جست‌وجوی استاد و پژوهشگر

Avniel Singh Ghumanمشاهده پروفایل

دانشیار

• visual cognition
• neural dynamics
• face recognition
• +۶ مورد دیگر

Dr. Avniel Singh Ghuman is an Associate Professor in the Department of Neurological Surgery at the University of Pittsburgh School of Medicine. He serves as Director of the Cognitive Neurodynamics Lab and plays a key role in advancing MEG (Magnetoencephalography) Research at the university. His work bridges clinical neurosurgery with fundamental neuroscience research to understand visual perception mechanisms. Dr. Ghuman's educational background includes: BA in Math and Physics from The Johns Hopkins University (1998) PhD in Biophysics from Harvard University (2007) Postdoctoral training at the National Institute of Mental Health Dr. Ghuman's research focuses on how the brain transforms visual input into meaningful perception of objects, faces, words, and social images in real-world contexts. His laboratory employs both invasive (intracranial EEG) and non-invasive (MEG) techniques to examine the spatiotemporal dynamics of neural activity during visual processing. The lab integrates multivariate machine learning methods, network analysis, and direct neural stimulation to investigate information processing at both local brain regions and distributed network levels. Recent work has pioneered methods for studying brain activity during authentic social interactions and natural behavior. His publication record demonstrates significant contributions to understanding real-world face perception, neural dynamics during natural behavior, and the application of advanced analytical techniques to brain imaging data. His research has revealed how brain network dynamics form a 'punctuated equilibrium' of stable states with transitory bursts between them, coinciding with behavioral shifts in everyday activities. Dr. Ghuman has received notable recognition for his work: Young Investigator Award from NARSAD (2012) Award for Innovative New Scientists from the National Institute of Mental Health (2015) His research has been featured in prominent media outlets including MIT Technology Review, The Wall Street Journal, and Carnegie Mellon University publications. As Director of the Cognitive Neurodynamics Lab, Dr. Ghuman leads a research program that has advanced our understanding of how the brain processes visual information in real-world environments, with implications for both fundamental neuroscience and clinical applications.

Ke Chenمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Artificial Intelligence
• Computational Cognitive Science
• +۹ مورد دیگر

Dr. Ke Chen is a Senior Lecturer in the School of Computer Science at The University of Manchester, leading the Machine Learning and Perception (MLP@UoM) Lab. His research focuses on machine learning, deep learning, reinforcement learning, and their applications in intelligent systems, computer vision, and audio/speech processing. He has supervised over 50 PhD students and holds editorial roles in journals like Neural Networks and IEEE Transactions on Neural Networks . Dr. Chen has received awards such as the NSFC Distinguished Principal Young Investigator Award (2001) and JSPS Research Award (1993). Education: PhD in Computer Science (1990), with academic positions at institutions including Peking University, The Ohio State University, and Kyushu Institute of Technology. His professional activities include roles in IEEE Computational Intelligence Society committees and external examiner roles at universities like Essex. Research interests span computational cognitive systems, biometric authentication, and video game AI. Key contributions include advancements in deep architectures, reinforcement learning, and speaker-specific feature extraction. His lab, MLP@UoM, explores topics like explainable AI and transfer learning. Recent publications (2024) include work on goal-conditioned reinforcement learning and bias-resilient algorithms. He is actively involved in international conferences, serving as a keynote speaker and program committee member.

• Internet of Things (IoT)
• Cybersecurity
• Sensor Networks
• +۳ مورد دیگر

Shiwei Fang is an Assistant Professor in the Department of Computer & Cyber Sciences within the School of Computer and Cyber Sciences at the University of North Georgia. He holds a Ph.D. in Computer Science from the University of North Carolina (2021) and a B.E. in Computer Science from the State University of New York (2015). His research focuses on IoT systems, cybersecurity, sensor networks, and edge computing, with notable contributions to multimodal analytics, privacy visualization tools, and geospatial tracking datasets. He advises the Graduate Student Organization and serves on the SCCS Academic Web Oversight Committee. Education: Ph.D., Computer Science, University of North Carolina, 2021 B.E., Computer Science, State University of New York, 2015 Research interests include IoT security, context-aware systems, and sensor fusion. His work on IoBT-MAX and GDTM datasets highlights expertise in experimentation frameworks and geospatial tracking. Recent publications explore privacy risks in IoT, AR-based privacy visualization, and efficient inference models for edge computing. He has contributed to over 25 peer-reviewed articles since 2015, with a focus on real-world IoT applications and hardware-software co-design. Service roles include faculty advising and committee participation. He teaches courses like CSCI 3170/5170 on Computer Organization, bridging theoretical computer science with practical hardware concepts.

• Cyber Security
• Cryptography
• Steganography
• +۶ مورد دیگر

Rainer Böhme is a Professor at the University of Münster, Germany. His research focuses on cyber security, cryptography, steganography, digital forensics, and blockchain technology. He has made significant contributions to understanding cyber risk quantification, central bank digital currencies (CBDCs), and the socio-technical challenges in cryptocurrency systems. Key areas of research include steganalysis (analysis of hidden data in digital media), forensic techniques for neural network inference pipelines, and the economic implications of cyber insurance. He actively contributes to conferences like the Financial Cryptography Workshops (FC) and the Workshop on Information Hiding and Multimedia Security (IH). Böhme's work bridges theory and practice, addressing real-world issues such as privacy in CBDCs, adversarial attacks on AI systems, and the role of law enforcement in cryptocurrency markets. His recent studies explore the security implications of image orientation in JPEG files and the detection of privileged parties in blockchain transactions. He has collaborated with institutions like the University of Vienna and ETH Zurich, and his research has been published in top-tier venues such as IEEE Transactions on Information Forensics and Security and the ACM Conference on Computer and Communications Security (CCS).

Jacob Whitehillمشاهده پروفایل

دانشیار

• Applied Machine Learning
• Speech and Speaker Recognition
• Educational Data Mining
• +۳ مورد دیگر

Jacob Whitehill is an Associate Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), affiliated with the Learning Science & Technologies (LST) program. His research focuses on applying machine learning to education and human-computer interaction, including speech recognition, emotion analysis, and automated classroom observation. He leads the NSF-funded project Developing New Scientific Instruments for Classroom Observation and collaborates on the AI Institute for Student-AI Teaming (iSAT) . His research interests span Applied Machine Learning (e.g., multi-modal systems, speaker diarization), AI for Education (e.g., automated instructional evaluation, child speech recognition), and Emotion Recognition (e.g., affective computing in classrooms). Recent work emphasizes classroom observation tools and improving student-teacher interaction analysis through video and audio data. Notable projects include: NSF-funded classroom observation tools AI Institute for Student-AI Teaming (iSAT) Schmidt Futures-funded Hybrid Human-Agent Tutoring for math education His team includes PhD students Xinlu He (Data Science), Jiani Wang (Computer Science), and Yiwen Guan (Computer Science), along with visiting scholar Cecilia Tivir. He advises students on topics like speaker recognition, educational data mining, and computer vision in classroom settings. Grants and collaborations include NSF, Schmidt Futures, and industry partnerships. His lab develops tools for automated feedback on teaching practices, leveraging LLMs and multimodal data. For more details, contact jrwhitehill@wpi.edu .

Jean Ponceمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Robotics
• +۳ مورد دیگر

Jean Ponce is a Professor of Computer Science at Ecole Normale Superieure (ENS) in Paris and a Part-Time Global Distinguished Professor at New York University's Courant Institute of Mathematical Sciences and Center for Data Science (CDS). He previously served as Director of the ENS Computer Science Department (2011-2017) and held positions at Inria (2017-2022), University of Illinois at Urbana-Champaign (1998-2006), MIT, Stanford, and Inria (1982-1985). Academic Leadership: Scientific Director of PRAIRIE Interdisciplinary AI Research Institute in Paris Startup Involvement: Co-founder and CEO of Enhance Lab (2022) Editorial Roles: Senior Editor-in-Chief of International Journal of Computer Vision (2019-2022) Conference Leadership: Chair of IEEE CVPR (1997,2000), ECCV (2008), and upcoming ICCV (2023) Research Focus: Computer vision, machine learning, robotics, and AI with applications in exoplanet imaging, 3D reconstruction, and image quality assessment. His work bridges statistical learning and deep learning approaches. Awards: IEEE Fellow (2003) ELLIS Fellow (2019) ERC Advanced Grant (2011) IEEE CVPR Longuet-Higgins Prizes (2016,2020) ICML Test-of-Time Award (2019) Patents & Publications: Co-author of influential textbook Computer Vision: A Modern Approach (translated into Chinese, Japanese, Russian). Holds two US patents and one pending French patent. Google Scholar h-index of 78 with over 55,000 citations.

• Cognitive Psychology
• Neuroscience
• Visual Perception
• +۳ مورد دیگر

Yelda Semizer Kaplan is an Assistant Professor at the New Jersey Institute of Technology within the College of Humanities and Social Sciences . Her research intersects cognitive psychology and visual neuroscience, focusing on fundamental mechanisms of human perception and attention. Specializes in temporal integration and ensemble perception Investigates peripheral vision limitations in complex tasks Develops computational models of maze-solving cognition Key research themes analyze how visual clutter affects search performance, how temporal dynamics influence attentional blink, and how spatial configurations impact cognitive processing. Her work has been featured in Journal of Vision and Attention, Perception & Psychophysics , with collaborations across neuroscience and human factors domains. Media engagement highlights include contributions to NJIT's Research Institutes Showcase (2021) and Cyberpsychology Seminar Series (2021). Current work explores mental maze-solving mechanisms through novel behavioral paradigms.

• Autonomous Systems
• Signal Processing
• Vehicle Health Management
• +۷ مورد دیگر

Dr Ivan Petrunin is a Research Professor in Signal Processing for Autonomous Systems and a DARTeC Fellow at Cranfield University's School of Aerospace, Transport and Manufacturing. His work focuses on advancing sensor technologies, data fusion, and decision-making systems for Cyber-Physical Systems, with applications in aerospace, ground-based autonomous systems, and urban air mobility. Key areas include Position, Navigation and Timing (PNT), vehicle health management, and AI-driven fault detection. He leads research at facilities like the Muti-User Environment for Autonomous Vehicle Innovation (MUEAVI) and collaborates with industry partners like Airbus, Rolls-Royce, and Thales. Education: BSc and MSc in Design of Electronic Equipment from National Technical University of Ukraine (1996–1998), followed by a PhD in Signal Processing for Condition Monitoring from Cranfield University (2013). Prior to Cranfield, he was a Lecturer in Digital Signal Processing at NTU Ukraine (2001–2005). Research Interests: Autonomous Systems & Sensor Fusion Machine Learning in Navigation and Safety GNSS Integrity & Urban Air Mobility Condition Monitoring & Structural Health Multi-Agent Reinforcement Learning Publications: Over 100 journal/conference articles and book chapters, with recent works emphasizing hybrid sensor fusion, resilient navigation architectures, and AI-driven solutions for GNSS-denied environments. Notable contributions include multi-sensor fusion frameworks for UAVs and Bayesian filter innovations. Awards: FRIN Fellowship, SMAIAA Membership, IEEE and ION Fellowships, and FHEA recognition. His work is supported by ESA, Innovate UK, and EPSRC. Advising & Labs: Supervises PhD students in UAV navigation and machine learning. Leads Cranfield's facilities for autonomous systems experimentation and advanced timing node infrastructure.

Tamara Sumnerمشاهده پروفایل

استاد

• AI in Education
• Classroom Discourse Analysis
• Educational Technology
• +۴ مورد دیگر

Tamara Sumner is a Professor at the Institute of Cognitive Science , University of Colorado. Her research focuses on leveraging AI and educational technology to improve teaching practices, particularly in STEM education, and fostering equitable learning opportunities. She co-leads the Institute for Student-AI Teaming (iSAT), reimagining AI's role in education. Her work emphasizes classroom discourse analysis, teacher professional development, and rural STEM pathways. Key research areas include: AI tools for automating feedback on teacher-student interactions Equity-focused learning analytics and visualizations Rural youth engagement in STEM through community partnerships Integration of computational thinking and sensor technologies in K-12 curricula Her recent articles highlight advancements in automated discourse analysis, equity-driven tools like the SEET system, and AI-augmented tutoring models. She has contributed to grants such as the BIGDATA: IA initiative (2018) and co-designed programs like DaSH Home for remote learning. Her work bridges research and practice, involving educators and communities in co-design processes. Current initiatives aim to address systemic inequities through technology, such as visual learning analytics for classroom reflection and STEM career pathways for underserved rural populations.

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Prof. Margret Keuper is a Professor in the Department of Computer Vision and Machine Learning at the Max Planck Institute for Informatics. Her research focuses on advancing machine learning and computer vision techniques, with an emphasis on model fairness, adversarial robustness, and multimodal interactions. She leads interdisciplinary projects exploring topics such as dataset analysis, generative models, and climate action through visual narrative analysis. Research Interests: Her work bridges theoretical foundations and practical applications in domains like adversarial training, image classification robustness, and robotics perception. She explores how vision-language models can be steered to align with human biases and develops methods for data-efficient learning and interpretability. Recent Contributions: Recent work includes FAIR-TAT (model fairness via adversarial training), VSTAR (video synthesis), and TikZero (zero-shot graphics program generation). Her publications in top venues like CVPR, ICCV, and ICLR highlight contributions to both methodological innovation and real-world impact. Collaborations: Works closely with researchers across Max Planck and academic partners, focusing on projects such as sensor layout optimization, climate discourse analysis via social media imagery, and domain-aware foundation model fine-tuning.

Dale Lawrenceمشاهده پروفایل

استاد

• Astrodynamics
• Satellite Navigation Systems
• Autonomous Systems
• +۱۰ مورد دیگر

Dale Lawrence is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, where he has served continuously since 1991. He directs research at the Research and Engineering Center for Unmanned Vehicles (RECUV), focusing on astrodynamics, satellite navigation systems, and autonomous aerial platforms for atmospheric science. His academic credentials include: PhD in Electrical Engineering from Cornell University (1985) MS in Electrical Engineering from Cornell University (1982) BS in Electrical Engineering from Colorado State University (1980) Professor Lawrence's research spans spacecraft attitude control , vibration isolation , and adaptive control systems , with pioneering work in haptic interfaces for scientific visualization and teleoperation. His recent work emphasizes unmanned aerial systems for Arctic atmospheric research, particularly turbulence measurement and boundary layer studies using custom UAV platforms like DataHawk. This work bridges aerospace engineering with climate science through field campaigns such as MOSAiC and LAPSE-RATE. His publication record reveals a clear trajectory toward Arctic atmospheric science and UAV-based sensing , with increasing focus on turbulence dynamics, sea-ice interactions, and autonomous system validation. The work consistently integrates hardware development (sensors, UAVs) with field deployment in extreme environments. Selected honors include: Best Commercial Potential Award at IEEE Symposium on Haptic Interfaces (2004) Best Paper Presentation at American Control Conference (1994) Teaching Excellence Awards from University of Cincinnati (1990, 1991) Distinguished Publication Award from Martin Marietta Astronautics (1988) Professor Lawrence has led major field campaigns including MOSAiC and LAPSE-RATE, securing funding from NSF and DOE for projects like ERASMUS and ShUREX. His RECUV team develops specialized UAV platforms (DataHawk, HELiX) for atmospheric research, with recent work focusing on machine self-confidence for autonomous decision-making in complex environments. While student advising details aren't specified, his projects involve extensive student participation in hardware development and field operations. He maintains active leadership in Arctic atmospheric research through the DataHawk UAV program and HELiX multispectral systems, with ongoing work on gossamer propeller technology for high-altitude applications and machine self-confidence frameworks for autonomous systems.

Mark Sabbaghمشاهده پروفایل

استاد

• Developmental Psychology
• Cognitive Neuroscience
• Social Cognition
• +۷ مورد دیگر

Mark Sabbagh is a Professor in the Department of Psychology at Queen's University , Canada. His research focuses on theory of mind , social learning , executive functioning , and conceptual change in preschoolers, as well as theory of mind and social functioning in adults. Education : Ph.D. (1998), M.Sc. (1996) in Psychology from the University of Oregon; B.A. (1993) in Psychology from the University of California, Santa Cruz. Cross-Appointments : Centre for Neuroscience Studies, Queen's University. His work integrates developmental psychology with cognitive neuroscience , examining neural correlates (EEG, fMRI) of social cognition and mental state reasoning. Additionally, he investigates clinical implications of theory of mind, including links to depression and autism spectrum disorders. Recent publications highlight his expertise in ERP studies , word learning , executive function , and neurogenetic influences on social cognition. His lab explores how probabilistic reasoning and environmental factors shape cognitive development. Current roles : Editor-In-Chief of Cognitive Development Journal (since 2014); Board Member, Cognitive Development Society (since 2013). Contact : sabbagh@queensu.ca | Office: 348 Humphrey Hall, Queen's University.

Christina Saengerمشاهده پروفایل

دانشیار

• Consumer Behavior
• Brand Identity Construction
• Social Media Marketing
• +۴ مورد دیگر

Dr. Christina Saenger serves as Associate Dean of the Williamson College of Business Administration at Youngstown State University (YSU), where she also holds an Associate Professorship in Marketing. She earned a PhD in Marketing from Kent State University (2012), an MBA in Strategic Marketing from the University of Akron (2005), and a BA in Business & Organizational Communication from the same institution (2003). Her professional background includes client account management in marketing and advertising firms prior to academia. Her research focuses on consumer behavior in social contexts, particularly how individuals use brands for identity expression and cognitive processing of product information. Key topics include word-of-mouth mechanisms, brand-gratitude dynamics, and the psychological impact of social exclusion on consumer behavior. Her work appears in top-tier journals like the European Journal of Marketing , Journal of Advertising , and Psychology & Marketing . Dr. Saenger has received numerous accolades, including YSU's Distinguished Professorship designations for research (2022), teaching (2021), and service (2017), as well as the Research Professorship Award (2017). She actively contributes to academic governance through editorial roles at the Journal of Advertising Research and Journal of Consumer Marketing . Her teaching spans marketing strategy, social media, consumer behavior, and interactive marketing. Professional Service: Editorial Review Board Member for Journal of Advertising Research , Ad Hoc Reviewer for Journal of Business Research , and Conference Paper Reviewer for the Association for Consumer Research. Recent Research Trends: Emerging focus on AI's impact on consumer trust (2024 study) alongside continued exploration of word-of-mouth as a compensatory behavior for self-threat and social exclusion.

Rachel Parkinsonمشاهده پروفایل

پژوهشگر ارشد

• Insect Neuroethology
• Environmental Toxicology
• AI in Biology
• +۳ مورد دیگر

Dr. Rachel Parkinson is a Research Fellow at Wolfson College, University of Oxford, and holds a Lecturer position in Biology at Keble College. She is also an Eric & Wendy Schmidt AI in Science Postdoctoral Fellow. Her research focuses on insect sensory processing, particularly how pollinators like bees perceive environmental stressors such as pesticides. She develops AI-driven tools to diagnose sublethal toxicity and leads projects using large language models for systematic reviews of pesticide risks. Her work aims to assess environmental threats to pollinators and devise mitigation strategies. Her research interests include neuroethology, pesticide impacts on insect behavior, and AI applications in ecological research. She collaborates with the Bee Lab to advance understanding of pollinator health and ecological resilience. Her interdisciplinary approach bridges biology, neuroscience, and computational methods to address global environmental challenges. Awards: Eric & Wendy Schmidt AI in Science Postdoctoral Fellow Labs/Teams: Bee Lab, University of Oxford

Paul Rosenمشاهده پروفایل

دانشیار

• Scientific Visualization
• Topology-Based Methods
• Network Visualization
• +۳ مورد دیگر

Paul Rosen is an Associate Professor at the University of Utah, affiliated with the Scientific Computing and Imaging Institute and the Kahlert School of Computing. He holds a Ph.D. in Computer Science from Purdue University (2010). Prior to his current role, he was an Assistant/Associate Professor at the University of South Florida (2015–2022) and a Research Assistant Professor at the University of Utah's SCI Institute (2010–2015). Research Focus: Rosen specializes in topology-based visualization techniques, with emphasis on network visualization, uncertainty quantification, and perceptual studies. His work bridges computational methods with human perception, aiming to enhance data understanding through effective visual design. Awards & Recognition: National Science Foundation CAREER Award (2019) Best Paper Awards at PacificVis 2016, IVAPP 2016, and multiple other conferences Honorable Mentions for IEEE VIS and VAST Challenge submissions Leadership: As General Chair of IEEE VIS 2024, Rosen led the planning for this flagship visualization conference, emphasizing community-driven design and in-person collaboration. Education Contributions: His research includes pedagogical innovations, such as predictive modeling for student feedback and peer review analysis in visual literacy courses.