John Hughes is a Professor at Chalmers University of Technology. His research focuses on functional programming, software testing, and formal methods. He is a co-author of the Haskell programming language and a pioneer of QuickCheck, a property-based testing tool. His work bridges foundational theory with practical applications in software engineering. Research Interests: Development of functional programming paradigms and their applications Property-based testing and automated software validation Type systems and compiler optimization techniques Concurrency and parallelism in functional languages His publications span influential works like Why Functional Programming Matters (1989) and A History of Haskell (2007). He has contributed to open-source tools and frameworks widely used in academia and industry.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۷۳۶-۷۵۰ از ۳٬۱۰۴ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
- Ontologies
- Semantic Integration
- Process Modelling
- +۶ مورد دیگر
Michael Gruninger is a Professor in the Department of Mechanical and Industrial Engineering at the University of Toronto, serving as Associate Chair of Undergraduate Studies. He holds a PhD and MSc in Computer Science from the University of Toronto and a BSc in Computer Science from the University of Alberta. His research focuses on semantic integration, process modeling, and mathematical logic applications in manufacturing and enterprise engineering. He contributed to the ISO 18629 standard for Process Specification Language. Research interests include ontologies, semantic web technologies, knowledge representation, and formal methods. He leads the Semantic Technologies Laboratory, advancing theories in mereotopology, spatiotemporal ontologies, and ontology engineering. Recent work emphasizes automated spatial reasoning in robotics and standards-based ontology development. Publications span ontology validation, mereological foundations, and applied semantic technologies. His work bridges theoretical computer science with practical enterprise systems and smart city applications. No awards are explicitly listed, though his contributions to ISO standards reflect industry impact. Advising and grants: No specific students/grants detailed here. His lab focuses on semantic technologies with applications in manufacturing and urban systems. Collaborations include NIST and the Industrial Ontologies Foundry.
Prof. Sergey Avrutin is a Professor of Comparative Psycholinguistics at Utrecht University's Department of Languages, Literature and Communication, within the College of Humanities. His research integrates information theory into language processing studies, focusing on typically and atypically developing children, adults, and individuals with aphasia. He previously led the NWO-sponsored PIONEER research program (2000-2005) and current projects explore rule induction from partially ordered input and entropy-driven models. Prof. Avrutin has held academic roles such as Research Leader, Promoter, and Executor across multiple NWO and EU-funded projects. His research spans syntax-discourse interface, language acquisition disorders, bilingualism diagnostics, and special registers like headlines and TV commentary. He collaborates with international institutions including Berlin's Zentrum für Allgemeine Sprachwissenschaft and Russia's Herzen State Pedagogical University. His teaching includes courses on Cognitive Science, Language and Law, and the Syntax-Discourse Interface. Recent work highlights contributions to understanding lexical access in aphasia, the role of prosody in anaphora resolution, and statistical learning mechanisms. His articles and projects reflect a focus on interdisciplinary methods, combining experimental and theoretical approaches to linguistic phenomena.
Igor Ivkovic was a Professor in the Department of Systems Design Engineering at the University of Waterloo, Canada. His work focused on integrating theory and practice in complex information systems, emphasizing system modeling, process modeling, and data modeling to bridge technical and business stakeholder needs. He taught courses such as Data Structures and Algorithms, Algorithms and Data Structures, and Digital Systems in recent years. Education: Holds a Doctorate in Electrical and Computer Engineering (2011), along with advanced certificates in university teaching (Certificate in University Teaching, 2011) and instructional skills (ISW, 2015). Earlier degrees include a Master of Mathematics in Computer Science (2003) and a Bachelor of Mathematics in Operations Research (2001), both from the University of Waterloo. Research Interests: Specialized in Information Systems, Software Engineering, and Knowledge Engineering. His work addressed challenges in model synchronization, software evolution, and architecture recovery, leveraging formal methods and model-driven approaches to enhance system consistency and interoperability. Notable Contributions: Authored influential papers on model synchronization for software evolution (2011) and improving the Gnutella protocol (2001), the latter earning a prize-winning award. He also pioneered educational innovations like Design Days Boot Camps (2017–2021), integrating remote learning and augmented reality into engineering education. Awards: Recognized for his 2001 research on the Gnutella protocol, which won a prestigious award through the LimeWire contest.
Jonathan Linمشاهده پروفایل
استادیار مدعو
- Robotics
- Biomechanics
- Human-Machine Interaction
- +۳ مورد دیگر
Jonathan Lin is an Adjunct Assistant Professor at the University of Waterloo, specializing in robotics and biomechanics with a focus on human motion analysis and assistive technologies. His research spans rehabilitation engineering, human-robot interaction, and sensor systems for clinical and mobility applications. Key research areas include real-time pose estimation for assistive robots, motion segmentation for rehabilitation monitoring, and humanoid robotics learning from human demonstrations. He has contributed to projects like the SkyWalker mobility aid robot and Segway-riding humanoid systems. His work bridges robotics, biomechanics, and healthcare, emphasizing practical applications in aging populations and clinical settings. No scientific awards are listed, but his publications reflect interdisciplinary innovation in motion analysis and assistive technologies. Advising and grants details are not explicitly provided, though collaborations with robotics and biomedical engineering teams are implied through his research outputs. His lab or team affiliations remain unspecified in the provided texts.
Zoe Klemfussمشاهده پروفایل
دانشیار
Dr. Zoe Klemfuss is an Associate Professor of Psychological Science at the University of California, Irvine (UCI), specializing in developmental and legal psychology. She holds a Ph.D. from Cornell University and directs the Child Narratives Lab (childnarrativeslab.com). Her research focuses on children’s memory accuracy, narrative development, and sociocontextual influences, with applications to legal contexts such as child sexual abuse testimony. She has published in top journals like Developmental Psychology and Annual Review of Clinical Psychology , supported by NIH grants. Key research areas include: Narrative development and eyewitness abilities in children, Sociocontextual factors shaping memory and well-being, Legal implications of children’s testimony accuracy, Parent-child communication strategies in stress/health contexts. Recent publications highlight her work on pandemic-related mental health, misinformation resistance, and juror decision-making influenced by emotional testimony. Her lab emphasizes translational research bridging cognitive development and societal applications. She has advised multiple students and collaborates on grants addressing child welfare and forensic psychology.
Uli Sattler is a Professor in the Computer Science Department at the University of Manchester, specializing in logics for knowledge representation and automated deduction. He holds a PhD from RWTH Aachen (1998) and a habilitation from TU Dresden (2003). His research focuses on Description Logics, ontology engineering, and their applications in fields like molecular biology. He contributes to ontology languages such as OWL and develops practical inference algorithms. Research Interests: Description Logics, automated reasoning, ontology engineering, and their integration with AI systems. His work addresses challenges like module extraction, entailment explanation, and decision procedures using automata and tableau techniques. Awards: Best Paper Award (2008) ISWC Best Student Paper Award (2011) SWSA Ten-Year Award (2018) Advising & Grants: Supervised 17 students and participated in initiatives like Gender Advancement through Transforming Institutions. Active in organizing conferences and peer-review panels. Labs/Teams: Part of the Information Management Group and the Data Science Institute at the University of Manchester.
Albert Qiaochu Jiangمشاهده پروفایل
پژوهشگر ارشد
Albert Qiaochu Jiang serves as a Visiting Research Fellow at the Department of Computer Science and Technology, University of Cambridge. His research integrates machine learning with formal theorem proving, focusing on neural theorem provers and mathematical reasoning systems. He leads the reasoning team at Mistral AI while maintaining academic supervision at Cambridge. His research interests center on machine learning for theorem proving , with specific expertise in neural-symbolic integration, autoformalization, and large language models for mathematical reasoning. His work bridges artificial intelligence with formal verification, developing systems that enhance automated reasoning capabilities through neural networks. Current projects involve improving premise selection for theorem provers, multilingual mathematical formalization, and creating efficient architectures for mathematical language models. Analysis of his recent publications reveals a strong focus on advancing neural theorem proving through innovative architectures like Target-Based Automated Conjecturing and Magistral. His research trajectory shows increasing sophistication in integrating language models with formal verification systems, with significant contributions to datasets like Numinamath and frameworks like Llemma. Key trends include optimizing compute efficiency in proof generation, enhancing multilingual mathematical reasoning, and developing interactive human-AI collaboration systems for formal mathematics. While no scientific awards are currently documented in available sources, his research output demonstrates significant impact in the intersection of AI and formal methods. As leader of Mistral AI's reasoning team, Jiang directs research on neural theorem proving systems while contributing to academic supervision at Cambridge. His work involves substantial industrial-academic collaboration, leveraging resources from both institutional contexts to advance mathematical AI. Current projects focus on creating practical systems for mathematical automation with real-world verification applications. His research operates at the intersection of academia and industry through Mistral AI's reasoning team, where he develops neural theorem proving systems with practical applications in formal verification. This dual affiliation enables rapid translation of theoretical advances into deployable tools for mathematical automation.
- Computer Vision
- Machine Learning
- Generative AI
- +۵ مورد دیگر
Dr. Jing Zhang is a Lecturer in the School of Computing at the Australian National University (ANU) , within the ANU College of Systems & Society . Previously, he served as a Research Fellow at ANU (2021–2022) and earned his PhD in 2021 under the supervision of Nick Barnes. His academic journey includes a Master’s (2010) and Bachelor’s (2007) from Northwestern Polytechnical University . Education: PhD, Australian National University, 2021 (Supervisor: Nick Barnes) Master’s Degree, Northwestern Polytechnical University, 2010 Bachelor’s Degree, Northwestern Polytechnical University, 2007 Research Interests: Jing Zhang’s research focuses on computer vision and machine learning , with a particular emphasis on generative AI . His work addresses challenges in image, video, and audio generation/editing; explainable model adaptation; out-of-distribution detection; and adversarial attacks/defenses. He explores techniques to enhance model robustness and generalization across diverse domains. Awards & Recognition: CVPR 2020 Paper Award Nominee for “UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders” Teaching & Supervision: Jing Zhang teaches COMP8536: Advanced Topics in Computer Vision (Semester 2, 2024) and ENGN4528/6528: Computer Vision (Semester 1, 2025). He currently supervises 4 PhD students as their primary advisor, focusing on cutting-edge research in computer vision and AI. Professional Contributions: Co-organizer of tutorials on salient object detection (ACCV 2019) and uncertainty estimation (ICCV 2021) Regular reviewer for top venues: CVPR, ICCV, ECCV, TPAMI, IJCV, and others Research Groups: While not explicitly stated, his work is likely affiliated with ANU’s computer vision research groups, focusing on generative AI and robust machine learning systems.
Bryan Rangerمشاهده پروفایل
استادیار
Bryan Ranger is the Ferrante Family Assistant Professor in the Department of Engineering at Boston College, with a courtesy appointment in the William F. Connell School of Nursing and affiliation with the Global Public Health and the Common Good Program. He leads the Biomedical Imaging and Instrumentation Lab, focusing on ultrasound imaging, AI/ML algorithms, and global health applications. B.S.E., University of Michigan, Ann Arbor M.S.E., University of Michigan, Ann Arbor Ph.D., Massachusetts Institute of Technology (NSF Graduate Research Fellow) His research spans biomedical imaging, AI-driven diagnostics, and low-cost medical device development for resource-limited settings. Key themes include human-centered design, bioreactor monitoring, ultrasound elastography, and educational ultrasound platforms. Collaborations include Brigham and Women's Hospital, Jimma University (Ethiopia), Ahmedabad University (India), and Boston College departments like Computer Science and Nursing. Selected publications demonstrate expertise in musculoskeletal imaging, phantom development, and ultrasound education. Awards include Google Research Scholar (2022), Google Award for Inclusion Research (2023), ATIG Grant (2023), and SI-RITEA Grant (2023). Funded projects involve Gates Foundation support for maternal nutrition assessment and NIH mHealth Training Institute (2025). Google Award for Inclusion Research (2023) Google Research Scholar Program Award (2022) ATIG Grant (2023) SI-RITEA Grant (2023) NSF Graduate Research Fellow (PhD period) He teaches first-year engineering labs and courses in biomedical imaging, emphasizing societal responsibility in engineering education. His lab includes student researchers like Hayoung Cho, who received the Finnegan Award, and has presented at conferences including BMES, IEEE GHTC, and KEEN workshops.
Michaela Bačíkováمشاهده پروفایل
استادیار
Michaela Bačíková is an Assistant Professor at the Faculty of Electrical Engineering and Informatics (FEI) of the Technical University of Košice (TUKE). Her research focuses on Human-Computer Interaction (HCI), domain usability, and domain analysis, with an emphasis on graphical user interfaces (GUIs), domain-specific languages (DSLs), and gesture-driven interaction. She leads the development of the DEAL tool, a domain analysis framework for extracting domain models from software systems. Her teaching includes courses on component-based programming, web technologies, and user interface design. Research Projects: DEAL (Domain Extraction ALgorithm) : A tool for analyzing GUIs to generate DSLs, ontologies, and usability metrics. EU Project: 'Evolving Architectural Knowledge in the Edge-to-Cloud Continuum' (participant). Educational initiatives: Integrating gesture-driven IDEs and social networks for mentoring in programming courses. Research Interests : Automated domain usability evaluation using DEAL. DSL-driven GUI generation and feature modeling. Innovations in teaching software development and user experience design. Grants & Labs : Recipient of FEI TUKE Grant no. FEI-2015-16 for domain usability metrics research. Active in the FEI lab developing DEAL and related tools.
Shakil M. Khanمشاهده پروفایل
استادیار
Dr. Shakil M. Khan is the SaskPower Assistant Professor in Artificial Intelligence at the University of Regina's Department of Computer Science. His primary research develops formal models for causal reasoning in artificial intelligence, focusing on knowledge representation and rational agent systems. He holds a Ph.D. from York University and leads the PRACToR lab. Education: Ph.D. Computer Science, York University (2018) B.Sc. Computer Science, University of Windsor Dr. Khan's research program develops logical frameworks for actual causation in nondeterministic domains, with applications to explainable AI and multi-agent systems. His work combines situation calculus with game-theoretic approaches to model causal relationships and responsibility attribution. Current projects investigate abstraction techniques for concurrent game structures and root cause analysis in hybrid dynamic systems. His publications demonstrate strong theoretical foundations in logic-based AI, with recent articles exploring the semantics of causality, knowledge representation, and agent modeling. Research keywords frequently include situation calculus, formal verification, and multi-agent systems. Dr. Khan supervises graduate students working on causal reasoning projects and has received NSERC Discovery funding (2022-2027). He serves on program committees for leading AI conferences including AAAI, IJCAI, and KR. Dr. Khan teaches courses in discrete structures, artificial intelligence, and knowledge representation.
Dr. Shimi Naurin Ahmad is an Associate Professor of Business Administration at Morgan State University's Earl G. Graves School of Business and Management. Her research focuses on Online Consumer Behavior and Text Mining of Online Word-of-Mouth, with a particular emphasis on leveraging large unstructured datasets to uncover behavioral patterns. Dr. Ahmad holds a Ph.D. in Business Administration from Concordia University's joint doctoral program with McGill, HEC, and UQAM, alongside an M.Sc. in Electrical Engineering from Concordia and a B.Sc. from Rajshahi University of Engineering and Technology. Research Interests: Online Consumer Behavior Text Mining Techniques Online Pricing Strategies Cross-Cultural Marketing Social Commerce Dynamics Her work has been published in top-tier journals such as the Journal of Marketing Analytics and International Journal of Information Management . Notably, her 2023 Journal of Marketing Analytics paper earned the Most Popular Article Award. She has secured grants including the Provost Innovation Grant and Transform Morgan Grant, supporting her research initiatives. Awards & Recognition: 2023 Most Popular Article Award (Journal of Marketing Analytics) Competitive Research Grants from Morgan State University Dr. Ahmad's research bridges technical disciplines like data mining with business applications, contributing to both academic and practical insights in consumer behavior and digital marketing strategies.
Nandini Sidnalمشاهده پروفایل
مدرس ارشد
Nandini Sidnal serves as Senior Learning Facilitator and National Academic Course Coordinator for Torrens University's Master of Software Engineering program through the Centre for Artificial Intelligence Research and Optimisation (AIRO). With over 20 years of international teaching experience in Computer Science, Engineering, and Networking, she has established herself as a key academic figure in AI and blockchain applications. Her educational foundation includes: PhD in Computer Science and Engineering (Cognitive Computing using Intelligent Agents) from Visvesvaraya Technological University (2012) M.Tech in Computer Science and Engineering (Parallel and Distributed Computing using Intelligent Mobile Agents) (2003) Bachelor of Engineering (1993) Nandini's research spans Artificial Intelligence, Blockchain Security, and Cognitive Computing , with strong emphasis on practical implementations in agriculture and healthcare. Her work integrates intelligent agents with distributed systems to solve real-world problems like food supply chain security and medical diagnostics, demonstrating consistent innovation from her early best paper award-winning thesis to current cutting-edge applications. Recent publications reveal a pronounced trend toward AI-driven agricultural optimization (dairy quality, aeroponics, nut farming) and healthcare diagnostics (epilepsy detection), alongside critical work in edge security. These outputs consistently bridge theoretical frameworks with tangible industry solutions, particularly in blockchain-secured IoT systems and deep learning applications. Her scientific recognition includes: Best Paper Award at an international conference for distributed computing research Nandini actively mentors high-impact projects including 'Strengthening Mobile-Based Services for Agriculture' and 'Enhancing VANET Performance with Cloud and Edge Technology.' Her industry collaborations with Intel (Parallel Programming integration) and Nokia (Mobility Research Lab establishment in Finland) demonstrate exceptional academic-industry synergy. The AIRO Centre serves as her primary research hub where she guides PhD candidates in blockchain-secured agri-supply chains and semantic recommender systems. Her Mobility Research Lab in Finland remains a cornerstone of her practical innovation legacy, focusing on next-generation mobile application development that continues to influence current VANET and edge computing research directions.
Dr. Syeda Fizzah Jilani is a Lecturer in the Department of Physics at Aberystwyth University, UK, and a course coordinator for the MSc Radio Spectrum Engineering program. She holds a PhD in Antennas and Electromagnetics from Queen Mary University of London (2018) and previously worked on US DOE-funded research at the University of Maine. Her research focuses on advanced antenna systems, 5G/6G wireless technologies, millimeter-wave applications, and AI-driven environmental and medical imaging solutions. She has authored/co-authored over 50 papers, a book titled Antennas and Propagation for 5G and Beyond , and secured grants from L3Harris and QinetiQ. Key achievements include the 2024 Aberystwyth University Visibility Award and inclusion in the global '100 Brilliant and Inspiring Women in 6G' list. She leads projects on spectrum monitoring, reconfigurable antennas, and smart city applications, while actively supervising PhD students and contributing to IEEE and IET committees. Education: PhD in Electronic Engineering, Queen Mary University of London (2015–2018) Research Interests: Electromagnetics and Antenna Design Millimeter-Wave and Terahertz Systems Flexible Wearable Antennas Deep Learning in Remote Sensing and Medical Imaging 6G/5G Wireless Communication Networks Sustainable Transportation Solutions Recent Research Trends: Her work spans cutting-edge antenna technologies for 6G, AI-driven environmental monitoring (e.g., landslide detection, air quality analysis), and medical imaging advancements (e.g., breast lesion classification). Recent publications highlight innovations in reconfigurable phased arrays, liquid metal phase shifters, and explainable neural networks for healthcare. Awards and Grants: Principal Investigator: 3-year Serapis Project with QinetiQ/DSTL (£X) PI: L3Harris Technologies Grant (£Y) Featured in '100 Brilliant and Inspiring Women in 6G' (2024) Aberystwyth University Visibility Award (2024) Advising & Grants: Supervises PhD scholars and leads industry-academia collaborations. Projects include spectrum monitoring systems with the UK Spectrum Centre and smart city MIMO antenna arrays. Active in professional service as an IEEE AP-S Young Professional Ambassador and IET Antennas Technical Committee member. Labs/Teams: Works within the Department of Physics' Antennas and Propagation group, focusing on 6G infrastructure and wearable electronics research.
فقط ۷۵۰ نتیجه اول نمایش داده میشود. برای رسیدن به نتایج دقیقتر، جستوجو را با فیلترها محدودتر کنید.