جست‌وجوی استاد و پژوهشگر

Laure Soulierمشاهده پروفایل

مدرس

• Design of language models for Information Retrieval (IR) and Natural Language Processing (NLP)
• Data-to-Text Generation
• Search-Oriented Conversational Systems
• +۳ مورد دیگر

Laure Soulier is a HDR (Habilitation à Diriger des Recherches) Lecturer at Sorbonne University within the MLIA team at the ISIR (Institute for Intelligent Systems and Robotics) laboratory. Her research focuses on the design of language models for Information Retrieval (IR) and Natural Language Processing (NLP) applications, including data-to-text generation , search-oriented conversational systems , language models for robotics , and continual learning with domain adaptation . Recent publications highlight her work on cross-encoders, co-speech gesture generation, and latent space metrics. She supervises an ANR-funded postdoctoral researcher position (SCAI/BnF program) and collaborates on projects involving multimodal techniques, user interaction analysis, and document vectorization. Her scientific contributions include best paper awards at CORIA 2021, SCAI@EMNLP 2019, CORIA 2015, and AIRS 2013. Laure Soulier’s work spans collaborative information retrieval models, entity ranking in heterogeneous networks, and neural approaches for knowledge-based IR. She has contributed to evaluation frameworks for LLMs in IR and co-speech gesture generation, with applications in e-commerce search, medical information retrieval, and social media-based collaboration. Her research integrates user roles, document representations, and reinforcement learning techniques.

• Natural Language Processing
• Computational Linguistics
• Artificial Intelligence
• +۷ مورد دیگر

Jing Jiang is a prominent researcher at Singapore Management University, specializing in Natural Language Processing (NLP), Computational Linguistics, and Artificial Intelligence. His work spans diverse areas including Vision-Language Models, Machine Translation, Knowledge Graph Reasoning, Sentiment Analysis, and Social Media Discourse Modeling. Key contributions include frameworks for consistent client simulation in mental health counseling and counterfactual contrastive prefix-tuning for many-class classification. He has pioneered methods in zero-shot VQA with interpretable reasoning graphs , cross-lingual understanding with universal syntax , and modularized zero-shot architectures . His research often combines theoretical insights with practical implementations, as seen in works on stereotypical bias in vision-language models (VLStereoSet), tensorized self-attention for dependency modeling, and collaborative relation-augmented attention for knowledge graph completion. Jing Jiang's collaborations span global experts in NLP and AI, with co-authors from institutions like SMU, Waseda University, and Microsoft Research.

Andreas Bullingمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer Vision
• Ubiquitous Computing
• +۴ مورد دیگر

Prof. Dr. Andreas Bulling is Full Professor of Computer Science at the University of Stuttgart , leading the Collaborative Artificial Intelligence research group at the Institute for Visualization and Interactive Systems. He is also a founding director of the Stuttgart ELLIS Unit and serves on multiple prestigious boards including IEEE Transactions on Visualization and Computer Graphics . Education: MSc in Computer Science (KIT), PhD in Information Technology (ETH Zurich) Research Interests: Human-Computer Interaction, Eye Tracking, Wearable Computing, Computer Vision, and Privacy-Preserving AI Scientific Leadership: UbiComp Steering Committee member, ACM ETRA General Chair (2020), and extensive editorial/guest editor roles Key Awards: ERC Starting Grant (2018), Henriette Herz Scout (2024), and multiple best paper awards at CHI, ETRA, and UIST Technical Contributions: Developed datasets (LPW, VisRecall++), created novel methods for gaze estimation, mental face reconstruction, and saliency prediction in visualizations His work bridges AI and Human-Computer Interaction with applications in immersive systems and healthcare technologies.

Andreas Fenderمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +۶ مورد دیگر

Andreas Fender is a researcher at the Visualization Institute of the University of Stuttgart (VISUS), affiliated with the Schmalstieg Working Group. He has held postdoctoral positions at ETH Zurich (Switzerland) and the University of Sussex (England), following his PhD at Aarhus University (Denmark) with an internship at Microsoft Research (USA). His research focuses on Human-Computer Interaction, particularly in Augmented and Virtual Reality (AR/VR) and camera networks. He develops novel input methods for productivity and artistic expression in Mixed Reality environments, creating hybrid physical-digital systems like OptiBasePen, PressurePick, InfinitePaint, and DeltaPen. Recent work includes contributions to Mixed Reality input methods (UIST 2024, CHI 2022) and collaborative systems (Asynchronous Reality). Projects like GuitarPie (UIST 2025) and OptiBasePen (UIST 2024) demonstrate his focus on mobile interaction and ergonomic design. Scientific accolades include the Best paper award at CHI 2022 Best application paper award at ISS 2019 . At VISUS, he collaborates with Dieter Schmalstieg and leads hiring for PhD students and PostDocs exploring physical-digital workflows, artistic tools, and critical AI engagement. His work integrates machine learning, hardware prototyping, and spatial user interfaces to redefine future workplaces.

Hanh Thi Nguyenمشاهده پروفایل

استاد

• Applied Linguistics
• Conversation Analysis
• Discourse Analysis
• +۱۲ مورد دیگر

Hanh Thi Nguyen is a Professor of Applied Linguistics in the Department of English and Applied Linguistics at Hawaii Pacific University, College of Liberal Arts. She earned her Ph.D. in English Language and Linguistics from the University of Wisconsin-Madison and holds a B.A. from the University of Hue, Vietnam. Her research centers on conversation analysis, interactional competence, second language acquisition, pragmatics, classroom and workplace discourse, learner identity, and Vietnamese linguistics . She explores how language learners develop communicative abilities across contexts, from classrooms to professional settings, using detailed interactional data. Her work bridges theory and pedagogy, informing language teaching and assessment practices. Dr. Nguyen has published extensively, including books such as Developing Interactional Competence at the Workplace (2024) and Developing Interactional Competence: A Conversation Analytic Study of Patient Consultations in Pharmacy (2012), and co-edited volumes on conversation analysis and Vietnamese pragmatics. Her recent articles examine epistemic stance, language ideologies in family talk, and computer-mediated language learning, showing a growing interest in longitudinal development and multimodal interaction. She has received numerous awards and grants, including the Golden Apple Award for Excellence in Scholarship (2019), multiple Faculty Development Grants, and a 2024 U.S. Department of State grant as Principal Investigator. She has served on editorial boards for journals such as RELC Journal and TESOL International Journal . Dr. Nguyen mentors students and collaborates widely, with frequent co-authorship with scholars like Taiane Malabarba and Minh Thi Thuy Nguyen. She teaches courses in sociolinguistics, discourse analysis, corpus linguistics, and language assessment. She also leads research labs and teams focused on conversation analysis and language socialization, and continues to present at major international conferences through 2025.

• Robotics
• Human-Robot Interaction
• Assistive Robotics
• +۹ مورد دیگر

Guillem Alenyà Ribas is a Researcher and Director of the Perception and Manipulation group at the Institut de Robòtica i Informàtica Industrial (IRI), a joint center of the Spanish National Research Council (CSIC) and the Polytechnic University of Catalonia (UPC), Barcelona. His research focuses on integrating robots into human environments, particularly in assistive robotics and the manipulation of deformable objects such as garments. His research interests span Human-Robot Interaction (HRI) , assistive robotics , explainable AI , robot personalization , deformable object manipulation , and benchmarking . He aims to make robots more transparent, adaptive, and safe in real-world applications. His work combines AI planning, vision, learning from demonstration, and user-centered design to develop systems that can assist in healthcare, domestic, and industrial settings. Recent publications reveal a strong trend in explainability and personalization in HRI, with a focus on frailty assessment in elderly care , real-time explanations , and counterfactual reasoning . His team also advances benchmarking in cloth manipulation , 3D reconstruction of clothed humans , and ontology-based reasoning for robot plans . This reflects a multidisciplinary approach combining robotics, AI, and social sciences. Coordinator of ROB-IN, CLOE-GRAPH, and BURG projects Principal Investigator in SeCuRoPS and DEMETER 5.0 Former coordinator of SIMBIOTS, HuMoUR, and SOCRATES He has supervised numerous PhD students, many of whom have received prestigious awards such as the Georges Giralt PhD Award and the AIHUB.CSIC Prize. His leadership in technology transfer and European projects highlights his role in bridging academic research with real-world applications. He leads the Perception and Manipulation group at IRI, fostering collaboration across disciplines and mentoring a large team of researchers, PhD students, and technical staff. The group actively contributes to open science through standardized datasets and reproducible methodologies.

Li Wanمشاهده پروفایل

مدرس

• Acoustics
• Speech Processing
• Machine Learning
• +۴ مورد دیگر

Li Wan serves as a Lecturer at the Language Centre within Queen Mary University of London's School of Languages, Linguistics and Film. Despite her institutional affiliation with language education, her research output demonstrates deep expertise in acoustics, machine learning, and sensor networks, reflecting an unusual interdisciplinary profile spanning engineering and biomedical applications. Her research interests center on acoustics and speech processing, with significant contributions to machine learning applications in sensor networks, signal processing, and natural language processing. Recent work focuses on binaural audio rendering, emotion recognition systems, and biomedical diagnostics using electrocardiogram data, often addressing real-world challenges like missing sensor data and class imbalance in classification tasks. This research bridges engineering disciplines despite her Language Centre appointment. Analysis of her 15 most recent publications reveals a strong trend toward physics-informed neural networks for audio applications and sensor-based human activity recognition. Her work frequently appears in specialized challenges like the SHL and Odyssey competitions, emphasizing practical implementations for locomotion recognition, drone audition, and text segmentation. Key methodological themes include multimodal fusion, data augmentation, and cross-domain adaptation. Scientific Awards: No formal awards or fellowships documented in provided sources While her Language Centre role suggests teaching responsibilities in Chinese language, her publication record indicates active research mentorship in engineering domains. No grants or student advisement details are publicly available, though her challenge competition participation implies collaboration with technical research teams. The absence of lab affiliations in current documentation contrasts with her hardware-oriented work on drone audition and sensor systems.

Preethi Srivathsaمشاهده پروفایل

استادیار

• Computer Architecture
• Internet of Things
• Cyber Security
• +۴ مورد دیگر

Dr. Preethi Srivathsa is an Assistant Professor - Senior Scale in the School of Computer Engineering at Manipal Academy of Higher Education (MAHE), Bengaluru. She holds a B.Tech, M.Tech, and Ph.D. (awarded by Presidency University in 2022). Her academic career includes positions at Presidency University (2019-2023) and East Point College of Engineering (2008-2019). Her research focuses on: Computer architecture and low-power hardware design IoT applications and cyber-physical systems Cryptography and blockchain security Machine learning implementations in hardware FPGA-based accelerators and optimization techniques Her publication portfolio shows strong emphasis on hardware-efficient algorithms, cryptographic systems (especially elliptic curve applications in blockchain), and emerging IoT architectures. Recent work integrates machine learning with hardware acceleration for smart home systems and agricultural technology. Awards and recognitions: Best Paper Award at IEEE iSES-2021 for low-power sorter design Infosys Bronze Partner Faculty (2013) She has developed intellectual property including IoT-based monitoring systems and blockchain educational frameworks. Technical skills include Verilog, FPGA design, IoT platforms (Arduino/Raspberry Pi), and multiple programming languages.

• Language Acquisition
• Cognitive Science
• Computational Modeling
• +۷ مورد دیگر

Emmanuel Dupoux is a Professor at École des Hautes Études en Sciences Sociales (EHESS), affiliated with the School of Advanced Studies in Social Sciences and the Laboratory of Cognitive Science and Psycholinguistics (LSCP). His work bridges cognitive science, computational linguistics, and machine learning to study infant language acquisition and social cognition. Co-creator and director of EHESS Cognitive Science Master program Former LSCP laboratory director (1998-2009) Current research focuses on textless speech modeling and ecological audio analysis Research areas include: Modeling early language acquisition mechanisms using Bayesian models and HMM Investigating phonological 'deafness' and critical age plasticity Studying social cognition development through infant-toddler experiments His technical contributions span speech processing toolkits like Shennong, emergent communication frameworks (STOP dataset), and innovative approaches to self-supervised speech modeling. Recent publications demonstrate breakthroughs in: Topography-inspired CNN designs for better memory efficiency Prosody-aware generative spoken language models (pGSLM) Textless emotion conversion systems He actively explores how machine learning can reverse-engineer infant language learning processes from ecological audio data, with applications in neurodegenerative disease diagnostics. Key collaborations include: INRIA's Cognitive Machine Learning (CoML) team Facebook AI Research (FAIR) partnerships VoxPopuli multilingual speech corpus development

Carsten Röckerمشاهده پروفایل

استاد

• Human-Computer Interaction
• Intelligent Assistance Systems
• Technology Acceptance
• +۳ مورد دیگر

Carsten Röcker serves as Professor for Human-Technology Interaction at TH OWL University of Applied Sciences and Arts and holds a leadership position on the Executive Board of the Institute Industrial IT (inIT). His institutional affiliations include the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB-INA) as Scientific Advisor, InnoZent OWL as Board Member, and the Graduate Institute OWL. He maintains active roles in the Graduate School for Applied Research in North Rhine-Westphalia and the International Graduate School on Intelligent Systems in Automation Technology. His research spans intelligent assistance systems, human-computer interaction, and technology acceptance, with particular emphasis on industrial applications. Key focus areas include inclusive design for disadvantaged workers , augmented reality in manufacturing , and AI-mediated communication frameworks . His work bridges theoretical foundations in psychology and social sciences with practical industrial implementations, evidenced by numerous publications on projection-based AR systems, cognitive assistance for assembly tasks, and ethical considerations in workplace technology. Röcker's scholarly contributions include over 150 publications and editorial work on 8 books. His research demonstrates consistent focus on Human-centered design for industrial automation Inclusive technologies for cognitively disabled workers Psychological well-being in technology-mediated workplaces Advanced interaction paradigms using AR/VR His extensive service includes reviewing for major funding agencies (Australian Research Council, Academy of Finland), journals (ACM Transactions, Personal and Ubiquitous Computing), and over 50 international conferences annually. He has organized numerous workshops on assistive environments and healthcare applications since 2009. As an educator, Röcker supervises graduate research through TH OWL's programs and contributes to the International Graduate School on Intelligent Systems. His technical leadership extends to directing the Human-Computer Interaction research group and co-leading the ProErgo and NextPlace research clusters focused on human-centered industrial systems.

Khaled R. Ahmedمشاهده پروفایل

دانشیار

• Big Data
• Deep Learning
• Parallel Computing
• +۶ مورد دیگر

Khaled R. Ahmed is an Associate Professor and Graduate Program Director at the School of Computing, Southern Illinois University. He serves as Director of the Big Data & Software Engineering Lab (BASE Lab), focusing on software engineering support for big data systems and deep learning algorithms. His research bridges computer science with practical applications in agriculture, safety, and environmental monitoring. Dr. Ahmed's research interests center on Big Data Software Engineering, Deep Learning, Parallel and Distributed Computing, and Computer Vision. His laboratory collaborates extensively with the agriculture college on precision agriculture projects, securing federal funding from USDA-NIFA for research on livestock monitoring and crop analysis. His work demonstrates a clear trajectory from foundational distributed systems research to applied deep learning solutions for real-world problems. His recent publications reveal a strong focus on agricultural applications of computer vision, including weed detection systems, livestock methane emission monitoring, and soybean growth stage analysis. The BASE Lab has developed innovative approaches using Vision Transformers, DETR, and RetinaNet for precision agriculture applications, with several papers published in top venues like CVPR and IEEE Transactions. USDA-NIFA Research Award for Detecting Subacute Ruminal Acidosis USDA-NIFA Research Award for Artificial Intelligence for Greener Livestock Illinois Innovation Network Seed Grant Outstanding Achievement Award at World Congress in Computer Science (2020) Dr. Ahmed has successfully mentored numerous graduate students, with several receiving Outstanding Thesis Awards. His BASE Lab actively recruits Ph.D. and MSc students with backgrounds in Deep Learning, Big Data, and Software Engineering. He maintains international connections through Fulbright programs, particularly with researchers from India and Egypt interested in AI and Deep Learning applications. The BASE Lab maintains strong industry and research collaborations, particularly in precision agriculture where computer vision techniques are applied to solve practical farming challenges. Current projects include real-time video analysis systems for safety applications, drone-based monitoring for natural disaster recovery, and weapon detection systems for public safety.

Matthias Gondan-Rochonمشاهده پروفایل

استاد

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

Matthias Gondan-Rochon is a Professor in the Department of Psychology at the University of Innsbruck. His research focuses on quantitative methods in psychology, multisensory processing, and statistical modeling of cognitive phenomena. He has developed several R packages, including rswipl , rolog , and mathml , which bridge computational logic and mathematical representation in psychological research. University: University of Innsbruck School: Institute of Psychology Department: Department of Psychology Academic Rank: Professor His work spans cognitive psychology, neuroscience, and clinical applications, with recent studies on traumatic brain injury outcomes, PTSD interventions, and multisensory integration. Publications emphasize reaction time modeling, diffusion processes, and methodological innovations. Notable collaborations include research on mentalization-based therapy for adolescents with borderline personality disorder and statistical tools for psychological assessment.

Procheta Senمشاهده پروفایل

مدرس

• Natural Language Processing
• Explainable AI
• Bias Mitigation
• +۳ مورد دیگر

Dr. Procheta Sen is a Lecturer in Computer Science at the University of Liverpool's Faculty of Science and Engineering, Department of Computer Science, where she joined in 2022 as part of the Natural Language Processing research group. Her work focuses on developing transparent, fair, and accessible AI language models through explainability research. She earned her PhD from Dublin City University, Ireland (2021) under supervisor Gareth J.F. Jones, with affiliation at ADAPT Centre Ireland. Prior to Liverpool, she conducted postdoctoral research with Emine Yilmaz in University College London's Web Intelligence Group. Dr. Sen's research spans three explainability categories: post-hoc methods (feature attribution, counterfactuals), mechanistic interpretability (neural network circuit mapping), and intrinsic interpretability (human-readable model design). She targets diverse end-users including clinicians, legal experts, and laypersons, with applications in bias mitigation and socially responsible AI systems. Her work bridges Natural Language Processing, Machine Learning, and Information Retrieval to address real-world challenges in transparency and equity. Analysis of her 2023-2025 publications reveals dominant trends in LLM bias analysis, legal document processing, and adaptive conversational systems. Key themes include mechanistic interpretability for bias detection, retrieval-augmented generation for dialogue systems, and multilingual knowledge extraction—demonstrating consistent focus on making AI both technically robust and socially beneficial across domains like law and finance. Dr. Sen actively advises PhD student Lingfang Li (AAAI 2025 accepted work) and emphasizes compassionate talent development. Her open-source research has been deployed in legal sector applications, and she organizes the annual NLP for Social Good symposium fostering interdisciplinary collaboration for responsible AI. She leads initiatives including the 2025 virtual NLP for Social Good Symposium and collaborates with institutions like Nokia Bell Labs Cambridge, maintaining active research momentum in transparent AI systems.

Emre Ugurمشاهده پروفایل

دانشیار

• Robotics
• Robot Learning
• Cognitive Robotics
• +۵ مورد دیگر

Emre Ugur is an Associate Professor in the Department of Computer Engineering at Bogazici University, where he serves as the head of the Cognition, Learning and Robotics (CoLoRs) laboratory. His research focuses on bridging the gap between continuous sensorimotor experiences and discrete symbolic representations in robotics. Funded by major international sources including the European Commission's Horizon 2020 program and TUBITAK, his work has significant implications for cognitive robotics and autonomous systems. Education: PhD in Computer Engineering from Middle East Technical University (METU, Turkey) Ugur's research interests center on cognitive and developmental approaches to robotics, with particular emphasis on neuro-symbolic integration, affordance learning, and symbol emergence. His work explores how robots can autonomously develop high-level cognitive capabilities through continuous interaction with their environment, similar to human cognitive development. His approach combines machine learning, cognitive science, and robotics to create systems that can learn, predict, and reason about their actions. His recent publications reveal a strong trajectory toward neuro-symbolic robotics, where he develops methods for extracting discrete symbolic representations from continuous sensorimotor experiences. This work enables robots to perform complex planning and reasoning tasks while maintaining connection to physical reality. There is also significant focus on social robotics, particularly in human-robot interaction, social navigation, and embodied cognition. Scientific Awards: The Young Scientist Award by the Science Academy (BAGEP) The Excellence in Teaching Award by the Faculty of Engineering (2023) As Principal Investigator of major projects including INVERSE (EU Horizon 2025), DEEPPLAN (TUBITAK), and previously DEEPSYM and IMAGINE, Ugur has established a robust research program that bridges theoretical advances with practical applications. He has supervised numerous PhD and Master's students who have made significant contributions to the field. His leadership extends to organizing major workshops at top robotics conferences including IROS, RSS, and ICRA. At the Cognition, Learning and Robotics (CoLoRs) lab, Ugur leads research on cognitive robotics, developmental robotics, and neuro-symbolic AI. The lab explores fundamental questions about how robots can develop understanding of their actions, learn from interaction, and form abstract representations necessary for high-level cognition. Current projects focus on symbolic reasoning, prediction, and planning in robotic systems.

• Design automation for intelligent cyber-physical systems
• Internet-of-Things applications
• Safe and robust machine learning for embodied AI
• +۷ مورد دیگر

Professor Zhu Qi is a faculty member in the Department of Electrical and Computer Engineering at Northwestern University's McCormick School of Engineering, with courtesy appointment in Computer Science. He leads the IDEAS Lab (Design Automation of Intelligent Systems Lab) where his research focuses on design automation for intelligent cyber-physical systems and Internet-of-Things applications. His research interests include safe and robust machine learning for embodied AI systems, cyber-physical security, energy-efficient CPS, and system-on-chip design. Professor Zhu's work particularly addresses safety, robustness, security, adaptability, resiliency, and energy challenges in the design and operation of embodied AI systems. His applications span connected and autonomous vehicles, robotics, advanced manufacturing, wearable computing, smart buildings and infrastructures, and IoT. Professor Zhu's recent publications reveal a strong focus on safety verification of neural network controlled systems, robust reinforcement learning methods, and applications of large language models in autonomous systems. His work often combines formal verification techniques with machine learning approaches to provide safety guarantees for AI-enabled cyber-physical systems. DATE 2022 Best Paper Award AutoSec 2021 Best Short Paper Award ACM TODAES 2016 Best Paper Award IEEE TCCPS Early-Career Award (2017) Humboldt Research Fellowship for Experienced Researchers (2017) NAE US Frontiers of Engineering participant (2020) Professor Zhu has secured multiple research grants from NSF (including FM, DESC, and Fuse grants), DOE, ONR, and industry partners including GM and Toyota. His advising includes PhD students Shuyue Lan and Hengyi Liang, and postdoc Chao Huang who became a Lecturer at University of Liverpool. He leads the IDEAS Lab which focuses on cross-layer design, verification, and adaptation of learning-enabled cyber-physical systems.