جستجوی استاد راهنمای دانشگاهی

Rage Uday Kiranمشاهده پروفایل

دانشیار

• Data Mining
• Parallel Computation
• Air Pollution Data Analytics
• +۳ مورد دیگر

Prof. Rage Uday Kiran is an Associate Professor at the University of Aizu in Aizu wakamatsu, Fukushima, Japan, with additional visiting researcher appointments at the University of Tokyo and the National Institute of Information and Communications Technology (NICT) in Tokyo. He holds a PhD in Computer Science from the International Institute of Information Technology, Hyderabad, and has published over 50 articles in top-tier venues including EDBT, SSDBM, PAKDD, and DASFAA. Education PhD in Computer Science - IIIT-Hyderabad, India (2005-2011) MS in IT Agriculture - DA-IICT, India (2003-2005) B.Tech in Agriculture Engineering - Acharya N. G. Ranga Agricultural Engineering College, India (1999-2003) Research Focus Dr. Kiran specializes in developing novel data mining models and high-performance algorithms for temporal, spatiotemporal, and transactional databases. His primary research explores pattern mining techniques for rare item discovery, parallel computation optimizations, and real-world applications in air pollution analysis, traffic congestion prediction, agricultural ICT systems, and recommender systems. His recent work focuses on utility-based pattern discovery in spatiotemporal contexts and periodic pattern detection in temporal databases, emphasizing scalability and efficiency for large-scale datasets. Professional Experience Project Assistant Professor - University of Tokyo (2015-2020) Researcher - NICT Tokyo (2015-2020) Post Doctoral Researcher - University of Tokyo (2012-2015) Technical Contributions Dr. Kiran maintains public datasets for pattern mining research and develops open-source tools including the PAttern MIning Python Kit (PAMI-PyKit). His technical expertise spans C/C++/Java, database systems (MySQL/PostgreSQL), web technologies, and cloud platforms (Azure/AWS).

Krishnamurthy Dvijothamمشاهده پروفایل

پژوهشگر

• AI Safety
• Robustness in AI
• Differential Privacy
• +۵ مورد دیگر

Krishnamurthy Dvijotham (Dj) is a research scientist with a focus on developing safe, reliable, and secure AI systems. His current role as a Research Lead at ServiceNow Research (2024-2025) builds on his extensive experience at Google DeepMind (Researcher, 2017-2024), Pacific Northwest National Laboratory (Researcher, 2016-2017), and a postdoctoral fellowship at Caltech's Center for Mathematics of Information. Research Interests: Mathematical optimization, control theory, AI robustness, differential privacy, neural network verification, power systems optimization. Scientific Awards: Best Paper at ICML 2024, Best Paper at UAI 2018, Best Paper at Constraints 2016, Best Student Paper at UAI 2014. Dvijotham's work emphasizes the application of rigorous mathematical frameworks to AI systems. His publications span certified robustness , adversarial defense mechanisms , privacy-preserving learning , and power grid optimization , reflecting interdisciplinary contributions to both theoretical and applied domains. He has mentored numerous PhD students and postdoctoral fellows, many of whom now hold academic or research positions at institutions like UC Berkeley, Google DeepMind, and Microsoft Research. His recent articles highlight advancements in diffusion models , selective deferral systems , and formal verification techniques , with a strong focus on security and reliability in AI deployment.

Helena Galhardasمشاهده پروفایل

دانشیار

• Databases
• Data Cleaning
• Data Integration
• +۴ مورد دیگر

Helena Galhardas is an Associate Professor at the Department of Computer Science and Engineering at Instituto Superior Técnico, University of Lisbon , and a researcher at INESC-ID . Her work focuses on data cleaning, data integration, information extraction, and ETL systems , with applications in clinical data management and big data frameworks. Academic Affiliation: Associate Professor, Department of Computer Science and Engineering, Instituto Superior Técnico, University of Lisbon Research Unit: INESC-ID (Information and Decision Support Systems) Contact: helena.galhardas@tecnico.ulisboa.pt | +351 21 423 32 46 Her research spans theoretical and applied domains, including clinical data systems like Umedicine for structured medical data management and PiCaSSo for pediatric palliative care. She has developed frameworks like AJAX for data cleaning, REEL for relation extraction, and ∂u∂u for distributed duplicate detection. Her work integrates machine learning with database systems , particularly in workflow optimization and one-to-many data transformations. Scientific contributions include: Best Student Paper Award (2009) Nomination for Best Paper Award (2009) Research projects: PiCaSSo (2025-26): Pediatric Palliative Care Support System LAIfeBlood : AI for Blood Management Data2Help : Data Science for EMS Optimization DataStorm : Cloud-based Data Management

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

Natalie Schluter is a Lecturer in Theoretical Computer Science at the IT University of Copenhagen , affiliated with NLPnorth and Machine Learning Algorithms. Her research focuses on Natural Language Processing (NLP) , Machine Learning , and Data Science , with specific contributions to automatic summarization, cross-lingual inference, and dependency parsing. She has secured multiple research grants and actively engages in public discourse on gender equality in academia. Principal Investigator (PI) for projects like GOOGLELOWNLP (2020–2025) and Danish Language Inclusion (2019–2021). Key research areas: Danish language technology, neural networks, and syntactic modeling. Email: nael@itu.dk Her publications highlight trends in machine translation , graph-based parsing , and low-resource NLP , often leveraging deep neural networks. She has contributed to 18 publications and participated in organizing events like the Women in Data Science (WiDS) Copenhagen conference. Media contributions include advocacy for gender equality in IT and NLP.

Manuel Lama Penínمشاهده پروفایل

استاد

• Machine Learning
• Process Mining
• Predictive Monitoring
• +۶ مورد دیگر

Manuel Lama Penín is a Full Professor at the Research Center on Intelligent Technologies (CiTIUS) with the University of Santiago de Compostela. His research bridges machine learning, process mining, and semantic modeling to address challenges in healthcare, industry, and e-learning. He has led 29 of 51 R&D projects and authored over 150 scientific works, including 52 journal articles. Research Areas: Process Mining & Conformance Checking Predictive Monitoring & Drift Detection Semantic Modeling & Service Computing Social Workflow Analysis & Data-to-Text AI in Healthcare & Educational Technologies Notable Projects: TRANSFIRESAUDE (2023, EU Health R&I Ecosystems) AQUATECHInn 4.0 (2023, Aquaculture Education) INCEPTION (2021, Concept Drift in Process Mining) Scientific Recognition: Recipient of the Transfer Technology award from the Galician Royal Academy of Sciences for co-founding InVerbis Analytics, a spin-off commercializing process mining research. Article Trends: His recent publications focus on explainable AI integration in EU regulations, drift detection methodologies, and natural language generation for process documentation. Collaborative efforts emphasize cloud-based solutions, healthcare process formalization, and predictive modeling across sectors.

• Deep Learning
• Natural Language Processing
• Artificial Intelligence
• +۲ مورد دیگر

Rowanda D. Ahmed is an Assistant Professor in the Department of Computer Engineering at Uskudar University, Istanbul, Turkey, and serves as the Data Science Ambassador for Stanford University in Turkey supporting Women in Data Science (WiDS) initiatives. Her academic credentials include: Bachelor of Science in Computer Engineering from Islamic University, Gaza, Palestine (2011) Master of Science in Computer Engineering from Islamic University, Gaza, Palestine (2011) Doctor of Philosophy in Computer Science from Izmir Institute of Technology, Izmir, Turkey (2019) Dr. Ahmed's research spans Artificial Intelligence, Machine Learning, and Data Mining with specialized expertise in Deep Learning and Natural Language Processing. Her work focuses on developing advanced computational models for text analysis and decision support systems, culminating in a published book and peer-reviewed publications. Her recent publication examines hybrid text summarization techniques that bridge extractive and abstractive approaches to improve cross-domain applicability, reflecting her commitment to advancing NLP methodologies through integrative frameworks. Through her WiDS Ambassador role, she actively promotes gender diversity in data science via mentorship programs and community engagement across Turkey.

• Comprehensibility of Texts
• Reading
• Writing Skills
• +۷ مورد دیگر

Dr. Jacqueline Evers-Vermeul is an Associate Professor at the Department of Languages, Literature and Communication at Utrecht University, specializing in Language and Communication within the Humanities Institute for Language Sciences. Her academic career spans over two decades since her promotion at Utrecht University in 2005, with a consistent focus on text structure, comprehension, and language education. Her research interests center on the comprehensibility of texts, reading and writing skills development, subject didactics, methods for document design and evaluation, and testing and assessment. She investigates how textual features affect comprehension across different educational contexts, with particular emphasis on discourse structure, connective use, and the relationship between text structure and content knowledge acquisition. Her work bridges theoretical linguistics with practical educational applications, particularly in primary and secondary education settings. Analysis of her recent publications reveals a strong trajectory toward integrating text structure instruction across disciplines, especially in science education. Her research shows increasing focus on practical applications for teachers, with numerous publications in both academic and professional journals. She has developed a significant body of work examining how explicit instruction in text structure enhances reading comprehension, writing skills, and content knowledge acquisition, with particular attention to vulnerable student populations. Dr. Evers-Vermeul serves in several important educational roles, including as Chair of the committee for the final examinations of Dutch for havo and vwo since 2020, Member of the Dutch Masters Team since 2019, and Member of the Advisory Board for the Recalibration of the Knowledge Base Teachers' College for Primary Education since 2024. Her current research projects include 'Bewust geletterd in het VO: lezen en schrijven met genres' (2024-2029), a large-scale NWO-funded study examining how genre-based approaches can improve reading and writing instruction in secondary education. Chair of the final examination committee for Dutch pre-university education (havo and vwo) since August 2020 Member of the Dutch Masters Team since January 2019 Member of the Advisory Circle for the Recalibration of Knowledge Bases for Primary Education since July 2024 Member of the Steering Committee for the Research Agenda for Primary Education Testing since January 2025 Former Chair of the Association Interuniversity Consultation on Language Proficiency (VIOT; 2018-2022) Her collaborative approach is evident in her numerous research partnerships across Dutch universities and educational institutions. She frequently works with colleagues from Groningen, Amsterdam, Nijmegen, and various teacher training colleges, demonstrating her commitment to bridging research and practice in language education.

Neslihan Iskenderمشاهده پروفایل

پژوهشگر

• Crowdsourcing
• Human-Computer Interaction
• Natural Language Processing
• +۳ مورد دیگر

Neslihan Iskender is a researcher at the Quality and Usability Labs of Technical University of Berlin since May 2017, focusing on crowdsourcing methodologies for quality assessment and natural language processing. She holds a BSc and MSc in Industrial Engineering from Karlsruhe Institute of Technology, with a specialization in technology and innovation management. Research Areas: Crowdsourcing for quality evaluation, hybrid human-machine workflows, real-time interaction systems, usability/UX/QoE assessment, and internal crowdsourcing in corporate environments. Teaching: Co-teaches courses in Quality & Usability, Interdisciplinary Media Projects, and Usability Engineering exercises since SS 2018. Projects: Leads ERICS (EIT-Digital refugee communication service), contributes to DEKA (digital innovation platform), OurPuppet (caregiver support systems), and ICU (employee participation solutions). Contributions: Published 11+ peer-reviewed works between 2019-2021 on crowdsourcing reliability, chatbot UX, German summarization metrics, and hybrid NLG workflows.

• Constrained Clustering
• Explainable AI
• Constraint Programming
• +۴ مورد دیگر

Thi-Bich-Hanh DIEP-DAO serves as a Lecturer with Habilitation à Diriger des Recherches (HDR) at the University of Orleans, where she is affiliated with the LIFO laboratory (Laboratory of Informatics of Orléans). She holds significant administrative roles including THAT Lab correspondent at the Doctoral School and Member of the Board, demonstrating leadership in academic governance and doctoral education. Her research centers on constrained clustering methodologies, with evolving focus areas including explainable AI, constraint programming applications, and knowledge integration in machine learning systems. Early work established foundational approaches for constraint-based clustering using declarative frameworks, while recent publications demonstrate sophisticated extensions to mineral prospectivity mapping, social media analysis, and knowledge graph-enhanced image classification. Her research consistently bridges theoretical constraint programming with practical applications across diverse domains. Analysis of her publication trends reveals increasing emphasis on explainability and knowledge integration since 2020, with notable contributions to incremental clustering systems and graph-based knowledge representation. Her work maintains strong methodological consistency in constraint programming while expanding into new application areas, particularly evident in her 2023-2025 publications on mineral prospectivity mapping and tweet-based event characterization. As an HDR-qualified researcher, Dr. DIEP-DAO actively supervises doctoral students and contributes to academic training through her roles in the Doctoral School. Her extensive collaboration network, particularly with Christel VRAIN, has produced over 60 publications since 2010, reflecting consistent research productivity. She is integral to the LIFO laboratory's data mining and constraint programming research group, where her work on declarative clustering approaches forms a core research pillar. Current projects focus on knowledge graph integration for explainable image classification systems and constraint-based social media analysis frameworks.

Charles Kahnمشاهده پروفایل

استاد

• Artificial Intelligence in Radiology
• Medical Imaging Informatics
• Clinical Decision Support Systems
• +۳ مورد دیگر

Charles Kahn is a Professor of Radiology with expertise in Artificial Intelligence in Radiology , Medical Imaging Informatics , and Clinical Decision Support Systems . His work focuses on integrating AI into clinical workflows, standardizing medical imaging practices, and developing ontologies to enhance healthcare interoperability. His research spans: AI-driven radiology reporting systems Automated imaging analysis using deep learning Language model applications for clinical guidelines Standardization frameworks for medical AI Ontology-based diagnostics and data integration Key trends in his recent work include the development of vision-language models for 3D CT representations, automated integration of AI results into radiology reports, and strategies to reduce bias in healthcare AI systems. His publications emphasize rigorous validation, reproducibility, and clinical adoption of AI tools. Scientific contributions and awards include: Fellow of the American College of Radiology (FACR) Fellow of the American College of Medical Informatics (FACMI) CHECKLIST FOR ARTIFICIAL INTELLIGENCE IN MEDICAL IMAGING (CLAIM) PRISMA AI reporting guidelines QUADAS-AI quality assessment tool He has mentored radiologists and imaging scientists, contributed to AI education, and addressed challenges in clinical AI deployment through collaborative panels with RSNA and MICCAI experts.

David Liben-Nowellمشاهده پروفایل

استاد

• Computational Social Sciences
• Social Networks
• Theoretical Computer Science
• +۵ مورد دیگر

David Liben-Nowell is a Professor in the Department of Computer Science at Carleton College, with research spanning computational social sciences, algorithmic modeling, and interdisciplinary applications of theoretical computer science. He contributes to ACM Technical Symposia on Computer Science Education (SIGCSE) and maintains active roles in academic leadership as an Associate Provost since 2022. AISTATS'25: Machine Learning & Social Choice SIGCSE'24: Student Enrollment Systems SIGCSE'22: Intro CS Pedagogy His research explores social network structures , spoken-word recognition , and computational biology through algorithmic frameworks, with applications in peer-to-peer systems and game theory. Recent work on AISTATS'25 addresses probabilistic ranking models, while SIGCSE publications focus on educational algorithms.

• Natural Language Processing
• Semantic Web Technologies
• Machine Learning
• +۳ مورد دیگر

Carlos Badenes-Olmedo is an Associate Professor in the Computer Systems Department at Universidad Politécnica de Madrid (UPM) . He is a member of the Ontology Engineering Group (OEG) , AI.nnovation Space , and co-founder of the spin-off company LibrAIry S.L. , which offers AI services for NLP and knowledge management. He also co-chairs the Knowledge Graph Summarization Workshop at ISWC. His research focuses on Natural Language Processing , Semantic Web Technologies , and Knowledge Graphs with applications in multilingual document similarity, topic modeling, and biomedical informatics. He has published extensively on cross-lingual search, scalable hashing algorithms, and AI in public health and procurement. Notable scientific awards include: DAAD Postdoc Funding (2021) Margarita Salas Mobility Grant (2021) ActuaUPM 3rd Prize for Best Startups (2020) Finalist for Margarita Salas Research Awards (2022) Finalist for Innovation Talent Recruitment Award (2021) He contributes to software engineering with tools like librAIry for distributed text mining, Corpus Viewer for NLP pipelines, and r4r for RESTful APIs over RDF data. His work bridges academia and industry through projects like TheyBuyForYou and TBFY Harvester for EU public procurement.

Gregory Dudekمشاهده پروفایل

استاد

• mobile robotics
• marine robotics
• foundation models for robotics
• +۱۳ مورد دیگر

Gregory Dudek is a James McGill Chaired Professor and Director of the School of Computer Science at McGill University . He leads the Mobile Robotics Laboratory , focusing on sensor-based robotics, multi-robot systems, and underwater perception. Education: B.Sc. (Queen’s University), M.Sc. (University of Toronto), Ph.D. (University of Toronto, Computer Vision) His research spans computational principles for mobile robotics, including foundation models (3FM framework for planning/self-healing), amphibious robots (Aqua family), and multi-sensor mapping . Key applications include reef monitoring, autonomous exploration, and robust field robotics. Awards : IEEE Gold Medal (2017) CS-CAN/INFO-CAN Lifetime Achievement Award (2024) Acfas Bombardier Prize (2010) Former students like Nicholas Roy (MIT), Florian Shkurti (Toronto), and Ioannis Rekleitis (Delaware) now hold faculty positions. The lab’s work integrates marine robotics and 5G/6G network optimization .

Josef van Genabithمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Translation
• Cross-lingual Processing
• +۳ مورد دیگر

Prof. Dr. Josef van Genabith serves as a Professor at the German Research Center for Artificial Intelligence (DFKI) in Saarbrücken, leading the Multilinguality and Language Technology research department. His work bridges theoretical and applied aspects of language technology with direct societal impact. His research spans Natural Language Processing (core focus), Machine Translation , and Cross-lingual Processing , with expanding interests in Sign Language Processing and AI for Education . He develops systems addressing real-world language barriers while emphasizing ethical AI frameworks through projects like TRAILS (Trustworthy and Inclusive Machines). Recent publications reveal three convergent trends: (1) rigorous evaluation of LLMs across linguistic boundaries in fact verification, (2) educational technology innovations for online learning accessibility, and (3) multimodal approaches to sign language data processing using social media sources. These reflect his commitment to inclusive language technology applicable across diverse communication modalities. He directs major initiatives including EUC PT (EU Council Presidency Translator), DEEPLEE (Deep Learning for End-to-End Language Technology Applications), and QT21 (Quality Translation 21), all targeting the elimination of language barriers in European digital infrastructure. His lab maintains active collaborations with EU institutions and industry partners focused on deployable language solutions.

• Human-Computer Interaction
• Computer-Supported Cooperative Work (CSCW)
• Healthcare Technology
• +۸ مورد دیگر

Ignacio Avellino is a tenured Research Fellow at Sorbonne Université working in the Institut des Systèmes Intelligents et de Robotique (ISIR) as part of the RPI-Bio team. His research focuses on Human-Computer Interaction at the intersection of remote collaboration (CSCW) , healthcare , learning , and robotics . Specializing in Surgical Telementoring , he studies technology interaction in operating rooms, particularly with surgical robots for remote expert mentoring. PhD in Human-Computer Interaction (2017) from Université Paris Saclay Postdoctoral Researcher at Interactive Systems Research Center, UMBC Postdoctoral Researcher at ISIR His research interests include telepresence systems , augmented reality , human-robot interaction , and medical informatics . Recent work explores AR-based surgical mentoring , medical discharge letter analysis , and collaborative surgical video summarization . Scientific contributions have been supported by the ISI grant (IUIS, 2022) . He supervises multiple PhD students including Anastasyia Zakreuskaya , Amanda Koh , and Nour Karoui , covering topics like AR surgical planning and interactive operating room systems . Active in academic service, he serves on the ACM CHI 2025 Health Subcommittee and co-chaired IHM '24 .