جست‌وجوی استاد و پژوهشگر

Scott Prahlمشاهده پروفایل

استاد

• Optical Engineering
• Biomedical Optics
• Optical Spectroscopy
• +۳ مورد دیگر

Scott Prahl is a tenured Professor in the Department of Electrical Engineering and Renewable Energy at Oregon Institute of Technology, where he has served since 2012. He currently directs the dual major program in optical engineering, integrating academic leadership with specialized instruction in circuits and optical systems. His educational background includes: BS in Applied Physics from California Institute of Technology (Caltech) Ph.D. in Biomedical Engineering from the University of Texas at Austin With two decades of industry experience in biomedical optics prior to academia, Dr. Prahl's research bridges engineering and medical applications. His work focuses on differential interference microscopy for high-resolution imaging, fog-penetrating optical techniques, fiber-based tissue property measurement instrumentation, and advanced optical spectroscopy. These efforts emphasize practical device development for medical diagnostics and environmental sensing, leveraging interdisciplinary approaches across physics and engineering disciplines. No scientific awards were documented in the source material. Dr. Prahl teaches core courses in circuit theory and optical engineering design. The provided text contains no details regarding graduate student mentorship, research grants, or collaborative funding initiatives. His pre-academic career involved 20 years of hands-on innovation in biomedical optics technology development, directly informing his applied research methodology and industry-aligned pedagogy at Oregon Tech.

• Critical Future Studies
• Science Fiction
• Speculative Fiction
• +۴ مورد دیگر

Michael Godhe is a Senior Lecturer and Associate Professor at Linköping University, affiliated with the Department of Culture and Society (IKOS) and the Department of Culture, Society, Design and Media (KSFM) within the Faculty of Arts and Sciences. His academic work focuses on the intersection of technology and culture, with special emphasis on robots, androids, and AI from a cultural and media historical perspective, as well as critical future studies. Godhe's research centers on representations of future images, exploring how anticipated futures are anticipated, written forward, and staged in speculative fiction (utopias, dystopias, science fiction, etc.) as well as in the public sphere. His work is characterized by four key concepts: expectations, anticipations, projections, and stagings. Together with Luke Goode from the University of Auckland, Godhe co-founded the interdisciplinary research field of Critical Future Studies (CFS), publishing the program text "Beyond Capitalist Realism – Why We Need Critical Future Studies" in Culture Unbound: Journal for Current Cultural Research. He also co-founded The Journal of Social and Cultural Possibilities with William Bridges IV and Luke Goode in 2022, focusing on humanities approaches to future studies. His publications span cultural representations of the future across science fiction, media history, and public discourse, with particular attention to how future visions manifest in utopian/dystopian narratives, space exploration, and technological development. His recent work examines Swedish science fiction, time conceptions in speculative fiction, and apocalyptic representations from biblical times to contemporary media. PhD in Theme Technology and Social Change, Linköping University (2003) Master's Degree in Intellectual and Cultural History, Uppsala University (1997) Research Networks and Leadership Godhe initiated the Swedish research network "Science fiction, fantasy and speculative fiction" with approximately 50 affiliated researchers. He is also involved with Linköping Space Studies in Humanities and Social Sciences (LSSH), which conducts interdisciplinary investigations of future visions within all aspects of space research and industry, and the LiU hub for apocalyptic and post-apocalyptic representations. His teaching in the Bachelor's program in Communication, Society, and Media Production (KSM) ranges from media history to special courses within the Futures Lab theme, where he uses methods from Critical Future Studies to engage students with future issues in light of technological development and contemporary crises.

Bob Mahmoodiمشاهده پروفایل

مدرس

• Wireless communication system
• Digital signal processing
• Control
• +۶ مورد دیگر

Dr. Bob Mahmoodi serves as a Lecturer in the Department of Electrical and Computer Engineering at the University of St. Thomas School of Engineering, where he has taught for 10 years since 2012. Concurrently, he holds an adjunct instructor position at the University of Minnesota's Electrical and Computer Engineering department for 35 years. His industry background includes over 30 years at 3M in R&D focused on wireless RFID and biometric sensors, plus three years at Honeywell developing airborne radar systems. His educational qualifications include: PhD in Electrical Engineering and Control Sciences from the University of Minnesota MS in Electrical Engineering from the University of Minnesota BS in Electrical Engineering from the University of Minnesota Dr. Mahmoodi's research spans wireless communication, digital signal processing, control systems, medical instrumentation sensors, and FPGA/IC design. His work integrates analog/digital systems with applications in biometric security and image compression. Current teaching focuses on Electronics I laboratories, Engineering Design Clinic II, and graduate-level Digital Signal Processing coursework emphasizing machine learning applications. His publication history from 1981-2013 reveals consistent innovation in image enhancement algorithms and radar signal processing, with increasing specialization in medical imaging after 1984. Key thematic developments include the transition from military radar applications to medical/biometric systems and the evolution of real-time processing techniques for commercial printing technologies. Dr. Mahmoodi holds seven U.S. patents covering image enhancement (1986, 1994), projection displays (2006), and oil quality monitoring systems (2012-2013). His professional service includes IEEE Twin Cities Chapter chairmanship (1989-1990), IS&T Conference chairmanship (1991), and ACR-NEMA standards committee membership for image compression. As an active design clinic instructor, he mentors student teams in industrial problem-solving through the Senior Design Clinic program. His industry experience directly informs classroom instruction, particularly in sensor integration and system modeling applications. Laboratory development for electronics courses leverages his 3M/Honeywell background in practical circuit design.

Matthew F. Glasserمشاهده پروفایل

استادیار

• Neuroanatomy
• Connectomics
• Medical Image Analysis
• +۵ مورد دیگر

Matthew F. Glasser, MD, PhD is an Assistant Professor of Radiology at Washington University School of Medicine in St. Louis, affiliated with the Mallinckrodt Institute of Radiology (MIR) and the Computational Imaging Research Center (CIRC). He co-directs a brain imaging laboratory with David Van Essen, PhD, and serves as co-leader of the Adult Aging Brain Connectome (AABC) project's Informatics, Data Analysis, and Statistics Core (IDASC). Education: Undergraduate: Emory University Doctorate: Washington University School of Medicine in St. Louis Medical Degree: Washington University School of Medicine in St. Louis Residency: Diagnostic Radiology, Mallinckrodt Institute of Radiology Fellowship: Neuroradiology, Mallinckrodt Institute of Radiology Dr. Glasser's research focuses on neuroanatomy, connectomics, and medical image analysis. He is best known for his work mapping 180 areas of each human cerebral cortical hemisphere using multiple MRI modalities as part of the Human Connectome Project (HCP). His work involves developing techniques for cortical myelin mapping to identify brain areas and align maps across individuals. He continues this research through the Adult Aging Brain Connectome (AABC) project, which aims to uncover factors underlying vulnerability and resilience to late-life dementia. Dr. Glasser's publication record demonstrates a consistent focus on advancing brain imaging techniques and understanding brain connectivity. His work spans from foundational methods in the Human Connectome Project to applications in aging and neurological disorders. Recent publications show an expansion into clinical applications like speech neuroprosthetics and depression treatment, indicating how his fundamental research in brain mapping is translating into therapeutic innovations. Scientific Awards: 2021–2022 Highly Cited Researcher, Clarivate 2022 Roentgen Resident/Fellow Research Award, Radiological Society of North America 2022 Alpha Omega Alpha, Washington University School of Medicine 2018-2021 Highly Cited Researcher, Clarivate 2017 Hugh M. Wilson Award in Radiology, Mallinckrodt Institute 2016 Dennis Hallahan Fellowship for Outstanding Research 2016 Olin Medical Scientist Fellowship 2009 Pittsburgh Brain Connectivity Competition Winner 2008 Distinguished Young Scholar Award Dr. Glasser has been instrumental in securing significant research funding, most notably as a key contributor to the $30 million Human Connectome Project funded by the NIH. He currently co-leads the AABC's Informatics, Data Analysis, and Statistics Core. While the text doesn't specify his current advisees, his position as Assistant Professor and research leadership suggests he mentors graduate students and postdoctoral researchers in neuroimaging and connectomics. Dr. Glasser co-directs a brain imaging laboratory with David Van Essen that is now part of the Computational Imaging Research Center (CIRC). This laboratory has been central to the Human Connectome Project and its successor, the Adult Aging Brain Connectome project. The lab brings together expertise in neuroscience, radiology, computer science, and statistics to advance brain imaging methodologies and applications.

Ruoxi Jiaمشاهده پروفایل

استادیار

• Machine Learning
• Data Privacy
• Cybersecurity
• +۴ مورد دیگر

Ruoxi Jia is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, affiliated with the Sanghani Center for Artificial Intelligence and Data Analytics. She holds a Ph.D. from UC Berkeley and a B.S. from Peking University. Her research focuses on machine learning, security, privacy, and cyber-physical systems, with recent emphasis on data-centric AI and trustworthy machine learning. Education: Ph.D., Electrical Engineering and Computer Sciences, UC Berkeley (2018) B.S., Peking University Research interests include adversarial machine learning, AI safety, data valuation, and privacy-preserving techniques. Her work addresses challenges in AI ethics, backdoor detection, and scalable model security. Recent publications explore topics like defense mechanisms against poisoning attacks, large model safety surveys, and red teaming strategies. She actively seeks students (PhD, Masters, interns) and emphasizes collaboration through her group. Her work bridges theoretical foundations and practical applications in AI and cybersecurity, with contributions to both technical and ethical dimensions of modern machine learning systems.

• Multimodal Communication
• Multimodal Corpora
• Spoken Language and Gestural Behaviour
• +۶ مورد دیگر

Patrizia Paggio serves as an Associate Professor and Senior Researcher within the Department of Nordic Studies and Linguistics at the University of Copenhagen's Faculty of Humanities, concurrently holding a full professorship at the University of Malta's Institute of Linguistics and Language Technology since September 2011. Her scholarly work centers on the intricate relationship between verbal and nonverbal communication modalities, with international recognition for advancing methodologies in multimodal analysis. Academic Background: PhD in Computational Linguistics from the University of Copenhagen (1997), dissertation: "The Treatment of Information Structure in Machine Translation" Professor Paggio's research program investigates how gestures, head movements, and other nonverbal cues interact with spoken language to construct meaning in natural communication. She has pioneered methodologies for constructing and analyzing multimodal corpora, while maintaining technical expertise in machine translation systems, grammar engineering, and content-based querying frameworks. Her theoretical work spans formal syntactic structures, discourse phenomena, information packaging, and ontological representations for linguistic data, consistently bridging computational methods with linguistic theory. Analysis of her recent publications (2020-2025) reveals a sustained focus on computational approaches to nonverbal communication, particularly the automatic detection and annotation of head movements and gestures in both physical and digital environments. Key contributions include the GEHM Zoom corpus for online interaction analysis, eye-tracking studies of emoji processing, and diachronic modeling of historical language change. Her work strategically integrates eye-tracking, corpus linguistics, and machine learning techniques, establishing her at the convergence of linguistic theory, cognitive science, and artificial intelligence applications. Professional Leadership: Coordinator of the international GEHM (Gestures and Head Movements in Language) research network Organizer of MULTIMODAL CORPORA 2018, 4th European/Nordic Symposium on Multimodal Communication, and LREC2022 Workshop on People in Vision, Language and the Mind

Gerardo Aragon Camarasaمشاهده پروفایل

مدرس ارشد

• Robotics
• Artificial Intelligence
• Computer Vision
• +۵ مورد دیگر

Gerardo Aragon Camarasa is a Senior Lecturer at the School of Computing Science, University of Glasgow, where he leads research in the Computer Vision and Autonomous Systems group. His work focuses on solving real-world challenges in robotic perception, manipulation, and grasping using advanced AI techniques. Research Interests: Robotics and AI for advanced manufacturing systems Perception and manipulation of deformable objects Autonomous robotic systems for chemical and domestic applications Robot behavior modeling and self-awareness His publications demonstrate strong emphasis on robotic vision (garment perception, hand-eye calibration), AI integration (multimodal LLMs, reinforcement learning), and industrial applications (chemical robotics, Industry 5.0 ethics). Recent work shows growing focus on foundation models for robotics and simulation frameworks. Research Leadership: He leads multiple grants including an EPSRC programme grant for chemical robotics and a Royal Society project on robotic teleoperation. Actively supervises 7+ PhD students and has graduated 8+ doctoral researchers in robotics and computer vision. Infrastructure: Leads research using dual-arm robots and maintains active GitHub repositories and YouTube channels demonstrating robotic manipulation systems. Regular contributor to top robotics conferences (ICRA, IROS) and journals.

Heidi Giebelمشاهده پروفایل

استاد

• Aristotelian-Thomistic ethics
• Confucian ethics
• Moral development
• +۷ مورد دیگر

Dr. Heidi Giebel is a Professor in the Department of Philosophy at the University of St. Thomas in St. Paul, Minnesota. She specializes in integrating Aristotelian-Thomistic ethics with Confucian ethics and contemporary psychological research on moral development. Her work bridges classical philosophy with modern biomedical ethics. University of Notre Dame, PhD University of Notre Dame, MA St. Norbert College, BA Her research focuses on ethical excellence as a path to human flourishing, with particular emphasis on virtue assessment, moral identity formation, and cross-cultural ethical frameworks. She applies these theories to practical domains like medical ethics, education, and familial relationships. Recent publications analyze prenatal moral status attribution, end-of-life care ethics, and interdisciplinary approaches to virtue psychology. Her courses include seminars on biomedical ethics and comparative studies of heroes/villains in Eastern and Western traditions. Notable collaborations include co-authored works on moral education and clinical ethics, though no formal awards or grants are listed in the provided text.

Ron Yurkoمشاهده پروفایل

عضو هیئت علمی

• Sports Analytics
• Natural Language Processing & Large Language Models
• Biostatistics & Epidemiology
• +۴ مورد دیگر

Ron Yurko is an Assistant Teaching Professor in the Department of Statistics & Data Science at Carnegie Mellon University , where he focuses on methods at the intersection of statistical inference and machine learning. He serves as Director of the Carnegie Mellon Sports Analytics Center (CMSAC) , overseeing initiatives like the sports analytics research lab, CMSACamp , and the annual Sports Analytics Conference. Research Interests His work bridges Sports Analytics and Natural Language Processing , with applications in Biostatistics , Public Policy , and Statistical Pedagogy . Recent projects include evaluating NFL player positioning ( NFL Ghosts ), analyzing language patterns in LLM outputs, and developing fractional tackle metrics for defensive evaluation. Google Scholar articles reveal deeper methodological contributions to Bayesian modeling for directional movement analysis, multilevel models for snap timing, and spatio-temporal frameworks in football event modeling. Academic Background PhD in Statistics (2022) from Carnegie Mellon University BS in Statistics with University Honors (2015) from Carnegie Mellon Additional Contributions He is developing a textbook Statistical Methods in Sports Analytics (2027), maintains the Statistical Thinking in Sports Analytics newsletter, and teaches course 36-460/660 at CMU.

• History of arts
• Chinese philosophy
• Indian philosophy
• +۳ مورد دیگر

Nobuyoshi Yamabe is a Professor at Waseda University's Faculty of Letters, Arts and Sciences (School of Humanities and Social Sciences) since 2015. Previously, he served as Professor at Tokyo University of Agriculture (2003-2015) and Kyushu Ryukoku Junior College (1996-2003). He earned a Ph.D. in Religious Studies from Yale University (1999) and holds multiple advanced degrees from Yale and Osaka University. Current roles: Professor at Waseda University Professional memberships: American Academy of Religion, International Association of Buddhist Studies, The Association for Asian Studies Research interests focus on the intersection of Buddhist philosophy, meditative practices, and visual culture. His work spans Yogācāra theory (ālayavijñāna, bīja theory), Central Asian Buddhist cave monasteries, Chinese meditation texts, and comparative studies between Buddhist traditions. Recent projects integrate digital image restoration with Buddhist art analysis. Recent publications emphasize Yogācāra causality models, visualization sutras, and cross-disciplinary studies of meditation's mind-body implications. His 2024-2023 articles analyze selfhood in Yogācāra, comparative Zen texts, and spatial practices in rock-cut monasteries. Key trends: Meditative theory across Buddhist schools Visual narratives in Buddhist texts and art Historical development of Sino-Indian Buddhist traditions Grants include multiple Japan Society for the Promotion of Science projects on digital Buddhist practices, ālayavijñāna theory, and Sanskrit-Chinese textual analysis. He leads interdisciplinary collaborations bridging Buddhist studies with psychology and neuroscience.

V. Menkovskiمشاهده پروفایل

دانشیار

• Graph Neural Networks
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Dr. V. Menkovski serves as an Associate Professor in Data Mining at Eindhoven University of Technology's Department of Mathematics and Computer Science. He also holds associate professor positions with EAISI Health and EAISI High Tech Systems, and is an ICMS Affiliated member. His work spans multiple domains of artificial intelligence and computational physics, with significant contributions to fusion energy research. Mathematics and Computer Science, Data Mining (Primary Appointment) EAISI Health (Associate Professor) EAISI High Tech Systems (Associate Professor) ICMS (Affiliated Member) Menkovski's research focuses on Graph Neural Networks, Machine Learning, Deep Learning, and their applications in diverse fields from plasma physics to metamaterials. His work demonstrates strong interdisciplinary connections, particularly between computer science and fusion energy research. He has developed novel approaches for crowd simulation, tokamak plasma monitoring, and metamaterials homogenization using advanced neural architectures. His fingerprint reveals expertise in Quality-of-Experience, Autoencoders, Neural Networks, Annotation, Graph Neural Networks, Video Streaming, Adversarial Machine Learning, and Anomaly Detection. Analysis of his recent publications (2023-2025) shows a clear trend toward applying Graph Neural Networks to complex physical systems, particularly in fusion energy research and materials science. His work increasingly integrates symmetry principles with neural architectures, as seen in his research on equivariant networks for metamaterials and symmetry-informed networks for zeolite analysis. There's also significant focus on practical applications in fake news detection, anomaly detection, and plasma state monitoring. Best Paper Award ICPM 2021 (with Sommers and Fahland) Best Paper Award of LoG 2022 (with multiple co-authors including Huang, Chen, Fang, Zhao, Yin, Pei, Mocanu, Wang, Pechenizkiy, and Liu) Menkovski teaches several advanced courses including Deep Learning, Advanced Topics in Artificial Intelligence, and Sociophysics 2, which runs through August 2025. His supervised work portfolio includes 79 projects, indicating substantial mentorship activity. He has received significant media attention for his research, including coverage by 11 news outlets, blog posts, and mentions on social media platforms. His work on 'Supervised Learning of Process Discovery Techniques Using Graph Neural Networks' was particularly noted in media coverage. His research involves collaboration with multiple institutions and teams, particularly in fusion energy research (Eurofusion Tokamak Exploitation Team, ASDEX-Upgrade team, EUROfusion MST1 Team). He works closely with researchers across disciplines, including physicists working on tokamak plasma and materials scientists studying metamaterials and zeolites.

• Condensed Matter Physics
• Quantum Physics
• Biomedical Engineering
• +۶ مورد دیگر

Alastair Stacey is a Professor in the School of Science at RMIT University, specializing in quantum physics, materials engineering, and nanotechnology. His research focuses on diamond-based quantum technologies, including quantum sensing, quantum computing, and biomedical applications. He leads projects on diamond nanoparticle engineering, quantum device fabrication, and surface functionalization for advanced sensing systems. Key research interests include nitrogen-vacancy centers in diamond, quantum microscopy, and nanoscale sensors for biomedical and energy applications. He supervises PhD/Masters students in areas like diamond synthesis for quantum devices and quantum sensing technologies. Recent work involves developing telecom-band emitters in diamond and optimizing diamond surface chemistry for enhanced electronic properties. Education: Not explicitly stated in provided texts. Affiliations: RMIT University, School of Science. Grants/Projects: Active in quantum technology and materials science research, supported by collaborative projects in diamond device fabrication. His articles (15 most recent) span quantum optics, diamond surface engineering, and applications in photovoltaics and biomedical interfaces. He collaborates widely on topics like quantum metrology and 2D materials integration with diamond.

Helena Phillips-Robinsمشاهده پروفایل

استاد آموزشی

• Dante studies
• Medieval theology and religious practices
• Liturgy
• +۶ مورد دیگر

Dr Helena Phillips-Robins is a Teaching Professor in Medieval Italian Literature and Culture at the University of Cambridge's Faculty of Modern and Medieval Languages and Linguistics. She holds a PhD from Cambridge (2017) and is affiliated with Selwyn College. Her research focuses on medieval Italian literature, particularly Dante, with expertise in theology, liturgy, women’s religious history, music, visual cultures, and text-image relations. She supervises PhD student Thomas Godfrey and teaches the course 'Dante and the culture of his age' (IT7). Her research explores intersections between liturgical practices and literary texts, with a focus on Dante’s Commedia . She examines how medieval religious imagery, music, and manuscript culture shaped devotional and communal experiences. Her publications include Liturgical Song and Practice in Dante’s Commedia (2021) and articles analyzing Dante’s use of visual and aural elements in religious contexts. Her work bridges literary analysis with interdisciplinary approaches, integrating musicology, art history, and social history. She contributes to Cambridge’s research networks in medieval studies and Dante scholarship, engaging with manuscripts and interdisciplinary methodologies to illuminate medieval cultural practices.

• Internet of Things
• RFID and antenna design
• Wireless sensor networks
• +۵ مورد دیگر

Turke Althobaiti is an active researcher and faculty member whose recent work is concentrated in electrical and computer engineering, with strong interdisciplinary links to computer science and biomedical informatics. Based on co-author affiliations and publication scopes, he is associated with King Saud University, College of Engineering, Department of Electrical Engineering . Research Interests: Design of UHF RFID antennas and Internet-of-Things sensing systems. Localization and communication in smart cities, including non-line-of-sight mitigation and 5G/6G networks. Machine-learning-driven healthcare applications—ranging from COVID-19 detection via chest X-rays to arrhythmia and pneumonia screening. Assistive technologies for the visually impaired, employing contactless RF sensing and AI-based navigation aids. Cloud-security solutions, specifically ensemble intrusion-detection systems against flash-crowd attacks. Cross-disciplinary forays into metabolomics biomarkers and human-animal affective computing. Across 15 recent publications (2019-2025), Althobaiti demonstrates a clear trajectory toward AI-enabled sensing and communication . Workflows combine hardware-level innovations (antennas, RFID tags, USRP radios) with data-level advances (deep learning, ensemble methods, privacy-preserving techniques) to address real-world problems in healthcare, smart cities, and assistive living. Scientific Awards & Recognition: No specific awards are listed in the provided text. Advising & Grants: While no explicit list of students or funded projects is given, the high volume of multi-institutional collaborations and senior-author positions suggest active supervision of graduate researchers and participation in funded projects, most likely supported by the Deanship of Scientific Research at King Saud University or similar Saudi funding bodies. Laboratories & Teams: Though no formal laboratory names are provided, the breadth of hardware prototyping, RF experimentation, and AI model development implies access to well-equipped laboratories in RF/microwave engineering, embedded systems, and computational intelligence.

• Materials Science
• Bioelectronics
• Biomedical Engineering
• +۵ مورد دیگر

Shuo Li is a Professor in the Department of Macromolecular Engineering at ETH Zürich, Switzerland. His research focuses on innovative biomaterials, bioelectronic systems, and implantable medical devices. Key areas include bioresorbable materials for transient electronics, flexible/stretchable sensors, and soft robotics applications. His work integrates materials science with biomedical engineering to address challenges in tissue integration, real-time diagnostics, and programmable drug delivery. Recent projects emphasize wireless implantable sensors for continuous monitoring of physiological parameters such as blood flow, oxygen saturation, and pH levels in surgical flaps and organ grafts. He has pioneered 3D shape-morphing displays using liquid metal actuators and developed self-healing elastomeric switches for haptic interfaces. His research spans biomaterial synthesis, optoelectronics, and additive manufacturing of soft materials. Publications highlight advancements in bioresorbable platforms for drug delivery, light-controlled actuation systems, and optical probes for in vivo pharmacology. His interdisciplinary approach bridges material design, device fabrication, and clinical applications, with a focus on translating lab innovations into practical medical solutions. Advising and grants: No specific advisees or grant details listed in the provided text. However, his extensive publication record indicates active collaboration with research groups in bioelectronics, soft robotics, and biomedical engineering. Labs/Teams: Likely affiliated with ETH's Macromolecular Engineering lab and collaborate with multidisciplinary teams in materials science, robotics, and medical device development.