جست‌وجوی استاد و پژوهشگر

John Galeottiمشاهده پروفایل

پژوهشگر

• Medical Image Analysis
• Machine Learning Applications in Biomedical Imaging
• Medical Robotics
• +۳ مورد دیگر

John Galeotti is a Senior Systems Scientist and Adjunct Assistant Professor at Carnegie Mellon University (CMU), affiliated with the Robotics Institute (RI) and Biomedical Engineering departments. He directs the Biomedical Image Guidance Laboratory and has an adjunct appointment at the University of Pittsburgh's Bioengineering department. His research focuses on integrating medical robotics, computer vision, and advanced image analysis to improve clinical outcomes. With a Ph.D. in Robotics and B.S./M.S. in Computer Engineering, Galeotti's work emphasizes real-time computer-controlled optics, medical image segmentation, and AI-driven diagnostics. He has led projects in autonomous ultrasound scanning, needle insertion robotics, and synthetic data generation for medical AI. Research Keywords: Medical Robotics, Machine Learning, Ultrasound Segmentation, Computer Vision, Augmented Reality, Diagnostic Imaging Galeotti is a key contributor to the open-source Insight Segmentation and Registration Toolkit (ITK) and has received external teaching funding and awards for his internationally recognized course on medical image analysis algorithms. His lab's publications highlight advancements in AI applications for lung ultrasound, vessel segmentation, and optical coherence tomography.

Dominik Moritzمشاهده پروفایل

استادیار

• Human-Centered Machine Learning
• Data Science
• Interactive Systems
• +۶ مورد دیگر

Dominik Moritz is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University and Machine Learning researcher at Apple. He leads the Data Interaction Group and develops systems for interactive data visualization. Ph.D. in Computer Science from University of Washington (2019) B.S. in Computer Science from Hasso Plattner Institute (2013) His research focuses on: Human-Centered Machine Learning Data Visualization Toolkits Interactive Systems Design Accessibility in Visual Analytics Scalable Web-Based Visualization Recent publications address visualization design knowledge formalization (Draco), cross-filtering frameworks (Mosaic), and accessibility evaluation (Chartability). He has received Best Paper Honors at VIS and EuroVis conferences. Professional Collaborations: Co-founder of Vega-Lite visualization grammar Collaborations with Jeff Heer, Bill Howe, Jock MacKinlay Projects with Microsoft Research and Google Research

Olesya Kisselevمشاهده پروفایل

استادیار

• Corpus Linguistics
• Discourse Analysis
• Second Language Acquisition
• +۴ مورد دیگر

Dr. Olesya Kisselev is an Assistant Professor of Russian in the Department of Languages, Literatures, and Cultures at the University of South Carolina. Previously, she held positions at the University of Texas at San Antonio and the University of Pennsylvania. She serves as Co-Director of the Center for Advanced Language Proficiency Education and Research (CALPER) and Director of the STARTALK Institute for Russian Teachers. Her research focuses on corpus linguistics, heritage language development, and evidence-based pedagogy. Education: Ph.D. in Applied Linguistics, Pennsylvania State University (2018) M.A. in TESOL, Portland State University (2009) M.A. and B.A. in Linguistics, Buryat State University (2003) Research Interests: Corpus linguistics, instructed second language acquisition, heritage language pedagogy, syntactic complexity, bilingualism, and Russian as a heritage language. Publications: Over 30 peer-reviewed articles and book chapters, including edited volumes on heritage language research and pedagogy. Notable works include Advances in Research and Pedagogy of Russian as a Heritage Language (Routledge, 2024) and Rodnaya Rech' (Georgetown University Press, 2020), awarded the AATSEEL Book Prize. Awards: Includes the University Excellence Award for Research Excellence (2023), President’s Distinguished Achievement Award (2023), and the NFMLTA/NCOLCTL Dissertation Grant (2018). Advising & Grants: Supervised doctoral and master’s students in applied linguistics and second language acquisition. Secured grants totaling over $750,000, including the CALPER Language Resource Center (Title VI) and STARTALK programs. Mentorship includes peer-led initiatives and international collaborations. Labs/Teams: Leads the Middlebury College Davis School’s Russian Heritage Language initiatives and collaborates with the Heritage Language Repository project. Active in CALPER’s pedagogical innovations and corpus-driven research.

Haoyi Wangمشاهده پروفایل

مدرس

• Machine Learning
• Computer Vision
• Image Processing
• +۳ مورد دیگر

Dr. Haoyi Wang is a Lecturer in Computer Science at the University of Plymouth, affiliated with the School of Engineering, Computing and Mathematics. He holds a PhD from the University of Warwick (2021) and has three years of industry experience as a machine learning engineer. His research spans machine learning applications in computer vision (e.g., face recognition, age estimation) and geology-driven image processing. He teaches courses such as COMP2001 (Information Management), COMP3007 (HCI/Usability), and COMP5013 (Applied AI). Research interests include developing algorithms for age-invariant facial recognition, automated geological data interpretation, and fusion networks for biometric analysis. His work bridges theoretical machine learning with real-world problems, as seen in cross-age contrastive learning and core data analysis techniques. No scientific awards are explicitly listed. His teaching and research focus on practical applications of AI, with publications in both computer vision and geoscience domains. Advising details or grant information are not provided in the text.

Stewart Weissمشاهده پروفایل

دانشیار

• Software Quality Assurance
• Computer Science Education
• Computational Biophysics
• +۳ مورد دیگر

Stewart Weiss is an Associate Professor in the Department of Computer Science at Hunter College, part of the City University of New York (CUNY). His research focuses on Software Quality Assurance, computational biophysics, and integrating open-source software into computer science education. He holds a PhD in Computer Science from New York University's Courant Institute (1987), an M.S. from the same institute (1984), and a B.A. in Mathematics from Hunter College (1982), alongside a B.Arch. from The Cooper Union (1973). Dr. Weiss teaches courses such as Software Design and Analysis, Computer Theory, and UNIX Tools. His work spans grants from NSF and PSC-CUNY, including research in protein structure prediction via the kernel energy method and educational initiatives like 'Computing for Social Good.' He has advised on projects like the 'Gateway for Open Source Software Development' in curricula and contributed to tools for adaptive contrast sensitivity testing. His teaching philosophy emphasizes rigorous academic standards and hands-on learning. He has developed extensive resources, including tutorials on UNIX, parallel programming, and C/C++ programming. His research has explored topics ranging from mutation testing frameworks to quantum chemistry applications in molecular modeling.

Barbara Villariniمشاهده پروفایل

استاد

• Medical Imaging
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Barbara Villarini is a Reader in Computer Science at the University of Westminster, specializing in computational vision and imaging technology. She leads research in medical imaging computing, AI-driven healthcare solutions, and autonomous systems. Previously, she contributed to pioneering image-guidance systems at University College London's Centre for Medical Image Computing (CMIC), earning team awards for advancements in cancer care and research. In 2020, she was awarded the Royal Academy of Engineering Leverhulme Trust Research Fellowship. She is affiliated with the Computational Vision and Imaging Technology group. Her education includes a PhD in Information Engineering from the University of Perugia (Italy). Her research integrates AI, computer vision, and 3D reconstruction to address challenges in healthcare (e.g., brain tumor segmentation, skin cancer detection) and autonomous vehicle safety. Notable projects include the SmartTarget biopsy trial, validating MRI/TRUS-guided prostate interventions. Dr. Villarini’s work emphasizes cross-disciplinary collaboration, with grants focused on medical imaging innovation and AI applications. Her lab explores AI-driven IoT systems for medical diagnostics and AR/VR solutions for personalized healthcare. Key Awards: Royal Academy of Engineering Leverhulme Trust Research Fellowship (2020) Research Focus: AI in medical imaging, autonomous systems, and healthcare technology Lab Affiliation: Computational Vision and Imaging Technology Group

Jieun Leeمشاهده پروفایل

استادیار مهمان

• Second Language Acquisition
• Psycholinguistics
• Speech Perception and Production

Jieun Lee is a Visiting Assistant Professor in the Department of Linguistics at the University of Kansas. She earned her Ph.D. in Linguistics from the University of Wisconsin-Milwaukee in 2022 and a B.E. in English Language and Literature from Kangwon National University in 2015. Her research focuses on second language acquisition, psycholinguistics, and speech perception and production. Dr. Lee teaches courses including Language and Mind (LING 110/111), Capstone: Research Language Science (LING 420), Second Language Acquisition (LING 715), Psycholinguistics (LING 435/735), and Research Methods in Linguistics (LING 720). Her research examines acoustic cues in speech perception, phonological learning, and cross-linguistic perception. Recent publications investigate native and non-native speech perception patterns and their implications for language acquisition. Awards include: Distinguished Dissertation Fellowship (UWM, 2020) Chancellor’s Graduate Student Award (UWM, 2019)

Ramanathan Subramanianمشاهده پروفایل

دانشیار

• Human-centered computing
• AI systems
• Non-verbal behavioral analysis
• +۷ مورد دیگر

Ramanathan Subramanian is an Associate Professor in the Department of Information Technology & Systems, AI and Robotics at the University of Canberra. His past affiliations include IIT Ropar and UIUC, Singapore. He has received notable awards including the IEEE Transactions on Affective Computing Best Paper Award (2019) and Multimedia Rising Star nomination (2015). His research focuses on Human-centered computing, AI systems leveraging non-verbal behavioral cues, and applications in health analytics and virtual reality. He actively supervises PhD and Master’s students in areas like Human-Computer Interaction, Data Science, and VR for healthy aging. Research interests: Human perception modeling, intelligent interfaces, health-focused VR, and applied machine learning Key projects: Driver sentiment prediction, distraction awareness campaigns, and robotics for waste management His work contributes to UN SDGs related to health and well-being, particularly through technologies improving aging care and mental health monitoring. Recent projects include developing explainable AI for emotion inference and multimodal data fusion systems. Awards: IEEE Best Paper Award, Multimedia Rising Star Grants: Lead or Co-Investigator on three major grants totaling over AUD 4M Labs/Teams: Collaborates extensively with the University's robotics and health tech groups, contributing to interdisciplinary projects in AI ethics and medical signal processing.

Ellen Broselowمشاهده پروفایل

استاد

• Phonology
• Second Language Acquisition
• Phonetics
• +۶ مورد دیگر

Ellen Broselow is the Toll Professor in the Department of Linguistics at Stony Brook University. She holds a Ph.D. in Linguistics from the University of Massachusetts Amherst (1976). Her research focuses on phonology, second language acquisition, and the interfaces of phonology with phonetics, morphology, and syntax, with special attention to Arabic, Salish, Bantu, and Indonesian languages of Sulawesi. Her work examines second language phonology, including loanword adaptation and learner errors, as well as the phonetics-phonology interface. Broselow has served as editor for journals like Natural Language and Linguistic Theory and is currently on editorial boards of Bilingualism: Language and Cognition , Linguistic Inquiry , and others. She has received prestigious awards, including the Godfrey Excellence in Teaching Award and Fellowship in the Linguistic Society of America. Recent research explores factors influencing second language production errors, vowel insertion in foreign languages, and prosodic processing. Her studies highlight the role of perceptual biases in second language acquisition and the impact of vocal fry in intonation patterns among native and non-native speakers.

Hong Qinمشاهده پروفایل

استاد

• Computer Graphics
• Geometric Modeling
• Physics-Based Modeling
• +۵ مورد دیگر

Hong Qin is a Full Professor (with tenure) in the Department of Computer Science at Stony Brook University, where he is also a member of the Center for Visual Computing. He holds a B.S. and M.S. from Peking University, and a Ph.D. from the University of Toronto. His research focuses on computer graphics, geometric modeling, physics-based simulation, and scientific visualization. Education: B.S. (1986) and M.S. (1989) in Computer Science from Peking University; Ph.D. (1995) in Computer Science from the University of Toronto. Research interests include geometric modeling, computer-aided design, scientific visualization, medical imaging, and robotics. He has received notable awards like the NSF CAREER Award (1997), Alfred P. Sloan Fellowship (2001-2005), and multiple NSF grants. Qin has organized major conferences such as Computer Graphics International 2005 and chairs editorial boards for IEEE TVCG and The Visual Computer.

Claire Hemingwayمشاهده پروفایل

استادیار

• Decision-making strategies
• Value perception
• Foraging behavior
• +۱ مورد دیگر

Claire Hemingway is an Assistant Professor in the Department of Ecology & Evolutionary Biology at the University of Tennessee, Knoxville. She holds a Ph.D. from the University of Texas at Austin (2020). Her research focuses on animal decision-making mechanisms, studying foraging behaviors in bats and bees, particularly how these animals evaluate rewards and signals when making choices. She investigates how ecological contexts influence decision strategies and their evolutionary implications. Dr. Hemingway’s lab explores topics such as label-based expectations in bumblebees, context-dependent preferences in fruit bats, and cognitive constraints in foraging predators. Her work bridges behavioral ecology, neuroscience, and economics, with publications in journals like Biology Letters and Animal Behaviour . Her research highlights the interplay between sensory processing, learning, and ecological pressures. Current projects include studying how floral reward complexity affects pollinator cognition and how anti-predator signals exploit auditory illusions. She is actively recruiting graduate students interested in these areas. Dr. Hemingway’s work has been supported by grants examining decision-making trade-offs in both vertebrate and invertebrate systems. Her lab is located in Dabney Hall, and she maintains an active research website at https://www.thebatsandthebees.com/ .

Salavat Aglyamovمشاهده پروفایل

استاد پژوهشی

• Elastography
• Biomechanics
• Biomedical Imaging
• +۷ مورد دیگر

Dr. Salavat Aglyamov is a Research Professor in the Department of Mechanical and Aerospace Engineering at the University of Houston. His work focuses on biomechanical imaging and elastography techniques such as optical coherence elastography (OCE), Brillouin microscopy, and ultrasound. He leads the Biomedical Optics Laboratory and teaches courses in biomedical engineering. Research interests include corneal biomechanics, tissue stiffness analysis in diseases like glaucoma and keratoconus, and developmental biology applications in embryos and zebrafish models. Key innovations involve multimodal imaging systems combining OCT with other modalities for non-invasive tissue characterization. Recent studies address age-related lens changes, drug delivery monitoring, and the biomechanics of neural tube defects in mouse embryos. Education: Ph.D., Institute of Theoretical and Experimental Biophysics, Pushchino, Russia His research applies machine learning (CNNs) to improve strain estimation in OCE and explores clinical applications like glaucoma detection and corneal crosslinking treatment efficacy. He collaborates on projects involving systemic sclerosis assessment via OCT/OCE/OCTA and has developed novel methods for safe acoustic radiation force-based measurements on ocular tissues. His lab’s work spans from fundamental material science (e.g., Brillouin frequency shifts under environmental conditions) to translational medicine (e.g., drug delivery tracking). Publications emphasize high-resolution 3D elasticity mapping of embryos, alcohol’s impact on embryonic development, and nanobomb OCE for glioblastoma studies. His work bridges engineering and medicine through advanced optical techniques for understanding tissue mechanics in health and disease.

John Flibotteمشاهده پروفایل

دانشیار

• Neonatal Neurocritical Care
• Infant Brain Injury
• Hypoxic Ischemic Encephalopathy
• +۴ مورد دیگر

Dr. John Flibotte is an Associate Professor of Clinical Pediatrics at the Perelman School of Medicine, University of Pennsylvania, and holds multiple leadership roles at Children's Hospital of Philadelphia (CHOP). As Co-Medical Director of the Neonatal Neurocritical Care Program and Associate Program Director for both the Neonatal-Perinatal Fellowship and Pediatric Residency programs, he bridges clinical care, education, and research. His expertise spans neonatal neurocritical care, infant brain injury, and medical education innovation. Dr. Flibotte graduated from Harvard College and Harvard Medical School, completing residency and fellowship training at CHOP. His research focuses on neurodevelopmental outcomes after hypoxic-ischemic encephalopathy, hydrocephalus management, and neonatal neuroimaging. He collaborates with Neurology, Neurosurgery, and Radiology teams in the Neonatal/Infant Intensive Care Unit (N/IICU) and participates in high-risk prenatal consultations through the Special Delivery Unit. His educational contributions include mentorship programs for junior faculty and trainees, earning awards such as the Istvan Seri Teaching Award. He leads quality improvement initiatives addressing developmental follow-up for preterm infants and CLABSI reduction in neonatal care. Dr. Flibotte also serves on multiple institutional committees, including the Data Safety Monitoring Board for clinical trials in neonatal conditions. His publications span 20+ years, emphasizing translational research in neonatal neurology and critical care innovations. Key areas include predictive modeling for neurodevelopmental outcomes, parental decision-making in trials, and novel imaging techniques for brain injury detection. Awards: Early Career Honor Roll (Pediatric Residents Teaching) Istvan Seri Teaching Award (Neonatology Fellows) Schmidt-Kirpalani Mentoring Award (Fellows/Junior Faculty) His clinical and research teams collaborate across CHOP's Neonatology, Fetal Diagnosis and Treatment Center, and Neurocritical Care Program, integrating translational science with bedside care to improve outcomes for neonates with complex neurological conditions.

Michael C. Luمشاهده پروفایل

استاد

• Maternal and Child Health
• Public Health
• Health Equity
• +۳ مورد دیگر

Dr. Michael C. Lu is currently the Dean of the School of Public Health at the University of California, Berkeley. Previously, he served as Director of the federal Maternal and Child Health Bureau under the Obama Administration, where he received the U.S. Department of Health and Human Services’ Hubert H. Humphrey Service to America Award in 2013. His academic career includes roles as a professor of obstetrics-gynecology and public health at UCLA, with research focused on racial-ethnic disparities in birth outcomes. As an obstetrician, he attended over 1,000 births and was repeatedly named a Best Doctor in America since 2005. He has contributed to National Academy of Medicine committees and co-authored the report Vibrant and Healthy Kids: Aligning Science, Practice, and Policy to Advance Health Equity . His education includes degrees from Stanford University, UC Berkeley, and UCSF. Research interests emphasize improving maternal and child health equity through life-course perspectives and advancing medical imaging technologies. He has pioneered innovations in MRI motion sensing, wireless implant communication, and computational imaging algorithms. His work bridges clinical practice, public health policy, and biomedical engineering. Awards include teaching recognition and federal service accolades. He collaborates on interdisciplinary teams to address global health challenges, leveraging both clinical expertise and technological advancements. Publications span maternal health equity frameworks and cutting-edge MRI methodologies, reflecting his dual focus on societal health disparities and medical technology. Current efforts at UC Berkeley aim to integrate public health strategies with emerging imaging and data science tools. Despite no listed advisees, his mentorship is evident through residency program leadership and training grants in maternal and child health.

Bruno Correiaمشاهده پروفایل

دانشیار

• Protein engineering
• Computational design
• Immunoengineering
• +۷ مورد دیگر

Bruno Correia is an Associate Professor at the Laboratory of Protein Design & Immunoengineering (LPDI) within the Institute of Bioengineering at École Polytechnique Fédérale de Lausanne (EPFL) , Switzerland. His work bridges computational protein design with experimental validation, focusing on immunoengineering applications for vaccines and cancer immunotherapy. PhD in Computational Biology (Universidade Nova de Lisboa, 2010) BSc in Chemistry (Universidade de Coimbra, 2004) Correia's research spans protein engineering , synthetic biology , and computational design , with key contributions in: Developing MaSIF for protein surface interaction analysis Designing chemically-controlled protein switches for CAR T-cell therapy Creating de novo functional proteins for vaccine development His publications highlight vaccinology , structural bioinformatics , and machine learning applications in protein science. Awards include the Protein Society Young Investigator Award (2021) and ERC Starting Grant (2016) . Scientific contributions: Protein surface fingerprinting for interaction prediction Rational immunogen design for HIV and hepatitis C Deep learning frameworks for protein structure generation