جست‌وجوی استاد و پژوهشگر

• Matrix Metalloproteases
• Biophysics
• Enzymology
• +۴ مورد دیگر

Susanta Sarkar is a Research Professor at Arizona State University's School of Molecular Sciences, affiliated with the Tempe campus. His email is Susanta.Sarkar@asu.edu. He holds a NIH R01 GM145210 grant as the sole PI ($1.1 million), focusing on MMP1's role in collagen degradation. His research integrates biophysics, enzyme dynamics, and drug development to target matrix metalloproteases (MMPs) in diseases like cancer and neurodegeneration. He employs single-molecule techniques to study enzyme-substrate interactions, aiming to develop precision therapies with minimal side effects. Education : Ph.D. in Physics, University of Oregon (2006) M.S. in Physical Sciences, Indian Institute of Science (2000) Postdoctoral Associate, Cornell University (2008), NIH Research Fellow (2013) Research Interests : MMPs' role in human health, single-molecule biophysics, allosteric modulation, and drug screening for Parkinson’s/Alzheimer’s. His work bridges fundamental biology and translational medicine, funded by NIH. Publications : Recent work includes substrate-specific MMP dynamics, alpha-synuclein interactions, and biofilm inhibition. His 2020 Biophysical Journal study was cover-selected and F1000-recommended. Over 15 publications since 2016 address enzyme activity, thermodynamics, and imaging. Grants & Awards : NIH R01 GM145210 (2022-2026), $2.25 million in total funding. Recognized for innovative methodologies in single-molecule studies. Advising & Training : Supervised 54 trainees, including 3 PhDs securing >$1.5M in grants post-graduation. Emphasizes financial literacy alongside science, with students averaging $30K+ retirement savings. Service : Served on 12 NSF/NIH panels, reviewer for 20+ journals including Nature Communications and Biophysical Journal. Labs/Teams : Integrates personal finance education in group meetings to boost focus and career readiness. Lab focuses on MMPs, antimicrobial biopolymers, and fluorescent nanodiamond imaging.

Vincent Archambaultمشاهده پروفایل

استاد

• Cell Biology
• Molecular Biology
• Cancer Research
• +۵ مورد دیگر

Professor Vincent Archambault holds a full professorship at the University of Montreal's Faculty of Medicine, Department of Biochemistry and Molecular Medicine, and leads the Cell Cycle Regulation Research Unit at the Institute for Research in Immunology and Cancer (IRIC). His work focuses on molecular mechanisms regulating the cell division cycle, particularly in Drosophila models, with implications for cancer research. Education: B.Sc. in Biochemistry, Université de Montréal (1999) Ph.D. in Cell Cycle Studies, Rockefeller University (2004) Postdoctoral training at University of Cambridge (2004–2009) Research Interests: Cell cycle control, mitotic regulation, cancer biology, protein kinases (e.g., Polo, Greatwall), phosphatase networks (PP2A), and Drosophila model systems. His research identifies therapeutic targets for cancer by studying disruptions in cell cycle pathways. Key contributions include co-discovering Greatwall kinase and its role in mitotic regulation. Over 50 peer-reviewed articles highlight his work on nuclear reassembly, cytokinesis, and phosphatase-kinase interactions. Awards: Maud Menten New Principal Investigator Award (2009) GE Healthcare New Scientist Award (2015) Human Frontier Science Program Fellowship (2005–2009) Grants: Over 15 projects funded by CIHR, CRSNG, and others, totaling millions in research support. Labs/Teams: Leads the IRIC Cell Cycle Regulation Unit, collaborating with teams like Sylvain Meloche and Jean-Claude Labbé.

Montserrat Rosمشاهده پروفایل

دانشیار

• Embedded Systems
• Sensor Networks Data Fusion
• Cyber-Physical Systems
• +۶ مورد دیگر

Montserrat Ros is an Associate Professor and Associate Dean (Education) at the School of Electrical, Computer and Telecommunications Engineering within the Faculty of Engineering and Information Sciences at the University of Wollongong, Australia. She has been with the university since 2006, initially joining as a Lecturer in Computer Engineering and progressing to her current senior academic and leadership roles. Her educational background includes: B.E.(Hons1)/B.Sc. double degree majoring in Computer Systems Engineering and Mathematics from the University of Queensland (2000) Ph.D. degree in Computer Engineering from the University of Queensland (2007) Professor Ros's research focuses on the intersection of embedded computing systems and practical engineering applications. Her work spans several key areas including embedded systems design, sensor network data fusion, cyber-physical systems development, and innovative approaches to engineering education. She has particular expertise in sensor-based localization techniques, computer architecture optimization, and code compression methodologies for resource-constrained environments. More recently, her research has expanded into machine learning applications for constrained systems and Internet of Things implementations. Analysis of her recent publication record reveals a strong emphasis on Internet of Things networks, UAV-based systems, and applications of artificial intelligence in both engineering education and manufacturing processes. Her work demonstrates a consistent pattern of bridging theoretical computer engineering concepts with practical real-world applications across diverse domains including healthcare, environmental monitoring, and industrial automation. Her significant contributions to academia have been recognized through numerous prestigious awards: 2019: AAUT Citation for Outstanding Contribution to Student Learning 2018: IEEE TALE 2018 Meritorious Service Award 2018: Featured in UOW Leadership in Education Booklet 2017: UOW Vice Chancellor's Award for Outstanding Contribution to Teaching and Learning 2016: UOW Women of Impact for inspiring young women in STEM 2015: UOW Vice Chancellor's Interdisciplinary Research Excellence Award 2012 & 2007: UOW Vice Chancellor's Awards for Teaching Excellence 2011: UOW Vice Chancellor's Award for Community Engagement Senior Fellow of WATTLE (Wollongong Academy for Tertiary Teaching & Learning Excellence) Professor Ros has secured substantial research funding across multiple projects spanning from 2006 to the present. Her grant portfolio demonstrates a consistent focus on engineering education innovation, sensor network development, and practical applications of embedded systems. Notable projects include "The AI Tutor: Enabling 24x7 student support across engineering" (2024), "AI/IoT-powered Airborne System for Monitoring Water Level and Tidal Floods" (2023), and "Smart Eye: Airborne and AI-Driven Assessment Solution of Sugarcane" (2022). She actively supervises HDR students and has completed multiple successful candidatures. Her leadership extends beyond research and teaching, as evidenced by her role as Associate Dean (Education) for the Faculty of Engineering and Information Sciences. She is also actively involved in community engagement through volunteering with the State Emergency Service (Wollongong SES) and Athletics Wollongong Club.

• Machine Learning
• Computer Vision
• Human Behavior Analysis
• +۵ مورد دیگر

Dr. Harshala Gammulle is a Research Fellow at Queensland University of Technology (QUT), School of Electrical Engineering & Robotics. She holds a PhD in Computer Vision from QUT (2019), receiving the QUT Executive Dean's Commendation for Outstanding Doctoral Thesis. Her expertise spans machine learning, computer vision, and spatio-temporal modeling for human behavior understanding. She leads interdisciplinary projects with funding from DST Group, SmartSat CRC, QLD DESI, and others. Research focuses include: human action recognition, medical anomaly detection, satellite image analysis, and AI for environmental monitoring. Key projects involve quantum-classical hybrid ML for biomedical signal analysis, disaster forecasting via hyperspectral data, and autonomous combat vision systems. She has supervised PhD/MPhil candidates in ML and quantum hybrid ML. Education: PhD (Computer Vision, QUT 2019), BSc (University of Peradeniya, Sri Lanka). Awards: WiT Emerging Achiever Technology Award finalist (2021), University Award for Academic Excellence (2015). Teaching includes units like Digital Signals and Image Processing (EGH444), and Computing & Data for Engineers (EGB103). Current grants involve QLD DESI, SmartSat CRC, and Rheinmetall Defence Australia collaborations. Active in labs like SAIVT and QUT's Early Career Research schemes.

Dave Clarkeمشاهده پروفایل

استاد مدعو

• Quantitative Exercise Biology
• Exercise Physiology
• Sports Analytics
• +۳ مورد دیگر

Dr. Dave Clarke is an Adjunct Professor in the Department of Biomedical Physiology and Kinesiology at Simon Fraser University, leading the Clarke Laboratory for Quantitative Exercise Biology . His research focuses on Exercise-responsive cell signaling , Sports analytics using wearable sensors , Evidence-based exercise programming , and Clinical exercise physiology . The lab integrates mathematical modeling, clinical insights, and biomechanical approaches to address questions in athletic performance, metabolic disorders, and wearable technology applications. Dr. Clarke collaborates with institutions such as TRIUMF and the BC Cancer Research Centre. Publications highlight his work in critical power modeling , AMP-activated protein kinase dynamics , and mitochondrial disease treatments . His lab emphasizes interdisciplinary training, offering mentorship in experimental design, data analysis, and translational research. The Clarke Lab is affiliated with SFU’s Faculty of Health Sciences and maintains active outreach programs for public health education. Notable projects include developing hydraulic models for recovery kinetics prediction and validating chloride test strips for sodium excretion analysis. The lab’s work has been featured in journals like Frontiers in Sports and Active Living and Orphanet Journal of Rare Diseases . For real-time updates, follow the lab on Facebook .

Søren Rud Kristensenمشاهده پروفایل

استاد

• Health Economics
• Healthcare Quality Improvement
• Healthcare Incentive Design
• +۳ مورد دیگر

Søren Rud Kristensen is a Professor at the Department of Public Health, University of Southern Denmark and holds an Honorary Senior Lecturer position at Imperial College London. His research focuses on healthcare organization and performance, particularly incentive design for quality improvement, with expertise in microeconometric analysis of large administrative datasets. He has held roles including Senior Lecturer (2017-2021) at Imperial College London. Key research areas include payment for performance systems, integrated care models, and clinical guideline implementation. He has published extensively on healthcare quality, patient safety, and health policy with 71+ peer-reviewed articles. His work addresses challenges like hospital competition effects, spillover mechanisms of financial incentives, and the impact of adverse events on patient outcomes. He has received multiple research grants including support for Manchester research stays and funding from Sygekassernes Helsefond. Teaching responsibilities include modules on integrated health care, quality management, and data-driven quality development. His current projects focus on regulating knowledge use in healthcare (PINCH project) and evaluating resource constraints in primary care. Labs/teams involvement includes collaborations through the Danish Centre for Health Economics (DaCHE) and international networks analyzing health systems in England, Brazil, Mozambique, and Zimbabwe. His work bridges economic theory with practical healthcare system improvements.

Briony Swire-Thompsonمشاهده پروفایل

استادیار

• Cognitive Psychology
• Misinformation Studies
• Social Psychology
• +۳ مورد دیگر

Briony Swire-Thompson is an Assistant Professor of Psychology at Northeastern University, affiliated with the College of Social Science and Humanities. She leads the Psychology of Misinformation Lab, which explores why people believe misinformation and how corrections can effectively promote belief change. Her expertise spans cognitive psychology, with a focus on misinformation dynamics across health, political, and social domains. Dr. Swire-Thompson holds a PhD from the University of Western Australia and was a Fulbright Scholar at MIT. She currently holds an NIH Pathway to Independence Award from the National Cancer Institute for her research on cancer misinformation. Education: PhD in Cognitive Science from University of Western Australia; Postdoctoral work at MIT as a Fulbright Scholar. Research interests include misinformation correction strategies, partisan bias in information processing, and the cognitive mechanisms underlying belief persistence. Her work has been published in journals like Science , Cognition , and Journal of Experimental Psychology . Awards include the NIH Pathway to Independence Award (2020) and Fulbright Scholarship (2016). She collaborates with Northeastern's Network Science Institute and Political Science Department, bridging cognitive science with societal impact. Her grants focus on combating health misinformation through evidence-based interventions.

Mingyang Luمشاهده پروفایل

استادیار

• Computational Systems Biology
• Gene Regulatory Networks
• Single Cell Genomics
• +۵ مورد دیگر

Mingyang Lu is an Assistant Professor in the Department of Bioengineering at Northeastern University. Previously, he led an independent research lab at The Jackson Laboratory since 2016. He holds a PhD in Biochemistry and Molecular Biology from Baylor College of Medicine (2010) and a BS in Physics from Fudan University (2003). His research focuses on computational systems biology, integrating mathematical modeling and bioinformatics to study gene regulatory networks, single-cell genomics, and epithelial-mesenchymal transitions. Key projects include developing tools like Gene Circuit Explorer (GeneEx) and investigating microRNA roles in stochastic networks. He has received the Maximizing Investigators’ Research Award (MIRA) from the National Institute of General Medical Sciences. Education : PhD in Biochemistry and Molecular Biology (Baylor College of Medicine, 2010); BS in Physics (Fudan University, 2003) Research Labs : Lu Lab (Northeastern), Center for Theoretical Biological Physics Dr. Lu has advised students including Kaitlyn Ramesh (Goldwater Scholar), Maya De Los Santos, and others. His work bridges computational methods with biological systems, emphasizing stochasticity and heterogeneity in gene expression. Recent grants include NSF support for genome-editing studies on microRNA roles and collaborative projects with the University of Maine.

Alex Keeneمشاهده پروفایل

استاد

• Neuroscience
• Sleep Disorders
• Metabolism
• +۳ مورد دیگر

Alex Keene is a Professor & Department Head at Texas A&M University, leading the Keene Lab focused on neural mechanisms underlying sleep, metabolism, and evolutionary adaptations. His research uses Mexican cavefish as a model to study sleep-metabolism interactions and evolutionary changes in nutrient-poor environments. Key contributions include genetic screens, brain atlases, and functional imaging of cavefish neural circuits. Education: B.Sc., University of Massachusetts-Amherst, 2002 Ph.D., Biomedical Sciences, University of Massachusetts Medical School, 2006 Research Interests: Dr. Keene explores how sleep and metabolism are genetically and neurologically integrated, particularly in extreme environments. His lab investigates cavefish adaptations, such as sleep intensity changes and hypothalamic reorganization, to uncover conserved mechanisms in sleep regulation and metabolic survival strategies. Publications: Recent work highlights sleep’s role in glial function, circadian rhythm disruption in cancer, and cavefish sensory evolution. His studies bridge genetics, neurobiology, and ecology to address fundamental questions in sleep physiology and evolutionary biology. Labs/Teams: The Keene Lab is located in Butler Hall (Office Rm 100, Lab Rm 201) and collaborates on projects involving comparative genomics, behavioral profiling, and neural imaging in model organisms.

Steven Korevaarمشاهده پروفایل

مدرس

• Deep learning
• Computer vision
• Medical Imaging
• +۱ مورد دیگر

Steven Korevaar is a Lecturer and holder of an Early Career Development Fellowship (ECDF) at the School of Computing Technologies, RMIT University. His research focuses on deep learning and computer vision, particularly in domain generalization, medical imaging analysis, and algorithmic evaluation. He is actively involved in supervising research projects such as 'Learning optimal control of games and machines in real-time' and 'Learning Robust and Generalisable Models for Computer Vision Using Animation'. His publications emphasize medical imaging applications, exploring domain adaptation techniques to enhance model generalization. He has contributed to interdisciplinary work in health informatics and computer-aided diagnosis, addressing challenges in medical image classification and domain invariance. Steven is open to supervising Master's and PhD students in relevant fields. His research aligns with RMIT's commitment to innovation in computing technologies, with a focus on real-world applications in healthcare and machine learning.

Michael B. Yaffeمشاهده پروفایل

استاد

• Cancer Biology
• Signal Transduction
• Precision Medicine
• +۷ مورد دیگر

Michael B. Yaffe is the David H. Koch Professor of Science and Professor of Biology and Biological Engineering at MIT, where he has been a faculty member since 2000. He serves as Director of the MIT Center for Precision Cancer Medicine and the KI Clinical Investigator Program. Clinically, he is an attending surgeon and intensivist at Beth Israel Deaconess Medical Center, specializing in injury and surgical oncology. Education: MD-PhD from Case Western Reserve University Training: Residency at University Hospitals of Cleveland; Fellowship at Harvard-Longwood Critical Care Program Dr. Yaffe's research focuses on protein kinase signaling pathways activated by DNA damage, cell injury, and inflammation. His work explores how these pathways regulate cancer behavior and treatment response through integrated experimental and computational approaches, with translational applications in systems pharmacology and precision medicine. His 15 most recent publications span DNA damage responses, mitotic stress, immunogenic cell injury, kinase signaling atlases, and reproducibility in science. Key trends include targeting pathway crosstalk for therapeutic synergy, leveraging R-loops in DNA repair-deficient tumors, and understanding immune activation post-chemotherapy. Scientific Awards: HHMI Physician-Scientist Fellowship Burroughs-Wellcome Fund Award MacVicar Faculty Fellow (2021) Association of American Physicians (2021) American Surgical Association membership Dr. Yaffe advises trainees in scientific career development and leads the Yaffe Lab at MIT, which pioneers novel technologies like peptide libraries and multiplex kinase reporters. His work bridges benchtop experiments with clinical applications in chemotherapy, radiation, and surgery, while also addressing inflammation-cancer connections.

• Applied Artificial Intelligence
• Machine Learning
• Health Informatics
• +۷ مورد دیگر

Dr. Abdur Forkan is a Senior Research Fellow in AI and Machine Learning at Swinburne University of Technology's School of Science, Computing and Emerging Technologies. He also holds honorary research positions at Peter MacCallum Cancer Centre and Northern Health. His work focuses on applied AI and machine learning across digital health, Industry 4.0, FinTech, AgriTech, and supply chain optimization. He has led over a dozen industry projects, delivering impactful solutions such as AI-driven healthcare systems, manufacturing efficiency tools, and agricultural disease prevention models. Education: PhD in Computer Science, RMIT University (2016) B.Sc. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2007) Research Interests: Data Science and Health Informatics Pervasive Computing and IoT Applications AI in Healthcare and Industry Awards: 2023 iAwards National Winner (Government/Public Sector Solution) 2023 iAwards VIC Winner (Technology Platform Solution) RMIT CSIT Publication Award (2015) Grants & Collaborations: Lead on projects with industry partners like VidVersity, Sphere Holdings, and Northern Health Focus on digital twin technologies, AI in clinical decision support, and healthcare platform development Teaching & Supervision: Sessional academic at RMIT and Swinburne Supervising HDR students on topics like AI in healthcare, greenspace health impacts, and chronic disease management

Sonit Singhمشاهده پروفایل

مدرس

• Artificial Intelligence
• Computer Vision
• Natural Language Processing
• +۷ مورد دیگر

Dr. Sonit Singh is a Lecturer at the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. Prior to this role, he served as a Postdoctoral Research Fellow at the same institution. He holds a PhD from Macquarie University, completed in collaboration with Macquarie. His research focuses on artificial intelligence, computer vision, natural language processing, and their applications in healthcare, particularly in medical imaging and diagnostic systems. Dr. Singh's academic background includes a strong emphasis on biomedical imaging, intelligent robotics, and computing education. His work bridges machine learning advancements with real-world clinical challenges, such as tumor segmentation, radiology report generation, and disease detection through imaging modalities like CT scans and ultrasound. His recent publications highlight innovations in 3D medical image localization, robust tumor segmentation networks, and clinical context-aware radiology report systems. These contributions underscore his expertise in integrating deep learning techniques with healthcare workflows. Dr. Singh collaborates with multidisciplinary teams, including medical professionals, to develop solutions for challenges like placenta segmentation and dietary intake monitoring using AI. While no specific awards or grants are explicitly listed, his extensive publication record reflects sustained academic engagement in high-impact areas. His research often addresses practical clinical needs, such as improving diagnostic accuracy and patient care through advanced computational methods.

• Biomechanics
• Musculoskeletal Disorders
• Biomaterials Engineering
• +۳ مورد دیگر

Prof. Stephen J. Ferguson is a Full Professor at ETH Zurich's Department of Health Sciences and Technology and Head of the Institute for Biomechanics. His research focuses on musculoskeletal biomechanics, biomaterials, and implant technologies addressing aging-related health challenges. He holds a Venia Docendi in Musculoskeletal Biomechanics and has led the Biomechanics Division at the University of Bern. Key honors include the ETH Golden Owl (2021) and ESB Clinical Biomechanics Award (2022). Education: Bachelor of Mechanical Engineering, University of Toronto (1991) Master's, Queen's University (1994) PhD, Queen's University (2000) Postdoc, University of Bern (2000-2002) Research Interests: Biomaterials for implants, musculoskeletal disorder mechanisms, computational biomechanics, and translational medical devices. Awards: ESB Clinical Biomechanics Award (2022) ETH Golden Owl (2021) European Spine Journal GRAMMER prize (2009) CTI Medtech Award (2005) Professional Activities: Five patent applications, course leadership in Biomedical Engineering and Spine Research, and director roles at ARTORG Spine Research Center. Labs/Teams: Leads the Institute for Biomechanics at ETH Zurich, focusing on cutting-edge biomechanical research and clinical translation.

• Causal Inference
• Clinical Trials
• Statistical Methods
• +۷ مورد دیگر

Dr. Alisa Stephens Shields serves as an Associate Professor in the Biostatistics Division of the Department of Biostatistics, Epidemiology and Informatics at the University of Pennsylvania Perelman School of Medicine. She also holds an adjunct faculty position at Harvard University where she earned her PhD in Biostatistics. Her leadership extends to directing the Biostatistics and Data Science Core at the Penn Center for AIDS Research (CFAR) and chairing the Student Recruitment Committee for Penn Biostatistics. Her educational background includes: BS in Mathematics from University of Maryland (2006) AM in Biostatistics from Harvard University (2009) PhD in Biostatistics from Harvard University (2012) Dr. Stephens Shields' research focuses on enhancing clinical trial design and analysis through innovative applications of causal inference methods. She has made significant contributions to patient-reported outcome development for population-appropriate trial endpoints, particularly in areas of pediatrics, chronic pain, urology, and infectious disease. Her work bridges statistical methodology with real-world health challenges, addressing issues of diversity in clinical trials and improving trial generalizability for complex, heterogeneous conditions. Analysis of Dr. Stephens Shields' publication record reveals a consistent trajectory of methodological innovation applied to pressing clinical problems. Her work spans from foundational statistical methods (particularly in causal inference) to direct applications in clinical research domains such as chronic pelvic pain, infectious disease, and cardiovascular health. A notable trend is her increasing focus on behavioral economic approaches to address diversity gaps in clinical trial participation, reflecting her commitment to health equity. Her scientific recognitions include: 2024 Myrto Lefkopoulou Distinguished Lectureship 2021 Committee of Presidents of Statistical Societies Leadership Award 2018 Distinguished Faculty Award, University of Pennsylvania Fellow of the American Statistical Association Dr. Stephens Shields demonstrates exceptional leadership in mentoring and educational initiatives. She co-developed a causal inference course for Penn's Master of Science in Clinical Epidemiology program and directs the Design of Interventional Studies course for doctoral students. As chair of the Student Recruitment Committee, she actively fosters diversity in quantitative health careers and regularly participates in diversity-focused workshops including the ENAR Fostering Diversity Workshop and STATFest. Her mentorship extends beyond Penn through her adjunct role at Harvard University. Dr. Stephens Shields leads or contributes to several significant research teams and initiatives including the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network, the Randomized Evaluation of Trial Acceptability by Incentive (RETAIN) trial, the Behavioral Economics to Transform Trial Enrollment Representativeness (BETTER) Center, and the Handoffs and Transitions in Critical Care research program. Her role as director of the Biostatistics and Data Science Core at CFAR demonstrates her leadership in HIV research methodology and statistical mentorship.