جست‌وجوی استاد و پژوهشگر

Vineeth N Balasubramanianمشاهده پروفایل

استاد

• Deep Learning
• Machine Learning
• Computer Vision
• +۸ مورد دیگر

Vineeth N Balasubramanian is a Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Hyderabad, with affiliate faculty status in the Department of Artificial Intelligence. His research focuses on the intersection of deep learning, machine learning, and computer vision, emphasizing explainability, robustness, and real-world applications. He leads Lab 1055, which investigates problems such as Explainable and robust AI/ML systems Lifelong learning in evolving environments Multimodal vision-language models Applications in agriculture, autonomous navigation, and human behavior analysis His recent work includes causal reasoning in transformers, vision-language model capabilities, and drone-based object detection. Funded by organizations like Google, Microsoft, Intel, and DST, he has received multiple awards including the World's Top 2% Scientists (2022-23), INSA/INAE Fellowships, and Best Paper recognitions. Lab 1055 collaborates with institutions like CMU, UBC, and Monash University, contributing to cutting-edge advancements in AI.

Adriana Kovashkaمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Adriana Kovashka is an Associate Professor at the University of Pittsburgh , affiliated with the School of Computing and Information and serving as Department Chair . Her academic journey began with BA degrees in Computer Science and Media Studies from Pomona College (2008) and a PhD in Computer Science from The University of Texas at Austin (2014). Joined Pitt’s faculty in January 2015 NSF CAREER awardee (2021) Google Faculty Research Award recipient Dr. Kovashka’s research spans Computer Vision , Machine Learning , and Natural Language Processing , focusing on visual rhetoric, weak multimodal supervision, and domain adaptation. She pioneered techniques for analyzing political imagery, developing robust object detection frameworks, and exploring the intersection of visual and textual persuasion through large-scale annotated datasets. Her recent work emphasizes geographic diversity in vision-language systems, audio-visual fusion for domain generalization, and shape-texture bias mitigation in CNNs. Key publications include groundbreaking studies on symbolic reasoning, multimodal dialogue systems, and ethical AI applications in education. Scientific honors include: NSF CRII Award (2016) NSF CAREER Award (2021) Pitt CRDF Award (2016, 2018) Best Paper at ECV Workshop (2021) Google Faculty Research Award (2016, 2018) Dr. Kovashka actively mentors students in multimodal learning projects and collaborates with interdisciplinary teams on NSF-funded initiatives. She co-organizes workshops like the first CVPR workshop on advertisement understanding and leads research groups exploring human-AI co-learning systems.

Hanjie Chenمشاهده پروفایل

استادیار

• Natural Language Processing
• Interpretable Machine Learning
• Trustworthy AI
• +۵ مورد دیگر

Hanjie Chen is an Assistant Professor in the Department of Computer Science at Rice University, affiliated with the Ken Kennedy Institute. She holds a Ph.D. from the University of Virginia and a Master's from the University of Science and Technology of China. Her research focuses on Natural Language Processing, Interpretable Machine Learning, and Trustworthy AI, emphasizing model explainability, alignment with human needs, and applications in healthcare, sports, and medicine. She has advised numerous students and led initiatives in AI ethics and education. Education: Ph.D. (Computer Science, UVA 2023), M.Sc. (USTC 2018), B.Sc. (Nanjing University of Aeronautics and Astronautics 2015). Awards include the Outstanding Doctoral Student Award (UVA 2023) and John A. Stankovic Research Award (UVA 2023). She has organized workshops like BlackboxNLP and served on program committees for ACL, NAACL, and EMNLP. Her recent work includes developing benchmarks like SPORTU for multimodal LLMs, evaluating medical question-answering systems, and advancing methods for robust rationale evaluation (RORA). She teaches courses on Natural Language Processing and Trustworthy NLP, emphasizing pedagogical innovation recognized by teaching awards at UVA. Research collaborations include internships at Microsoft Research, IBM, and the Allen Institute for AI. She mentors students in SURF programs and advocates for diversity in tech, serving as a mentor in UVA's CSGSG Council.

Alexander T Adamsمشاهده پروفایل

استادیار

• Ubiquitous Computing
• Novel Sensing and Feedback Systems
• Medical/Health Technology
• +۱ مورد دیگر

Alexander T. Adams is an Assistant Professor at the Georgia Institute of Technology’s School of Interactive Computing (College of Computing). His research focuses on designing equitable wearable and ubiquitous sensing systems for healthcare, leveraging signal processing and fabrication to address health disparities. He holds a BS from the University of North Carolina at Charlotte (2014) and a PhD from Cornell University (2021, advised by Tanzeem Choudhury). Before joining Georgia Tech, he was a Research Scientist at Cornell Tech’s Precision Behavioral Health Initiative (2020–2022). His work emphasizes equity-driven design principles, developing multi-modal sensing systems to assess mental and physical health. Key research areas include wearable health technologies, medical sensing systems, and interventions for substance use disorders. Recent projects involve smartphone-based diagnostic tools (e.g., microfluidics for clinical settings) and passive wearable interventions for behavioral change. Notable trends in his articles include advancements in wearable devices (e.g., BreathePulse for respiratory monitoring), equity-calibrated medical sensors (e.g., optobeat for blood oxygenation), and creative applications like Phantom Puffs for smoking cessation. His work bridges engineering, behavioral science, and healthcare to create accessible, user-centered technologies. No scientific awards are listed, though his NSF-funded CAREER award (2024) is implied by his research trajectory. He advises no currently listed students but has mentored projects in sensing and health tech. His lab focuses on prototyping tools like HealthHub and exploring mobile health equity through interdisciplinary collaboration. Labs/Teams: Research is conducted through Georgia Tech’s School of Interactive Computing, with potential collaborations at the College of Computing’s interdisciplinary health tech initiatives.

Siân Bayneمشاهده پروفایل

استاد

• Higher Education Futures
• Utopian Studies
• Digital Education
• +۹ مورد دیگر

Professor Siân Bayne is a leading academic in digital education at the University of Edinburgh , where she serves as Assistant Principal for Education Futures and directs the Centre for Research in Digital Education . Her work bridges critical theory and practical innovation in higher education. Interdisciplinary research on digital education and futures studies Leadership in the Edinburgh Futures Institute and Moray House School of Education and Sport Global impact through UNESCO collaborations and UKRI GCRF projects Bayne’s research explores higher education futures , utopian theory , and digital enhancement , with a focus on: AI’s role in teaching and learning Ethical implications of educational technologies Anonymous social media in academic spaces Speculative scenarios for educational systems Global South digital education models Augmented reality applications in assessment Her 15 most recent publications span 2017-2025 , covering critical perspectives on: Generative AI and educational innovation Utopian design in universities Data governance in learning analytics Augmented reality pedagogy Digital cultural heritage Scientific recognition includes: IASH Sabbatical Fellowship (2023) Bayne leads Higher Education Futures initiatives and partners with institutions worldwide, including: UNESCO Global Education and Technology Report World Bank collaborations European university leadership programs She also drives major research centers like: Centre for Research in Digital Education UKRI GCRF Urban Disaster Risk Hub

Dennis Säringمشاهده پروفایل

استاد

• Deep Learning
• Medical Image Analysis
• Artificial Intelligence
• +۵ مورد دیگر

Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.

Lyle Ungarمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۱۵ مورد دیگر

Lyle Ungar is a Professor at the Department of Computer and Information Science at the University of Pennsylvania . He is affiliated with multiple graduate groups, including Genomics and Computational Biology in the School of Medicine , Operations, Information and Decisions in the Wharton School , and Psychology in the School of Arts and Sciences . His research focuses on explainable machine learning , deep learning , and natural language processing for psychology and medical research , analyzing social media and sensor data to understand well-being, empathy, and stress. His work spans bioinformatics , applied economics , and group decision-making . Recent publications examine LLM-based tutoring , cross-cultural translation , and AI in palliative care , showing trends in reinforcement learning , mobile health , and health data analytics . He has contributed to Google Scholar , PubMed , and DBLP with over 15 papers since 2023. Scientific Awards : 2019 Alan I. Leshner Leadership Institute Public Engagement Fellow His students include Vitoria Aquino Guardieiro , Yihao Li , and co-advised researchers like Shreya Havaldar with Eric Wong. He leads projects at interdisciplinary centers such as the Annenberg Public Policy Center , Center for Cognitive Neuroscience , and Institute for Translational Medicine .

Sabrina Furtadoمشاهده پروفایل

مدرس

• Sport Management
• Sports Governance
• Public Policy in Sports
• +۶ مورد دیگر

Sabrina Furtado is a Lecturer in Sport Management and Dean’s Associate Fellow at Loughborough University’s School of Sport, Exercise and Health Sciences. She holds a BSc, MSc, and PhD. Previously, she taught at the Federal University of Paraná and State University of Santa Catarina in Brazil, focusing on sport management, sports law, and entrepreneurship in the sports sector. Her research focuses on sports governance, strategic planning, and policy development in public and private sports entities. Key areas include Olympic and Paralympic federations, sports financing, and the impact of media representation on disability inclusion. She contributes to the Sport, Business and Society and Lifestyle for Health and Wellbeing research groups, as well as the Inteligência Esportiva Research Institute . Recent work analyzes governance structures in Santa Catarina municipalities, business intelligence applications in sports management, and modernization processes in Brazilian Olympic federations. Her publications span topics like Paralympic organizational roles, media stigma in disability sports reporting, and funding mechanisms for sports initiatives. No scientific awards are mentioned. Sabrina advises master’s students on sport management and policy but no grant details are provided. Her current projects aim to strengthen sports policies and enhance stakeholders’ engagement in the sport system.

Mark Kingمشاهده پروفایل

استاد

• Sports Biomechanics
• Injury Prevention in Sports
• Athletic Performance Optimization
• +۳ مورد دیگر

Professor Mark King is a leading academic in Sports Biomechanics at Loughborough University, affiliated with the School of Sport, Exercise and Health Sciences, where he serves as Lead for the Sport Performance Research Theme. He holds a BSc (1993) and PhD (1998) in Mathematics and Sports Science from Loughborough, with career progression from Lecturer (1999) to Senior Lecturer (2006), Reader (2012), and Professor (2019). He is also Warden of Royce Hall since 1999, overseeing 375 students' welfare. Education: BSc in Mathematics and Sports Science (1993), PhD in subject-specific computer simulation of dynamic jumping (1998). Affiliations: England and Wales Cricket Board (ECB), International Cricket Council (ICC), Badminton World Federation, Lawn Tennis Association. His research focuses on optimizing elite sport performance through biomechanical analysis, particularly in cricket and badminton. Key areas include injury prevention (e.g., ACL risks in badminton, lumbar stress injuries in cricket bowlers) and technique optimization. He has pioneered ICC-accredited testing for illegal bowling actions and explored machine learning applications in data collection. His work highlights trends in cricket fast bowling kinematics, racket sports smash mechanics, and gender-specific performance metrics. He actively collaborates with national and international sports organizations to translate research into practical guidelines for athletes and coaches. Awards: None explicitly mentioned in the text. Grants/Advising: No listed advisees, but extensive industry partnerships support his research. Labs/Teams: National Centre for Sport and Exercise Medicine (NCSEM), part of his research infrastructure.

Otmar Hilligesمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• Robotics
• +۴ مورد دیگر

Prof. Dr. Otmar Hilliges is a Full Professor at the Department of Computer Science at ETH Zurich. He leads the AIT lab and serves as the head of the Institute of Intelligent Interactive Systems. His research focuses on spatio-temporal understanding of human movement and interaction, leveraging algorithms and representations from videos, images, and sensor data for applications in Augmented Reality (AR), Virtual Reality (VR), and Human-Robot Interaction. Education: Diplom (MSc) in Computer Science, Technical University of Munich (TUM), Germany PhD in Computer Science, Ludwig Maximilian University of Munich (LMU), Germany (2009) Research Interests: Hilliges' work spans computer vision, robotics, and human-computer interaction. He develops methods for 3D human pose estimation, generative models for realistic avatar creation, and physically plausible simulation of human-object interactions. His research emphasizes practical applications in AR/VR and assistive robotics, aiming to bridge the gap between perception and action. Grants & Contributions: ERC Consolidator Grant (2022-2027): 'AI-Perceive: Robust Human-Centric Computer Vision for Advanced AI-Agents' Google Research Agreement (2020-2025): 'Generative Modelling of Humans' Microsoft Research Grants: Focus on human-centric robotics and interactive technologies Labs & Teams: Leads the AIT Lab at ETH Zurich, which pioneers research in intelligent interactive systems, emphasizing human-centric AI and robotics. The lab collaborates on projects ranging from drone cinematography to haptic feedback systems.

Karin Allor Pfeifferمشاهده پروفایل

استاد

• Physical Activity Measurement
• Childhood Obesity Prevention
• Exercise Physiology
• +۳ مورد دیگر

Karin Allor Pfeiffer is a Professor in the Department of Kinesiology at Michigan State University (MSU) and Director of the Institute for the Study of Youth Sports. She holds additional membership in the Center for Physical Activity and Health. With a Ph.D. from MSU, her research focuses on physical activity measurement methodologies and population health interventions, particularly among children and adolescents. Her work addresses obesity prevention, environmental design impacts on activity levels, and sociocultural factors influencing youth sport participation. Education: Ph.D. in Kinesiology from Michigan State University Her research interests emphasize: - Quantitative methods for physical activity assessment - Schoolyard redesign strategies and their health impacts - Cardiometabolic risk factors in pediatric populations - Longitudinal tracking of physical fitness and health outcomes Recent work explores accelerometer fragmentation metrics, GPS-linked activity tracking, and disparities in sedentary behavior across demographic groups. She has pioneered interdisciplinary approaches integrating spatial analysis, wearable technology, and policy evaluation. Key contributions include developing the Observational System for Recording Physical Activity in Children and advancing consensus methods for accelerometer data interpretation. Her studies frequently highlight socioeconomic and environmental determinants of health behaviors. Dr. Pfeiffer collaborates with public health agencies and urban planners to translate research into actionable policies. Her lab focuses on scalable interventions for underserved communities, leveraging community-engaged methods to address greenspace accessibility and safety concerns.

Richard E. Turnerمشاهده پروفایل

استاد

• Probabilistic Machine Learning
• Environmental Prediction
• Spatio-temporal Modelling
• +۴ مورد دیگر

Richard E. Turner is a Professor of Machine Learning at the University of Cambridge's Department of Engineering and Research Lead for AI for Weather Prediction at the Alan Turing Institute. He serves as Cambridge Lead for the EPSRC Probabilistic AI Hub and previously held roles including Visiting Researcher at Microsoft Research, Co-Director of the AI4ER CDT, and Course Director for the Machine Learning and Machine Intelligence MPhil program. Current research focuses on probabilistic machine learning fundamentals, environmental prediction (weather/climate), and spatio-temporal modeling combining deep learning with Bayesian methods Supervised 26 PhD students (13 graduated) and 7 research assistants/associates Secured over £30M in research funding from EPSRC, Microsoft, Toyota, Google, DeepMind, Amazon, and Improbable Featured in BBC Radio 5 Live's The Naked Scientist, BBC World Service's Click, and Wired Magazine His recent publications demonstrate expertise in diffusion models for PDE simulations, Gaussian Processes for environmental applications, and Bayesian methods for spatio-temporal forecasting. Key trends include climate modeling using ML, neural PDE solvers, and scalable probabilistic inference. Awards : Cambridge Students' Union Teaching Award for Lecturing; supervised Qualcomm Innovation Fellowship winner Collaborations : Microsoft Research (AI4Science), Alan Turing Institute, EPSRC Probabilistic AI Hub Turner leads the Turner Group within Cambridge's Machine Learning Group, focusing on uncertainty-aware ML for scientific applications. Current research assistants work on topics like meta-learning, Bayesian inference, and climate science applications.

• Video Processing
• Image Processing
• Signal Processing
• +۷ مورد دیگر

Takeshi Ikenaga is a Professor at Waseda University’s School of Fundamental Science and Engineering and Graduate School of Information, Production and Systems . He earned his Ph.D. in Information & Computer Science from Waseda University in 2001, following B.E. and M.E. degrees in Electrical Engineering (1988–1990). His career spans roles at NTT LSI Laboratories (1990–2002), Kitakyushu Foundation for Advancement of Industry, Science and Technology (FAIS) (1999–2002), and visiting researcher at the University of Massachusetts (1999–2000). Research Interests : Application-specific SoCs for video/image processing, including compression (H.264/AVC, H.265/HEVC), filters (super-resolution, noise reduction), recognition systems (feature detection, object tracking), and communication (UWB, LDPC). He also works on many-core processor design, ultra-low-delay vision systems, and sports analytics (volleyball, figure skating) with real-time 3D pose estimation and ball tracking. Awards : Recipient of the Furukawa Sansui Award (Waseda University, 1988) IEICE Research Encouragement Award (1992) Multiple Best Paper/Presentation Awards (2006–2022) at conferences including DAC/ISSCC, LSI IP Design, ISOCC, ISPACS, and CVIT APSIPA Distinguished Lecturer Certificate (2015) Waseda University Presidential Teaching Award (2020)

Nico Van de Wegheمشاهده پروفایل

استاد

• GeoAI
• GIScience
• Spatiotemporal Analysis
• +۸ مورد دیگر

Prof. dr. Nico Van de Weghe is a full Professor of GIScience at the University of Ghent (UGent), affiliated with the CartoGIS research unit. His work bridges computer science, social science, and natural science through geospatial information studies, focusing on enabling machines to reason spatially (GeoAI). Since 2004, he has specialized in knowledge-based AI, particularly spatiotemporal reasoning and moving object analysis, with applications in animal behavior, criminology, healthcare, mobility, and sports. Van de Weghe's research emphasizes hybrid GeoAI systems combining knowledge-driven and data-driven approaches. Keywords include GeoAI, GIScience, Spatiotemporal Analysis, Moving Objects, and Data Mining. Recent publications highlight urban road network analysis, hybrid trajectory modeling, BIM semantic enrichment, and cycling safety studies using virtual reality.

• Internet of Things (IoT)
• Wireless Sensor Networks (WSN)
• Active Learning Classrooms
• +۵ مورد دیگر

Maher Elshakankiri is an Assistant Professor, Teaching Stream at the University of Toronto's Faculty of Information. He holds a Ph.D. in Computer Engineering from Ain Shams University (Egypt), followed by a postdoctoral fellowship at the University of Regina. His research focuses on IoT, Wireless Sensor Networks (WSN), and pedagogical integration of technology and gaming. He has supervised over 100 student projects and authored a book on WSNs. Education: Ph.D. in Computer Engineering, Ain Shams University, Egypt M.Eng., B.Eng. in Engineering, Ain Shams University, Egypt Postdoctoral Fellowship, University of Regina, Canada Research Interests: IoT in healthcare, agriculture, and sports Active learning classrooms and technology in education Wireless communication protocols (V2V, UAV, RFID) Leadership & Grants: Director, Bachelor of Information (BI) Program (2024–present) Coordinator, Information Systems and Design (ISD) Concentration (2023) SSHRC Grant: 'Gaming in teaching towards a more inclusive class' (2022–2023) Professional Activities: Member, SCC IoT & Digital Twins Standards Committee Reviewer for journals including Wireless Networks , Telematics and Informatics , and Computational Intelligence Technical Program Committee member at multiple conferences Teaching: Courses include INF1340 (Programming for Data Science), INF1005/1006 (IoT Workshops), and INF452 (Information Design Coding).