جست‌وجوی استاد و پژوهشگر

Jamie S. Myersمشاهده پروفایل

دانشیار

• Cancer-Related Cognitive Impairment
• Oncology Nursing
• Cancer Survivorship
• +۵ مورد دیگر

Jamie S. Myers, PhD, RN, AOCNS, FAAN serves as a Research Associate Professor at the University of Kansas Medical Center School of Nursing, leveraging 40 years of advanced practice oncology nursing experience. Her institutional affiliations include active leadership roles in the SWOG Clinical Trials Research Network (Symptom Control and Quality of Life Committee Chair) and the Oncology Nursing Society (30+ years of national service, including Oncology Nursing Foundation Research Grant Review Co-Chair). Dr. Myers' educational background comprises: PhD in Oncology, University of Kansas School of Nursing MN in Medical-Surgical Nursing (Oncology emphasis), University of Kansas School of Nursing BSN in Medical-Surgical Nursing, University of Kansas School of Nursing Post Doctoral Fellowship in Cancer Survivorship, University of Pittsburgh Her research program centers on cancer-related cognitive impairment, specifically investigating prevention and management strategies for cognitive changes during and after cancer therapy. This encompasses qualitative studies of survivors' lived experiences, predictive modeling of cognitive decline, novel assessment methods for cognitive effort, and multimodal interventions including psychoeducation-based cognitive rehabilitation, combined exercise programs with nutritional counseling, and mindfulness-based approaches. Current work examines biomarker correlations and digital health applications for objective cognitive assessment. Analysis of her 15 most recent publications reveals a strong focus on interventional studies for cognitive rehabilitation (60%), with increasing emphasis on digital health tools (25%) and biomarker research (15%). Her work consistently targets breast and prostate cancer populations, with growing attention to health disparities related to adverse childhood experiences and social determinants of health. Scientific recognition includes: Fellow of the American Academy of Nursing (FAAN) Advanced Oncology Clinical Nurse Specialist certification Advanced Oncology Nurse certification Advanced Practice Registered Nurse licensure Dr. Myers currently leads NRG-CC011, a multi-center randomized trial on cognitive training for breast cancer survivors, and serves as Site-PI for multiple SWOG network studies. Her research program integrates clinical trials with implementation science, focusing on translating cognitive rehabilitation strategies into community oncology settings through the NCI Community Oncology Research Program. She actively contributes to the SWOG Nursing Research Subcommittee and collaborates with interdisciplinary teams across symptom management, neurocognitive assessment, and digital health innovation to advance survivorship care standards.

Carla Teixeira Lopesمشاهده پروفایل

دانشیار

• Information Retrieval
• Human-Computer Interaction
• Health Informatics
• +۴ مورد دیگر

Carla Teixeira Lopes is an Associate Professor in the Department of Informatics Engineering at the Faculty of Engineering, University of Porto (FEUP), and a Senior Researcher at the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC). Her career spans academic and research roles, blending expertise in information retrieval with human-computer interaction to enhance digital accessibility. Ph.D. in Informatics Engineering (2013), FEUP M.Sc. in Information Management (2005), FEUP B.Sc. in Informatics Engineering and Computing (1999), FEUP Her research focuses on improving online health information retrieval and leveraging linked data for cultural heritage preservation. She develops tools to optimize search behavior, readability assessment, and semantic archival systems. Recent work includes applications of large language models (e.g., Llama 3, GPT) for text simplification and entity linking. Carla’s publications reflect interdisciplinary trends in Natural language processing Health informatics Linked data architectures Archival modernization Image metadata frameworks She contributes to digital library practices and gender balance studies in informatics academia. As a Senior Researcher at INESC TEC, she bridges academic and applied research, emphasizing user-centric design and data interoperability. Her email is ctl@fe.up.pt .

Michael Cianfroccoمشاهده پروفایل

دانشیار

• Structural Biology
• Cryo-Electron Microscopy (Cryo-EM)
• Microtubule-Based Intracellular Transport
• +۴ مورد دیگر

Michael Cianfrocco is an Associate Professor at the University of Michigan, holding dual roles in the Department of Biological Chemistry (Medical School) and the Life Sciences Institute. His research focuses on structural biology and microtubule-based transport, leveraging cryo-electron microscopy (Cryo-EM), single-molecule methods, and computational tools to study motor proteins like kinesin and dynein. Education: B.S. in Biochemistry, Providence College (2007) Ph.D. in Biophysics, University of California, Berkeley (2012) Postdoctoral Fellowships at Harvard Medical School and UC San Diego (2013–2017) Research Interests: His lab investigates how motor proteins transport cargo in cells, with emphasis on specificity, regulation, and pathogen hijacking. They also develop computational tools like cryoEDU and CryoRL to streamline Cryo-EM workflows. Key areas include viral transport mechanisms, microtubule dynamics, and AI-driven microscopy automation. Awards: 2013 Damon Runyon Cancer Research Foundation Award 2017 University of Michigan Biological Sciences Scholar Advising & Leadership: Director of the Perrigo Undergraduate Summer Fellowship Program. Mentors students in the Life Sciences Institute and collaborates with teams in cellular and molecular biology. Active in graduate programs in Biomedical Sciences, Chemical Biology, and Biophysics. Labs & Teams: Leads the Cianfrocco Lab, which includes researchers, postdocs (e.g., Andrew Hensley, Lai Wei), and a vibrant graduate cohort. Collaborates with experts in structural biology, computational science, and virology.

Majed Almotairiمشاهده پروفایل

استادیار

• Information Systems
• Information Security
• Education Technology
• +۳ مورد دیگر

Majed Almotairi is an Assistant Professor of Information Systems at Indiana Tech's Talwar College of Engineering and Computer Sciences since July 2023. Previously, he served as Assistant Professor at Southern Arkansas University (2019-2023) and Adjunct Professor at Towson University (2017-2019). He holds a Doctor of Science in Information Technology from Towson University (2019), a Master of Science in Information Systems from the University of East Anglia (2012), and a Bachelor of Education in Computing from King Saud University (2008). His research focuses on advancing Information Systems through customized learning solutions in education and healthcare contexts. Key areas include digital badging systems for student employability, healthcare decision support systems leveraging patient data, and metadata-driven health record management in cloud environments. His work bridges IT innovation with practical applications in education and healthcare delivery. Almotairi teaches courses such as Information Security, Database Management, Web Development, and Capstone Projects. His teaching philosophy emphasizes student success through personalized academic support both in and out of the classroom. His recent publications (2017-2023) reflect a strong emphasis on healthcare IT, customized learning frameworks, and information systems governance. No scientific awards are explicitly listed in his profile. His professional experience includes over 10 years in academia, with roles spanning teaching, research, and curriculum development in information systems and computer sciences.

Markus Wenzelمشاهده پروفایل

دانشیار

• Medical Imaging
• Deep Learning
• Healthcare AI
• +۳ مورد دیگر

Prof. Markus Wenzel is an Associate Professor of Medical Cognitive Computing at the School of Computer Science & Engineering, Constructor University Bremen. His research focuses on interpretable deep learning and computer-aided diagnosis systems for healthcare applications, particularly in medical imaging. He holds a PhD in 'Complexity Reduction in Image-Based Breast Care' (2014) from University Bremen and a BSc in Computer Science (With Distinction) from the Distance Learning University, Hagen. Wenzel has extensive industry experience, including roles at Fraunhofer MEVIS as a Key Scientist in Computational Breast Care (since 2021) and Senior Scientist (2005–2021). His work emphasizes clinical practicality, such as breast MRI segmentation and AI-driven diagnostic tools. Research highlights include developing the QuantMed platform for translational research and exploring generative adversarial networks (GANs) for medical data synthesis. He has authored over 50 peer-reviewed publications, with recent work focusing on CNN-based lesion detection, swarm learning, and uncertainty quantification in medical imaging. Awards include a prestigious scholarship from the Studienstiftung des Deutschen Volkes and certification as a Scientific Trainer (2022). Wenzel collaborates with clinicians to bridge AI research and clinical practice, addressing challenges like model interpretability and data scarcity in healthcare. His contributions span medical imaging analysis, AI-driven decision support systems, and robust deep learning frameworks for heterogeneous medical data.

Maren Beckerمشاهده پروفایل

استادیار

• Econometric Modelling
• Advertising Effectiveness
• Marketing Decisions
• +۴ مورد دیگر

Maren Becker is an Assistant Professor of Marketing and Research Methods at ESCP Business School’s Berlin Campus. Her research focuses on econometric modeling of marketing decisions, particularly analyzing advertising strategies and their effectiveness. She holds a PhD from the University of Cologne (2017) and has held visiting scholar positions at the University of Texas at Dallas (2016) and previously served as an Assistant Professor at Vrije Universiteit Amsterdam. Her work bridges academic research with practical applications, addressing topics like digital disintermediation, TV advertising authenticity, and content consistency in brand messaging. Before academia, Maren worked as a Senior Analyst and Consultant for a major market research firm and gained experience through internships at the Permanent Mission of Germany to the UN in New York, an NGO in São Paulo, and various industries. Her research has been published in top-tier journals such as the Journal of Marketing and Journal of Marketing Research , and featured in media outlets like Die Zeit and Harvard Business Manager . Key research themes include: Evaluating advertising content’s impact on consumer behavior Analyzing managerial applications of marketing science Assessing digital strategies’ effects on incumbent market dynamics Her interdisciplinary approach incorporates econometric rigor with real-world marketing challenges, contributing to both academic discourse and industry practice.

Nan Niuمشاهده پروفایل

دانشیار

• Requirements Engineering
• Machine Learning
• Software Engineering
• +۵ مورد دیگر

Dr. Nan Niu is an Associate Professor in the Department of Electrical Engineering and Computer Science (EECS) at the University of Cincinnati. He specializes in requirements engineering, software traceability, and model-driven approaches. His work focuses on machine learning applications, continuous deployment, and testing scientific software. Dr. Niu holds a Ph.D. in Computer Science from the University of Toronto (2010, supervised by Steve Easterbrook), an M.Sc. from University of Alberta (2006), and a B.Eng. from Beijing Institute of Technology (2004). Research interests include software engineering challenges in AI/ML systems, automated refactoring, and environment-driven requirements engineering. His research is funded by agencies like NSF, NSA, and industry partners like P&G. Recent publications address topics like POS tagging in code, GUI reuse via vision-language models, and privacy concerns in mobile apps. Teaching: Software Engineering (EECE3093C), Requirements Engineering (CS5127/6027), and Large-Scale Software Engineering (CS5128/6028) Labs/Teams: Active in requirements traceability and scientific software testing Awarded over 15 honors including NSF CAREER Award (2014-2019), Best Paper Awards at RE (2016,2018,2021), and teaching excellence recognition.

Helena De Rezendeمشاهده پروفایل

مدرس ارشد

• Patient Safety
• Healthcare Leadership
• Systematic Reviews and Meta-Analysis
• +۵ مورد دیگر

Helena De Rezende is a Senior Lecturer in Adult Nursing at Bournemouth University , England, with a focus on patient safety education , systematic review methodology (JBI and GRADE), and relational leadership . She serves as a PhD supervisor and Visiting Professor at the University of São Paulo, Brazil, where she contributes to global nursing education frameworks. Education PhD in Nursing Management (University of São Paulo, 2020) PGCE in Intensive Care Nursing (Unyleia Faculty, São Paulo, 2016) MSc in Health Services Management (ISCTE Executive Education, Lisbon, 2010) BSc (Hons) in Nursing (University of Campinas, 1999) Her research interests span patient safety , systematic reviews , leadership in healthcare , and cultural competency training . Recent publications (2025–2022) emphasize second victim phenomenon , simulation-based training , and leadership strategies to improve nurse well-being. Scientific contributions include Fellow of the Higher Education Academy Wessex Health Partners Grant for the SAFETY Project (2025) Leadership in Sigma Europe Region Communications Committee (2022–2025) Co-chair of European Communication Committee, Sigma European Region Her teaching portfolio at Bournemouth University includes research methods , patient safety , and clinical leadership for undergraduate nursing students. She actively engages in international collaborations, conference presentations, and peer-review activities for journals like Nurse Educator and Revista da Escola de Enfermagem da U S P .

David Gefenمشاهده پروفایل

استاد پژوهشی

• Trust in Technology
• IT Outsourcing
• Research Methodology (SEM)
• +۴ مورد دیگر

David Gefen: Academic Profile David Gefen, PhD, is the Provost Distinguished Research Professor and Academic Director of the Doctorate in Business Administration (DBA) Program at Drexel University’s LeBow College of Business. He holds a dual appointment in Decision Sciences and Management Information Systems. His research focuses on trust in IT systems, outsourcing, research methodology (SEM), and text analysis, with over 150 peer-reviewed publications in top journals like MISQ and ISR. Education & Career: Joined Drexel in 1997 after industry roles in software development. Earned an M.Sc. in Computer Information Systems and PhD from Georgia State University under Detmar Straub. Previously served as Senior Editor at MISQ and Editor-in-Chief roles at JMIS and JAIS. Research Interests: Explores trust dynamics in digital technologies, ERP implementation, and text analysis applications in healthcare and consumer behavior. Notable contributions include frameworks for measuring distrust in chatbots and analyzing adverse drug interactions via text mining. Awards & Recognition: Ranked in top 0.08% of global scientists (ScholarGPS), top 0.3% (Scientific Index 2023), and #703 in global Business & Management research (Research.com). Recognized for prolific HCI publications (3rd/4th, 1990–2008). Service: Senior Editor at JAIS, Advisory Board Member at JMIS, and active in editorial roles for top journals. Served on ICIS panels addressing curriculum reform and MIS research methods. Grants & Labs: Secured $50,000 for research on AI and epistemic welfare in ChatGPT discourse. Collaborates with Einstein Medical Center on telemedicine portals and Children’s Hospital of Philadelphia on telemedicine adoption barriers.

• Character animation
• Computer animation for movies and games
• 3D and 2D animation
• +۳ مورد دیگر

Jose Fonseca is a Lecturer in Games Technology at Bournemouth University's Department of Creative Technology, Faculty of Science & Technology. His academic career began with a part-time lecturing role at NCCA (Faculty of Media and Communication) in 2014, focusing on 3D modeling fundamentals. PhD in Computer Animation (Bournemouth University, 2016) MA in Digital Arts - Animation (Universidade Católica Portuguesa, 2002) Licentiate Degree in Teaching Visual Arts and Technology (Escola Superior de Educação de Santarém, 1997) His research focuses on character animation and body expression in 3D environments, blending traditional art principles with computational methods. Key areas include: 3D/2D animation pipelines Virtual human modeling Gaming animation integration Automated art guidelines Kinematic expression systems Animation pre-production workflows Recent publications span computer animation methodology, feedback optimization in 3D modeling, and hand tracking frameworks. His work bridges academic research with practical applications in gaming and cinematic animation. Scientific awards : Fellow of the Higher Education Academy (2019-) Prior external responsibilities include PhD examiner duties at Queensland University of Technology, with memberships in ACM SIGGRAPH and Society for Animation Studies.

• Database Systems
• Data Management
• XML Technologies
• +۶ مورد دیگر

Serge Abiteboul is a prominent researcher affiliated with INRIA (France) specializing in database systems, data management, and distributed computing. His work spans foundational research in XML technologies, active XML systems, probabilistic databases, and ethical data science. He has contributed to influential projects like the Active XML framework and pioneered research on distributed data management systems. Holds the SIGMOD Edgar F. Codd Innovations Award (1998) Co-authored over 300 publications across journals like ACM TODS , VLDB Journal , and conferences such as SIGMOD, PODS, and ICDE Key research areas include: XML query languages and architectures Probabilistic and uncertain data management Workflow systems and collaborative computing Ethical considerations in data systems Notable contributions include the WebdamLog system for distributed data management and foundational work on Active XML . His recent focus on responsible data science addresses transparency, fairness, and regulatory compliance challenges.

Michael Chris Deckerمشاهده پروفایل

استاد

• Emergency Medicine
• Quality Improvement
• Patient Satisfaction
• +۳ مورد دیگر

Michael Chris Decker, MD is a Professor in the Department of Emergency Medicine at the Medical College of Wisconsin, where his work centers on enhancing clinical operations through research in quality improvement, patient satisfaction, and healthcare administration. His research explores practical applications in emergency medicine settings, including kaizen methodology for departmental engagement, the relationship between clinical efficiency and teaching effectiveness, and interdisciplinary team dynamics. These investigations aim to optimize emergency department workflows and resource allocation in academic medical environments. Publications spanning 2002–2014 reveal consistent focus on operational challenges, with key contributions in quality assurance, cost modeling, and team-based care. The body of work demonstrates methodological rigor in addressing real-world emergency medicine administration problems. No scientific awards or recognitions are documented in the available information. Details regarding student advising, research grants, or laboratory affiliations are not provided in the source material.

Timothy Ngمشاهده پروفایل

مدرس

• Formal Languages
• Automata Theory
• High-Performance Computing
• +۴ مورد دیگر

Timothy Ng is a Lecturer in the Department of Computer Science at the University of Chicago. He teaches courses in the introductory and theory sequences for the Computer Science major in the College, as well as the theory core for the Masters Program in Computer Science. His research focuses on formal languages, automata theory, and high-performance computing. He has a strong background in parallel scripting frameworks, distributed-memory systems, and compiler optimization techniques for extreme-scale applications. Ng holds a PhD from Queen’s University, where he was advised by Kai Salomaa and David Rappaport. He completed a postdoctoral fellowship at the Cheriton School of Computer Science, University of Waterloo, working with Lila Kari. His work emphasizes practical programming models for high-performance computing, including implicit parallelism and dataflow coordination in scientific computing environments. His research articles span topics like implicit parallel scripting, distributed-memory computing, and big data staging for scientific applications. His contributions include frameworks like Swift/T and Photon, which address scalability and efficiency in parallel environments.

Michael Bussmannمشاهده پروفایل

پژوهشگر ارشد

• Laser Plasma Acceleration
• Plasma Physics
• Computational Physics
• +۳ مورد دیگر

Dr. Michael Bussmann is the Founding Manager of the Center for Advanced Systems Understanding (CASUS) at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR). He holds a Research Fellow position and has been a Group Leader at HZDR since 2016, focusing on computational radiation physics and laser-plasma interactions. His academic journey includes a PhD in Physics from Ludwig-Maximilians University Munich, with research encompassing laser-cooling of ion beams, plasma dynamics, and high-performance computing. Bussmann's work bridges experimental and computational physics, particularly in advancing particle acceleration technologies and plasma-based applications. Research Interests: His primary focus lies in laser plasma acceleration, computational physics, radiation physics, and the development of exascale simulation tools. Notably, he contributes to projects like PIConGPU and explores applications of AI in scientific workflows. His interdisciplinary approach integrates plasma physics with medical research, such as federated learning for oncology. Publications: Recent work spans topics from exascale plasma simulations to AI-driven medical research, reflecting his dual expertise in computational science and applied physics. Key contributions include optimizing laser-ion acceleration using machine learning and advancing federated learning frameworks in cancer studies. Awards: While no specific awards are listed, his sustained leadership in high-impact research and contributions to HZDR’s initiatives highlight his recognized expertise. Grants & Collaborations: Bussmann leads the CASUS initiative, fostering collaboration between HZDR and international partners. His projects often involve EU frameworks and industrial partnerships, emphasizing translational research in energy and healthcare. Labs/Teams: Directs the Computational Radiation Physics group at HZDR and oversees CASUS, a hub for data-driven systems research. His teams develop cutting-edge simulation tools and explore interdisciplinary applications of plasma physics.

• High-Performance Computing (HPC)
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Murali Emani is a researcher affiliated with Argonne National Laboratory, IL, USA. His work focuses on High-Performance Computing (HPC), machine learning, and artificial intelligence acceleration. Emani holds a PhD in Computer Science from the University of Edinburgh (2015). He specializes in optimizing large-scale systems, including performance evaluation of AI accelerators, transformer models, and neural architecture search. His research bridges HPC infrastructure with AI applications, addressing challenges in resource allocation, inference efficiency, and cross-architecture benchmarking. Key contributions include frameworks for GPU memory optimization (XUnified) and holistic performance evaluation of large language models across diverse hardware (e.g., BaKlaVa, Centimani). He collaborates extensively with institutions like the University of Chicago, NVIDIA, and MLCommons on initiatives such as DeepSpeed4Science and GenSLMs for genome-scale language models. His work frequently appears in top venues like IPDPS, SC, and Euro-Par. Emani’s research emphasizes practical system-level innovations, with applications spanning bioinformatics (SARS-CoV-2 evolutionary analysis), protein design, and exascale computing. He advocates for FAIR principles in HPC data management and contributes to open benchmarks like MLPerf HPC.