially in rheumatology and autoimmune diseases. Analysis of Dr. Keen's publication record reveals a strong focus on statistical methodology development applied to complex biomedical problems, particularly in rheumatology and autoimmune diseases. His work demonstrates consistent integration of advanced statistical techniques with clinical research questions, with particular emphasis on multivariate analysis of complex disease patterns. The trajectory of his research shows increasing specialization in statistical applications for systemic sclerosis, lupus, and related conditions, while maintaining strong contributions to fundamental statistical methodology and educational resources. Professional Statistician (P.Stat.) by Statistical Society of Canada Professional Statistician (PStat) by American Statistical Association Fellow of the Royal Statistical Society Pen and Scroll Award of the American Academy of Otolaryngic Allergy (2005) Certificate of Teaching Excellence from the University of Manitoba (1996) Commemorative Medal for the 125th Anniversary of the Confederation of Canada (1993) Dr. Keen actively supervises graduate students in PhD Health Sciences, MSc Mathematics, and BSc Mathematics programs at UNBC. He serves as a statistical consultant for clinical trials and public health intervention studies, applying his expertise in research design and analysis. His consulting work spans multiple domains including rheumatology, pulmonary medicine, and genetic epidemiology. Dr. Keen is available as a media expert on statistical matters and has contributed to developing standardized health assessment tools through his involvement with World Health Organization classification systems.

Zhibo ZhangView profile

Professor

• Climate Science
• Atmospheric Sciences
• Aerosol Physics
• +5 more

Dr. Zhibo Zhang is a Professor in the Department of Physics at UMBC and serves as Associate Director of Academics at the Joint Center for Earth Systems Technology (JCET). He holds a Ph.D. (2008) and M.S. (2004) in Atmospheric Sciences from Texas A&M University and a B.S. (2001) in Atmospheric Sciences from Nanjing University. His research focuses on aerosol-cloud-radiation interactions, climate modeling, and remote sensing applications. Key areas include quantifying aerosol effects on Earth's energy budget, analyzing low-level cloud dynamics in the Southeast Atlantic, and improving climate model representations of aerosol-cloud processes. Research is supported by NASA, DOE, NSF, and JCET. His group, the Aerosol, Cloud, Radiation-Observation and Simulation (ACROS) Group, employs satellite data (e.g., NASA's A-Train, DOE's ARM) and global/regional models to study climate change, air quality, and weather impacts. Recent work examines African biomass burning aerosols' interactions with marine boundary layer clouds and the role of cloud diurnal cycles in regional warming. Dr. Zhang has received prestigious awards including the UMBC Mid-Career Award (2022) and the IRC Young Scientist Award (2016). He has held leadership roles such as UMBC Physics Graduate Program Director (2014–2019) and has authored over 100 peer-reviewed publications. His work addresses critical gaps in climate model parameterization, aerosol radiative effects, and satellite data interpretation. Current research priorities include developing the CAMRO-Dust database, improving dust aerosol retrievals using thermal infrared methods, and leveraging machine learning for cloud detection and classification. Collaborations emphasize multi-sensor data fusion and bridging observational and modeling communities to advance Earth systems understanding.

Michael O'NeillView profile

Associate Professor

• Epigenetics
• Genomic Imprinting
• Sex Chromosome Biology
• +3 more

Michael O'Neill is an Associate Professor at the University of Connecticut , affiliated with the Department of Molecular and Cell Biology / Genetics and Genomics . His research focuses on epigenetic mechanisms in neurodevelopmental disorders and sex chromosome biology, particularly the role of X-linked imprinted genes in transgenerational effects and meiotic sex chromosome inactivation (MSCI). PhD: University of Texas at Austin Post-doctoral study: University of Melbourne, Princeton University Research highlights include: Elucidating the X Chromosome Imprinting Hypothesis through Turner Syndrome mouse models Discovering the role of Xlr3 in MSCI and its transgenerational consequences Investigating epigenetic transmission across generations Characterizing retroelement dynamics in speciation and genome evolution His recent publications emphasize X-linked gene regulation , retrotransposon activity , and transgenerational epigenetic effects across mammals, fish, and oceanic species. Contact: michael.oneill@uconn.edu | Phone: 860-486-6856

Mackenzie HoffordView profile

Assistant Professor

• Clinical Informatics
• Internal Medicine
• Sepsis Prediction
• +3 more

Mackenzie Hofford is Assistant Professor of Medicine in the Division of General Medicine at Washington University School of Medicine, serving as Associate Chief Research Information Officer. His clinical practice focuses on primary care, diabetes management, and chronic disease treatment. Research expertise centers on clinical informatics with emphasis on: Sepsis prediction models EHR data utilization Clinical decision support systems Predictive analytics in critical care Publications demonstrate consistent focus on developing validated tools for sepsis detection, respiratory support classification, and healthcare algorithm implementation across hospital systems. Contributes to policy discussions including responses to healthcare legislation impacting informatics practice. Affiliated with the Institute of Clinical and Translational Sciences (ICTS), Institute for Informatics, and Center for Applied Health Informatics.

Emily PostanView profile

Senior Lecturer

• Bioethics
• Data Ethics
• AI Ethics
• +5 more

Dr. Emily Postan serves as Senior Lecturer and Chancellor's Fellow in Bioethics at the University of Edinburgh's Edinburgh Law School, where she also holds the position of Deputy Director of the Mason Institute for Medicine, Life Sciences and the Law with lead responsibility for policy engagement. Her academic leadership extends to Director of Postgraduate Academic Guidance within the Law School. Her educational background includes a PhD from the University of Edinburgh (2017), LLM (Distinction), MA(Hons), and MLitt by research in Philosophy from the University of Edinburgh and University of Stirling. Prior to her academic career, she spent a decade in policy management at the Scottish Government. Postan's research centers on the intersection of biomedical technologies, personal information, and identity formation, with particular focus on how health informatics shapes our self-conception. Her work critically examines ethical governance frameworks for bioinformation, emphasizing the narrative dimensions of identity. She explores how AI-driven health data classification impacts belonging and social categorization, particularly through her current project 'Identity by Algorithm: Ethical Impacts of Categorisation by Health AI'. Her scholarly output reveals consistent engagement with neuroethics, genomic regulation, and AI ethics, with publications spanning from foundational identity theory to practical policy recommendations. The trajectory shows increasing focus on algorithmic governance in healthcare, culminating in the 2025 international consensus paper on AI trust frameworks. 2018 Rising Star lecture at International Neuroethics Society Annual Meeting Project leadership for Nuffield Council on Bioethics’ 2013 Novel Neurotechnologies report Key contributions to Scottish policy through Mason Institute submissions on organ donation, human tissue legislation, and Adults with Incapacity Act reforms As a doctoral supervisor, she mentors researchers in bioethics and medical law, currently guiding Gokce Kolukisa's work on 'Genome Editing in International Law'. Her Wellcome Trust-funded project 'Confronting the Liminal Spaces of Health Research Regulation' (2017-2021) established her as a leading voice in health research governance. Postan actively engages with media and policymakers on bioethics issues, bridging academic research and real-world application through the Mason Institute's policy portfolio.

Michael HeilemannView profile

Associate Professor

• Acoustics and Vibration
• Human-Computer Interfaces
• Spatial Audio
• +3 more

Michael Heilemann is an Associate Professor of Electrical and Computer Engineering at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from the same university (2018) and has been on faculty since 2018, focusing on instructional roles. His research emphasizes acoustics and vibration, human-computer interfaces, spatial audio, and digital audio effects, funded by the NSF, ONR, and New York State initiatives. He has been awarded eight patents and multiple teaching awards. Education: B.S. Physics (Canisius College, 2013); M.S. and Ph.D. in Electrical Engineering (University of Rochester, 2015 and 2018). Research interests include structural acoustic sensing, smart surfaces, and embedded machine learning for sound analysis. Notable work includes the University of Rochester room impulse response dataset and touch-location sensing on elastic surfaces. Awards include the AES Best Technical Paper (2022) and ECE Teaching Excellence (2023-2024). His work bridges signal processing and mechanical systems, with applications in audio interfaces, tactile feedback, and smart environments. Collaborative grants support projects like smart acoustic surfaces as multimodal interfaces.

Masoud FakhimiView profile

Senior Lecturer

• Modelling and Simulation
• Sustainable Development
• Operations Research
• +4 more

Dr. Masoud Fakhimi is a Senior Lecturer in Operational Research at the University of Surrey's Surrey Business School, affiliated with the Surrey Institute for People-Centred AI, Institute for Sustainability, and Centre for Business Analytics in Practice. He holds a PhD, MSc, and BSc in relevant fields. His research focuses on hybrid modeling and simulation methodologies applied to healthcare, sustainability, supply chain management, and Industry 4.0. He has received awards for teaching excellence and doctoral supervision, notably Surrey Business School's 'Teacher of the Year' (2021) and 'Postgraduate Research Supervisor of the Year' (2022). His academic background includes degrees in operational research and analytics. Research interests span hybrid simulation frameworks, sustainable operations management, and data-driven decision-making in healthcare and renewable energy sectors. He collaborates with industry and academic stakeholders on projects addressing circular economy challenges and AI-driven solutions. Key publications include a Springer monograph on hybrid modeling and simulation (2024) and peer-reviewed articles on healthcare system analysis, machine learning applications in biomarker detection, and disruptive technologies in agriculture. His work emphasizes cross-disciplinary approaches to complex decision-making in dynamic environments. Masoud supervises doctoral students in hybrid modeling and simulation methodologies, particularly in healthcare contexts. He actively contributes to research centers focused on AI ethics, sustainability, and business analytics innovation.