جست‌وجوی استاد و پژوهشگر

Yuetian Maoمشاهده پروفایل

پژوهشگر

• Intelligent Software Engineering
• Query Refinement
• Code Search
• +۳ مورد دیگر

Yuetian Mao is a Doctoral Candidate and Research Associate at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology (CIT). He holds a Master's degree in Software Engineering from Shanghai Jiao Tong University (2020-2023) and a Bachelor's degree in the same field from the same institution (2016-2020). His research focuses on Intelligent Software Engineering and Query Refinement , particularly in the application of large language models (LLMs) to code search and optimization tasks. His work addresses challenges in Code Vulnerability Detection , GUI Testing Simulation , and LLM-based Tool Use for software development. Recent publications analyzed include topics in Code Search , Query Reformulation , HiveQL Anti-patterns , and LLM-enhanced Software Engineering . His research also intersects with Human-Centric AI , Accessibility Testing , and Automated GUI Repair . Scientific Awards : Hypergryph Scholarship (2021.11) The First Prize Graduate Study Scholarship (2020.9, 2021.9, 2022.9) Yuetian is part of the Chair of Software Engineering & AI at TUM's Heilbronn campus, contributing to projects in Model Context Protocols , Generative Engine Optimization , and EU AI Act Compliance research.

Xiaoyan Liمشاهده پروفایل

مدرس ارشد

• Question Answering
• Cross-lingual Question Answering
• Information Retrieval
• +۴ مورد دیگر

Xiaoyan Li serves as a Senior Lecturer in the Department of Computer Science at Princeton University, where she focuses on teaching and mentoring undergraduate students through junior independent work supervision each semester. Her academic credentials include: Ph.D. in Computer Science, University of Massachusetts Amherst (2006) M.S. in Computer Science, University of Massachusetts Amherst (2006) M.S. in Management Information Systems, Tsinghua University (1996) B.S. in Management Information Systems, Tsinghua University (1992) Dr. Li's research centers on Question Answering systems and Information Retrieval , with pioneering work in novelty detection using sentence-level patterns and cross-lingual applications. Her expertise spans Machine Learning techniques for data mining, relevance modeling, and query expansion, particularly in multilingual contexts. She has made significant contributions to syntactic feature analysis in Chinese question answering and time-based language models for dynamic information needs. Her publication history (2001-2008) reveals a concentrated focus on novelty detection and robust relevance models, with prominent outputs in ACM SIGIR, CIKM, and TREC proceedings. The research trajectory shows evolution from syntactic analysis (early 2000s) to adaptive passage retrieval techniques (late 2000s), consistently addressing core challenges in information access through pattern-based and machine learning approaches. At Princeton, Dr. Li teaches foundational and advanced courses including Machine Learning and Data Science (COS IW02&03), Introduction to Computer Systems (COS217), and Artificial Intelligence (COS402). Previously at Mount Holyoke College, she developed curriculum for Object-Oriented Programming, Data Structures, and Intelligent Information Retrieval courses, demonstrating extensive pedagogical range across computer science disciplines.

Hawk Bo Wangمشاهده پروفایل

استادیار

• Computer Vision
• Deep Learning
• Human Pose Estimation
• +۳ مورد دیگر

Hawk Bo Wang is an Assistant Professor in the Department of Computer Science at the University of Mississippi (Ole Miss). His research focuses on computer vision and deep learning, with particular emphasis on enhancing model robustness and generalization for human-centric applications. Dr. Wang maintains an active research program with publications consistently appearing at top-tier conferences including CVPR, ICCV, ECCV, and NeurIPS. Dr. Wang earned his PhD from the School of Computing at the University of Utah. Before joining academia, he accumulated nearly a decade of industry research experience at GE Global Research, Tencent US, and CtrsVision, providing him with valuable real-world perspective on AI deployment challenges. His research interests center on computer vision and deep learning , specifically addressing model robustness and generalization for human pose estimation and human-object interaction (HOI) . Dr. Wang investigates how to make models perform reliably in challenging real-world conditions including low-light environments, occlusions, and with unseen object categories. Analysis of Dr. Wang's recent publications reveals a strong trajectory in human-centric computer vision research. His work demonstrates increasing sophistication in handling challenging scenarios, with recent papers focusing on zero-shot learning for HOI detection, domain adaptation for low-light pose estimation, and few-shot learning approaches. Many of these papers have been accepted at premier venues ranked among the top in computer vision and AI research. Dr. Wang's contributions to the field have been recognized through: Outstanding Reviewer Award at WACV 2024 Outstanding Reviewer Award at ECCV 2022 Dr. Wang serves as an Area Chair for ECCV 2024 and regularly participates in program committees for major conferences including CVPR, ICCV, ECCV, and AAAI. He actively mentors students and welcomes prospective PhD candidates interested in computer vision research to contact him with their materials. His research addresses the critical gap between model performance on curated benchmarks and real-world effectiveness, making significant contributions to practical AI deployment.

Irina Nikishinaمشاهده پروفایل

پژوهشگر

• Semantics
• Argument Mining
• Taxonomy Enrichment
• +۳ مورد دیگر

Irina Nikishina is a postdoctoral researcher at the University of Hamburg's Department of Informatics, working in the Language Technology Group under Prof. Chris Biemann. As a researcher in computational linguistics and natural language processing, she contributes to projects like ACQuA-2.0, focusing on semantics, argument mining, taxonomies, and knowledge graphs. PhD in Computational and Data Science and Engineering (2022), Skolkovo Institute of Science and Technology Bachelor's and Master's degrees from National Research University Higher School of Economics (NRU HSE) Her research spans taxonomy enrichment, comparative question answering systems, and biomedical concept representation. She organizes shared tasks like RUSSE’2020 and RuArg-2022, and co-founded the RusNLP semantic search engine for Russian NLP conferences. She chairs the Network Analysis track at the International Conference on Analysis of Images, Social Networks and Texts (AIST) and has served as secretary for AIST 2020 and 2021. Recent publications focus on large language models' performance in lexical semantics, multilingual comparative argumentation systems, and knowledge graph integration for QA tasks. Her work includes developing tools like TaxFree for candidate-free taxonomy enrichment and exploring cross-modal approaches for taxonomic graph expansion.

Ido Daganمشاهده پروفایل

استاد

• Natural Language Processing
• Textual Entailment
• Semantic Representation
• +۵ مورد دیگر

Ido Dagan is a Professor at the Department of Computer Science at Bar-Ilan University , Israel, and founder of the Natural Language Processing (NLP) Lab . He is a Fellow of the Association for Computational Linguistics and served as ACL President (2010) and Executive Committee member (2008–2011), leading the establishment of Transactions of the Association for Computational Linguistics . Dagan’s research focuses on applied semantic processing , including textual entailment , natural semantic representation , multi-text information consolidation , and interactive text summarization . His recent work addresses attributable text generation , summary-source alignment , and cross-sentence argument detection , with applications to fact verification and hallucination detection. Key trends in his publications include cross-document coreference resolution , question-answering systems , semantic parsing , and interactive summarization . Notable collaborative projects involve UI trajectory analysis and long-context QA with Arman Cohan and Jacob Goldberger. Scientific Awards Fellow, Association for Computational Linguistics (ACL) President, ACL (2010) Executive Committee, ACL (2008–2011) Advising & Collaborations Dagan has supervised numerous PhD, MSc, and postdoctoral students since 1997, including Shachar Mirkin and Shmuel Amar . He collaborates with researchers like Ori Ernst , Avi Caciularu , and Aviv Slobodkin , with grants from institutions like IBM Haifa Scientific Center and AT&T Bell Laboratories .

Cristian Mihaescuمشاهده پروفایل

مدرس

• Computer Science
• Machine Learning
• Distributed Systems
• +۳ مورد دیگر

Cristian Mihaescu is a Lecturer at the Department of Computer Science and Engineering (DCTI), University of Craiova, within the Faculty of Automatic Control, Computers and Electronics. He is actively involved in teaching and research related to machine learning, distributed systems, and educational data mining. Teaching: Data Structures and Algorithms, Parallel and Distributed Algorithms, Machine Learning, Distributed Systems Engineering Research Focus: Machine learning applications in education, social network analysis, and compiler optimization Technological Interests: Microservices, data mining, and intelligent system design

Günter Neumannمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Artificial Intelligence
• +۷ مورد دیگر

Prof. Günter Neumann is a Professor of Computational Linguistics at Saarland University and a Research Fellow at the German Research Center for Artificial Intelligence (DFKI) . He has over 30 years of experience in research software development, with a focus on language technology , information extraction , and question answering systems . PhD in Computer Science (1994) and Venia Legendi in Computational Linguistics (2004) from Saarland University Visiting researcher at Stanford , CMU , and MIT His research spans computational linguistics , artificial intelligence , and their applications in defence , healthcare , and education . He leads projects like AtLaS (AI-based NLP for low-quality data in defence), PRECISE4Q (predictive modeling in stroke medicine), and iREAD (personalized reading apps). Recent publications focus on low-resource language retrieval , cross-lingual transfer , and graph-based reasoning in biomedical domains. He has participated in numerous program committees (ACL, AAAI, LREC) and contributed to advancements in multilingual question answering , knowledge graph reasoning , and medical text de-identification . He has collaborated with institutions like Fondazione Bruno Kessler , econob , and NICE Systems . Current tools developed with his team power semantic search services for Informationsdienst Wissenschaft and the Deutsche Allianz Meeresforschung portal.

Arooj Fatimaمشاهده پروفایل

مدرس ارشد

• Computer Science
• Semantic Web Technologies
• User Experience Design
• +۴ مورد دیگر

Dr. Arooj Fatima is a Senior Lecturer at the Medical Technology Research Centre, affiliated with the Faculty of Science and Engineering and the School of Computing and Information Science at Anglia Ruskin University. Her expertise spans Computer Science, Semantic Web Technologies, User Experience Design, and Artificial Intelligence. She teaches courses in user experience design, interaction design, usability, and advanced web solutions, while her research focuses on semantic data technologies, intelligent web applications, and usability evaluation. PhD in Computing, Anglia Ruskin University MSc in Computing, Anglia Ruskin University Her research explores semantic search, knowledge acquisition, effective user interfaces, and reliable usability evaluation techniques. Her publications highlight advancements in SPARQL query processing, federated query optimization, linked data integration, and AI-driven search frameworks. Arooj is a member of the Computing, Informatics and Applications Research Group and has over a decade of industry experience in web development, databases, APIs, and mobile applications. She welcomes prospective PhD students in her research areas and contributes to the university's BEng and MSc Computer Science programs. Her work bridges academic research with practical applications in semantic web technologies and user-centric design.

Beatrice Markhoffمشاهده پروفایل

استاد

• Semantic Web
• Knowledge Engineering
• Semantic Interoperability
• +۵ مورد دیگر

Beatrice Markhoff is a Professor of Computer Science (CNU 27) at the University of Tours , affiliated with the Faculty of Science and Technology (Blois site) and the Computer Science Department . She is a member of the UMR CNRS 7324 - CITERES - Archaeology and Territories Laboratory (CITERES-LAT) and the Maison des Sciences de l'Homme Val de Loire (MSH VdL) . Her research focuses on semantic interoperability , Web of data , knowledge representation , and knowledge extraction , with significant collaborations in cultural heritage disciplines . Doctorate in Computer Science, University of Franche-Comté (1995) HDR (Habilitation to Direct Research), François Rabelais University of Tours (2013) Her research themes include semantic interoperability, knowledge engineering, and data mining, with applications in cultural heritage. She co-created the International Workshop on Semantic Web for Cultural Heritage and co-edited special issues for the Semantic Web Journal and JOCCH . She leads projects like ANR SESAMES (2018-2023), H2020 ARIADNEplus (2019-2022), and H2020 4CH (2021-2023). Her academic contributions span XML data management, semantic web technologies, and functional programming. Key projects include carto4CH for cultural heritage mapping and OpenArchaeo for knowledge graph profiling. She has co-supervised PhD theses on topics like LOD querying and knowledge extraction from Wikidata .

• Machine Learning
• Structured Prediction
• Tree Automata
• +۶ مورد دیگر

Marc Tommasi is a Professor in Computer Science at the University of Lille, affiliated with the CRIStAL laboratory where he leads the Magnet research team. Previously, he was a founding member of the Mostrare project team at INRIA Lille. His academic career spans research in machine learning foundations and applications to structured data. His research focuses on: Machine learning theory and algorithms Structured prediction for trees and graphs Tree automata and set constraints Decentralized learning systems Sparse representations for structured data Natural language processing techniques Information extraction from semi-structured data His publication portfolio demonstrates consistent focus on spectral methods for graph learning, probabilistic tree modeling, and conditional random fields, with applications spanning network analysis, XML processing, and natural language tasks. Recent work emphasizes large-scale network modeling and spectral clustering techniques. He has supervised 13 PhD students including ongoing work in decentralized machine learning (Mahsa Asadi), privacy-preserving speech recognition (Brij Srivastava), and multilingual dependency parsing (Mathieu Dehouck), with completed theses covering graph construction, spectral clustering, and tree transducer learning. Significant research projects under his coordination include Pamela (decentralized ML), Lampada (structured data representations), Marmota (statistical ML for trees), Crotal (CRFs for NLP), ATASH (document transformations), and WebContent (information extraction). He maintains active involvement in the Magnet team at CRIStAL focusing on machine learning for graphs and NLP.

Kyoung-Min Kimمشاهده پروفایل

پژوهشگر

• Large Language Models (LLMs)
• Database Systems
• Inference Optimization
• +۳ مورد دیگر

Kyoung-Min Kim is a Researcher at the Data-Intensive Applications and Systems Laboratory (DIAS) within the College of Computing and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). His work intersects large language models (LLMs) and database systems, focusing on improving inference efficiency and reliability. Email: kyoung-min.kim@epfl.ch Office: BC 224, EPFL, Station 14, Lausanne Research Interests: Recent publications highlight his expertise in: LLM inference optimization GPU resource management Cost modeling for AI systems Scheduling algorithms for scalable inference Preemption strategies reducing computational costs Constraint satisfaction frameworks for system performance Key Contributions: Kim co-developed INFERMAX , an analytical framework comparing LLM inference schedulers. His work demonstrates 30% GPU cost reduction through preemption techniques.

Angelos Charalambidisمشاهده پروفایل

استادیار

• Programming Languages and Software Systems
• Declarative Programming Languages
• Computational Logic
• +۱ مورد دیگر

Angelos Charalambidis is an Assistant Professor at Harokopio University, affiliated with the Department of Informatics and Telematics. His academic and professional engagements focus on theoretical and applied aspects of computational logic and programming languages. Education: B.S. in Informatics, University of Athens (2005) M.S. in Computer Systems, University of Athens (2008) Ph.D. in Higher-Order Logic Programming, University of Athens (2014) His research interests include declarative programming languages, computational logic, and reasoning techniques, contributing to the broader field of Programming Languages and Software Systems. He has also explored applications in knowledge representation, preference modeling, and cloud-native systems. The trends in Angelos Charalambidis's publications highlight advancements in logic programming, including higher-order logic, fixpoint theory, ordered disjunction, and federated query processing. His work bridges theoretical foundations with practical implementations in formal methods and computational logic.

Jackie Chi Kit Cheungمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Jackie Chi Kit Cheung is an Associate Professor at the School of Computer Science, McGill University , and holds the Canada CIFAR AI Chair at Mila - Quebec AI Institute. His research bridges Natural Language Processing (NLP) with insights from linguistics and psychology, focusing on system evaluation, automatic summarization , and computational semantics . Key Affiliations : Mila - Quebec AI Institute, Centre for Research on Brain, Language and Music, Centre for Intelligent Machines His lab develops state-of-the-art NLP systems while proposing challenge datasets and evaluation measures. Research emphasizes broader applications in education , health , and language revitalization . Recent work includes the ACL 2024 COSMIC framework for summarization evaluation (SAC Award). He teaches advanced courses like Formal and Neural Models of Pragmatics (Winter 2024) and Evaluation of NLP Systems (Winter 2025). His group includes 10 PhD students, 8 Master's students, and active collaborations with institutions like Mila and SRI International. Scientific Recognition : Canada CIFAR AI Chair SAC Award for ACL 2024 paper Current projects explore representational harms in LLMs , long-context modeling , and mechanistic hallucination mitigation . Students and co-supervised researchers work on fairness, robustness, and commonsense reasoning.

• Wireless Communications
• Internet of Things (IoT)
• Electric Vehicles
• +۶ مورد دیگر

Nagham Saeed serves as Associate Professor in Electrical and Electronic Engineering at the School of Computing and Engineering, University of West London, a position she has held since April 2023. Previously, she was Senior Lecturer in Electrical Engineering at the same institution from November 2017 to April 2023, following roles as Electronic Lecturer at Uxbridge College (2012-2017) and Electronic/Control Lecturer at Brunel University (2007-2012). Her academic credentials include: Ph.D. in Optimization in Wireless Networks and Communications (Brunel University, 2007-2011) M.Sc. in Mechatronics (University of Technology, Baghdad, 1997-1999) B.Eng. in Computer and Control (University of Technology, Baghdad, 1988-1992) DTLLS Diploma in Teaching (University of Westminster, 2012-2014) BAPP in Learning and Teaching (Brunel University, 2009-2010) Assessing Competence Certification (Uxbridge College, 2014) Dr. Saeed's research spans wireless communications, IoT, electric vehicles, and AI-driven energy optimization. Her work focuses on Bluetooth Low Energy applications for healthcare monitoring, battery management systems for EVs, sustainable ICT practices, and GIS-based land use analysis. She pioneers solutions for energy-efficient radio access networks and develops AI models for vehicle classification and low-resource language processing. Analysis of her 2022-2025 publications reveals three dominant trends: (1) AI integration for sustainable energy systems in telecommunications and transportation, (2) blockchain-secured vehicular networks for 6G infrastructure, and (3) cross-disciplinary applications of IoT in healthcare and environmental monitoring. Her research consistently bridges electrical engineering with computer science to solve real-world sustainability challenges. Professional recognition includes: MDPI Reviewer Acknowledgements (2020) for Algorithms, Applied Sciences, and Information journals While her 2022 educational research on feedforward teaching approaches demonstrates pedagogical engagement, no student supervision or grant management details are documented. Current institutional affiliations show no dedicated laboratory facilities or research teams specified in available records.

Bo Luoمشاهده پروفایل

استاد

• Machine Learning Security
• Internet of Things (IoT) Security
• Cyber-Physical Systems (CPS) Security
• +۶ مورد دیگر

Bo Luo is a Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas . He serves as Director of the High Assurance and Secure Systems (HASS) Research Center within the Institute for Information Sciences (I2S) , a National Center of Academic Excellence in Cyber Defense and Research by the National Security Agency. Education: Ph.D. in Information Sciences and Technology, Pennsylvania State University (2008) M.Phil. in Information Engineering, Chinese University of Hong Kong (2003) B.E. in Electronic and Information Engineering, University of Science and Technology of China (2001) His research focuses on security and privacy at the intersection of data science, AI/ML, IoT/CPS, and network security . Current projects include adversarial machine learning, privacy compliance in smart devices, and hardware-enabled security solutions. He leads the InfoSec Research Group , mentoring students in areas like IoT security, deep learning vulnerabilities, and cryptographic systems. Recent article trends highlight IoT device vulnerabilities (2025), privacy compliance in automotive apps (2024), adversarial AI-art detection (2024), and secure computation frameworks (2024). His work appears in top venues like ACM CCS , USENIX Security , and IEEE TDSC . Scientific Recognition: ACSAC 2021 Distinguished Paper Award ACSAC 2017 Best Paper Award CCS 2022 Best Paper Honorable Mention ICPC 2024 Distinguished Paper As Principal Investigator for the Jayhawk SFS CyberCorps Scholarship , he trains future cybersecurity professionals. His lab collaborates on cyber-physical security and AI safety , with alumni placed at institutions like Beloit College, Apple, and Amazon.