جستجوی استاد راهنمای دانشگاهی

Chua Tat Seng is a Professor at the School of Computing, National University of Singapore (NUS), holding the KITHCT Chair Professorship since 2009. He serves as co-Director of the NExT++ Center, a joint research center between NUS and Tsinghua University focused on Extreme Search. His academic career spans over three decades at NUS, where he has held various leadership positions including Acting Dean of the School of Computing (1998-2000) and Acting Head of the Department of Information Systems & Computer Science (1996-1998). Professor Chua's research spans unstructured data analytics , multimedia information retrieval , recommendation and conversation systems , and emerging applications in e-commerce and fintech . He established the Lab for Media Search (LMS) at the School of Computing and has been instrumental in advancing multimodal learning and search technologies. His work bridges theoretical foundations with practical applications, particularly in developing trustable AI systems for real-world deployment. His recent publications demonstrate a strong focus on large language models for recommendation systems , multimodal learning , and generative AI applications . The research trends show increasing emphasis on LLM-based recommendation, multimodal understanding, and addressing fundamental challenges in AI reliability, fairness, and efficiency. His work spans theoretical advancements in representation learning to practical applications in e-commerce, finance, and healthcare domains. ACM SIGMM Technical Achievement Award 2015 Multiple Best Paper Awards across ACM Multimedia, IEEE Transactions, and MMM conferences (2007-2020) Professor Chua has supervised 37 PhD students since 2004, establishing himself as a dedicated mentor in the academic community. His research has been supported by substantial grants including NExT++ ($12 million), Base Metals Price Forecasting ($200,000), and Multilingual Multimodal Knowledge Graph ($500,000). He maintains active collaborations with Tsinghua University, University of Southampton, and industry partners like Four Elements Capital and Singapore Press Holdings. As co-Director of the NExT++ Center, he leads a major research initiative focused on Web Intelligence and User Empowerment. His visiting professorships at Tsinghua University (2017-present) and Zhejiang University (2021-present) reflect his international impact in the field of multimedia and AI research.

• unstructured data analytics
• multimedia information retrieval
• recommendation systems
• +۶ مورد دیگر

Manik Varma is a Distinguished Scientist and Vice President at Microsoft Research India, and an Adjunct Professor at the Indian Institute of Technology Delhi. He is a Fellow of the Indian Academies of Science (IASc, INSA, NASI), the Indian National Academy of Engineering (INAE), and the Association for Computing Machinery (ACM). He has received prestigious awards such as the Shanti Swarup Bhatnagar Prize and Microsoft Gold Star Award. Education : BSc in Physics from St. Stephen's College (David Raja Ram Prize) BA in Theoretical Physics from the University of Oxford (Rhodes Scholar) DPhil in Computer Vision and Machine Learning from the University of Oxford (University Scholar) Post-doctoral Fellow at the Mathematical Sciences Research Institute (MSRI), Berkeley Visiting Miller Professor at UC Berkeley His research focuses on Machine Learning (Extreme Classification, Resource-efficient ML, Supervised Learning), Information Retrieval (Computational Advertising, Dense Retrieval, Recommender Systems), and Computer Vision (Image Search, Object Recognition). Recent work includes graph-regularized encoders, label variance reduction, and multimodal classification frameworks. His publications span extreme classification algorithms like NGAME , SiameseXML , and DECAF , with applications in IoT, web search, and recommendation systems. He leads a research group at Microsoft Research India and advises PhD students at IIT Delhi. Scientific Awards : Shanti Swarup Bhatnagar Prize (Government of India) Microsoft Gold Star and Achievement Awards WSDM 2019 Best Paper Prize BuildSys 2019 Best Paper Runner-up Fellow of ACM, IASc, INSA, NASI, INAE He has supervised numerous PhD students, including Sonu Mehta and Suchith Prabhu, and collaborates with institutions like Microsoft Research India, IIT Delhi, and UC Berkeley. His research has led to scalable solutions for billion-label classification and resource-constrained IoT applications.

• Machine Learning
• Deep Learning
• Information Retrieval
• +۱۶ مورد دیگر

Ronald McGarvey is a Full Professor at IÉSEG School of Management since 2022, with prior roles including Associate Professor with Tenure at the University of Missouri (2013-2022) and Senior Operations Researcher at RAND Corporation (2002-2022). He holds a Ph.D. in Industrial Engineering and Operations Research from Pennsylvania State University and an H.D.R. in Industrial Engineering from the University of Paul Sabatier, France. Education : H.D.R. (2024), Industrial Engineering, University of Paul Sabatier Ph.D. (2002), Industrial Engineering and Operations Research, Pennsylvania State University His research focuses on Operations Research and Robust Optimization applied to diverse domains: Healthcare Logistics : Modeling access disparities in rural obstetric care for American Indian populations Environmental Sustainability : Analyzing biomass energy systems, forest carbon impacts, and waste management frameworks Network Design : Developing optimization models for supply chain resilience, military logistics, and urban transit safety Policy Analysis : Evaluating multi-state environmental collaborations and localized food systems His publications demonstrate strong interdisciplinary applications of mathematical programming and spatial optimization to real-world challenges in healthcare access, energy sustainability, and transportation systems. Key Collaborations : Working with researchers in public health (Thorsen, Noble), environmental science (Aguilar), and engineering (Mirzaee, Gutierrez-Lopez)

• Operations Research
• Robust Optimization
• Sustainable Systems
• +۳ مورد دیگر

Fabian Suchanek is a full professor at Institut Polytechnique de Paris, specifically affiliated with Télécom Paris. He leads research in the Data, Intelligence, and Graphs (DIG) team within the Computer Science department. His academic career focuses on bridging artificial intelligence with structured knowledge representations. Suchanek's research interests span artificial intelligence, knowledge bases, and natural language processing, with particular emphasis on knowledge graph construction , rule mining , knowledge-based language models , and explainable AI . His work demonstrates how structured knowledge can enhance machine learning systems, particularly large language models, by providing factual grounding and interpretability. The research group he leads develops practical systems that address real-world knowledge management challenges. His recent publications showcase a strong trajectory in knowledge-intensive AI, with notable contributions to knowledge graph completion, rule mining techniques, and neural approaches to knowledge base validation. The research demonstrates increasing integration between symbolic and neural approaches to AI. Best Student Paper Award at KR 2024 for work on contextual reasoning Best Demo Award of IJCAI 2024 for rule mining in knowledge graphs French Open Research Award for the YAGO project Best Paper Award of ESWC 2021 for Neural Knowledge Base Repairs Suchanek has secured significant research funding, evidenced by his active recruitment of PhD students for knowledge-based language model research. He has held visiting positions, including at Nanyang Technological University (June-September 2023), and is recognized internationally through keynote invitations such as the Singapore ACM SIGKDD Symposium 2023. He has deliberately stepped back from administrative duties at Institut Polytechnique de Paris to focus on research. His laboratory maintains strong industry connections through open-source software projects including the YAGO knowledge base, AMIE for rule mining, STACI for explainable AI, and several other tools that have become standard in knowledge representation research.

• Artificial Intelligence
• Knowledge Bases
• Natural Language Processing
• +۳ مورد دیگر

Dr. Jérôme Verny is an Associate Professor specializing in transport, logistics, and supply chain management. He is the founder and director of the research institute in innovative transport and logistics, as well as the co-founder of the DISC Master's program (Digital & Innovative Supply Chain) in Paris and the Mobility Accelerator. His expertise spans digitalization in logistics, blockchain applications, and sustainable development. Educated at the University of Lille Nord de France (PhD in Economics and Management) and engineering schools like École Nationale des Ponts et Chaussées, he advises both public institutions (OECD, EU) and private enterprises on transportation strategies. Research Interests: Dr. Verny focuses on supply chain innovation, digital transformation, and strategic logistics. His work integrates blockchain technology for supply chain transparency, optimizes last-mile delivery in urban environments, and analyzes the impact of geopolitical actors like China on global trade networks. He also explores sustainable practices in transportation, including CO2 reduction strategies and pandemic response logistics. Awards: Recipient of the 2009 OECD-FIT Young Researcher Prize in Transport. His contributions bridge academic research with practical applications in industry, policy, and international trade. Key Activities: Co-founded the DISC Master’s program and leads research initiatives on blockchain adoption, Arctic shipping routes, and Mediterranean trade dynamics. He actively contributes to conferences such as the International Association of Maritime Economists (IAME) and publishes in journals like Structural Change and Economic Dynamics and International Journal of Shipping and Transport Logistics . Labs/Teams: Directs the Institut de Recherche en Transport et Logistique Innovante and collaborates with institutions like the OECD and European Commission on transport policy. His interdisciplinary approach involves engineering, economics, and data science to address global supply chain challenges.

• Supply Chain Management
• Transportation Systems
• Logistics
• +۴ مورد دیگر

Rida Khatoun is a Professor in Cybersecurity at the Computer Sciences and Networks (Infres) Department at Télécom Paris. He holds a M.Sc. in Computer Engineering and a Ph.D. from the University of Technology of Troyes (UTT), France, awarded in 2004 and 2008, respectively. His research focuses on cybersecurity in networks, including cloud computing security, IoT security, vehicular networks security, intrusion detection systems, and blockchain technology. He has taught at Telecom Paris since 2014, Shanghai Jiao Tong University (SJTU) since 2016, and other institutions in China and France since 2005. His work spans theoretical frameworks and practical solutions for network security challenges. Key research areas include DDoS attack detection, vehicular communication security, and cryptographic protocols. He leads the Cybersecurity and Cryptography (C²) research team and is affiliated with the Laboratoire Traitement et Communication de l'Information (LTCI). His contributions include developing secure routing protocols (e.g., ASROP), statistical trust systems in wireless networks, and blockchain-based authentication for IoT. He has authored over 115 publications, including peer-reviewed articles and conference proceedings, with recent work addressing vehicular platooning security, TLS handshake optimization for C-ITS, and machine learning for cyberbullying detection. Rida’s academic activities include teaching courses on network security protocols, wireless network fundamentals, and QoS mechanisms. He collaborates internationally, contributing to smart city cybersecurity architectures and 6G programmable communications. His research emphasizes practical cybersecurity solutions for emerging technologies, ensuring robust protection against evolving threats in vehicular, IoT, and cloud environments.

• Cybersecurity
• Network Security
• Cloud Computing Security
• +۶ مورد دیگر

Salim ROSTAMI is an Associate Professor at the IÉSEG School of Management in France, specializing in Operations Management. He holds a Ph.D. in Economics and Mathematics Sciences from KU Leuven (2019) and a Master’s in Engineering from KU Leuven (2013), alongside a Bachelor’s in Industrial Engineering from Ferdowsi University of Mashhad (2012). His research focuses on scheduling under uncertainty, project planning, combinatorial optimization, and healthcare logistics. Notable achievements include the 2016 2nd Best Conference Paper Award from the University of Valencia. Education: Ph.D., Economics and Mathematics Sciences, Operations Management, KU Leuven, Belgium (2019) Master, Engineering, Operations Research, KU Leuven, Belgium (2013) Bachelor, Engineering, Industrial Engineering, Ferdowsi University of Mashhad, Iran (2012) His work spans stochastic resource-constrained project scheduling, sequential testing of systems, and chemotherapy appointment scheduling. He has published widely in journals like the European Journal of Operational Research and Flexible Services and Manufacturing Journal. Teaching roles include courses on operations management and project management across undergraduate and graduate programs. Awards: 2016: 2nd Best Conference Paper Award, University of Valencia His research emphasizes practical applications in healthcare and project management, leveraging dynamic programming and metaheuristic algorithms. Collaborations include work with institutions like École des Mines de Saint-Étienne and KU Leuven.

• Operations Research
• Scheduling under Uncertainty
• Project Planning and Scheduling
• +۳ مورد دیگر

Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.

• Supply Chain Management
• Logistics
• Operations Management
• +۶ مورد دیگر

Maxime Menuet is a Professor of Economics at Université Côte d'Azur (GREDEG) and a Research Associate at IPAG Business School in Paris. His academic credentials include a PhD in Economics and dual M.Sc. degrees in Macroeconomics/Finance and Mathematics from the University of Orléans, complemented by a 2023 HDR (Habilitation à Diriger des Recherches) from Paris VIII. 2023: HDR in Economics, Paris VIII 2018: PhD in Economics, University of Orléans 2015: M.Sc in Macroeconomics and Finance, University of Orléans 2015: M.Sc in Mathematics (Theoretical Probability), University of Orléans His research focuses on Economic Theory and Political Economy , with specialized expertise in public debt , macroeconomic stability , conflict dynamics , and interdisciplinary intersections with theology and history . Recent work explores environmental sustainability through fiscal policy, ideological clashes in macroeconomic governance, and historical economic thought from Jansenist perspectives. Maxime's publications since 2023 show strong interdisciplinary trends, blending theological analysis with economic modeling (e.g., New Testament debt language), refining game-theoretic conflict models , and advancing ecological macroeconomic frameworks for sustainable debt management. ANR Young Researcher Grant Best Paper Award, TIMTED Conference Visiting Scholarships: Duke University, Osaka University, UCAM Montreal As Deputy Director of EUR ELMI and co-director of the European Research Group on Money, Banking, and Finance, he leads major interdisciplinary initiatives. His teaching portfolio mirrors his research, covering economic theory, political economy, and debt/conflict dynamics.

• Economic Theory
• Political Economy
• Macroeconomics
• +۵ مورد دیگر

Christine Di Martinelly is an Associate Professor in Operations Management at IÉSEG School of Management. She holds two PhDs in Economic and Management Sciences from Louvain School of Management and Applied Sciences from INSA Lyon. Her research focuses on operations management, healthcare systems, supply chain optimization, and resource allocation. Di Martinelly's extensive publication record addresses operational challenges in healthcare, including surgical scheduling, inventory management, and resource allocation. Her work employs mathematical modeling, optimization algorithms, and multicriteria decision analysis to improve efficiency in healthcare delivery systems. She has served as Academic Director at IÉSEG since 2014 and has professional experience as a consultant at Arthur Andersen earlier in her career.

• Operations Management
• Healthcare Systems
• Supply Chain Optimization
• +۱ مورد دیگر

Gang (Gary) Tan is a Professor at the Pennsylvania State University's College of Engineering, specializing in computer security, formal methods, and programming languages. He co-directs the Institute for Networking and Security Research (INSR) and leads the Security of Software (SOS) Group, focusing on compiler, programming language, and formal method techniques to enhance computer security. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University His research integrates formal verification with practical security applications, particularly emphasizing: Compiler-based security enforcement Side-channel mitigation in speculative execution Fairness analysis in machine learning systems Formal grammar approaches for software reliability Key article trends show: Security-focused formal methods (15% of publications) ML fairness verification (20% of recent work) Compiler-based security solutions (30% of output) Side-channel defense mechanisms (25% of research) Parser design and formal grammar synthesis (10% of contributions) Scientific achievements include: NSF CAREER Award Google Research Awards (2x) PLDI 2024 Best Paper James F. Will Career Development Professorship Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Dr. Tan actively contributes to academic communities through: DARPA ISAT study group membership Program committee roles (CGO 2024, ECOOP 2018, etc) Leadership in security research initiatives

• Computer Security
• Formal Methods
• Programming Languages
• +۲ مورد دیگر

Benoît Sagot is a Senior Researcher in Natural Language Processing and Computational Linguistics at Inria , currently holding the 2023-2024 Informatics and Digital Sciences Annual Chair at Collège de France. He directs the ALMAnaCH research team and contributes to the PRAIRIE Institute for AI research. Research Focus: His work spans neural language models, machine translation, text simplification, multimodal NLP, and lexical resource development for French and low-resource languages. He explores computational morphology, etymology, and historical linguistics, with applications in opinion mining and computational oenology. Recent Articles emphasize language model interpretability, cross-lingual transfer, and multimodal integration (speech, image). Tools & Resources: He has developed morphological lexicons (Le fff, Alexina), corpora (OSCAR, CAMEMBERT), and parsing pipelines (SxPipe). Projects: Involved in initiatives like ANR BASNUM (Furetière's dictionary digitization) and 3IA PRAIRIE (AI research). His career combines foundational work in syntactic analysis with evolving deep learning approaches.

• Natural Language Processing
• Computational Linguistics
• Machine Translation
• +۷ مورد دیگر

Elliot J. Crowley is a Senior Lecturer (Associate Professor) at the School of Engineering, University of Edinburgh, where he co-leads the Bayesian and Neural Systems research group. He serves as Programme Manager for Electronics and Electrical Engineering and has developed a comprehensive machine learning course for 4th year electronic engineering students at the University of Edinburgh. Dr. Crowley's research focuses on simplifying machine learning systems with specific expertise in automated machine learning, low-resource deep learning, and engineering applications of machine learning. His work bridges theoretical advances with practical implementations, particularly in neural architecture search and computer vision applications, with emphasis on making complex ML systems more accessible and efficient. His recent publications demonstrate significant contributions to neural architecture search spaces, training-free instance segmentation, and state space models for visual recognition, appearing in top venues including NeurIPS 2024, BMVC 2024, and AutoML 2025. These works show a consistent focus on developing practical ML solutions that can operate effectively in resource-constrained environments. Selected awards and grants: EPSRC New Investigator Award Investigator on the dAIEdge Horizon Network Co-investigator on the EPSRC AI Hub for Causality in Healthcare AI Dr. Crowley currently supervises several researchers including Postdoc Linus Ericsson and PhD students Miguel Espinosa, Shiwen Qin (with Shay Cohen), and Cameron Barker (with Henry Gouk). His former students include Chenhongyi Yang (now a Research Scientist at Meta) and Jack Turner (now a Software Engineer at Qualcomm). He actively seeks new PhD students with strong research proposals and available funding for UK students through CDTs. His research group, the Bayesian and Neural Systems group, focuses on developing practical machine learning solutions that can be deployed in resource-constrained environments, with particular emphasis on making complex ML systems more accessible to engineers and practitioners.

• Machine Learning
• Automated Machine Learning
• Neural Architecture Search
• +۳ مورد دیگر

Dr. Yi-Ping Fang is an Assistant Professor at the EDF Chair SSEC with a joint appointment at the Industrial Engineering Laboratory, CentraleSupélec, Université Paris-Saclay, France. His research focuses on computational methods for risk, vulnerability, and resilience analysis of critical infrastructures including smart grids, electrified transportation, and interdependent lifeline systems. Risk Analysis Resilience Engineering Optimization Under Uncertainty Game Theory Applications His work applies advanced techniques like distributionally robust optimization, POMDP modeling, and interdependency analysis to enhance infrastructure resilience against climate change, natural hazards, and intentional attacks. Publications demonstrate expertise in hybrid optimization algorithms, stochastic modeling, and network vulnerability assessment. Recent trends include: Smart grid resilience enhancement Uncertainty quantification in infrastructure systems Multi-stage decision modeling Game-theoretic approaches for interdependent networks Integration of deep learning for dynamic system prediction

• Risk Analysis
• Resilience Engineering
• Optimization Under Uncertainty
• +۷ مورد دیگر

Benoit Combemale is a Full Professor of Software Engineering at the University of Rennes , currently on leave as Research Director at Inria . He is affiliated with the DiverSE research team (joint between IRISA and Inria) and the SM@RT team at IRIT. He serves as Editor-in-Chief of the Springer-Nature journal Software and Systems Modeling (SoSyM) and holds leadership roles in academic conferences like ACM SIGPLAN Intl. Conference on Software Language Engineering and MODELS . Education : Habilitation (2015) and PhD (2008) in Software Engineering from University of Rennes and University of Toulouse, respectively. Research : Focuses on Model-Driven Engineering , Digital Twins , and ICT for Sustainability , with applications in cyber-physical systems, scientific computing, and industrial systems. Recent Publications highlight trends in digital twin modeling, energy-aware software engineering, polyglot programming, and formal verification for heterogeneous systems. His scientific awards include: Editor-in-Chief of SoSyM Steering Committee member of ACM SIGPLAN Intl. Conference on Software Language Engineering General Chair for ICT4S 2023 and MODELS 2016 PC Chair for MODELS 2024, ECMFA 2019, and SLE 2014 Coordinator of Dagstuhl Seminars and Bellairs workshops Advising includes 30+ students in topics ranging from digital twin engineering to software testing and language design. He leads the GEMOC Initiative and contributes to projects like SciHook and GEMOC Studio .

• Software Engineering
• Model-Driven Engineering
• Software Language Engineering
• +۷ مورد دیگر