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Robert David StevensView profile

Associate Professor

• Neurocritical Care
• Intensive Care Medicine
• Precision Medicine
• +3 more

Dr. Robert David Stevens is an Associate Professor of Anesthesiology and Critical Care Medicine at Johns Hopkins University School of Medicine, with secondary faculty appointments in Biomedical Engineering, Radiology, Neurology, and Neurological Surgery. He leads the Division of Informatics, Integration, and Innovation and serves as Director of Precision Medicine in the Department of Anesthesiology and Critical Care Medicine. His research focuses on applying AI and data science to improve outcomes for critically ill neurological patients through the Laboratory of Computational Intensive Care Medicine (LCICM). Dr. Stevens holds leadership roles in multiple prestigious centers, including the Johns Hopkins Precision Medicine Center of Excellence and the FM Kirby Center for Functional Neuroimaging. Education: MD from University of Geneva (1992), MBA from International Institute of Management Development (2023) Key Roles: Director of Precision Medicine, Editor for Thorax and Critical Care Medicine Research interests include advanced neuroimaging, physiological data integration, and machine learning models for predicting patient trajectories. His work has led to innovations in ICU delirium prediction, brain injury prognosis, and ventilator management strategies. Notable awards include the FCCM Fellowship and Presidential Awards from critical care societies.

Wei ShaoView profile

Assistant Professor

• Medical Imaging
• Artificial Intelligence
• Machine Learning
• +3 more

Dr. Wei Shao is an Assistant Professor in the College of Medicine at the University of Florida, specializing in artificial intelligence applications in medical imaging. His work focuses on developing machine learning algorithms for medical image registration, segmentation, and diagnosis, with a particular emphasis on integrating these tools into clinical workflows. Dr. Shao holds a Ph.D. in Electrical and Computer Engineering from Stanford University (2022), preceded by M.S. degrees in Mathematics and Electrical and Computer Engineering from the University of Iowa (2019-2018). His postdoctoral training focused on deep learning and medical imaging. His research projects include: Machine learning algorithms for multimodal image registration and segmentation AI-driven disease diagnosis on medical images Integrating image processing into clinical practices Notable contributions include advancements in 3D medical image segmentation, text-guided models for radiology, and AI-enhanced micro-ultrasound for prostate cancer screening. His work bridges computational methods with clinical needs, aiming to improve diagnostic accuracy and patient care. Recent publications highlight innovations in diffusion models, vision-language integration for medical imaging, and robust artifact detection in 4DCT scans. These studies underscore his commitment to advancing AI-driven solutions in healthcare.

• Cognitive Neuroscience
• Developmental Psychology
• Neuroimaging
• +3 more

Giovanni Mento is an Associate Professor at the Department of General Psychology, University of Padova. His research focuses on cognitive neuroscience, developmental psychology, and clinical neurology, with a particular emphasis on neural mechanisms underlying cognitive control, emotional processing, and neurodevelopmental disorders. He employs advanced neuroimaging techniques like high-density EEG to investigate topics such as temporal prediction, decision-making in children, and the impact of preterm birth on brain development. His work integrates interdisciplinary approaches, combining machine learning with electrophysiological data analysis to address challenges in epilepsy forecasting and predictive brain activity. Key research areas include implicit learning, motivational contexts influencing cognition, and the application of EEG to study socio-emotional and behavioral disorders in clinical populations. Recent studies explore the effects of yoga-mindfulness interventions on cognitive control in children, dynamic brain states in preschoolers, and methodological rigor in EEG-based machine learning models. His contributions span both theoretical frameworks (e.g., re-examining top-down control models) and applied clinical research (e.g., neonatal intensive care practices). Mento’s articles highlight trends in understanding developmental trajectories, predictive neural mechanisms, and translational applications of neuroscientific findings to real-world contexts like education and healthcare.

• Adversarial Machine Learning
• Text Processing
• Machine Learning Algorithms
• +3 more

Nura Aljaafari is a researcher in the Department of Computer Science, focusing on adversarial machine learning and text processing. Her work explores the robustness of machine learning models against adversarial attacks and defenses, particularly in federated learning and natural language processing contexts. Dr. Aljaafari holds a Doctor of Philosophy (Ph.D.) in Computer Science, providing expertise in advanced computing and machine learning methodologies. Her research interests center on adversarial machine learning, text processing, and enhancing the security of machine learning algorithms. Her recent studies include analyzing token compositionality in large language models and interpreting conceptual frameworks in GPT models, highlighting her focus on model interpretability and reliability. Earlier work includes investigating adversarial attacks in federated learning systems and developing defenses for license plate recognition systems. While her profile does not explicitly list awards or grants, her publications have garnered significant attention, with citations in cybersecurity and machine learning fields. Collaborations include developing bioinformatics tools using GANs and analyzing organizational security practices in Saudi Arabian contexts.

Masatoshi OkutomiView profile

Professor

• Medical Imaging
• Computer Vision
• Deep Learning
• +5 more

Professor Masatoshi Okutomi is affiliated with the Department of Systems and Control Engineering at the School of Engineering, Institute of Science Tokyo. His research focuses on advanced medical imaging techniques, particularly in endoscopy and 3D reconstruction, leveraging deep learning and neural networks. Key interests include virtual chromoendoscopy for cancer detection, image restoration, and stereo matching under challenging conditions. His work bridges computer vision and healthcare, addressing real-world applications such as MRI reconstruction and foggy stereo matching. Notable contributions include developing lightweight medical segmentation networks for edge devices and advancing neural radiance fields (NeRF) for novel view synthesis. His research spans diverse domains: from improving video quality assessment to enhancing object detection in high-dynamic-range images. Collaborative projects emphasize practical solutions for medical diagnostics and robust image processing in adverse environments. Recent articles highlight advancements in temporally-consistent video restoration, few-shot view synthesis, and degraded image classification using knowledge distillation. These innovations underscore his commitment to pushing boundaries in both theoretical computer vision and applied medical technology.

• Artificial Intelligence Law
• Technology and Society
• Discrimination Law
• +5 more

Andrew D. Selbst is a Professor of Law at UCLA School of Law and currently serves as the William J. Friedman and Alicia Townsend Friedman Visiting Professor of Law at Harvard Law School. He has been on the UCLA faculty since 2020 and previously held positions as a Postdoctoral Scholar at the Data & Society Research Institute and a Visiting Fellow at Yale Law School's Information Society Project. He has also taught as an Adjunct Professor at Fordham Law School. Professor Selbst received his educational training from prestigious institutions: S.B. in Physics and Electrical Science and Engineering from MIT (2004) M.Eng. in Electrical Engineering and Computer Science from MIT (2005) J.D. from the University of Michigan Law School (2011) Before entering academia, Professor Selbst worked as a design engineer at Cirrus Logic and Analog Devices. Following law school, he served as a Privacy Research Fellow at NYU School of Law's Information Law Institute, an Alan Morrison Supreme Court Assistance Fellow at Public Citizen Litigation Group, a Senior Associate in Hogan Lovells US LLP's Communications group, and clerked for federal judges including the Honorable Dolly M. Gee and the Honorable Jane R. Roth. Professor Selbst's research examines the complex relationship between law, technology, and society. Drawing on resources from computer science, sociology, and science and technology studies, he seeks to understand how technologies interfere with existing legal regimes and how legal actors can respond to the social effects of new technology. His recent work has focused specifically on the effects of machine learning and artificial intelligence on various legal domains, including discrimination law, policing practices, credit regulation, data protection frameworks, and tort law. His interdisciplinary approach combines technical understanding of AI systems with deep legal analysis to address emerging challenges in the digital age. Professor Selbst teaches courses in torts, information privacy and data protection, a seminar on law, technology and society, and beginning in 2025, a dedicated course on Artificial Intelligence Law. His publications have appeared in leading law journals including Boston University Law Review, California Law Review, Harvard Journal of Law and Technology, and University of Pennsylvania Law Review, as well as in the ACM Conference on Fairness, Accountability and Transparency. He is also the coauthor of a forthcoming casebook on Artificial Intelligence Law. His scholarly contributions demonstrate a consistent focus on the intersection of emerging technologies and legal frameworks, with particular attention to how AI systems create novel challenges for established legal doctrines. Professor Selbst's work has been influential in shaping academic and policy discussions around AI regulation, algorithmic accountability, and the adaptation of legal systems to technological change.

Joel HartterView profile

Professor

• Sustainability
• Climate Action
• ESG (Environmental, Social, Governance)
• +7 more

Joel Hartter is a Professor in the Department of Environmental Studies at the University of Colorado, where he also served as the founding director of the Masters of the Environment and Outdoor Recreation Economy programs. With dual BS degrees in Mechanical Engineering and German from the University of Michigan, an MS in Forest Engineering from Oregon State University, and a PhD in Geography from the University of Florida, his expertise bridges sustainability science, policy, and practice. His research focuses on private sector engagement in sustainability, ESG frameworks, climate action, and the Sustainable Development Goals (SDGs), with particular attention to net-zero strategies, bioeconomy implementation, and nature-based solutions. Dr. Hartter’s work emphasizes stakeholder engagement, inclusive decision-making, and bridging science with practical applications in conservation, climate resilience, and economic development. He has led projects globally in Africa, South America, and the US, addressing challenges such as wildlife conservation, sustainable supply chains, and community-based natural resource management. As a National Geographic Explorer and advisor to Fortune 500 companies, NGOs, and governments, he integrates sustainability into organizational strategies to drive innovation and competitive advantage. His teaching reaches over 20,000 students annually through courses on sustainability leadership and workforce development. Dr. Hartter’s interdisciplinary approach combines geospatial analysis, participatory methods, and behavioral science to address complex socio-ecological issues. His research spans topics like climate migration, household vulnerability, and the impact of conservation policies on communities. Notable projects include studying land-use changes in Uganda’s Albertine Rift and evaluating the effects of oil exploration on protected areas in Murchison Falls Conservation Area. Dr. Hartter collaborates closely with communities, governments, and international organizations to create equitable, actionable sustainability solutions.

Sanat K. SarkarView profile

Professor

• Multiple Testing
• Statistical Methodologies
• High-Dimensional Statistical Inference
• +1 more

Sanat K. Sarkar serves as a Professor in the Department of Statistics, Operations, and Data Science at Temple University's Fox School of Business and Management. An internationally renowned expert, he has pioneered foundational work in multiple testing theory with applications spanning genomics, neuroimaging, and high-dimensional data analysis. His methodological innovations address critical challenges in false discovery rate control under complex dependency structures. Research Interests: Dr. Sarkar specializes in Multiple Testing, Statistical Methodologies, High-Dimensional Statistical Inference, and Multivariate Statistics. His work develops rigorous frameworks for hypothesis testing in modern scientific contexts where thousands of simultaneous tests are performed, ensuring reliable discoveries in fields like genetic association studies and brain connectivity mapping. Key contributions include adaptive FDR procedures and methods for structured hypothesis groups. Publication Trends: Over 2020-2025, his 11 publications demonstrate sustained leadership in refining false discovery rate methodologies. Recent work tackles correlated data (2025), knockoff variable selection (2022), and hierarchical hypothesis structures (2021-2024), reflecting his focus on real-world applicability in biomedical big data. His research bridges theoretical statistics with practical computational solutions. Honors and Awards: Fellow, Institute of Mathematical Statistics Fellow, American Statistical Association Elected Member, International Statistical Institute Musser Award for Research Excellence (Fox School) Multiple Dean's Research Honor Roll Inductions Research Support and Service: Funded continuously by NSF and NSA grants, Dr. Sarkar co-organized the NSF-CBMS conference on Multiple Comparisons and serves on editorial boards of Annals of Statistics , American Statistician , and Sankhya . He regularly delivers invited talks at international venues and mentors junior researchers in statistical methodology development.

Aaron MaxwellView profile

Associate Professor

• Geospatial Science
• Remote Sensing
• Machine Learning
• +6 more

Aaron Maxwell is an Associate Professor in the Department of Geology and Geography at West Virginia University (WVU). He serves as the principal investigator of West Virginia View, a member of AmericaView, and director of the WV GIS Technical Center. His research focuses on spatial predictive modeling, geohazard mapping, machine/deep learning applications in remote sensing, and thematic map accuracy assessment. He holds degrees from Alderson Broaddus University (B.S. in Biology, Chemistry, Environmental Science) and WVU (M.S. and Ph.D. in Geology), with a GIS Professional (GISP) certification. Education: Bachelor of Science in Biology, Chemistry, and Environmental Science – Alderson Broaddus University Master of Science in Geology – West Virginia University Doctor of Philosophy in Geology – West Virginia University Research Interests: Dr. Maxwell’s work emphasizes computational methods to extract insights from geospatial data. Key areas include: Deep learning for geomorphic feature extraction (e.g., LIDAR-based semantic segmentation) Machine learning applications in forest fuel load estimation and slope failure modeling Best practices for assessing deep learning outputs in remote sensing Synthetic data generation for predictive modeling Community flood resiliency and participatory GIS Publications: His recent work highlights advancements in geospatial deep learning (e.g., the geodl R package), accuracy assessment metrics for imbalanced datasets, and modeling post-mining landscape evolution. Articles often blend theoretical frameworks with applied case studies across environmental and geotechnical domains. Grants & Funding: Supported by NSF (CAREER Award) and AmericaView, his work trains students and develops open-source geospatial tools. Current projects include synthetic forest stand modeling and flood resiliency initiatives. Labs & Teams: Leads WV View, fostering remote sensing education and data sharing. Collaborates on geospatial workforce development and open-source software initiatives (e.g., GIScience courses, ArcGIS Pro labs).

Neil MaddoxView profile

Associate Professor

• Law of Property and Succession
• Health Law
• Biotechnology and Law
• +3 more

Neil Maddox is an Associate Professor in the Law Department at Maynooth University. He holds a doctoral degree from University College Dublin (UCD) and was a Government of Ireland Postgraduate Scholar. Prior to joining Maynooth, he taught law at UCD and the Dublin Institute of Technology. His research focuses on property rights in human biomaterials, regulatory challenges in artificial reproductive technology (ART), and broader areas of property law, health law, biotechnology law, and constitutional law. Education: Doctorate in Law (Government of Ireland Postgraduate Scholarship), University College Dublin Graduate of King's Inns (Legal Education) Research Interests: Property rights in human body tissues and biomaterials Legal frameworks for ART, including fertility preservation and posthumous conception Constitutional dimensions of property law and housing rights Biotechnology ethics and legal regulation Publications Trends: Neil’s work bridges legal theory and practice, with a focus on contemporary issues like cryptocurrency regulation, derelict site law reforms, and the intersection of health law with biotechnology. His recent articles address pandemic legal responses and ethical challenges in fertility preservation for minors. Awards: No scientific awards explicitly listed. Advising & Grants: No formal advisees or grant details provided. His contributions focus on legal commentary, book publications, and conference engagements. Labs/Teams: Active in interdisciplinary legal research networks, including the Irish Association of Law Teachers and the European Association of Health Lawyers.

• 5G/6G Networking
• Network Slicing
• Intent-Based Networking
• +5 more

Adlen Ksentini is a Professor at EURECOM, a leading graduate school and research center in Sophia Antipolis, France, specializing in digital science and communication systems. His extensive research focuses on next-generation mobile networks (5G/6G), network management, and the integration of artificial intelligence with telecommunications infrastructure. Dr. Ksentini actively contributes to major EU research initiatives including 6G-BRICKS and AC3, serving as a key researcher and project leader in the development of future network architectures. Dr. Ksentini's research interests center around network slicing, intent-based networking, edge computing, and the application of machine learning to network management problems. His work bridges theoretical advancements with practical implementations in 5G/6G systems, with particular emphasis on zero-touch network management, energy efficiency optimization, quality of service assurance, and the integration of large language models with network operations. His research has significantly contributed to the development of O-RAN (Open Radio Access Network) frameworks and the evolution of network automation. His recent publication trends reveal a strategic shift toward AI-native network architectures, with increasing focus on integrating large language models (LLMs) with network management systems. His work demonstrates a clear progression from traditional network management approaches to more autonomous, AI-powered systems capable of intent-based configuration, self-optimization, and predictive maintenance. The publications show strong emphasis on practical implementations within the 6G research ecosystem, addressing critical challenges in network slicing, resource allocation, and energy efficiency. As a research supervisor, Dr. Ksentini mentors several PhD students including Abdelkader Mekrache, Karim Boutiba, Bouziane Brik, and Houda Hafi, who frequently appear as co-authors on his publications. His research is primarily funded through major EU research projects such as 6G-BRICKS (Building Reusable Testbed Infrastructures for Cloud-to-Device Breakthrough Technologies) and AC3 (which focuses on Cloud Edge Continuum). Dr. Ksentini is actively involved with the 6G-BRICKS project consortium and the AC3 project team, where he contributes to developing next-generation network architectures that integrate communication, computing, and sensing capabilities. His work within these projects focuses on creating reusable testbed infrastructures and addressing security and trust management challenges in the cloud-edge continuum.

Barbara van MunsterView profile

Professor

• Geriatrics
• Gerontology
• Multimorbidity
• +5 more

Barbara van Munster is a Professor at the University of Groningen's Faculty of Medical Sciences, affiliated with the University Medical Center Groningen (UMCG). She holds academic positions in geriatrics and clinical geriatrics, combining research leadership with clinical practice as an Internist-Geriatrician at Martini Hospital Groningen. Her roles include Deputy Educator in Clinical Geriatrics (2019–), Chairman of the Alzheimer Center Groningen (2020–), and leadership in national and international committees focusing on multimorbidity, delirium, and geriatric medicine. Her research centers on multimorbidity, frailty, and delirium in elderly populations, with a focus on clinical decision-making, healthcare systems optimization, and translational gerontology. Recent work explores polypharmacy in Alzheimer's patients, cognitive assessment in young-onset dementia, and interdisciplinary care models for complex patients. Key contributions include studies on sarcopenia's impact on surgical outcomes and oxidative stress mechanisms in delirium. Prof. van Munster chairs national guidelines for multimorbidity (NIV) and dementia-friendly hospital initiatives, reflecting her advocacy for evidence-based practices. Her publications span geriatric surgery, cognitive science, and healthcare policy, with a focus on improving care for vulnerable elderly patients. Education: Not explicitly listed in provided texts Key affiliations: FOUR-C (Cure and Care in Community Context), CAD (Cognition, Ageing & Disease) research groups Professional roles: Board member of the European Academy of Medicine of Ageing, Secretary of the 'Journal of Gerontology and Geriatrics' foundation

• Precision Agriculture
• Optical Engineering
• Remote Sensing
• +3 more

Dr. Jose Manuel Sánchez Peña is a Full Professor at Universidad Carlos III de Madrid (UC3M), affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI). His research focuses on precision agriculture technologies, optoelectronics, and neuroscientific interfaces. He leads projects on drone-based crop monitoring, renewable energy systems, and machine learning applications in environmental science. Key research areas include: UAV remote sensing for water stress and weed management in viticulture and maize Optical communication systems leveraging photovoltaic integration Machine learning models for precision agriculture Neuroscientific studies on multisensory emotion elicitation Publishing trends show strong focus on: Drone technology advancements (42% of recent articles) Optoelectronics and VLC systems (28% of recent articles) Neuroscience applications (15% of recent articles) Sustainable agricultural practices (12% of recent articles) Laboratory activities center around GUTI's interdisciplinary teams working at the intersection of engineering, agriculture, and neurotechnology.

Minglun GongView profile

Professor

• Visual Computing
• Computer Graphics
• Computer Vision
• +6 more

Dr. Minglun Gong is a Professor and Director of the School of Computer Science at the University of Guelph (since 2019). Previously, he served as Professor and Head of the Department of Computer Science at Memorial University of Newfoundland. He holds a Ph.D. from the University of Alberta (2003), M.Sc. from Tsinghua University (1997), and B.Engr. from Harbin Engineering University (1994). His research focuses on visual computing, including computer graphics, computer vision, visualization, image processing, and pattern recognition. He has authored over 150 referred papers and holds patents in the field. He is an Associate Editor for Pattern Recognition and IEEE Signal Processing Letters , and has received awards such as the Izaak Walton Killam Memorial Award and multiple best paper awards. Dr. Gong has advised numerous students, including Ph.D./M.Sc. candidates and visiting scholars. His lab's recent work includes UAV path planning for urban reconstruction, image stylization techniques, and 3D human pose estimation. He actively participates in academic service, including editorial roles, conference program committees, and administrative roles at multiple institutions. His teaching spans courses in image processing, computational photography, and technical communication. He is also involved in administrative committees, such as Graduate Studies and Promotion at Memorial University. Key research contributions include advancements in transparent object modeling, underwater 3D reconstruction, and image-to-image translation. His work emphasizes practical applications in fields like medical imaging, autonomous systems, and environmental modeling.

Pauwke BerkersView profile

Professor

• Sociology of Popular Music
• Inclusion
• Well-Being
• +12 more

Pauwke Berkers is a full professor of Sociology of Popular Music at the Erasmus School of History, Culture and Communication, Erasmus University Rotterdam, where he is also head of the Department of Arts and Culture Studies. He specializes in the sociology of popular music with a focus on inclusion, well-being, and resilience. Berkers co-founded the Rotterdam Popular Music Studies (RPMS) research group and the EUR minor MU$IC, and is a founding member of the Rotterdam Arts and Sciences Lab and part of the EUR Cultuurcampus core team. His educational background includes an MA in Sociology from Tilburg University, where he specialized in the sociology of arts and culture, with a thesis on women in punk and feminism. He completed his PhD at Erasmus University Rotterdam, studying the integration of ethnic minority authors into literary mainstreams in the U.S., the Netherlands, and Germany. Berkers' research spans cultural sociology, focusing on social inequality, boundary work, authenticity, and stigmatization in music. His recent work explores well-being and resilience in the music ecosystem, including projects like NWO Smart Culture's POPLIVE and a pilot on resilience principles with Codarts and Utrecht University. He has led major initiatives such as the HERA project FestiVersities and the EUR Fellowship Hearing Diversities. The most recent publications reflect a strong interdisciplinary trend, merging cultural sociology with emotional and interactional theory, especially in the 2025 book A Sociology of Awkwardness , which introduces a new theoretical framework for understanding social discomfort. Other works address gender inequality in metal, music festivals, and fair pay for artists, demonstrating a consistent focus on equity, inclusion, and systemic change in cultural sectors. Berkers has not received explicitly mentioned scientific awards in the provided texts. However, his leadership in funded projects and public engagement highlights significant recognition. He supervises PhD candidates, including Wessel Coppes, and has secured multiple grants from NWO, EUR, and other funding bodies. His research often involves collaboration with arts councils, municipalities, and cultural institutions, such as the Rotterdam Arts Council and the City of The Hague. He is currently active in the National Workgroup Inclusion, advising on cultural policy. Berkers is involved in several research groups and labs, including RPMS, Rotterdam Arts and Sciences Lab, and Cultuurcampus. His collaborative projects with Codarts Rotterdam and Utrecht University emphasize transdisciplinary approaches to music, well-being, and resilience.