جستجوی استاد راهنمای دانشگاهی

Yanlei Diao is a Professor of Computer Science at École Polytechnique (France) with a joint appointment at the University of Massachusetts Amherst. She received her PhD from UC Berkeley in 2005. Her research focuses on scalable data systems, particularly in big data analytics, cloud computing optimization, and real-time stream processing. Research Interests: Her work spans cloud infrastructure optimization (UDAO project), explainable anomaly detection in data streams (EXAD), interactive data exploration (AIDEme), genomic data analysis (GESALL), and uncertain data management (CLARO). She leads the CEDAR team at Inria/LIX focusing on cloud-scale data exploration. Awards & Honors: ERC Consolidator Grant (2017-2023) CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) Keynote speaker at ACM DEBS 2021 and SWIFT 2023 AI Forum Best Paper Award at SIGMOD 2011 ACM SIGMOD Dissertation Honorable Mention (2005) Advising & Leadership: Mentored over 20 PhD students and postdocs, currently supervising 7 researchers. Served as PVLDB PC Co-Chair (2025-2026) and ACM SIGMOD Editor-in-Chief (2014-2019). Leads multiple projects with industry partners including Alibaba Cloud.

• Big Data Analytics
• Cloud Computing
• Data Stream Processing
• +۴ مورد دیگر

Prof. Bruno Defude is a Professor at Telecom SudParis, part of the University of Paris-Saclay. He has been affiliated with the institution since 1992, holding roles such as lecturer-researcher, department director, and currently serves as Deputy Director of Research and Doctoral Training. He leads the ACMES studies initiative and focuses on interdisciplinary research in distributed systems, cloud computing, and educational technologies. Education: Doctorate in Computer Science (1986), Grenoble INP Habilitation à Diriger des Recherches (HDR) (2005), UPMC Research Interests: Prof. Defude's work spans cloud computing architectures, data integration challenges, process mining, sensor networks, and adaptive learning systems. His contributions emphasize scalable solutions for distributed environments and privacy-aware service composition. Recent Trends: Recent publications highlight advancements in natural language querying of process data, multi-objective task scheduling in fog computing, and spatio-temporal data aggregation in vehicular networks. His work bridges theoretical foundations with practical implementations in distributed systems. Labs/Teams: Director of ACMES studies, involved in interdisciplinary research collaborations across computer science and telecommunications domains.

• Cloud Computing
• Data Integration
• Process Mining
• +۴ مورد دیگر

Marios Kountouris is a Professor at EURECOM in the Department of Communication Systems. He holds a Ph.D. in Electrical Engineering from Telecom ParisTech (France), an M.S. from Telecom ParisTech, and a Diploma in Electrical & Computer Engineering from the National Technical University of Athens (Greece). His career includes roles as Principal Scientist at Huawei Technologies (France), Assistant/Associate Professor at CentraleSupélec (France), Adjunct Professor at Yonsei University (South Korea), and Post-doctoral researcher at the University of Texas at Austin (USA). His research focuses on communication theory, machine learning for wireless communications, low latency networking, and stochastic modeling. Notable contributions include work on ultra-reliable low-latency communication (URLLC), network densification, and semantic communication frameworks. Distinctions: IEEE Communication Society Young Author Best Paper Award 2020 2016 IEEE ComSoc Communication Theory Technical Committee Early Achievement Award 2013 IEEE ComSoc Outstanding Young Researcher Award (EMEA Region) Recent research trends emphasize semantic-aware resource allocation, federated learning in wireless networks, and next-generation waveforms like AFDM. His articles explore optimization frameworks, real-time systems, and AI-driven telecom innovations.

• Communication Theory
• Machine Learning for Wireless Communications
• Low Latency Networking
• +۳ مورد دیگر

Raja Appuswamy is an Assistant Professor in the Department of Data Science at EURECOM, focusing on data management on modern hardware and molecular information storage. His research integrates cutting-edge storage technologies with bioinformatics, particularly in DNA-based data storage. He teaches courses in cloud computing, distributed systems, and databases. His work spans Optimizing storage hierarchies with DNA archival systems Hardware-conscious algorithms for GPUs and heterogeneous architectures Error correction in molecular storage Long-term database preservation strategies Key research interests include Cross-architecture data joins (e.g., OneJoin, XJoin) Cold storage innovation with CMOSS and OligoArchive Integration of bio-inspired storage with traditional computing and explores interdisciplinary challenges at the intersection of computer science and molecular biology. Publications emphasize scalable solutions for DNA storage density, error tolerance, and archival systems. Awards highlight contributions to DNA-based image encoding, storage reliability, and page cache checksums. Current projects focus on enzymatic DNA ligations for storage density improvement, motif-based error correction, and hardware acceleration for knowledge graphs. His work targets both theoretical advancements and practical implementations in storage systems.

• Cloud Computing
• Distributed Systems
• High-Performance Computing
• +۵ مورد دیگر

Walid Gaaloul is a Professor at Télécom SudParis, part of the Institut Polytechnique de Paris (IP Paris) and Institut Mines Télécom. He serves as Deputy Director of the SAMOVAR research laboratory and leads the ACMES research team. He is also a member of the DIEGO group within the Computer Science Department at Télécom SudParis. Previously, he was a researcher at the Digital Enterprise Research Institute (DERI) and an adjunct lecturer at the National University of Ireland, Galway (NUIG). He holds an M.S. (2002) and Ph.D. (2006) in Computer Science from the University of Lorraine, France, and a habilitation (2014) from Pierre et Marie Curie University, Paris. His research focuses on Business Process Management, Process Mining, Cloud Computing, and Service-Oriented Computing. He has authored over 200 publications in these domains and actively contributes to international conferences and journals as a reviewer and committee member. His work spans topics like cloud resource allocation, process discovery from emails, IoT service optimization, and blockchain-based process execution. His articles explore cutting-edge topics such as energy-efficient IoT service migration, trustworthy decentralized auctions, and formal verification of edge service monitoring. He collaborates on national and European projects addressing cyber-physical systems and distributed cloud-edge infrastructures.

• Business Process Management
• Process Mining
• Cloud Computing
• +۳ مورد دیگر

Professor Vassilis Christophides is a Full Professor at the École Nationale Supérieure d'Électronique et de ses Applications (ENSEA), part of the University of Cergy-Pontoise. His research focuses on Machine Learning Systems, Data Science & Big Data Computing, Databases and Semantic Web Systems, and Digital Libraries. He has published over 155 articles in top-tier journals/conferences like ACM SIGMOD and IEEE ICDE. Teaching includes courses such as Machine Learning, Big Data Computing, and Transparency in AI at the undergraduate and master's levels. He actively serves in conference roles (e.g., Tutorial Chair at WISE 2022), steering committees (EDBT Association), and as a reviewer for ERC grants. His work emphasizes ethical AI, explainable systems, and scalable data management across domains like Cultural Heritage and Environmental Sciences. Notable contributions include the BDA 2021 Best Paper Award and leadership in projects like the NOON research group. His work bridges theoretical advancements with real-world applications in data-driven decision-making and system optimization.

• Machine Learning Systems
• Data Science
• Big Data Computing
• +۵ مورد دیگر

Dominique Geniet serves as an Associate Professor at the University of Poitiers, France, working within the College of Engineering. He is affiliated with the LIAS Laboratory (Laboratoire d'Ingénierie des Applications de la Signalétique), which maintains dual locations at ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers) and ISAE-ENSMA (École Nationale Supérieure de Mécanique et d'Aérotechnique). His research spans theoretical computer science and practical applications in real-time systems, with significant contributions to scheduling theory, system validation, and more recently, data management. Professor Geniet's research focuses on hard real-time systems with strict temporal constraints, employing formal methods including regular languages, generating functions, and discrete geometry. His early work concentrated on theoretical foundations of scheduling algorithms for uniprocessor and multiprocessor systems, evolving toward distributed real-time systems validation, and more recently expanding into data warehousing optimization and query scheduling. His interdisciplinary approach bridges theoretical computer science with practical applications in critical systems where timing constraints are paramount. Analysis of his publication trajectory reveals a consistent focus on real-time systems with evolving applications. The earliest works (1995-2005) emphasize theoretical foundations using formal language theory and mathematical models for scheduling and validation. The middle period (2005-2012) shows expansion into distributed systems and geometric approaches to validation. The most recent publications (2012-2018) demonstrate a strategic pivot toward data management problems while maintaining the core focus on timing constraints and optimization. This evolution reflects both theoretical depth and practical adaptation to emerging computational challenges. Professor Geniet has been actively involved with the Real Time Team and Data Engineering Team within LIAS Laboratory. His work demonstrates strong collaboration with researchers including Gaëlle Largeteau-Skapin, Annie Choquet-Geniet, and Ladjel Bellatreche, suggesting participation in both theoretical research groups and applied projects with potential industrial relevance. The dual affiliation with ENSIP and ISAE-ENSMA indicates work spanning broader engineering contexts beyond pure computer science.

• Real-time systems
• Hard real-time scheduling
• Multiprocessor systems
• +۵ مورد دیگر

Pascal Richard is a Full Professor specializing in Real-Time Systems at the Institute of Technology, University of Poitiers. He is affiliated with the LIAS (Laboratoire d'Ingénierie des Applications de la Résolution des Systèmes) laboratory, which has locations at both ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers) in Poitiers and ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace - École Nationale Supérieure de Mécanique et d'Aérotechnique) in Chasseneuil. His research spans over two decades with continuous publication from 1999 through 2023. Professor Richard's primary research interests focus on real-time scheduling theory, embedded systems, and avionics. His work particularly emphasizes AFDX networks , cache-related preemption delays , self-suspending tasks , and worst-case response time analysis . His research bridges theoretical foundations with practical applications in safety-critical systems, particularly in the aerospace domain. He has made significant contributions to the understanding of scheduling anomalies, feasibility analysis, and the development of approximation schemes for complex real-time problems. His publication record demonstrates strong collaboration with researchers across France and internationally, with consistent contributions to major real-time systems conferences including RTSS, ECRTS, and RTNS. His work shows an evolution from foundational scheduling theory toward increasingly complex systems including multiprocessor platforms, mixed criticality systems, and integrated modular avionics architectures. Professor Richard has contributed to the real-time community through numerous journal publications in Real-Time Systems , IEEE Transactions on Computers , and IEEE Transactions on Industrial Informatics , among others. His most recent work continues to address cutting-edge challenges in real-time scheduling for modern computing platforms.

• Real-Time Systems
• Scheduling Algorithms
• Embedded Systems
• +۵ مورد دیگر

Jérôme Darmont is a Professor in the Department of Computer Science at Lumière University Lyon 2, where he teaches advanced database technologies and supervises doctoral research. He is a key member of Laboratoire ERIC, a joint research unit between Universities Lyon 2 and Lyon 1, with a web presence at https://eric.msh-lse.fr/ . His research interests center on database systems, with particular expertise in data lakes, XML technologies, XQuery language, and business intelligence applications. His work bridges theoretical database concepts with practical implementations, as evidenced by his teaching of PL/pgSQL programming and advanced data querying techniques. Analysis of his recent publications reveals a consistent focus on data management challenges, particularly in the areas of data lake architecture, metadata modeling, and the integration of heterogeneous data sources. His research increasingly incorporates machine learning techniques for data analysis and quality improvement, reflecting the evolving landscape of database technologies. As an active supervisor, he currently guides multiple PhD candidates including Simon Weinberger, Eliz Peyraud, and Noé Lebreton, whose doctoral defenses are scheduled for late November and December 2025. His involvement in doctoral education demonstrates his commitment to training the next generation of database researchers. Through Laboratoire ERIC, he participates in various research initiatives and academic events, contributing to the broader computer science research community in Lyon and internationally, particularly through conference participation in venues like ADBIS and DaWaK.

• Database Systems
• Data Lakes
• XML Technologies
• +۴ مورد دیگر