جست‌وجوی استاد و پژوهشگر

Ken Hylandمشاهده پروفایل

استاد

• Academic Discourse
• Writing
• Language Education
• +۷ مورد دیگر

Ken Hyland is an Honorary Professor at the University of East Anglia (School of Education & Lifelong Learning) and an Honorary Professor at Jilin University in China. With over 29 books and 280 papers, he is recognized as the world's leading scholar in language and linguistics by the Stanford/Elsevier Top 2% of World Scientists analysis. Former Director of the Centre for Applied English Studies at the University of Hong Kong Former Professor at UCL Institute of Education, London Foundation Fellow of the Hong Kong Academy of the Humanities His research spans academic discourse , writing pedagogy , language education , and metadiscourse analysis , with a focus on second language writing , feedback practices , and AI's role in writing . Recent projects explore ChatGPT's rhetorical strategies and digital literacy in writing evaluation. His publications demonstrate expertise in corpus linguistics , genre analysis , and cross-cultural communication . Articles show trends in analyzing AI-generated texts, medical discourse, and evolving academic writing conventions. 2022: Most Influential Scholar in Global Applied Linguistics Co-editor of Applied Linguistics and founding co-editor of Journal of English for Academic Purposes Ken has taught in Sudan, Saudi Arabia, Malaysia, Papua New Guinea, New Zealand, and Hong Kong. He contributes to projects like the LIT Educational Hub (2021–2023), enhancing digital university experiences in BRI countries.

Russ Cucinaمشاهده پروفایل

استاد

• Medical Informatics
• Genomics
• Healthcare Analytics
• +۴ مورد دیگر

Russ Cucina, MD, MS, is a Professor of Medicine in the Division of Hospital Medicine at the University of California, San Francisco (UCSF). He holds dual roles as Vice President and Chief Health Information Officer for UCSF Health System, overseeing analytics, software infrastructure, and genetic/genomic services. His academic and professional focus integrates clinical informatics, healthcare technology, and genomic medicine to advance patient care and institutional missions. Dr. Cucina's education includes an MD from UC Davis, an MS in Biomedical Informatics from Stanford, and a BA in Molecular and Cell Biology from UC Berkeley. He is board-certified in Internal Medicine. His research interests span electronic health record (EHR) interventions, clinical decision support systems, pharmacogenomics implementation, and healthcare operations optimization. Notable achievements include the 2010 Distinguished Paper Award from the American Medical Informatics Association and the AMDIS Award for clinical informatics excellence. His work emphasizes translating data-driven solutions into actionable clinical practices, such as reducing telemetry overuse and improving discharge processes. Dr. Cucina leads UCSF's genetics/genomics laboratories and strategic partnerships in health IT. He is a vocal advocate for leveraging technology to enhance healthcare quality and accessibility, with a focus on personalized medicine and system-wide informatics advancements.

Ryan T. Whiteمشاهده پروفایل

دانشیار

• Deep Learning
• Machine Learning
• Artificial Intelligence
• +۱۱ مورد دیگر

Ryan T. White is an Associate Professor at Florida Institute of Technology in the Department of Mathematics and Systems Engineering within the College of Engineering and Science. He serves as Director of the NEural TransmissionS (NETS) Lab, focusing on deep learning, computer vision, and data science. He is also an Affiliate Faculty member in Electrical Engineering and Computer Science. Ph.D. in Applied Mathematics (2015) from Florida Tech His research bridges deep learning and computer vision with applications in autonomous satellite operations , physics-informed neural networks for biomedical and geoscience problems, and NLP in aerospace domains. Projects include real-time edge computing , stochastic process analysis , and generative AI for synthetic data. The NETS Lab he directs has produced 15+ recent publications in conferences like IEEE Aerospace, AIAA SCITECH, and AAS/AIAA, with funding from the U.S. Space Force, Air Force Research Lab, and NSF. His teaching spans graduate/undergraduate courses in deep learning , machine learning , probability , and honors calculus . Current advisees include Ph.D. candidates and M.S. students working on topics like 3D object detection , information-theoretic neural analysis , and geophysical signal processing . The lab’s scientific contributions include real-time satellite feature detection , physics-guided neural networks for blood flow modeling, and entropy-based visual explanations for AI interpretability. Collaborations span Georgia Tech , Mulitscale Cardiovascular Fluids Laboratory , and Engage-AI for global development projects analyzing UNDP Sustainable Development Goals.

• Artificial Intelligence
• Machine Learning
• Internet of Things (IoT)
• +۵ مورد دیگر

G. Thippa Reddy is a prolific researcher with a focus on advanced technologies such as artificial intelligence, machine learning, and blockchain, particularly in healthcare, IoT, and cybersecurity domains. His work spans interdisciplinary areas including federated learning, edge computing, and smart city infrastructure. He has collaborated extensively with researchers like Praveen Kumar Reddy Maddikunta, Gautam Srivastava, and Mamoun Alazab, producing over 150 publications in high-impact journals like IEEE Access, IEEE Internet Things Journal, and IEEE Transactions on Industrial Informatics. His research emphasizes practical applications of AI in real-world scenarios, such as privacy-preserving medical systems, secure UAV networks, and inclusive education for individuals with disabilities. He explores cutting-edge topics like the Metaverse's role in Industry 5.0, blockchain-enhanced security frameworks, and the integration of large language models into intelligent transportation systems. Key contributions include frameworks for federated learning in healthcare, optimized routing protocols for underwater communications, and explainable AI (XAI) methods for industrial automation. His work often addresses challenges in scalability, privacy, and ethical deployment of emerging technologies.

• Machine Learning
• Image Retrieval
• Data Clustering
• +۳ مورد دیگر

Mohammed Lamine Kherfi is a researcher affiliated with Université de Ouargla, Algeria. His work focuses on machine learning, image retrieval, and data clustering with applications in computer vision and optimization. He has collaborated extensively with researchers like Oussama Aiadi, Mebarka Allaoui, and Djemel Ziou. His research bridges theoretical advancements in machine learning with practical applications in areas such as fruit classification, semantic image retrieval, and deep learning models. Key research areas include optimization algorithms (e.g., PSO integration with t-SNE), multi-view learning, and Bayesian methods for image representation. He has contributed to improving clustering techniques, feature extraction, and the development of lightweight neural network architectures. His work often emphasizes efficient and energy-aware solutions for real-world problems. Over 30 publications span prestigious venues like Expert Systems with Applications, IEEE Access, and Multimed Tools Appl. His collaborative network includes institutions in Algeria and international partners, reflecting a global impact in computational intelligence and computer vision.

Samuel Dahanمشاهده پروفایل

دانشیار

• Legal AI
• Dispute Resolution
• Global Work
• +۴ مورد دیگر

Samuel Dahan is an Associate Professor at Queen’s University Faculty of Law and Director of the Conflict Analytics Lab. He holds visiting faculty positions at Cornell University, Paris Dauphine University, ENA, and Harvard University. His expertise spans Legal AI, Dispute Resolution, and Global Work, with a focus on open-source platforms like OpenJustice and the Deel Lab for global employment policy. Education: MA: Sorbonne-Ecole Normale Supérieure Ulm LLM: Katholieke Universiteit Leuven PhD: University of Cambridge Research Interests: Dahan’s work integrates data science with legal challenges, including AI-driven legal tools, conflict resolution analytics, and global workforce compliance. He leads initiatives like OpenJustice, an open-source platform with over 20,000 monthly queries, and the Deel Lab for HR tech innovation. Notable Achievements: Secured $1.1M in grants (NSERC-MITACS Partnership). Published in top venues: AAAI, ICML, McGill Law Journal. Keynote speaker at the French Supreme Court Hearing, Stanford Codex, and Law Society of Ontario. Labs & Teams: Directs the Conflict Analytics Lab at Queen’s University and co-leads the Deel Lab. His teams develop tools like the Deel AI Classifier and MyOpenCourt, addressing legal challenges through data-driven solutions.

Selin Ahipasaogluمشاهده پروفایل

استاد

• Operational Research
• Convex Optimization
• Robust Optimization
• +۵ مورد دیگر

Prof. Selin Damla Ahipasaoglu is a Professor in Operational Research at the University of Southampton's School of Mathematical Sciences . She serves on the management team of the UKRI CDT SustAI (Artificial Intelligence for Sustainability) as Senior Tutor and Co-Lead for the Transportation and Logistics Theme . Her work bridges mathematical optimization with practical applications in sustainability, finance, and transportation systems. Research Interests : Convex Optimization Robust Optimization Discrete Choice Theory Experimental Design Machine Learning Current Research : Focused on robust optimization and its applications in discrete choice modeling, portfolio optimization, and transportation systems. She explores theoretical frameworks alongside real-world implementations, particularly through interdisciplinary projects like the UKRI CDT SustAI. Teaching : In the 2025/2026 academic year, she teaches MATH3017: Mathematical Programming and MATH2013: Operational Research II . She supervises PhD students in Mathematical Sciences, including Kexin Lai, Samuel Jericho Ward, and others.

• Artificial Intelligence
• Image Processing
• Narrative Planning
• +۳ مورد دیگر

Associate Professor Julie Porteous is affiliated with the School of Computing Technologies at RMIT University. Her research focuses on Artificial Intelligence applications including narrative planning, medical image processing, and human-agent interaction. She supervises research projects in areas such as dynamic transportation networks, medical imaging frameworks, and explainable AI in planning systems. Her work combines AI techniques with storytelling, medical diagnostics, and collaborative decision-making. Notable contributions include SellaMorph-Net for medical image segmentation and advancements in automated narrative generation systems. She actively contributes to conferences like AAMAS and AAAI, publishing on topics ranging from story sifting algorithms to intention communication in multiagent environments. Dr. Porteous collaborates on projects involving interactive narrative platforms, virtual urban environments, and neurofeedback systems for adaptive storytelling. She maintains an ORCID profile (0000-0003-4618-2359) and is open to supervising PhD/Masters students in her research areas.

Robert G. Kingمشاهده پروفایل

استاد

• Macroeconomics
• Monetary Economics
• Economic Growth

Robert G. King is a Professor at Boston University, specializing in Macroeconomics, Monetary Economics, and Economic Growth. He holds a PhD from Brown University and maintains an office at SSW 502. His research focuses on monetary policy credibility, inflation dynamics, and macroeconomic stability, with recent work exploring regime shifts and policy design in open economies. He actively advises BU's graduate students via scheduled Zoom meetings. Education: PhD in Economics from Brown University. His work bridges theoretical models (e.g., New Keynesian frameworks) with empirical analysis of inflation and productivity shocks. Notable contributions include studies on central bank credibility and the Volcker disinflation. Research Interests: King’s work addresses core macroeconomic questions such as how monetary policy expectations shape economic outcomes, the role of firm-level productivity shocks, and the implications of globalization for inflation-output tradeoffs. He also explores automation in systems management and telecommunications infrastructure optimization. Grants and Advising: While specific grants are not listed, his extensive publication record indicates sustained research activity. Students engage with him via BU’s Zoom platform, requiring appointment scheduling via Google Calendar. No lab affiliations are explicitly mentioned in the provided texts.

Jianping Luمشاهده پروفایل

استاد

• Medical Imaging
• Radiology
• Biomedical Engineering
• +۳ مورد دیگر

Professor Jianping Lu is a leading academic at the University of North Carolina at Chapel Hill, affiliated with the Department of Physics and Astronomy within the College of Arts and Sciences. His work focuses on advancing medical imaging technologies, particularly in X-ray and computed tomography (CT) systems, with a strong emphasis on carbon nanotube (CNT) X-ray sources. He holds a Ph.D. in Physics from the City University of New York (1988). Education: Ph.D. in Physics, City University of New York, 1988 Research Interests: Development of novel imaging systems, including stationary tomosynthesis and multisource CBCT Optimization of X-ray technology for clinical applications (e.g., oncology, cardiology, dentistry) Integration of artificial intelligence (AI) for diagnostic accuracy and automated analysis Portable and low-cost medical imaging solutions Recent Work Trends: His 2025 publications highlight advancements in AI-driven diagnostics for pancreatic cancer, improved contrast in adaptive radiation therapy, and stationary chest tomosynthesis systems. Key innovations include low-cost dual-energy CBCT and carbon nanotube-based X-ray arrays, which enhance image quality while reducing radiation exposure. His 2024 studies further explore cardiac imaging, dental tomosynthesis, and system optimizations for clinical adoption. Awards: None explicitly listed in the provided text. Advising & Grants: While student advisees are not listed, his research is likely supported by grants focusing on medical imaging innovation. Collaborations span physics, engineering, and clinical departments to bridge technical and clinical challenges. Labs/Teams: Likely affiliated with UNC’s imaging research groups, particularly those developing CNT X-ray technologies and clinical imaging systems for cancer and cardiovascular applications.

• Biomechanics
• Soft Tissue Mechanics
• Cardiovascular Biomechanics
• +۵ مورد دیگر

Gerhard Holzapfel is a Professor at TU Graz's Department of Biomechanics. His research focuses on biomechanics of soft biological tissues, cardiovascular systems, and advanced material modeling. He leads the Institute of Biomechanics, conducting experimental and computational studies on tissue mechanics, vascular diseases, and medical device design. Education : Details not explicitly provided in source text. Research Interests : Dr. Holzapfel's work spans constitutive modeling of soft tissues, computational fluid dynamics (CFD) in vascular systems, mechanobiology of cells and tissues, and biomaterials. He emphasizes translating biomechanical insights into clinical applications such as endovascular devices and surgical simulations. His studies often integrate microstructural analysis with macroscopic mechanical behavior to understand pathologies like atherosclerosis and aortic dissection. Publications : Recent work highlights advancements in fiber dispersion models for skin mechanics, Bayesian frameworks for material calibration, and CFD-driven evaluations of TEVAR (thoracic endovascular aortic repair). His articles emphasize predictive modeling of tissue behavior under various loading conditions, with applications in cardiology and regenerative medicine. Awards : No specific honors or fellowships mentioned in the provided text. Advising & Grants : No student/advisor relationships or grant details explicitly listed. The Institute of Biomechanics likely supports collaborative projects in biomechanical engineering and medical research. Labs/Teams : Director of TU Graz's Institute of Biomechanics, leading interdisciplinary teams in biomechanics, material science, and computational modeling. Collaborates with clinical partners on vascular biomechanics and surgical device development.

Nguyen Thanh Sonمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Multimodal Deep Learning
• Knowledge Base Systems
• +۳ مورد دیگر

Nguyen Thanh Son is a Research Scientist at the Artificial Intelligence Initiative under the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. He holds a PhD in Information Systems from the School of Information Systems, Singapore Management University (SMU), where he was advised by Associate Professor Hady Lauw. His research focuses on natural language processing, opinionated text mining, and multimodal deep learning. Previously, he completed a visiting PhD program at Carnegie Mellon University (CMU) and an internship at IBM Research Lab in Dublin, Ireland. He also earned a Bachelor of Information Systems from the University of Engineering and Technology (UET), Vietnam National University, Hanoi, with academic distinctions in research. Research Interests: His work spans natural language processing, emotion recognition, knowledge base systems, and agentic AI. He has contributed to advancements in large language models, multimodal encoding, and retrieval-augmented systems. Grants & Awards: He secured a Singapore Aerospace Programme grant (SGD 360,000) as PI and co-led an A*STAR grant (SGD 6 million). His accolades include the SMU Presidential Doctoral Fellowship and top research prizes during his undergraduate studies. Labs & Teams: Active in IHPC's AI initiatives and collaborated with CMU and IBM on projects like sentiment analysis and ontology building. His work bridges academic research and industrial applications in AI.

Jianliang Wuمشاهده پروفایل

استادیار

• Systems Security and Privacy
• Formal Analysis
• Machine Learning Security and Privacy
• +۴ مورد دیگر

Jianliang Wu is an Assistant Professor in the School of Computing Science at Simon Fraser University. His research focuses on systems security and privacy, formal analysis, and machine learning security. He holds a PhD from Purdue University (2022), and MSc and BSc from Shandong University (2015 and 2012). His research interests include Bluetooth security, IoT privacy, and formal methods for protocol analysis. He teaches courses such as Network Security, Software Security, and Networks, including CMPT 403 (System Security and Privacy) and CMPT 479 (Special Topics in Computing Systems). His work spans both theoretical and applied cybersecurity, with a strong emphasis on real-world system vulnerabilities and mitigation strategies. Recent research highlights include systematic reviews of Bluetooth protection strategies, analyses of IoT data exposure via companion apps, and formal model-driven discovery of protocol design flaws. His contributions address critical challenges in wireless communication security and IoT ecosystem vulnerabilities. No scientific awards are explicitly mentioned in the provided text. Advising and grants details are not available here. He is affiliated with the School of Computing Science, which hosts labs like the Tangent Lab, though direct lab affiliations for Wu are not specified.

Francesco Lelliمشاهده پروفایل

استادیار

• Artificial Intelligence
• Data Science
• Digitalization
• +۷ مورد دیگر

Francesco Lelli is an Assistant Professor at Tilburg School of Economics and Management (TiSEM), Tilburg University, where he holds a position in the Department of Information Systems and Operations Management. His academic work bridges theoretical research with practical applications in digitalization, smart technologies, and industry transformation. He actively contributes to the Master in Information Management program, teaching Business Process Integration and Service-Oriented Architecture courses. His research focuses on human-device interaction, artificial intelligence ethics, Industry 4.0 applications, and data-driven decision-making. He has published extensively on topics like smart device agency, cybersecurity in financial systems, and interoperability frameworks. Notable datasets include studies on S&P500 security breaches and human-smart device relationships. Recent publications highlight trends in AI ethics, Industry 4.0 digital twins, and sociotechnical system analysis. His work emphasizes societal relevance, with projects addressing technology adoption challenges and ethical dimensions of emerging technologies. Francesco maintains an open-door policy for collaboration and mentorship, offering thesis guidance in information systems, cloud computing, and AI applications. He actively engages with industry partners to ensure research translates into real-world impact.

• Artificial Intelligence
• Robotics
• Computer Vision
• +۴ مورد دیگر

Hulya Yalcin is an Assistant Professor in the Department of Mechanical Engineering at Istanbul Technical University. Her research focuses on artificial intelligence applications in robotics, computer vision, and precision agriculture. She leads projects in musculoskeletal modeling, plant phenology monitoring, and assistive technologies for elderly care. Her work contributes to UN Sustainable Development Goals related to innovation, health, and sustainable agriculture. Key projects include using deep learning for crop yield estimation and developing exergaming systems to improve elderly health. She has authored 52 research outputs and secured funding for initiatives like AISENSE (EU-funded exergames) and plant classification via computer vision. Publications span robotics control, medical engineering, and agricultural informatics. Notable contributions include knee orthosis gait learning via deep reinforcement learning and low-resource Turkish speech recognition improvements. As Principal Investigator, she manages projects on plant classification using CNNs, drone-based depth mapping, and multimodal assisted living systems. Her research bridges AI with practical applications in healthcare, agriculture, and robotics.