جست‌وجوی استاد و پژوهشگر

Antoine Miechمشاهده پروفایل

پژوهشگر

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

Antoine Miech is a Researcher at DeepMind's Vision Group , with prior affiliations at Inria and Ecole Normale Supérieure where he completed his computer vision Ph.D. under Ivan Laptev and Josef Sivic . He has collaborated with researchers from Facebook AI and Google during his academic career. Research Interests span video understanding, weakly-supervised machine learning, and multimodal analysis. His work focuses on: Text-video embedding Self-supervised video representation Action localization Anticipatory video modeling Scalable multimodal learning Scientific Contributions include: HowTo100M - A massive dataset of narrated instructional videos MIL-NCE - A novel loss function for video-text alignment MEE - A model for handling heterogeneous data Context Gating - Learnable pooling architecture Awards & Recognition : Google Ph.D. Fellowship (2018) Technical Leadership : Created the LOUPE TensorFlow toolbox for feature pooling and maintained annotated video dataset catalogs. Organized the Data Science Game competition (2016-2017).

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Christian Eichhorn is an Assistant Professor in the Department of Computer Science at Technical University of Munich, specializing in Human-Computer Interaction, Virtual Reality, and Augmented Reality applications. His research primarily focuses on developing serious games and immersive technologies for healthcare, education, and older adults. He has established a strong collaborative network, particularly with David A. Plecher and Gudrun Klinker, resulting in numerous publications in top HCI and VR venues. Dr. Eichhorn's research interests center around creating accessible and engaging technology applications. His work demonstrates particular expertise in developing serious games for various educational purposes (language learning, history education), healthcare applications (rehabilitation, dementia care), and technologies specifically designed for older adults. His research combines technical innovation in AR/VR systems with practical applications addressing real-world challenges in healthcare and education. Analysis of his recent publications (2022-2025) reveals a consistent focus on practical applications of immersive technologies. His work spans educational tools for programming and language learning, healthcare applications for rehabilitation and clinical training, and specialized technologies for older adults. The research demonstrates a strong interdisciplinary approach, bridging computer science with healthcare, education, and gerontology. His technical contributions include innovations in AR/VR system design, collaborative environments, and novel interaction techniques. Dr. Eichhorn has been actively involved in organizing workshops and contributing to major conferences in the VR/AR field, including IEEE VR and ISMAR. His collaborative approach is evident in his extensive co-authorship network spanning multiple institutions. His laboratory work focuses on developing practical AR/VR applications, with particular emphasis on creating systems that bridge virtual and physical experiences. Current projects include serious games for health behavior change, rehabilitation assessment tools using wearable sensors, and social VR environments for older adults.

Marc Toussaintمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Marc Toussaint is Full Professor leading the Learning & Intelligent Systems Lab at TU Berlin's EECS Faculty. His research integrates machine learning, optimization, and AI reasoning to solve fundamental robotics problems like physical reasoning and human-robot interaction. He holds a physics diploma from University of Cologne and PhD from Ruhr-Universität Bochum. Key research themes include: Task-motion planning integration Reinforcement learning for robotics Physical simulation and control Probabilistic inference methods Recent publications focus on efficient kinodynamic planning, belief space planning under uncertainty, and neural policy learning. He develops open-source robotic tools like the 'robotic python package' used in academic courses worldwide. Toussaint collaborates with Amazon Robotics and MIT CSAIL, and has held positions at Max Planck Institute and University of Stuttgart.

Flora Salimمشاهده پروفایل

استاد

• Machine Learning
• Time-series Analysis
• Spatio-temporal Data Mining
• +۵ مورد دیگر

Flora Salim is a Professor in the School of Computing Technologies at RMIT University. She serves as co-Deputy Director of the RMIT Centre for Information Discovery and Data Analytics (CIDDA) and an Associate Investigator of the ARC Centre of Excellence in Automated Decision Making and Society. Her research focuses on human behavior modeling, machine learning with time-series and spatio-temporal data, and edge AI applications in IoT and wearables. Flora has secured over $10M in research funding from ARC, industry partners, and government bodies. Notable awards include the 2021 PACM IMWUT Distinguished Paper Award, 2019 Humboldt-Bayer Fellowship, and RMIT's 2018 Research Impact Award. She leads the CRUISE research group and has held visiting professorships at the University of Kassel and University of Cambridge. Editorial roles: Associate Editor of PACM on IMWUT, Area Editor of Pervasive and Mobile Computing Steering Committee member of ACM UbiComp Her work bridges ubiquitous computing and machine learning, with applications in urban analytics, mobility, and health monitoring. Recent projects include self-supervised learning for multimodal data and forecasting with heterogeneous time-series. Supervision areas: Deep learning for sensor data, explainable AI, and wearable-based emotion sensing Teaching programs: Master of Artificial Intelligence and Master of Data Science

Sonit Singhمشاهده پروفایل

مدرس

• Artificial Intelligence
• Computer Vision
• Natural Language Processing
• +۷ مورد دیگر

Dr. Sonit Singh is a Lecturer at the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. Prior to this role, he served as a Postdoctoral Research Fellow at the same institution. He holds a PhD from Macquarie University, completed in collaboration with Macquarie. His research focuses on artificial intelligence, computer vision, natural language processing, and their applications in healthcare, particularly in medical imaging and diagnostic systems. Dr. Singh's academic background includes a strong emphasis on biomedical imaging, intelligent robotics, and computing education. His work bridges machine learning advancements with real-world clinical challenges, such as tumor segmentation, radiology report generation, and disease detection through imaging modalities like CT scans and ultrasound. His recent publications highlight innovations in 3D medical image localization, robust tumor segmentation networks, and clinical context-aware radiology report systems. These contributions underscore his expertise in integrating deep learning techniques with healthcare workflows. Dr. Singh collaborates with multidisciplinary teams, including medical professionals, to develop solutions for challenges like placenta segmentation and dietary intake monitoring using AI. While no specific awards or grants are explicitly listed, his extensive publication record reflects sustained academic engagement in high-impact areas. His research often addresses practical clinical needs, such as improving diagnostic accuracy and patient care through advanced computational methods.

Yana Meerzonمشاهده پروفایل

استاد

• Theoretical Performance Studies
• Dramaturgy
• Migration and Displacement
• +۵ مورد دیگر

Yana Meerzon is a Full Professor in the Department of Theatre at the University of Ottawa, affiliated with the Faculty of Arts. Her academic roles include teaching advanced courses such as Performance and Migration , THE 5130 Dramaturgy , and THE 5934 Theatre at the Crossroads of Narratives . She holds additional adjunct roles at institutions like Carleton University’s Cultural Mediations Program and Dalhousie University’s Department of English. Her research focuses on theoretical approaches to performance and migration, including studies on displacement, multilingualism, and identity politics. She has authored four books and co-edited nine collections, with recent works exploring Russian nationalism and migration narratives. Her current SSHRC-funded project examines the intersection of migration and neo-nationalism in European theatre. Meerzon’s academic leadership includes serving as President of the Canadian Association for Theatre Research (2020–2022) and membership in global organizations like IFTR and EASTAP. Her educational background includes a Ph.D. from the University of Toronto and advanced degrees from the Russian Academy of Theatre Arts (GITIS). Her scholarly contributions span over 86 publications, including analyses of Wajdi Mouawad’s work, Michael Chekhov’s pedagogy, and digital performance in crises. She actively engages in public discourse through interviews and media links, emphasizing the ethical and cultural dimensions of migrant theatre practices in Canada and beyond.

• Generalization in deep learning
• Sparse estimation
• Portfolio optimization using reinforcement learning
• +۶ مورد دیگر

LIU Peng is an Assistant Professor of Quantitative Finance (Practice) at the Lee Kong Chian School of Business, Singapore Management University. He holds a Ph.D. in Statistics and Data Science (Part-time) from the National University of Singapore (2021), an M.S. in Business Analytics (2015), and a B.Eng. in Electronic Science and Technology (2012). Prior to his academic role, he worked as a Manager at Standard Chartered Bank (2019–2022) and in analytics roles at Marina Bay Sands and IBM. Education: Ph.D. (NUS), M.S. (NUS), B.Eng. (Beijing Technology and Business University) His research focuses on generalization in deep learning, sparse estimation, portfolio optimization via reinforcement learning, financial text mining, risk management, and Bayesian optimization. His work bridges theoretical advancements with practical applications in quantitative finance and data science. Notable contributions include studies on explainable neural networks, Bayesian optimization frameworks for portfolio management, and risk analytics integrating human decision-making. His recent articles emphasize model risk assessment, cost-aware optimization, and financial data analysis. Awards: Best Ph.D. Graduate Research Award (NUS, 2020), Google TensorFlow Developer Certificate (2020–2023) He teaches courses in quantitative finance, machine learning, and risk management, and has secured grants including the Research Capability Building Fund (2023–2025). His research aligns with strategic priorities in digital transformation and financial innovation.

• Quality Inspection and Control
• Predictive Modeling
• Smart Manufacturing Systems
• +۳ مورد دیگر

Dr. Yu (Chelsea) Jin is an Assistant Professor in the Department of Industrial Engineering at the University at Buffalo, specializing in quality inspection, predictive modeling, and data analytics for advanced manufacturing systems. She holds a PhD in Industrial Engineering from the University of Arkansas, an ME from the University of Michigan, and dual BS degrees in Network Engineering and Finance from Jinan University. Her research focuses on integrating machine learning and physics-based models to optimize manufacturing processes, such as additive manufacturing, PCB assembly, and pharmaceutical distribution systems. She has developed frameworks like ReflowNet for reflow oven optimization and physics-informed neural networks for thermal profile prediction. Her work emphasizes both theoretical advancements and practical applications in smart manufacturing and healthcare logistics. Dr. Jin's recent publications highlight contributions to generative AI for knowledge retrieval, AGV system optimization, and multi-source transfer learning for pandemic modeling. She actively collaborates with industry partners to bridge academic research and real-world manufacturing challenges.

• Transportation Safety
• Automated Vehicles
• Human Factors in Transportation
• +۳ مورد دیگر

Rakotonirainy Andry is a Professor at Queensland University of Technology (QUT), affiliated with the Centre for Accident Research & Road Safety - Queensland (CARRS-Q). His research focuses on transportation safety, automated vehicles, human factors, and intelligent transportation systems (ITS). He leads interdisciplinary projects exploring driver behavior, connected vehicle technologies, and the societal impacts of automation. Key areas include accident prevention, human-vehicle interaction, and equity in transport systems. His work integrates machine learning, simulation studies, and behavioral analysis to address challenges in road safety. Notable contributions include studies on driver stress detection, automated vehicle acceptance, and the Australian Naturalistic Driving Study (ANDS). He collaborates with institutions globally, advancing innovations like connected vehicle pilots and multimodal AI for traffic safety. Research interests span automated driving systems, vulnerable road user protection, and policy implications of emerging technologies. His findings contribute to safer transportation policies and technologies, emphasizing both technical and human-centric perspectives.

Katarína Labudováمشاهده پروفایل

دانشیار

• Margaret Atwood Studies
• Canadian Literature
• Speculative Fiction
• +۷ مورد دیگر

Katarína Labudová serves as an Associate Professor at the Department of English Language and Literature within the Faculty of Arts and Letters at Catholic University in Ružomberok, Slovakia. She holds the additional role of Erasmus+ Department Coordinator, facilitating international academic exchanges. Dr. Labudová earned her PhD in Comparative Literatures in 2011 and maintains regular office hours for student consultations on Tuesdays from 10:30-12:00 by appointment. Her research interests center on Margaret Atwood's literary works, particularly examining food motifs within speculative fiction across Atwood's major dystopian narratives. Labudová has extended her scholarly focus to include Angela Carter's writings, fairy tale adaptations, biblical myth reconstructions, and the intersection of narrative theory with cultural studies. Her methodological approach combines feminist criticism, comparative literature analysis, and cultural anthropology perspectives to explore how literature reflects and critiques social power structures. Labudová's publication record reveals a consistent trajectory of scholarly engagement with Atwood's works from 2010-2022, culminating in her 2022 monograph Food in Margaret Atwood's Speculative Fiction and textbook Studying Margaret Atwood: Shifting the Boundaries of Genres . Her articles demonstrate increasing specialization in food symbolism within dystopian literature, with particular attention to how dietary restrictions function as mechanisms of patriarchal control. Recent work has expanded to analyze Slovak and Romani folk narrative traditions alongside contemporary literary adaptations. As an educator, Dr. Labudová teaches courses on British and Canadian literature, bringing her research expertise directly into the classroom. Her academic work bridges literary analysis with cultural critique, examining how narrative forms both reflect and challenge societal norms regarding gender, power, and environmental sustainability. Her contributions to Margaret Atwood scholarship have established her as a significant voice in contemporary Canadian literary studies within Central European academia.

Stavros Shiaelesمشاهده پروفایل

دانشیار

• Cyber Security
• Malware Analysis
• Anomaly Detection
• +۱۳ مورد دیگر

Dr. Stavros Shiaeles is an Associate Professor in Cybersecurity at the Faculty of Technology , University of Portsmouth, and Co-Director of the Portsmouth AI and Data Science Centre (PAIDS) . With over 130 publications and 3000+ citations, he specializes in cybersecurity, applied AI, and threat mitigation frameworks. Academic Qualifications : PhD in Electrical and Computer Engineering (Democritus University of Thrace, 2013), MEng in Electrical and Computer Engineering (Democritus University of Thrace, 2007), MBA in Human Resource Management (University of Plymouth, 2016), and PG Cert in Academic Practice (University of Plymouth, 2017). Research Interests span cybersecurity, malware detection, blockchain, 6G networks, AI/ML applications, digital forensics, and post-quantum cryptography. His work addresses threats in IoT, financial systems, and critical infrastructure while exploring SDG4 (Quality Education) through cybersecurity training. Recent publications emphasize AI-driven anomaly detection (e.g., ransomware behavior analysis, 6G traffic monitoring), deepfake forensics, synthetic image attribution, and hybrid blockchain/AI security architectures. He also curates datasets for malware analysis and synthetic media classification. Scientific Awards : IEEE SMC TCHS Outstanding Service Award (2021). Grant Funding : Over €18M secured in EU Horizon 2020 grants, including €8M as Principal Investigator for the ongoing XTRUST-6G project. Active in KTPs, consulting, and research commercialization opportunities.

Kotaro Haraمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Human-Machine Collaborative Systems
• Accessibility Design
• +۸ مورد دیگر

Kotaro Hara is a Full-time Faculty Assistant Professor of Computer Science at Singapore Management University's School of Computing and Information Systems. His research focuses on Human-Computer Interaction, Human-Machine Collaborative Systems, and Accessibility Design, with applications in urban mobility, digital transformation, and aging population support. He holds a PhD from the University of Maryland (2016). Research Areas: Accessibility, Crowdsourcing, Future of Work, Urban Sustainability Recent publications explore Augmented Reality for low-vision runners, conversational agents for dementia care, and novel tactile data visualization methods. His work integrates natural language processing, multimodal interfaces, and AI ethics frameworks across diverse domains. Academic collaborations include advising PhD candidate Sheshadri Smitha. Contact: kotarohara@smu.edu.sg

Wolfgang Stammerمشاهده پروفایل

پژوهشگر

• Explainable AI
• Neuro-Symbolic Architectures
• Concept Learning
• +۳ مورد دیگر

Wolfgang Stammer is a PostDoc researcher in the Machine Learning Group at TU Darmstadt's Computer Science Department. His work focuses on making AI models more interpretable and interactive, particularly in explainable AI (XAI), neuro-symbolic architectures, and systematic compositionality challenges in neural networks. He completed his Ph.D. in Machine Learning at TU Darmstadt (2019–2025), an M.Sc. in Computer Science at Goethe University Frankfurt (2016–2018), and a B.Sc. in Cognitive Science at the University of Osnabrück (2011–2015). Research Interests : Stammer's research bridges gaps between human understanding and AI capabilities. Key areas include: Explainable AI (XAI) and interactive machine learning (XIL) Neuro-symbolic integration for logical reasoning and visual concepts Mitigating shortcut learning and confounding factors in datasets Concept discovery and program synthesis for interpretable models Publications : His work spans foundational contributions to AI benchmarks (e.g., V-LoL, SLR-Bench) and frameworks (Neural Concept Binder, Revision Transformers). Recent studies highlight AI's limitations in systematic generalization and propose solutions for aligning reinforcement learning agents with human values. Grants & Labs : He contributes to the Machine Learning Lab at TU Darmstadt and co-organized workshops like the Interactive Machine Learning Workshop @ AAAI 2022. His research bridges theoretical advances with practical applications in healthcare and ethical AI systems.

Nader El-Bizriمشاهده پروفایل

استاد

• Arabic Sciences and Philosophy
• Architectural Theory
• Phenomenology
• +۳ مورد دیگر

Nader El-Bizri is a tenured full Professor of Civilization Studies and Philosophy at the American University of Beirut (AUB), where he previously served as Director of the General Education core program and Associate Dean of the Faculty of Arts and Sciences. He is also an Affiliated Scholar at the University of Cambridge's Department of History and Philosophy of Science and an Associate of King's College. His academic career includes roles at universities such as Harvard, Cambridge, and the London Consortium. El-Bizri holds a PhD in Philosophy (1999) from the New School for Social Research and an MArch-II in Architecture (1994) from Harvard University. His expertise spans Arabic Sciences and Philosophy, Architectural Theory, and Phenomenology, with a focus on historical and cross-cultural intellectual traditions. His research integrates philosophy, science, and architecture, exploring topics like Ibn al-Haytham's optics, Avicenna's metaphysics, and Heideggerian phenomenology. He has edited major works such as the Epistles of the Brethren of Purity series for Oxford University Press and serves on editorial boards globally. His awards include the Kuwait Foundation Prize and a Mellon Fellowship. El-Bizri has advised on cultural projects including the Science Museum, Aga Khan Trust for Culture, and Solomon Guggenheim Museum. His architectural practice spans London, New York, and Beirut, and he has appeared on BBC and France Culture programs. Current research emphasizes the interplay between pre-modern Islamic sciences and modern philosophical frameworks.

Xin Wangمشاهده پروفایل

استادیار

• Natural Language Processing
• Computer Vision
• Machine Learning
• +۶ مورد دیگر

Xin (Eric) Wang is an Assistant Professor in the Computer Science Department at the University of California, Santa Barbara (UCSB) , and serves as Head of Research at Simular AI. His research focuses on Multimodal and Embodied AI Agents , blending methodologies from machine learning, computer vision, natural language processing, and robotics. Education: Ph.D. in Computer Science, UC Santa Barbara B.Eng. in Computer Science, Zhejiang University Research Interests: Natural Language Processing Computer Vision Multimodal AI Embodied AI Trustworthy AI Systems His work emphasizes agents that collaborate with humans in complex environments, addressing ethical design and generalizable reasoning. Awards: Best Paper Awards at CVPR 2019 and ICLR 2025 Google Faculty Research Award, 2022 eBay & Cisco Faculty Awards (2022–2024) Amazon Alexa Prize Awards (multiple years) Advising & Grants: Supervised students Dr. Xuehai He and Dr. Jing Gu. Secured grants from Microsoft, Adobe, eBay, and Snap. Organized workshops on vision-language research and embodied AI. Labs/Teams: Leads the ERIC Lab at UCSB, focusing on multimodal agent systems and ethical AI design.