جستجوی استاد راهنمای دانشگاهی

Glaucio H. Paulinoمشاهده پروفایل

استاد

• Topology Optimization
• Computational Mechanics
• Fracture Mechanics
• +۳ مورد دیگر

Glaucio H. Paulino holds the Margareta Engman Augustine Professorship in Civil and Environmental Engineering at Princeton University, where he also serves as a Professor at the Princeton Institute for the Science and Technology of Materials (PRISM). His work bridges computational mechanics, topology optimization, and materials science. Paulino leads a research group focused on advancing structural design methodologies, fracture mechanics, and functionally graded materials. His team has pioneered polygonal finite elements and multiresolution topology optimization techniques, addressing challenges in mesh bias and computational efficiency. He has published over 240 peer-reviewed articles and mentored 19 PhD and 11 MS students. Notable contributions include the PPR cohesive model for fracture analysis and adaptive mesh refinement for dynamic simulations. Paulino's research extends to practical applications such as high-rise building design and sustainable construction materials. Awards include election to the European Academy of Sciences and Arts and ASME’s Melville Medal. Current projects involve functionally graded cement-based materials, extrusion processing, and digital image correlation for material characterization. His lab collaborates with industry partners like Skidmore, Owings & Merrill LLP to translate topology optimization into real-world engineering solutions. Paulino’s interdisciplinary approach integrates computational modeling with experimental validation, fostering innovations in civil infrastructure resilience.

Mercè Olivaمشاهده پروفایل

دانشیار

• Media Studies
• Popular Culture
• Television Studies
• +۴ مورد دیگر

Mercè Oliva is an Associate Professor at the Department of Communication, Pompeu Fabra University (UPF), Barcelona. She serves as Director of the B.A. Programme in Audiovisual Communication and Coordinator of the MEDIUM Research Group. Her academic background includes a PhD in Social Communication (2010) and a Bachelor's in Audiovisual Communication (2002) from UPF. Research Focus: Television and Reality TV Celebrity and Media Culture Neoliberalism and Political Communication Video Games as Cultural Artifacts Her recent publications analyze: Visual motifs in political coverage (handshakes, hugs, kisses) Citizens' responses to neoliberal resilience narratives Celebrity tax evasion cases (e.g., Cristiano Ronaldo) Video game cover art as neoliberal propaganda Working-class stereotypes in Spanish media ('chonis', 'canis') Key collaborations include co-PI roles in projects like 'Heroes of the Crisis' (2015-2019) and 'Redistributive Imaginaries' (2022-2025), funded by Spain's Ministry of Economy and AEI/NextGenerationEU.

Davide Scaramuzzaمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Autonomous Navigation
• +۴ مورد دیگر

Davide Scaramuzza is a Professor and Director of the Robotics and Perception Group at the University of Zurich. He holds a Ph.D. from ETH Zurich and has conducted postdoctoral research at the University of Pennsylvania and Stanford. His research focuses on autonomous drone navigation using visual and event-based sensors, leading to breakthroughs like AI drones outperforming human pilots in racing (Nature 2023). He pioneered algorithms for Mars helicopter navigation and developed the PX4 autopilot system. Key awards include the Kiyo-Tomiyasu IEEE Technical Field Award (2024), ERC Consolidator Grant (2019), and multiple best paper awards. His entrepreneurial ventures include co-founding Zurich-Eye (later Meta Zurich) and SUIND for agricultural drones. He co-authored the textbook Introduction to Autonomous Mobile Robots , widely used in academia. Research spans event camera algorithms, visual-inertial SLAM, and reinforcement learning for agile flight. His lab's work is featured in IEEE Spectrum, The Guardian, and Forbes. He advises UN initiatives on AI for disaster response and nuclear safety. Current projects include Graph-Generating State Space Models (CVPR 2024) and event-based vision for automotive systems (Nature 2024).

Zhi Chenمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Dr. Zhi Chen is a Lecturer in Computing at the School of Mathematics, Physics and Computing, University of Southern Queensland, specializing in Artificial Intelligence and Machine Learning with applications spanning digital agriculture and healthcare systems. Education: Master of Information Technology (MIT), University of Queensland, 2018 PhD, University of Queensland, 2023 Research Focus: His work centers on zero-shot learning, domain adaptation, and multimodal systems, addressing core challenges in computer vision and deep learning. Current projects integrate AI with agricultural risk modeling and medical diagnostics, emphasizing real-world deployment of robust algorithms under data-scarce conditions. Publication Trends: Recent output (2022-2025) shows concentrated expertise in source-free domain adaptation and generalized zero-shot learning, with significant contributions to plant disease recognition (via mobile multimodal systems) and diabetes subgroup analysis. His work consistently appears in premier venues including AAAI, CVPR, and ACM MM, demonstrating methodological innovation applied to critical domains like climate-resilient agriculture and precision medicine. Supervision: Currently serves as Associate Supervisor for a doctoral candidate developing parametric insurance models for oyster farms to mitigate climate-related risks from king tides and extreme weather events. Awards: No scientific awards were documented in the provided materials.

• Computer Vision
• Image Analysis
• Machine Learning
• +۵ مورد دیگر

Serge Belongie is a Professor at the Department of Computer Science (DIKU) at the University of Copenhagen, where he holds dual affiliations with the Pioneer AI research section and the Image Analysis, Computational Modelling, and Geometry section. His academic position places him at the forefront of interdisciplinary research connecting computer vision with language models, geospatial analysis, and cultural understanding. Professor Belongie's research program encompasses several critical domains in modern artificial intelligence: Advanced computer vision and image analysis techniques Vision-language model integration and multimodal systems 3D point cloud processing and semantic segmentation Geospatial representation learning for environmental applications Fine-grained object recognition and detection Cultural context understanding in AI systems His recent publication record reveals a sophisticated trajectory toward developing precise control mechanisms for vision-language models, with applications spanning forensic analysis, cultural heritage preservation, and social media understanding. The research demonstrates increasing sophistication in handling cultural context and enabling fine-grained manipulation of visual content through natural language interfaces. Professor Belongie maintains an active research group producing significant scholarly output, with over 280 research publications documented in his academic profile. His work is supported by research funding that enables cutting-edge exploration in multimodal AI systems with practical societal impact. He plays a key role in the Pioneer AI center at the University of Copenhagen, which focuses on advancing artificial intelligence through interdisciplinary collaboration and innovative research approaches that bridge theoretical computer science with real-world applications.

Yun-Nung Chenمشاهده پروفایل

استاد

• Natural Language Processing (NLP)
• Dialogue Systems
• Machine Learning
• +۳ مورد دیگر

Professor Yun-Nung Chen works at the Department of Computer Science and Information Engineering , National Taiwan University , focusing on Natural Language Processing and Dialogue Systems . With a Ph.D. from Carnegie Mellon University , their research bridges Machine Learning and Language Understanding in conversational AI. Education Ph.D. in Language Technologies, Carnegie Mellon University (2015) M.S. in Computer Science, National Taiwan University (2011) B.S. in Computer Science, National Taiwan University (2009) Research Trends Recent work emphasizes Retrieval-Augmented Generation , Knowledge Editing in LLMs , and Temporal Modeling for dialogue systems. Key themes include cross-modal understanding , semantics-driven dialogue , and robust language modeling across domains. Scientific Recognition Best Student Paper, IEEE ASRU 2013 Best Student Paper, IEEE SLT 2010 Distinguished Master Thesis, ACLCLP 2011 Best Paper Finalist, ISCA INTERSPEECH 2012 Current projects involve StreamBench for continuous agent improvement and Taiwan LLM for culturally aligned language models.

Ghazal Bargshadyمشاهده پروفایل

مدرس

• Affective Computing
• Artificial Intelligence
• Computer Vision
• +۷ مورد دیگر

Dr. Ghazal Bargshady is a Lecturer at the University of Canberra , with expertise in Affective Computing , Artificial Intelligence , and Healthcare Technology . Her roles include teaching units such as Computer Vision, Data Analytics, and Soft Computing, as well as supervising PhD and Master by Research students in AI-driven projects for healthcare and road safety. Education: She earned her PhD in Artificial Intelligence and Computer Vision from the University of Southern Queensland in 2020. Research Interests: Dr. Bargshady specializes in Computer Vision Deep Learning Biosignal Processing Facial Expression Analysis Human Factors in AI Wearable Sensors Multimodal Data Fusion Brain–Computer Interfaces Her work addresses real-world challenges in pain assessment, depression recognition, and driver safety using cutting-edge AI models. Article Trends: Her recent publications focus on Transformer architectures , fNIRS signal analysis , multimodal pain detection , and depression severity estimation via facial video data. These studies highlight her contributions to AI in healthcare , transportation safety , and biomedical signal processing . Teaching Activities: Dr. Bargshady has lectured units including Programming for Data Science , Computer Vision , and Soft Computing , emphasizing practical AI applications.

Ming-Jun Laiمشاهده پروفایل

استاد

• Multivariate Splines
• Sparse Solutions of Underdetermined Linear Systems
• Wavelet Theory
• +۸ مورد دیگر

Ming-Jun Lai is a Professor in the Department of Mathematics at the University of Georgia. His career spans decades, focusing on multivariate splines, sparse solutions of linear systems, wavelet theory, and their applications in numerical analysis and machine learning. Education: Lai received his Ph.D. from Texas A&M University and completed postdoctoral training at the University of Utah. He has supervised 22 Ph.D. students and two current Ph.D. candidates. Multivariate Splines: Applied to scattered data fitting, numerical PDE solutions, image enhancement, and surface design. Sparse Solutions: Used in compressed sensing, low-rank matrix recovery, and graph clustering. Wavelet Theory: Construction of biorthogonal and tight wavelet frames for image edge detection. Optimal Transport: Numerical solutions for Monge-Ampère equations. Research Trends (2025–2023): Recent work includes interpolating space curves with geometric continuity, spherical spline smoothing, and applications in machine learning, particularly graph clustering and optimal control in biological systems. Scientific Awards: UGA Research Medal (2002) McCay Award (2013) Advisees: Lai has mentored 24 Ph.D. students, including Zhaiming Shen (2024), Jinsil Lee (2023), and current students Valerio Palamra and Ye Tian. Laboratory & Collaborations: He collaborates with institutions like Georgia Tech, UCLA, and Zhejiang University, applying splines in aerospace engineering and biomedical imaging.

Shahram Shiraniمشاهده پروفایل

استاد

• Multimedia Communications
• Image/Video Processing
• Medical Image Processing
• +۵ مورد دیگر

Dr. Shahram Shirani is a Professor and holds the L.R. Wilson/Bell Canada Chair in Data Communications in the Department of Electrical & Computer Engineering at McMaster University. He also serves as Acting Chair of the department. His research focuses on multimedia communications, image/video processing, medical imaging, and hardware architectures. He teaches courses like Image Processing (COMPENG 4TN4) and 3D Image Processing and Computer Vision (ECE 736). Shirani earned his B.Sc. from Isfahan University of Technology (1989), M.Sc. from Amirkabir University of Technology (1994), and Ph.D. from the University of British Columbia (2000). His achievements include the Faculty of Engineering Leadership Fellowship (2014–15) and leadership roles in editorial boards for IEEE Transactions on Multimedia and Circuits and Systems for Video Technology. Research interests include video quality assessment, biomedical signal processing, and edge computing for traffic monitoring. His lab develops algorithms for multimedia representation, compression, and hardware implementation. Recent work includes AI-driven medical sound datasets, real-time noise removal in MRI, and efficient CNN pruning techniques. He advises over 15 graduate students and collaborates on projects like the HLS-CMDS dataset and cardiac segmentation reviews. His lab’s contributions span biomedical engineering, autonomous systems, and smart sensor technologies.

Yuan-Fang Liمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Natural Language Processing
• Multimodality
• +۵ مورد دیگر

Yuan-Fang Li is an Associate Professor in the Department of Data Science & AI at Monash University's Faculty of Information Technology. He also serves as Associate Dean International. His research focuses on knowledge graphs, natural language processing, multimodality, and graph representation learning. He holds a PhD from National University of Singapore (2006) and a Bachelor of Computing (Honours) from the same institution (2002). Affiliations: Monash University (since 201?), National University of Singapore (PhD 2002-2006) Key Projects: Leading research on neuro-symbolic systems (HARNESS project), large-scale multimodal knowledge management, and maritime knowledge graphs Teaching: Taught courses including FIT4002, FIT4004, and supervised over 20 PhD students Research interests include complex question answering over knowledge graphs, knowledge extraction from text/images, and structural/temporal graph learning. He has published 152+ works with notable contributions to scene graph generation, event extraction, and LLM-based reasoning. Key awards include the 2020 Best Student Paper Award and 2017 Kurzweil Prize. Grants: ARC Discovery Projects, industry collaborations (e.g., Outotec Oy) Labs/Teams: Active in Monash's Data Science & AI research groups, leading neuro-symbolic AI initiatives

Ed Chienمشاهده پروفایل

استادیار

• Computer Science
• Graphics
• Computational Engineering
• +۳ مورد دیگر

Ed Chien is an Assistant Professor at Boston University's Department of Computer Science within the College of Arts & Sciences. He specializes in applying differential geometry and topology to graphics, computational engineering, and machine learning. Previously, he was a postdoctoral researcher at MIT's CSAIL and Bar-Ilan University. His work focuses on mathematically rigorous solutions to problems in geometric data processing and optimal transport. Education PhD in Mathematics, Rutgers University (2015) A.B. in Mathematics & Physics, Dartmouth College (2009) Research Highlights Dr. Chien's research includes fundamental studies on hexahedral mesh topology for Finite Element Modeling, optimal transport applications in machine learning, and singularity-free geometric algorithms. His work bridges theoretical mathematics with computational tools for engineering and graphics. Publications span top venues like NeurIPS, Eurographics, and SIGGRAPH, reflecting contributions to geometry processing and machine learning intersections. Program committee roles include Eurographics SGP (2019) and AAAI (2020). Awards & Recognition No specific awards listed, but notable service includes program committee memberships and peer-reviewed contributions to leading conferences. Grants & Advising Active in mentoring through academic positions but no explicit grant details provided. Research focuses on advancing geometric algorithms and optimal transport methodologies.

Jia-Bin Huangمشاهده پروفایل

دانشیار

• Computer Vision
• Computer Graphics
• Machine Learning
• +۴ مورد دیگر

Jia-Bin Huang is an Associate Professor in the Department of Computer Science at University of Maryland, College Park , with a secondary appointment at the University of Maryland Institute for Advanced Computer Studies . His work bridges computer vision , computer graphics , and machine learning . His research focuses on 3D scene reconstruction , neural radiance fields , generative models , and multimodal foundation models . He has made significant contributions to video super-resolution , text-driven 3D modeling , and inverse rendering techniques. 15 recent publications (2024-2025) at top venues: CVPR , NeurIPS , SIGGRAPH Asia , 3DV , and ECCV Pioneering work in Urban Scene Inverse Rendering , Generative Video Editing , and 3D Human Digitization He has received multiple awards including the 3M Non-Tenured Faculty Award , ETRA Best Paper , and NSF Grants . His lab trains 12 PhD students and has graduated 18 Masters/PhD students now at institutions like Stanford , Meta , and Google .

Lianne Lefsrudمشاهده پروفایل

دانشیار

• Risk Management
• Sustainability
• Organizational Theory
• +۵ مورد دیگر

Lianne Lefsrud serves as Associate Professor and Risk, Innovation, and Sustainability Chair (RISC) in the Department of Chemical and Materials Engineering at the University of Alberta's Faculty of Engineering. Her interdisciplinary research bridges engineering, social sciences, and policy to transform risk management practices across energy, mining, construction, and railroading industries, directly influencing regulations, building codes, and industry operations for sustainable development. Her academic credentials include: BSc in Civil Engineering (Cooperative Program), University of Alberta (1994) MSc in Interdisciplinary Civil & Environmental Engineering and Sociology, University of Alberta (1996) PhD in Strategic Management and Organization, Alberta School of Business (2014) Dr. Lefsrud's research centers on risk management frameworks for sustainability challenges. She examines hazard identification, social license to operate, and technology adoption drivers in high-hazard industries, with emphasis on prospective risk assessment (e.g., hydrogen infrastructure design) and retrospective analysis (e.g., microplastic pollution impacts). Her work integrates circular economy principles into energy systems while addressing unintended consequences across UN Sustainable Development Goals. Recent publications (2024-2025) demonstrate heavy focus on machine learning applications for rail and construction safety, hydrogen infrastructure risk analysis, and science denial mitigation. Key patterns show cross-industry adaptation of AI for incident prediction, regulatory gap analysis for emerging energy systems, and socio-technical approaches to reconcile sustainability goals with operational realities. Scientific recognition includes: Erb Post-Doctoral Fellowship (University of Michigan) Dow Sustainability Research Fellowship (Ross School of Business) Dr. Lefsrud mentors graduate students through industry-integrated projects like her Sustainable Design course where teams generated patents and city solutions. Her research secures Alberta Innovates funding with 1:4 industrial-to-federal matching, collaborating with Suncor, Transport Canada, and Canadian Standards Association. Grants target practical implementations including railcar inspection systems and hydrogen safety protocols. She co-founded Insight Risk Systems and leads the Lefsrud Lab, prioritizing inclusive teams with under-represented groups (women, Indigenous, LGBTQ2S+, neurodiverse) to tackle 'wicked problems' in sustainability. The lab leverages interdisciplinary partnerships across engineering, computer science, psychology, and environmental sociology for real-world risk management solutions.

• Clinical Reasoning
• Diagnosis
• Medical Education
• +۶ مورد دیگر

Rabih Geha, MD is an Associate Professor of Medicine at the University of California, San Francisco (UCSF) School of Medicine. Based at the San Francisco VA Medical Center, he serves as the Director of Education for the Emergency Department, overseeing the education of Psychiatry, Emergency Medicine, and Internal Medicine residents. Clinically, Dr. Geha splits his time between the emergency room and the inpatient teaching wards, bringing practical experience to his educational roles. Dr. Geha completed his medical education at Alpert Medical School of Brown University in Providence, RI (MD, 2014), followed by residency training at UCSF (2017) and a chief residency at UCSF (2018). His educational background has provided a strong foundation for his current roles in medical education and clinical practice. Dr. Geha's research and professional interests center on clinical reasoning, diagnosis, medical education, and diagnostic schema development. He is particularly focused on innovative approaches to teaching diagnostic reasoning and improving medical decision-making processes. His work addresses critical challenges in medical education, including developing tolerance for ambiguity among medical students, addressing cognitive biases in clinical reasoning, and creating effective frameworks for diagnostic problem-solving. Dr. Geha is passionate about anti-racism initiatives in medicine and promoting women in medicine through his educational platforms. Analysis of Dr. Geha's publication record reveals a consistent focus on clinical reasoning education and diagnostic challenges. His work spans various medical specialties including internal medicine, hospital medicine, dermatology, endocrinology, and infectious diseases, demonstrating his broad clinical expertise. A notable trend in his research is the development of innovative educational tools and frameworks for clinical reasoning, including the exploration of natural language processing applications for case library development. His publications frequently address cognitive aspects of medical decision-making, diagnostic errors, and strategies for improving diagnostic accuracy. Dr. Geha is the co-founder of Clinical Problem Solvers, a multimodal medical education venture run by a global and diverse team. This initiative hosts a weekly podcast covering topics such as diagnostic reasoning, anti-racism, and women in medicine, along with virtual morning reports and a clinical reasoning training academy. Through this platform, he has significantly impacted medical education beyond the UCSF campus, reaching a worldwide audience of medical learners and educators.

• Cinematography
• Film Art
• Documentary Filmmaking
• +۳ مورد دیگر

Ryszard Lenczewski is a distinguished Professor of Film Art at The Leon Schiller National Higher School of Film, Television and Theatre in Łódź, where he has served as a lecturer at the Cinematography Department since his graduation in 1974. He held the position of Vice-Dean from 2008 to 2014 and has been instrumental in shaping generations of Polish cinematographers. As a member of prestigious film organizations including the Society of Cinematographers (PSC), the European Film Academy (EFA), the British Academy of Film and Television Arts (BAFTA), and the American Academy of Motion Picture Arts and Sciences (AMPAS), Lenczewski has established himself as a significant figure in international cinema. Lenczewski's research and creative interests span cinematography, film art, documentary filmmaking, visual storytelling, and camera techniques. His extensive filmography demonstrates mastery across feature films, documentaries, and television productions, with notable works including the Oscar-winning film "Ida" (2013) where he served as cinematographer. His approach combines technical precision with profound artistic expression, emphasizing visual narrative and emotional depth through innovative camera work and lighting techniques. Throughout his career, Lenczewski has supervised numerous student films, guiding emerging talent in cinematography techniques and visual storytelling. His pedagogical approach emphasizes hands-on experience and creative experimentation, reflected in the diverse range of student projects he has mentored from 2013 through 2025. 2013 Decoration Silver Medal for Merit to Culture - Gloria Artis 2015 Golden Camera 300 Lifetime Achievement Award at the Manaki Brothers Film Festival 2018 Gold Medal "Gloria Artis - For Merit to Culture" 2019 "Golden Glan" award from Charlie cinema in Łódź 2020 Society of Cinematographers (PSC) Lifetime Achievement Award 2022 Polish Filmmakers Association Award 2024 Silver Cross of Merit Lenczewski's creative output reveals a consistent exploration of visual narrative techniques, with recent student projects focusing on experimental cinematography, sensory film experiences, and innovative approaches to time, space, and emotion in visual storytelling. His work demonstrates mastery across documentary, feature film, and educational contexts, establishing him as a versatile and influential figure in contemporary cinematography.