جستجوی استاد راهنمای دانشگاهی

Recep Firat Cekinel is a Turkish NLP researcher who recently obtained his Ph.D. in Computer Engineering from Middle East Technical University (METU). He spent 13 months as a visiting predoctoral researcher at the University of Tübingen and is currently a researcher on the EU-funded EXA4MIND project, where he develops NLP pipelines that convert natural language into database queries using large language models. His research focuses on responsible, scalable AI systems and bridges foundational NLP work with real-world applications. Education: Ph.D. in Computer Engineering, Middle East Technical University (METU), Türkiye Visiting Predoctoral Researcher, University of Tübingen, Germany (13 months) Research Interests: Dr. Cekinel’s work spans natural language processing , multimodal fact-checking , explainable AI , and large language models . He is particularly interested in building responsible and scalable AI systems that integrate foundational research with practical deployments, such as natural-language interfaces for high-performance computing environments. Recent Publication Trends: His 2025 publications reveal a concentrated effort on multilingual and multimodal fact-checking , satire-style debiasing , and NL-to-database-query generation . Earlier work explores graph-based event extraction , Turkish irony detection , and cultural-heritage text mining , demonstrating a trajectory from low-resource Turkish NLP toward globally applicable, responsible-AI systems. Contact & Code: Email: rfcekinel@ceng.metu.edu.tr Office: METU Computer Eng. Dept. A-206, 06800 Ankara, Turkey Phone: +90-(312)-210-5593 GitHub: firatcekinel Google Scholar: profile available

• Natural Language Processing
• Multimodal Fact-Checking
• Explainable AI
• +۷ مورد دیگر

Dr. Indika Kahanda is an Assistant Professor in the School of Computing at the University of North Florida , where he leads the BioMedInfo Lab focusing on bioinformatics and biomedical informatics. Previously, he held the same position at the Gianforte School of Computing (Montana State University) from 2018 to 2023. Education: PhD in Computer Science (2016), Colorado State University MS in Electrical and Computer Engineering (2010), Purdue University BS in Computer Engineering (2007), University of Peradeniya, Sri Lanka His research applies machine learning and natural language processing to large-scale biomedical data, with key focuses on computational methods for functional genomics and automated text mining tools for biomedical literature. Current projects include Pangenomics , student misconception detection , and inconsistency detection in medical literature . Recent publications highlight his work in LLM evaluation for healthcare applications, protein function prediction , and medical transcription error analysis . He contributes to biomedical datasets like miRNAFinder and MLHCBugs, with technical expertise in deep learning, ensemble methods, and metamorphic testing.

• Bioinformatics
• Biomedical Informatics
• Machine Learning
• +۳ مورد دیگر

Ljubiša Bojić is a Senior Research Fellow at the Digital Society Lab (DigiLab) within the Institute for Philosophy and Social Theory at the University of Belgrade and concurrently at the Institute for Artificial Intelligence of Serbia. He serves as External Faculty at the Complexity Science Hub Vienna, focusing on AI's societal implications, particularly AI alignment, recommender systems, and metaverse ethics. His work bridges communication science, futurology, and digital humanism to address critical challenges in technology governance. Education: Ph.D. in Communication Science, University of Lyon II, France (2014) Research Focus: Bojić investigates how AI systems can uphold human values through ethical design, with emphasis on recommender algorithms as the most powerful social force shaping contemporary society. His pioneering work on digital addictions examines how AI-driven platforms create echo chambers and social polarization. He advocates for declaring recommender systems a public good and digital identity a human right, exploring both the addictive risks and therapeutic potentials of immersive technologies like the metaverse. Publication Trends: His recent output (2022-2025) reveals a strategic evolution from analyzing digital addiction mechanisms toward developing concrete AI governance frameworks. Key themes include linguistic pragmatics in large language models, consciousness metrics in AI, and cross-platform social dynamics. His research increasingly informs global policy through rigorous computational social science methods applied to real-world challenges like vaccine hesitancy and political polarization. Scientific Recognition: Fellow, Institute for Human Sciences Vienna (IWM) (2023) Member, United Nations Environment Programme Foresight Expert Panel (2023) Policy Engagement: Bojić co-developed Serbia's AI ethics standards and advised Spain's AI strategy. His Horizon Europe project TWON generated Policy Handout No. 8, mandating algorithms to deliver emotionally balanced, diverse content. His 'CERN for AI' framework influenced G7 policy briefs and was featured by the World Economic Forum. He regularly testifies before international bodies on AI governance. Institutional Leadership: As founder of EMERGE: Forum on the Future of AI Driven Humanity and initiator of the Belgrade Digital Freedom Pledge (signed by OSCE officials), he drives global conversations on digital rights. At DigiLab, he leads research on social media dynamics using big data analytics, while coordinating international networks like COST Action CA21129 on opinion analysis.

• Artificial Intelligence
• AI Ethics
• Recommender Systems
• +۵ مورد دیگر

Maria Halkidi is an Associate Professor in the Department of Digital Systems at the University of Piraeus, Greece, where she conducts cutting-edge research in data mining and machine learning with over two decades of academic experience. Her educational background includes: Bachelor's degree in Informatics from the University of Piraeus (1997) Master's degree from Athens University of Economics and Business (1999) Ph.D. from Athens University of Economics and Business (2003) Dr. Halkidi's research focuses on fundamental and applied aspects of data mining, particularly recommender systems, graph data mining, cluster validity assessment, and distributed data mining. Her work bridges theoretical frameworks with practical implementations in sensor networks, social media, and real-time analytics, contributing significantly to algorithmic development in these domains. Analysis of her recent publications reveals a strong trajectory toward fairness and diversity optimization in recommender systems, alongside innovative approaches to graph clustering quality assessment and scalable sentiment analysis. Her research consistently addresses real-world challenges in dynamic data environments, with increasing emphasis on multi-stakeholder optimization and privacy-aware recommendation frameworks. Scientific awards: No specific awards or honors were documented in the provided materials. Dr. Halkidi has participated extensively in National and European-funded research projects, including a prestigious Marie-Curie fellowship at the University of California, Riverside. She serves on program committees for major international conferences in data mining and machine learning, demonstrating active community engagement. While specific graduate students aren't listed in the source materials, her professorial role indicates ongoing mentorship of Master's and Ph.D. candidates. She maintains active research affiliations with the Network oriented systems & services lab and the DataStories research group at the University of Piraeus, where she collaborates on interdisciplinary projects involving big data analytics, social network analysis, and distributed systems.

• Data Mining
• Machine Learning
• Recommender Systems
• +۶ مورد دیگر

Jie Liu is a Researcher at the Institute of Software, Chinese Academy of Sciences and a Professor and Doctoral Supervisor at University of Chinese Academy of Sciences. He is also a Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences and an Executive Committee Member of the System Software Committee of the CCF Computer Society. His research is conducted within the Software Engineering Technology R&D Center. Dr. Liu received his Ph.D. from the University of Science and Technology of China in 2011 and his B.A. from the same institution in 2004. He has progressed through the ranks at the Institute of Software, CAS, starting as an Assistant Research Fellow (2011-2014), then Associate Research Fellow (2014-2024), and currently as a Researcher (since 2024). His research spans Big Data Intelligent Analysis Models and Systems at the intersection of AI, Software Engineering, and System Software. Specifically, his work covers three main areas: Big Data and Machine Learning Systems (statistics and AI algorithm model libraries, data quantitative analysis tools, LLM reasoning optimization, Earth Big Data); Intelligent Software Engineering (code model constraint decoding, data science agents, system log analysis agents); and Knowledge-Enhanced Intelligent Model Construction (knowledge extraction, knowledge graphs, domain AI model design). His research has resulted in innovative approaches to handling complex data analysis challenges across multiple domains. Dr. Liu's research has produced significant outcomes including EarthDataMiner, which supports SDG indicator calculations and won the 2024 Beijing Municipal Science and Technology Progress First Prize. His work on RISC-V software migration technology has been integrated into the Ruiqian tool (https://rvpt.top/), demonstrating practical applications of his research in emerging computing architectures. Beijing Science and Technology Progress Award, First Prize, 2024 2023 Surveying and Mapping Science and Technology Award, Special Prize, 2023 DASFAA Best Paper Runner-up, Second Prize, 2013 Dr. Liu has successfully guided numerous graduate students who have secured positions at major technology companies including Alibaba, ByteDance, Southern Power Grid, and Agricultural Bank of China. He has secured funding through multiple National Natural Science Foundation projects, National Key R&D Program projects, and over ten other research initiatives. His research collaborations span industry leaders like Huawei, JD.com, and TravelSky, as well as academic institutions within the Chinese Academy of Sciences. He teaches graduate courses such as 'Machine Learning Systems' and 'Cloud Computing and Big Data Technology' at University of Chinese Academy of Sciences, and has established a research group focused on developing innovative solutions at the intersection of AI and software engineering with real-world applications in earth sciences, healthcare, and intelligent systems.

• Big Data Intelligent Analysis
• Machine Learning Systems
• Intelligent Software Engineering
• +۳ مورد دیگر