جستجوی استاد راهنمای دانشگاهی

Pedro Arruda Faustini is a Postdoctoral Research Associate at the School of Computing at Macquarie University. His research focuses on artificial intelligence, natural language processing, and network security. Macquarie University, School of Computing His work spans adversarial machine learning, privacy-preserving AI, and voice assistant technologies. He has contributed to semantic reformulation in spoken QA systems and applied reinforcement learning to network security. Recent research includes differential privacy in language models and reconstruction attack analysis in federated learning. Key article trends include adversarial text analysis , privacy metrics , voice assistant design , and secure machine learning . Collaborations highlight interdisciplinary work in network function virtualization and speech interfaces . Pedro's work has been published in venues like Computational Linguistics , ACL , and INTERSPEECH , with notable contributions to fake news detection and non-functional requirements estimation . Advising and Collaborations : Collaborated with researchers like Dr. Mark Dras, Dr. Shaday Moshe Tonni, and Dr. Shlomo Berkovsky. Collaborations span computational linguistics, embedded systems, and network security domains.

• Artificial Intelligence
• Natural Language Processing
• Network Security
• +۳ مورد دیگر

Dr. Daniel Beck is a Senior Lecturer in the School of Computing Technologies at RMIT University. His research focuses on interdisciplinary areas including Artificial Intelligence, Machine Learning, Information Systems, and their applications in Health Services and Linguistics. He actively supervises projects exploring topics like Large Language Models in design empathy, Alzheimer’s disease progression modeling, and multilingual NLP tasks. His work bridges computational methods with real-world challenges in healthcare, education, and technology ethics. Research Interests: His key areas include AI ethics, graph-based biomedical discovery, Bayesian modeling for disease trajectories, and NLP applications in clinical documentation. He contributes to advancing methodologies such as graph embeddings, state-space emotion modeling, and quality estimation in machine translation. Teaching & Supervision: Beck coordinates courses in Computing Technologies and mentors projects like 'Between activism and literacy: The mediatization of data journalism in Indonesia' and 'Can large language models provide investment advice like humans?' Publications: His 2023-2025 works emphasize AI’s role in healthcare (e.g., Alzheimer’s biomarker analysis), ethical AI autonomy debates, and multimodal NLP innovations. Recent studies highlight contributions to medical record generation via synthetic dialogue and empathic accuracy prediction in design contexts.

• Artificial Intelligence
• Machine Learning
• Information Systems
• +۵ مورد دیگر

Assoc. Prof. Roman Kern is affiliated with the Institute of Machine Learning and Neural Computation at Graz University of Technology and serves as Chief Scientific Officer at Know-Center Research GmbH , a competence center for Big Data analytics. His research bridges natural language processing, data science, and machine learning with a focus on causal inference and discovery, applied to scientific publication mining, intelligent transportation systems, and smart production. Research Interests : Causal inference, NLP, data science, trustworthy AI, knowledge discovery, and interdisciplinary applications. Projects : VanillaFlow (sustainable electrolytes for batteries), REWAI (causal discovery in textile manufacturing), and EPN-2024-RI (planetary science infrastructure). Teaching : Courses include Knowledge Discovery, Natural Language Processing, and Introduction to Scientific Working at TU Graz. His recent publications analyze causal relationships in semiconductor manufacturing, differential privacy, and LLM applications in healthcare and environmental monitoring. Roman Kern actively mentors students through thesis topics on causality, LLMs, and data privacy frameworks, while leading applied research projects with industry partners.

• Natural Language Processing
• Machine Learning
• Data Science
• +۷ مورد دیگر

Chatzisavvas Konstantinos is a Postdoctoral Fellow at Aristotle University of Thessaloniki. His research focuses on Machine Learning applications in renewable energy systems, assistive technologies, natural language processing, and electrical engineering. He has contributed to advancements in photovoltaic forecasting, low-vision assistive software, and sentiment analysis using deep learning architectures. His work bridges theoretical computer science with practical solutions for energy efficiency and accessibility. His research interests span machine learning, renewable energy forecasting, and the development of intelligent systems for healthcare and administrative services. Recent studies include transformer-based models for PV energy prediction and Rasch analysis for low-vision assessment tools. Publications highlight interdisciplinary efforts, combining quantum information theory with applied machine learning. Despite no explicit mention of academic awards or student advisement, his contributions to NLP, energy systems, and assistive tech reflect a strong focus on impactful research.

• Machine Learning
• Computer Science
• Renewable Energy
• +۳ مورد دیگر

Dr. Martin Kappus serves as Head of the Professorship for Accessibility (ad interim) at the ZHAW School of Applied Linguistics in Zurich. His research focuses on inclusive communication technologies, translation ergonomics, and the integration of language technology in academic contexts. He leads projects like 'Inclusive Information and Communication Technologies' and explores machine translation applications for academic texts. Key research interests include optimizing translation tool interfaces, accessibility standards for multilingual communication, and the human factors in translation workflows. His work bridges applied linguistics with technology development, emphasizing user-centered approaches in language industry practices. Recent projects include investigating automatic text simplification evaluation frameworks and comparing subtitling guidelines across Swiss regions. He has presented at international conferences such as EST Congress and HumEval, contributing to both theoretical and practical advancements in accessible communication. Publications span peer-reviewed journals like Revista Tradumàtica and Handbook of the Language Industry , reflecting his contributions to translation studies, technology, and accessibility. His edited volumes address barriers in communication design for educational and digital content.

• Inclusive Communication Technologies
• Translation Technology
• Machine Translation
• +۶ مورد دیگر

Annette McElligott is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. Her work spans digital health transformation, eHealth systems, natural language processing (NLP), and cognitive styles in computer science education. She has contributed to multilingual ontology development, technical text analysis, and Irish-English language technology. Her research interests include systemic digital change in healthcare, the adoption of ePrescribing in primary care, and cognitive assessment of computer systems students. She has pioneered interactive approaches to multilingual concept ontologies and explored distributed representations for cross-lingual lexical analysis. Her publications range from foundational NLP work in the 1990s (e.g., software manual parsing using link parsers) to recent studies on digital health education programs. She has collaborated on projects involving the Princeton WordNet extension, industrial parsing frameworks, and Irish language computational tools. No scientific awards or active grants are explicitly listed in the provided materials. Her advising record remains unreported here. She maintains a focus on bridging technical communication, healthcare informatics, and language technology through interdisciplinary approaches.

• Digital Health Transformation
• E-Health Systems
• Natural Language Processing
• +۳ مورد دیگر

Delphine Bernhard is a Lecturer in Computer Science at the Faculty of Languages, University of Strasbourg, since September 2011. She serves as head of the computer science department at the Faculty of Languages and co-head of the Master's degree in Language Technologies since 2016. Her research focuses on natural language processing, text mining, and lexical resource creation for under-resourced languages like Alsatian dialects. Institution: University of Strasbourg Academic Unit: Faculty of Languages Department: Computer Science Role: Lecturer & Department Head Teaching: Databases for CAWEB Master's program Her research explores natural language processing for under-resourced languages , particularly focusing on Alsatian dialects . Key areas include POS tagging , syntactic annotation , lexical resource development , and language revitalization through digital tools. She works on corpus creation , parallel corpora , and machine learning adaptation for regional language processing . Delphine Bernhard's publications demonstrate expertise in computational dialectology , low-resource language processing , linguistic annotation , and regional language preservation . Her work spans POS tagging , dependency parsing , emotion analysis in theater , and metadata management for regional languages of France . She contributes to the RESTAURE and DIVITAL projects, focusing on computational processing for regional languages . Her work includes FAIR corpus creation , spelling normalization , and lexicon development for Alsatian dialects . She explores cohesive features for text readability and develops crowdsourcing solutions for language resource bottlenecks .

• Natural Language Processing
• Text Mining
• Language Resources Creation
• +۵ مورد دیگر

Alejandro Martínez Mingo is an Associate Professor at the Autonomous University of Madrid (UAM) in the Social Psychology and Methodology department and an Adjunct Professor at IE University’s School of Sciences and Technology in Data Science. He holds a PhD in Psychology (ongoing), an MBA from EOI, and advanced degrees in Statistics and Psychology from UAM. His research focuses on quantum models in semantic representation, computational linguistics, and political framing analysis. He has contributed to the Spanish Ministry of the Interior’s violence risk assessment system through his work at the Forensic and Security Sciences Institute (2014–2016). As CEO of Wibber (2016–2018), he secured significant funding and won awards from accelerators like Actúa UPM and Lazarus. He collaborates with the Ricardo Olmos and Guillermo de Jorge-Botana research team at UAM, exploring intersections of computer science and natural language processing. His recent work emphasizes quantum computing applications and semantic vector spaces. Awards include recognition from Actúa UPM, Santalucía Impulsa, and Lazarus accelerators. He advises on cardiac diagnostics via strain analysis, as seen in his 2021 and 2019 studies.

• Data Science
• Computational Linguistics
• Natural Language Processing
• +۴ مورد دیگر

Dr. Alptekin Temizel is a Full Professor at the Graduate School of Informatics, Middle East Technical University (METU), Ankara, Turkey. He leads the METU Deep Learning and Computer Vision Lab (DLCV) and the GPU Research and Education Center. His research focuses on computer vision, deep learning, GPU computing, and medical image analysis. He holds a B.Sc. in Electrical and Electronic Engineering from METU (1999) and a Ph.D. in Computer Vision from the University of Surrey, UK (2006). Affiliations: Executive Board Member, Neuroscience and Neurotechnology Center of Excellence Executive Board Member, METU Center for Image Analysis (OGAM) DLI Certified Instructor and DLI University Ambassador (NVIDIA) Education: B.Sc.: Electrical and Electronic Engineering, METU, Turkey (1999) Ph.D.: Center for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK (2006) Research Interests: Deep Learning & Computer Vision Applications Medical Image Analysis & Healthcare AI Adversarial Machine Learning & Model Security GPU Parallel Computing & System Optimization Federated Learning in Medical Imaging Recent Achievements: 3rd place in Federated Brain Tumor Segmentation (FeTS) Challenge at MICCAI 2021 Developed SAHI package (2M+ downloads) LIMUC dataset for Ulcerative Colitis endoscopy Teaching: MMI 727: Deep Learning: Methods & Applications MMI 713: Applied Parallel Programming on GPU DI 725: Transformers and Attention-Based Deep Networks MMI 712: Machine Learning Systems Design & Deployment

• Computer Vision
• Deep Learning
• GPU Computing
• +۳ مورد دیگر

Dr. Sriparna Saha is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Patna, India. She holds a Ph.D. from the Indian Statistical Institute Kolkata and has held leadership roles including Head of Department (2021-2023) and Associate Dean for Research and Development (2019-2021). Her research focuses on AI, machine learning, natural language processing, bioinformatics, and multiobjective optimization. She has authored over 400 publications with an h-index of 38 and received awards such as the NASI Young Scientist Platinum Jubilee Award and Google India Women in Engineering Award. Her work spans multimodal systems, medical image analysis, and computational social systems. Education: M.Tech (2005) and Ph.D. (2011) in Computer Science from Indian Statistical Institute Kolkata. Research Interests: Multimodal information processing, NLP, machine learning, bioinformatics, and optimization techniques. Awards: Includes Lt. Rashi Roy Memorial Gold Medal, BIRD Award, and multiple fellowships (Humboldt, CNRS, etc.). Administrative Roles: IEEE Student Branch Councilor, Senate Member, and Visvesvaraya Nodal Officer at IIT Patna. Her recent work includes advancements in multimodal recommendation systems, breast cancer prognosis models, and computational social systems for crisis management. She has also contributed to hate speech detection in multilingual contexts and medical imaging diagnostics.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۵ مورد دیگر

Ilia Markov is an Assistant Professor at the Vrije Universiteit Amsterdam, affiliated with both the Faculty of Social Sciences and Humanities and the Network Institute. His research focuses on computational linguistics, natural language processing, and artificial intelligence, with particular emphasis on hate speech detection and counterspeech strategies. Education: PhD in Computer Science (with honors) from the National Polytechnic Institute, Mexico (2018) Dr. Markov's research aims to foster more inclusive and respectful online communication by mitigating online hate speech and developing context-aware, personalized counterspeech strategies tailored to authors' sociodemographic profiles. He also investigates cross-domain scalability and the reasoning capabilities of AI models. His work bridges computational linguistics with social computing, focusing on practical applications for creating safer online environments. His research demonstrates technical sophistication in developing novel computational methods while maintaining awareness of social implications. His publication record shows a clear trajectory from foundational work in authorship analysis and native language identification to current research on hate speech detection and counterspeech generation. Recent publications emphasize multimodal approaches that integrate text and image analysis, cross-lingual transfer learning techniques, and ethical considerations in deploying AI systems for social media moderation. His work increasingly addresses low-resource language scenarios and the challenges of adapting models across different social contexts. Scientific Awards and Recognition: Outstanding Academic Performance Award for PhD students at the National Polytechnic Institute Senior Area Chair for LREC-COLING 2024 Area Chair for LREC 2026 Dr. Markov has co-organized several international competitions on automatic authorship identification and serves in editorial roles for major conferences in computational linguistics. His collaborative work spans multiple institutions across Europe and Latin America, reflecting the international nature of his research community. He has published over 65 peer-reviewed papers in journals and conference proceedings, demonstrating consistent productivity and impact in his field. As part of the Network Institute at VU Amsterdam, Dr. Markov contributes to interdisciplinary research that combines computational methods with social science perspectives to address contemporary challenges in digital communication. His affiliation with this institute provides a rich environment for exploring the societal implications of his technical work while maintaining rigorous methodological standards.

• Computational Linguistics
• Natural Language Processing
• Artificial Intelligence
• +۶ مورد دیگر

Luis Morgado da Costa serves as an Assistant Professor at the Faculty of Social Sciences and Humanities and the Network Institute of Vrije Universiteit Amsterdam, specializing in computational approaches to language resources and multilingual systems. His research spans Computational Linguistics , Natural Language Processing , and Corpus Linguistics , with concentrated expertise in WordNet development, Semantic Networks , and Multilingualism . He pioneers methodologies for constructing lexical databases across diverse languages, particularly focusing on under-resourced linguistic communities through open-source frameworks. Recent publications demonstrate consistent innovation in lexical resource expansion, including rapid collection techniques for languages like Abui and sense-tagged corpora for Cantonese. His work bridges theoretical linguistics with practical NLP applications, emphasizing cross-lingual interoperability and open-access data sharing. At Vrije Universiteit Amsterdam, he teaches foundational courses including Introduction to Python for Humanities , Programming in Python for Text Analysis , and Advanced NLP , while maintaining active affiliation with the Network Institute's interdisciplinary research on digital communication systems.

• Computational Linguistics
• Natural Language Processing
• Multilingualism
• +۴ مورد دیگر

Dr. William Teahan is a Lecturer in the School of Computer Science and Engineering at Bangor University. His research focuses on Artificial Intelligence, Machine Learning, and Natural Language Processing, particularly applying text compression-based models to Information Retrieval and text mining. Prior to Bangor, he held roles including Research Fellow at Robert Gordon University (1999-2000), Invited Researcher at Lund University (1999), and Research Assistant at the University of Waikato (1998), where he completed his Ph.D. in text compression models for English text. Key research interests include AI agent behavior, evolutionary programming, and cross-linguistic NLP applications (e.g., Arabic, Welsh, Chinese). He leads projects such as KESS II (2018-2024) and AMBER (2013-2018), focusing on data visualization, procedural animation, and organic photovoltaic material analysis using machine learning. Collaborations span robotics, virtual reality, and ethical AI frameworks. Teahan’s work bridges theoretical advancements in compression algorithms with practical applications in text mining, OCR systems, and energy materials. His contributions include developing compression-based toolkits and exploring VR’s impact on parameter optimization in animation systems.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Davide Picca is a Lecturer (MER 2) at the Section of Language and Information Sciences, Faculty of Letters, University of Lausanne since 2016. His academic journey includes a PhD in Computer Science and Mathematical Methods (2010, University of Lausanne) and a degree in Philosophy of Science (specializing in Cognitive Science, 2003, University of Bologna). Research focuses on formal ontologies and semiotic theories , particularly applied to computational hermeneutics, moral foundation prediction, and cultural heritage digitization. Collaborations include Columbia University, ISTC-CNR Rome, Yahoo! Research Barcelona, and IBM Research. Key contributions span Emotional analysis in classical literature (Dostoevsky, Homer, Shakespeare) Ontology-based systems for Project Gutenberg texts and legal corpora Interdisciplinary methods combining fluid dynamics and emotion modeling Recent work explores AI ethics through semiotic lenses, moral prediction frameworks, and computational approaches to intangible cultural heritage preservation.

• Formal Ontologies
• Semiotics
• Computational Linguistics
• +۳ مورد دیگر

Michael Piotrowski is an Associate Professor in the Section of Language and Information Sciences at the University of Lausanne (UNIL), appointed since August 2021. He holds expertise in computational linguistics, digital humanities, and historical text processing. His career includes roles as a software developer, researcher, and academic, with notable contributions to the Leibniz Institute for European History (Mainz) and the DARIAH European infrastructure project. He earned his doctorate in computer science from Otto von Guericke University Magdeburg with a thesis on document-oriented e-learning components. Research interests focus on knowledge representation, formal modeling in humanities, and computational approaches to historical texts. His work bridges computer science and the humanities, emphasizing interdisciplinary innovation. Notable publications include foundational texts like Natural Language Processing for Historical Texts (2012) and contributions to computational historiography, digital humanities institutional frameworks, and uncertainty modeling in historical analysis. Piotrowski has led projects such as managing digitization of Swiss legal sources and developing tools for historical text processing. His academic contributions span e-learning technologies, NLP applications, and computational methods for cultural heritage. He actively participates in international DH initiatives and publishes on methodological challenges in digital humanities.

• Digital Humanities
• Computational Linguistics
• Historical Text Processing
• +۴ مورد دیگر